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{"pages":[{"title":"QZ's Paper Ranking","text":"It is a personal and arbitrary ranking list of references I read. Probably all papers that activates me to update this list are good papers. 排名 Rank 标题 Title 课题组 Groups 小记 Note 1 Decoupling of catalysis and transition state analog binding from mutations throughout a phosphatase revealed by high-throughput enzymology Daniel Herschlag@Stanford; Polly M. Fordyce@Stanford","link":"/ref-rank/index.html"}],"posts":[{"title":"2022 HRC复盘感受","text":"Hey, password is required here. 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Note","text":"Docking is one of the key problem bringing the substrate to the enzyme modeling. But most current docking methods performs poorly with larger substrates. This note record usages of the AutoDock Vina for testing. Site Specific Docking (Autodock Vina)就是通过grid box的选取来决定site Input files1. pdbqt file for proteinStart with the pdb file of the apo protein: Remove water (Can it work with the key water?) Add Hydrogens (What’s the difference between polar only or not) File formating: (pdb) -> (pdbqt) 2. pdbqt file for ligand File formating: (pdb) -> (pdbqt) 3. Configuration file Grid bot setting This limited grid box achieves the site specification by containing only the key residues. 所以需要自动决定Grid box来实现高通量 调查一下一般的选择条件 A txt file that contains (grid.txt) proteinspacing ###npts ## ## ##center ## ## ## Job setting (conf.txt) receptor= protein.pdbqtligand= SO.pdbqtcenter_x= ###center_y= ###center_z= ###size_x= ##size_y= ##size_z= ##out= vina_outSO.pdbqtlog= logSO.txtexhaustiveness= 8 Run Vina./vina -–config conf.txt -–log logSO.txt Python binding (Autodock python)","link":"/2021/10/28/AutoDock-Note/"},{"title":"Brain Care","text":"Hey, password is required here. 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Notes","text":"Note for using CASSCF methods. General Workflow Decide a input initial orbital (MO or UNO or GVB orbital) Select a active space base on the fractional occupancy of the initial orbital (The active space is inital orbital depended) Do CASSCF: Take active space and inital guess orbitals optimize casscf orbital (canonical) result in Natural Orbital Analyze and rationalize the fractional occupancy of the corresponding orbital Active Space SelectionUNO-CAS method https://aip.scitation.org/doi/10.1063/1.4922352 calculate natural orbitals with UHF and natural orbitals with fractional occupancy (e.g., between 0.02 and 1.98) constitute the active space. GVB method https://pubs.acs.org/doi/10.1021/acs.jpca.0c05216 Use GVB orbital’s occupation to determine the active space and serve as initial guess, which converge faster. especially for metal systems. In most cases it gives smaller active space and results in lower energy.The GVB orbital can be constituted by pairing UNO Software PracticeGAUSSIAN http://sobereva.com/264https://cloud.tencent.com/developer/article/1690190 DETERMINE Active Space (UNO) #P UHF/BasisSet guess=mix #P HF/BasisSet guess=(naturalorbitals,read,save,only) CASSCFsometimes need to use guess=alter and indexes at the end of the file to indicate the correct orbital. #p cas(6,6)/BS guess=(read,alter) geom=allcheck…19,17 energy is found after EIGENVALUE. (Containing solvation if SMD applied) MOKIT https://gitlab.com/jxzou/mokit/-/blob/master/doc/MOKIT_manual.pdfGVB CAS method:https://pubs.acs.org/doi/10.1021/acs.jpca.0c05216 The automr module autometicaly determining the workflow and the active space based on the input gjf file.See syntax of gjfs for automr in the manual.automr in.gjf > out.out workflow: UHF(UNO) -> GVB -> CASSCF Need to install pyscf and gamess Need to modify GAMESS (see Manual 4.4.9) if use ist != 0 than fchk is needed. Environment Settings Runing on Hoffman2 sub.cmd >folded> # >>> conda initialize >>>> # !! Contents within this block are managed by 'conda init' !!> __conda_setup="$('/u/home/s/shaoqz/project-houk/bin/anaconda3/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"> if [ $? -eq 0 ]; then> eval "$__conda_setup"> else> if [ -f "/u/home/s/shaoqz/project-houk/bin/anaconda3/etc/profile.d/conda.sh" ]; then> . "/u/home/s/shaoqz/project-houk/bin/anaconda3/etc/profile.d/conda.sh"> else> export PATH="/u/home/s/shaoqz/project-houk/bin/anaconda3/bin:$PATH"> fi> fi> unset __conda_setup> # <<< conda initialize <<<> # load gaussian> . /u/local/Modules/default/init/modules.sh> module load gaussian/g16_sse4> export GAUSS_SCRDIR=$TMPDIR> export GAUSS_EXEDIR=$g16root/g16/bsd:$g16root/g16 #need to redirect the EXEDIR> module li> # load mokit> export MOKIT_ROOT=/u/home/s/shaoqz/project-houk/bin/mokit> export PATH=$MOKIT_ROOT/bin:$PATH> export PYTHONPATH=$MOKIT_ROOT/lib:$PYTHONPATH> # load gamess> export PATH=$PATH:/u/project/houk/shaoqz/bin/gamess> export GMS=/u/project/houk/shaoqz/bin/gamess> AnalysisCompare different initial orbital and active spaceSCF energy can only be compared when active space is in the same size. Low energy means better solution.e.g.: UNO-CAS(5,5) vs GVB-CAS(1,1) is invalid. Even though CAS are determined to be so by UNO and GVB. Based on natural orbitalsMost CASSCF results are presented by NO and their fractional occupancy. Most analysis do wavefunction analysis base on these NO. (like a better wavefunction)e.g.: Radical coupling: The occupancy of the bonding and antibonding orbital shows the weight of diradical. Based on CASSCF orbitalsDetermine configuration coefficients (ratio)do population analysis for each configuration (understand its chemical meaning) Problem: chemical meaning of configurations are often ambiguous. Most software do not export casscf orbitals.Software support: cidump module with pyscf: https://github.com/hebrewsnabla/pyscf_addon/blob/main/cidump.py Gaussian output: Only provide the combination coefficient of the slater determinant. Hard to build a specific configuration.You can always converge with pyscf first and provide to orca or gaussian. MiscCASSCF vs UCASSCFMost CASSCF practice use one set of orbital and fractional occupation of the orbital. (like UNO-CAS and GVB-CAS) Only pyscf support UCASSCF treating alpha and beta orbital, but just for develop use. Radical systems are oftwn treat with UNO method or UNO-GVB method to make the CASSCF initial orbital. And result in natural orbital.","link":"/2021/03/17/CASSCF-Notes/"},{"title":"Design Pattern Note","text":"Hey, password is required here. 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Notes","text":"Hey, password is required here. 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Toolbox for Catalysis","text":"Hey, password is required here. 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","link":"/2022/12/21/Enzyme-s-Toolbox-for-Catalysis/"},{"title":"[Exp]Culture Medium Preparation","text":"Hey, password is required here. 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password is required here. 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with autodE","text":"autodE is a Python module designed for the automated calculation of reaction profiles from just SMILES strings of reactant(s) and product(s) by the Tom Young and the duarte group.(http://fduartegroup.org/)I tried to run it on Hoffman2 for some weird TSs. https://github.com/duartegroup/autodE Install anaconda3 For Hoffman2 a user installed conda is needed due to the permission problem. Download the .sh file from the anaconda website. (https://www.anaconda.com/products/individual) install with bash *.sh. It will also write the .bashrc for initilization. autodE make a new environment with conda $ conda create -n autode$ conda activate autode Install autodE $ git clone https://github.com/duartegroup/autodE.git$ cd autodE$ conda config --append channels conda-forge --append channels omnia$ conda install --file requirements.txt$ python setup.py install run test (https://duartegroup.github.io/autodE/install.html#quick-test) Job submission Using conda with the submission script requires initialization. Copy what’s in the .bashrc like this: # >>> conda initialize >>># !! Contents within this block are managed by 'conda init' !!__conda_setup="$('~/bin/anaconda3/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"if [ $? -eq 0 ]; then eval "$__conda_setup"else if [ -f "~/bin/anaconda3/etc/profile.d/conda.sh" ]; then . "~/bin/anaconda3/etc/profile.d/conda.sh" else export PATH="~/bin/anaconda3/bin:$PATH" fifiunset __conda_setup# <<< conda initialize <<< Or just source a file containing these lines. and then activate conda activate autode load gaussian . /u/local/Modules/default/init/modules.shmodule load gaussian/g16_sse4export GAUSS_SCRDIR=$TMPDIR load XTB source /u/home/${initial}/${USER}/bin/XTB/Config_xtb_env.bash Not necessary if xtb is installed with conda run autodE python input.py Also notice that the submission script is strict with unix file format. Windows user can use doc2unix or :set ff=unix in vi to change the format. Input ScriptIn version 1.0.0a2 Config.max_cores is set directly to %mem in the gaussian input. This leads to errors running on TaiYi and slow down the job on Hoffman2.","link":"/2020/11/06/Experience-with-autodE/"},{"title":"Fixed Thread","text":"Form http://archive.ambermd.org/201209/0203.html A chat formatJonathan Gough: The basic (or complex) question I have is: How do you take a PDB and change one residue to another residue? (essentially a point mutation of an existing structure) I thought I remembered reading how it could be done, but looking back I can’t seem to find where it might be. I can think of a few ways one could accomplish this, but I wanted to ask if there is an explanation in the manual or a tutorial that I am just missing. (Can someone point me in the right direction) I searched the archives and saw some old posts regarding using other programs. One could manually add/change things3+???? Not necessarily looking for a step by step but a push in the right direction. Francois: You could edit the PDB file: (i) remove the side chain of the amino acid to be mutated; (ii) rename the backbone of this residue according to the residue name of the mutation. Then, you load the modified PDB file in the LEAP program, which will automatically add the missing atoms (i.e. the side chain) in agreement with the FF library of the mutated residue. Carlos Simmerling: This isn’t a good method- leap doesn’t care at all where it puts the side chain and unless you’re very lucky you will have bad steric clashes that can invert chivalry and other bad things. You want to use a program that searches rotamers for something that fits as best as possible Carmenza Martinez: Not sure if anybody has suggested it previously but for single point mutations or multiple mutations of residues I have found swissPDB to be quite useful: http://spdbv.vital-it.ch/ Just as Prof. Simmerling leap is not efficient at filling in the blanks when you remove things and renamed them just as Francois suggested. Now, when you say 3+???? I don’t understand what you mean…changing the protonation state perhaps? for that you will need more than what swiss PDB could provide. Perhaps somebody else in the forum will provide useful advide for that. sorry I meant to say just as Prof. Simmerling said…the said got deleted…sorry Jonathan Gough: Thank you all for your help! Very good suggestions. I am using swiss PDB right now. I said 3+ as I could think of at least 1 if not multiple more ways to do it (other applications or combinations of applications) Carlos Simmerling: what often happens in my experience is that the steric clashes are bad enough that the atoms get pushed around, and the chirality inverts because of that. eventually you minimize the clash away, but in the process things are no longer correct. we’ve even seen really weird cases such as where a Phe ended up with a protein chain going through the middle of the ring obviously no way that will ever get fixed in MD. I guess I’m just warning people that if you have a high energy structure, just because you minimize it doesn’t mean things are ok. you should always visually inspect the area where you made the change. Aron Broom: Yikes, point taken. Also for anyone who finds this thread, PyMol has a mutation function that uses a rotamer library Francois(In a different context): You follow the same approach for a modified nucleotide residue thanfor a mutated amino acid residue. You remove the base and rename theresidue name for the ribose derivative according to the residue namedefined in the FF library for the mutated/modified nucleotide. x/tLEaPwill do the job and add the missing atoms for the modified residue. To convince Carlos (if one needs to) LEaP has a geometry optimizer(all structure or selected parts), can invert chirality center andmodify dihedral angle values to correct the generated modification.Most of these commands were only available in xLEaP; atq4md-forcefieldtools.org we have introduced them in tLEaP allowing tomake these commands ‘scriptable’…See http://q4md-forcefieldtools.org/Tutorial/Tutorial-1.php http://q4md-forcefieldtools.org/Tutorial/leap-mol2.php The strength of LEaP (I mean x/t) is that it is free (sense offreedom), it is directly usable (when one has installed theAmberTools) and very powerful (when one uses it the correct way);obviously one needs to understand how it works (may be not that easy). The Email formatThe is reformed emails are in the folded block. The Email >foldedDear Vaibhav Dixit,> If I have a DNA or RNA lets say dodecamer, how can I mutate it? Means how can I replace A with G or T with C?See the former email I sent about the t/xLEaP program and the answerfrom Bill.You follow the same approach for a modified nucleotide residue thanfor a mutated amino acid residue. You remove the base and rename theresidue name for the ribose derivative according to the residue namedefined in the FF library for the mutated/modified nucleotide. x/tLEaPwill do the job and add the missing atoms for the modified residue.To convince Carlos (if one needs to) LEaP has a geometry optimizer(all structure or selected parts), can invert chirality center andmodify dihedral angle values to correct the generated modification.Most of these commands were only available in xLEaP; atq4md-forcefieldtools.org we have introduced them in tLEaP allowing tomake these commands 'scriptable'...See http://q4md-forcefieldtools.org/Tutorial/Tutorial-1.php http://q4md-forcefieldtools.org/Tutorial/leap-mol2.phpThe strength of LEaP (I mean x/t) is that it is free (sense offreedom), it is directly usable (when one has installed theAmberTools) and very powerful (when one uses it the correct way);obviously one needs to understand how it works (may be not that easy).regards, Francois> On Tue, Sep 11, 2012 at 6:02 AM, Aron Broom <broomsday.gmail.com> wrote:>>> Yikes, point taken.>>>> Also for anyone who finds this thread, PyMol has a mutation function that uses a rotamer library.>>>> ~Aron>>>>>> On Mon, Sep 10, 2012 at 6:24 PM, Carlos Simmerling <>> carlos.simmerling.gmail.com> wrote:>>>> > what often happens in my experience is that the steric clashes are bad enough that the atoms get pushed around, and the chirality inverts because of that. eventually you minimize the clash away, but in the process things are no longer correct. we've even seen really weird cases such as where a Phe ended up with a protein chain going through the middle of the ring obviously no way that will ever get fixed in MD.>> >>> > I guess I'm just warning people that if you have a high energy structure, just because you minimize it doesn't mean things are ok. you should always visually inspect the area where you made the change.>> >>> >>> > On Mon, Sep 10, 2012 at 5:53 PM, Aron Broom <broomsday.gmail.com> wrote:>> >>> > > Just as an addition/question here concerning the LEaP approach: if you delete everything EXCEPT the backbone AND beta-carbon (or in the case of mutating glycine to something, just rename the "sidechain" hydrogen to a carbon) would LEaP then use that and thereby avoid the problem of messing up chirality or something extreme, and leave you only with the problem or steric clashes?>> > >>> > > If so, it's clearly not as ideal as using a program that has a rotamer library as has been suggested here, but still isn't devestating if you are willing to do some minimization or something or the sort.>> > >>> > > ~Aron>> > >>> > > On Mon, Sep 10, 2012 at 4:30 PM, Jonathan Gough>> > > <jonathan.d.gough.gmail.com>wrote:>> > >>> > > > Thank you all for your help! Very good suggestions. I am using swiss PDB right now.>> > > >>> > > > I said 3+ as I could think of at least 1 if not multiple more ways to do it (other applications or combinations of applications).>> > > >>> > > >>> > > >>> > > > On Mon, Sep 10, 2012 at 3:43 PM, Carmenza Martinez < crm3680.gmail.com >wrote:>> > > >>> > > > > sorry I meant to say just as Prof. Simmerling said...the said got deleted...sorry>> > > > >>> > > > > On Mon, Sep 10, 2012 at 3:39 PM, Carmenza Martinez < crm3680.gmail.com >wrote:>> > > > >>> > > > > > Not sure if anybody has suggested it previously but for single point mutations or multiple mutations of residues I have found swissPDB to be quite useful: http://spdbv.vital-it.ch/ Just as Prof. Simmerling leap is not efficient at filling in the blanks when you remove things and renamed them just as Francois suggested. Now, when you say 3+???? I don't understand what you mean...changing the protonation state perhaps? for that you will need more than what swiss PDB could provide. Perhaps somebody else in the forum will provide useful advide for that.>> > > > > >>> > > > > > Best regards>> > > > > >>> > > > > > On Mon, Sep 10, 2012 at 3:01 PM, Carlos Simmerling < carlos.simmerling.gmail.com> wrote:>> > > > > >>> > > > > >> This isn't a good method- leap doesn't care at all where it puts the side chain and unless you're very lucky you will have bad steric clashes that can invert chivalry and other bad things. You want to use a program that searches rotamers for something that fits as best as possible.>> > > > > >> On Sep 10, 2012 2:48 PM, "FyD" <fyd.q4md-forcefieldtools.org> wrote:>> > > > > >>>> > > > > >> > Dear Jonathan,>> > > > > >> >>> > > > > >> > You could edit the PDB file: (i) remove the side chain of the amino acid to be mutated; (ii) rename the backbone of this residue according to the residue name of the mutation. Then, you load the modified PDB file in the LEAP program, which will automatically add the missing atoms (i.e. the side chain) in agreement with the FF library of the mutated residue.>> > > > > >> >>> > > > > >> > regards, Francois>> > > > > >> >>> > > > > >> >>> > > > > >> > > The basic (or complex) question I have is:>> > > > > >> > >>> > > > > >> > > How do you take a PDB and change one residue to another residue?>> > > > > >> > > (essentially a point mutation of an existing structure)>> > > > > >> > >>> > > > > >> > > I thought I remembered reading how it could be done, but looking back I can't seem to find where it might be. I can think of a few ways one could accomplish this, but I wanted to ask if there is an explanation in the manual or a tutorial that I am just missing. (Can someone point me in the right direction)>> > > > > >> > >>> > > > > >> > > 1. I searched the archives and saw some old posts regarding using other programs.>> > > > > >> > > 2. One could manually add/change things>> > > > > >> > > 3+????>> > > > > >> > >>> > > > > >> > > Not necessarily looking for a step by step but a push in the right direction.>> > > > > >> >>> > > > > >> >>> > > > > >> >>> > > > > >> > _______________________________________________>> > > > > >> > AMBER mailing list>> > > > > >> > AMBER.ambermd.org>> > > > > >> > http://lists.ambermd.org/mailman/listinfo/amber>> > > > > >> >>> > > > > >> _______________________________________________>> > > > > >> AMBER mailing list>> > > > > >> AMBER.ambermd.org>> > > > > >> http://lists.ambermd.org/mailman/listinfo/amber>> > > > > >>>> > > > > >>> > > > > >>> > > > > >>> > > > > > -->> > > > > > Carmenza Martinez>> > > > > >>> > > > > >>> > > > >>> > > > >>> > > > > -->> > > > > Carmenza Martinez>> > > > > _______________________________________________>> > > > > AMBER mailing list>> > > > > AMBER.ambermd.org>> > > > > http://lists.ambermd.org/mailman/listinfo/amber>> > > > >>> > > > _______________________________________________>> > > > AMBER mailing list>> > > > AMBER.ambermd.org>> > > > http://lists.ambermd.org/mailman/listinfo/amber>> > > >>> > >>> > >>> > >>> > > -->> > > Aron Broom M.Sc>> > > PhD Student>> > > Department of Chemistry>> > > University of Waterloo>> > > _______________________________________________>> > > AMBER mailing list>> > > AMBER.ambermd.org>> > > http://lists.ambermd.org/mailman/listinfo/amber>> > >>> > _______________________________________________>> > AMBER mailing list>> > AMBER.ambermd.org>> > http://lists.ambermd.org/mailman/listinfo/amber>> >>>>>>>>> -->> Aron Broom M.Sc>> PhD Student>> Department of Chemistry>> University of Waterloo>> _______________________________________________>> AMBER mailing list>> AMBER.ambermd.org>> http://lists.ambermd.org/mailman/listinfo/amber>>> --> With regards>> Vaibhav A. Dixit> Ph.D. Scholar> Department of Medicinal Chemistry> Natl. Inst. Pharm. Edu. & Res. (NIPER)> Sector 67, Phase X, S.A.S. Nagar (Mohali)> Punjab -160 062 INDIA> Phone (Mobile): +919915214408> E-mail: vaibhavadixit.gmail.com> www.niper.nic.in","link":"/2020/09/04/Fixed-Thread/"},{"title":"FACE CONFLICT HOLD CONSISTANCY","text":"Hey, password is required here. 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","link":"/2020/12/28/FACE-CONFLICT-HOLD-CONSISTANCY/"},{"title":"Great Qoute","text":"“The more accurate (and complex) the calculations become the more the concepts tend to vanish into thin air.”–Robert Mulliken What’s really important is the insight, the qualitative concept. Including trivial terms increase accurcy but also mess up the understanding,","link":"/2020/07/08/Great-Qoute/"},{"title":"GSM on hoffman2","text":"Reference: wiki from the developer (https://github.com/ZimmermanGroup/molecularGSM/wiki) Tiptorial form Tyler Benton (On Hof2: /u/project/houk/tylerben/shared/GSM/readme.txt) Tutorial from the Zimmerman Group (https://sites.lsa.umich.edu/zimmerman-lab/tutorial/surface-growing-string-method/) Personal notes on using GSM with different software on hoffman2. Create Working Directorycopy the reference directory to make a new one cp /u/project/houk/tylerben/shared/GSM/xxxx_GSM/template ./[project_name] GSM with GaussianFile settinggstart - set gaussian input route line // Need the Force keyword ggrad - Only need to be sure the script is specifying the correct G16 path. inpfileq - The setting for gsmThe only 3 that may need to changes TS_FINAL_TYPE 0 for rotation / 1 for bond change NNODES Max number of nodes used for GSM. odd number from 9-15 for DE-GSM higher value to fit more complicated PES SM_TYPES Select SSM/GSM/FSM If use job queue.cmd - job submission script job/out name core/memory Run the job Put the input geometry in initial0001.xyz with 2 structures in a row. mkdir scratch and place initial0001.xyz under the ./scratch/ chmod +x gsm.gaussian Use qrsh run qrsh to land on the node load module load gaussian Use export OMP_NUM_THREADS=# to set the cores GSM main program uses. run the job with ./gsm.gaussian 1 1 >> test.log 2>&1 & the first number is for specifying the initial000# file. the second number is for ncpu value in Gaussian input. (for xtb: The in total cpu uses are “ncpu * OMP_NUM_THREADS”. Not sure what it is in gaussian. I tried to set them both into 24 and request a 24 core node. It seems just using 24 cores. Use submission scriptsource .bashrc and put the above command used on the compt node in the script. Restart a job https://sites.lsa.umich.edu/zimmerman-lab/tutorial/surface-growing-string-method/restarting-growing-string-calculation/ rename stringfile.xyz#### to restart.xyz#### (same number) In inpfileq: change RESTART to 1 (somehow if stringfile.xyz#### hasn’t pop up yet, just resubmit the job would work.) Aborted with core* files and says chk file is emptyThe program misjudge the bond pair. Most likely confused by the leaving group. Installation https://github.com/ZimmermanGroup/molecularGSM Load cmake > 3.17.0 BTW, is it nessessary to build a new one in a new server? Misc Energy unit is kcal/mol. more It seems the original GSM is not in active maintance. Instead they are more active on the pyGSM now.","link":"/2020/07/18/GSM-on-hoffman2/"},{"title":"In Memory of the 2020-Spring Semester","text":"One of the teacher asked us to submit hand writing papers along with at least 5 hand painting figures.","link":"/2020/06/30/In-memory-of-the-2020-spring-semester/"},{"title":"HMMER Notes","text":"HMMer notes, avoid redundant searching 安装从源代码编译 cd {源代码目录}./configure --prefix={your-install-dir}makemake checkmake install 注意确保configure成功 使用安装成功后会在{your-install-dir}下出现bin目录并包含所有可执行程序 创建目标序列对应的MSAjackhmmer --incE 0.001 --max -A msa.sto query_sequence.fasta uniref90.fasta 具体的参数可以参考https://www.ebi.ac.uk/Tools/hmmer/search/jackhmmer","link":"/2023/05/08/HMMER-Notes/"},{"title":"LSF system on SUSTech TaiYi","text":"ReferenceAbout TaiYi and LSF manualhttps://hpc.sustech.edu.cn/process/download.htmlIBM LSF documenthttps://www.ibm.com/support/knowledgecenter/SSWRJV_10.1.0/lsf_welcome/lsf_welcome.htmlSpent a whole afternoon trying to figure out how to debug on the computational node. Interactive Shell on nodeThe pseudo shell method from the document wont work.bsub -IDirectly ssh to the node works.ssh [node_name]","link":"/2020/11/11/LSF-system-on-SUSTech-TaiYi/"},{"title":"Misc Notes of PyMol","text":"preventing redundant searching Select all Na+select (name Na\\+) + is the default list separator. So it needs to be escaped. related reading","link":"/2020/12/05/Misc-Notes-of-PyMol/"},{"title":"MIUI trouble with AT&T - the APN mismatch","text":"How to use AT&T data in a phone with MIUIBugs over bugs and out of date informations - that’s when ATT meet MIUI StoryRe-entering the US after 2 years and late for the start of the semester, I desperately need a stabe phone number for all the registrations. I have a list of about 10 items waiting for a number to continue.So I went to the local att store and the madam seems new to my phone but still confidently set me up. After leaving the store, I found the network is not working. The signal is full, but not network IO exists. I can call and text but not data. After rebooted for several times, I realize there should be a systemetic error in either my phone or att. It’s probabaly gonna be the APN problem.I go back to the store 40min before my next meeting. The dealer took 30min asking his/her colleague for help. They finally believe my APN statment when the 3rd guy came. He showed me a web page of APN settings and taught the other two what should they do next time. Up to this time, I do not have enough time. So I went for the meeting and took a photo of the APN settings.When I tried to set APN myself, I found it never works. I was always told that I am not allowed to edit the APN by the system even though the interface is designed as it’s for editing. The new APN I typed in with effort just disappears after I tap “save”.Searching with google and baidu, I found many people has the same problem but no one really solves it. The best solution from the internet can make the network works but I have to turn of 4G and 5G, type in the APN, watch APN disappear, turn 4G everytime after rebooting the phone.Back to my phone, I found only changing the first setting will not make APN disappear. So I screened for which setting term cause the bug. It was the MNC. The default is 280 but the clerk told me to enter 410. And I found this link. The clerk is telling me the wrong MNC! That’s why it cause the bug! Is is 280 on my ticket but no one in the store know how to read that. SolutionThe key is not to change the MNC. Go to 双卡和移动网络 and click the ATT card Go to the APN settings 名称：NXTGENPHONE APN：NXTGENPHONE no change no change no change no change no change MMSC: http://mmsc.mobile.att.net 彩信代理: proxy.mobile.att.net 彩信端口: 80 MCC: 310 MNC: [keep default! Change this number will cause the bug. The default number should be the same as the 4-6 digit of the SIM number on the ticket] not change for the rest tap 更多 on the bottom and save","link":"/2021/09/02/MIUI-trouble-with-AT-T-the-APN-mismatch/"},{"title":"Intro Fragments: Enzyme Engineering","text":"Hey, password is required here. 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Mutation - residue swap","text":"Hey, password is required here. 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Writing Notes","text":"Hey, password is required here. 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Notes","text":"Hey, password is required here. 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of hexo encrypt with http","text":"“为网站安装安全证书解决hexo-blog-encrypt插件无法使用的问题” link: https://p1htmlkernalweb.mybluemix.net/articles/为网站安装安全证书解决hexoblogencrypt插件无法使用的问题_4007585_csdn.html对于Github pages直接勾选自带的强制https功能即可link: https://docs.github.com/cn/github/working-with-github-pages/securing-your-github-pages-site-with-https","link":"/2020/07/05/Problem-of-hexo-encrypt-with-http/"},{"title":"Plot IGM analysis with PyMol","text":"Plot IGM analysis from Multiwfn using PyMol. IGM is an useful analysis of spatial distribution of steric hindrance. Plotting IGM result is much easier and looks better in PyMol. Related Multiwfn Documentshttp://sobereva.com/407 Related PyMol Documentshttps://pymolwiki.org/index.php/Ramp_New Run IGM analysis Save optimized geometry as .mol2 fileSo that can be opened by both Multiwfn and Gview load into Multiwfn & run IGM 20102 // 2 fragments[atom index] // fragment #1 (atom group tool from Gview helps)[atom index] // fragment #22 // grid quality3 // save files to current dir Now we have dg_inter.cub, dg_intra.cub, dg.cub and sl2r.cub. Plot with PyMol load the .mol2, dg_inter.cub and sl2r.cub into PyMol. Use “Other Visualization Settings for structures” from https://www.shaoqz.cn/2020/06/29/PyMol-Orbital/ Build Isosurfaceisosurface IGM1, dg_inter.cub, 0.01set transparency, 0.2 Grammer: isosurface {new object name}, {.cub name}, {isovalue} Color the surface with sl2rramp_new ramp1, sl2r, [-0.05, 0, 0.05], [blue, white, red]color ramp1, IGM1","link":"/2021/08/03/Plot-IGM-analysis-with-PyMol/"},{"title":"PyMol-Notes","text":"PyMol notes, avoid redundant searching 计算和展示surface的细节SASA vs SESSASA和SES是两种不同的面积定义方式 展示时使用set surface_solvent来调整显示的surface类型 计算时用get_area计算面积时使用set dot_solvent来调整计算的surface类型 Misc总的来讲SASA在直观性上不如SES，会高估凸面积，低估凹面积","link":"/2022/12/19/PyMol-Notes/"},{"title":"Progdyn2017的部署与使用","text":"Hey, password is required here. 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","link":"/2020/09/14/Progdyn2017%E7%9A%84%E9%83%A8%E7%BD%B2%E4%B8%8E%E4%BD%BF%E7%94%A8/"},{"title":"PyMol Orbital Visualization","text":"Notes for a Houk Group style molecular orbital visualization in PyMol Gaussian .fchk to .cubefor i in {27,28,29};do cubegen 0 MO=$i {Name}.fchk {Name}-$i.cub -2 h;done In PyMolBuild Isosurfaceisosurface {desired-isosurface-name}-n, {filename.cube}, -0.02isosurface {desired-isosurface-name}-p, {filename.cube}, +0.02 Transparencyset transparency, 0.2 From 0 to 1 Color SurfaceLet’s go Houkie style set surface_color, density, *nset surface_color, forest, *p Other Visualization Settings for structuresFrom Cooper set valence, 0hide everythingshow sticksshow spheresshow labelsshow dashesset stick_radius, .07set sphere_scale, .18set sphere_scale, .13, elem Hset bg_rgb=[1, 1, 1]set stick_quality, 50set sphere_quality, 4color gray85, elem Ccolor red, elem Ocolor slate, elem Ncolor gray98, elem Hset stick_color, blackset ray_trace_mode, 1set ray_texture, 2set antialias, 3set ambient, 0.5set spec_count, 5set shininess, 50set specular, 1set reflect, .1set dash_color, blackset dash_gap, .2set dash_length, .1set dash_round_ends, 0.1set dash_radius, .05set ray_trace_gain, 10set stick_h_scale, 1set ray_shadow, offset label_size, 60set label_distance_digits, 2set orthoscopic, on Combining Transparent Objects in Ray TraceUse Setting->Transparency->Multi-layerref","link":"/2020/06/29/PyMol-Orbital/"},{"title":"PyMol & Multiwfn Electrostatic Potential (ESP) Visualization","text":"Generate ESP .cub file from the Multiwfn and plot it in PyMol Related Multiwfn Documentshttp://sobereva.com/443http://sobereva.com/196 Related PyMol Documentshttps://pymolwiki.org/index.php/Ramp_New Generate .fchk file with Gaussian Run a single point calculation and save the wavefuncation information to the .chk file %chk=xxx.chk Make the formchk file and refine it with sed. (Make it readable to GaussView)for i in *.chk; do formchk $i ${i%chk}fchk && sed -i 's/MM charges/MM charge /g' ${i%chk}fchk && sed -i 's/MicOpt/Opt /g' ${i%chk}fchk; done Generate .cub file with Multiwfn Single file set the cubegen path in $Multiwfn_HOME/setting.iniThis greatly accelerate the calculation open Multiwfn.exe load the .fchk file Run ESP calculationThe following numbers are the Multiwfn control-index5 # Output and plot specific property within a spatial region (calc. grid data)1 # Electron density 2 # Medium quality grid, covering whole system2 # Export data to Gaussian-type cube file in current folder Here we got the .cub file for ESP isosurface density.cub0 # Return to main menu5 # Output and plot specific property within a spatial region (calc. grid data)12 # Total electrostatic potential (ESP)1 # Low quality grid , covering whole system # Running: "cubegen 4 potential=SCF xxx.fchk ESPresult.cub -1 h ESPgridtmp.cub > nouseout"2 # Export data to Gaussian-type cube file in current folder Here we got the .cub file for ESP color mapping totesp.cub Multiple fileA .bat/.ps1 file can help dealing with multiple .fchk Multiwfn XXX.fchk < ESPiso.txtmove /Y density.cub density1.cubmove /Y totesp.cub ESP1.cub The .txt file contain the control-index listed above Visualize the surface with PyMol open the structure (save a .mol2 from any of the .cub) and these two .cub files Use “Other Visualization Settings for structures” from https://www.shaoqz.cn/2020/06/29/PyMol-Orbital/ Build Isosurfaceisosurface ESP1, density, 0.002set transparency, 0.2 Grammer: isosurface {new object name}, {.cub name}, {isovalue} Color the surface with ESPramp_new ramp1, totesp, [0, 0.3, 0.36], [blue, white, red]color ramp1, ESP1 Grammer: ramp_new {new object name}, {ESP .cub name}, [Value list], [Corresponding color list]Grammer: color {color object}, {object} The extreme point analysisIn Multiwfn with the .fchk loaded 12 # Quantitative analysis of molecular surface3 # Spacing of grid points for generating molecular surface: 0.2500000.150 # Start analysis now!5 # Export molecule as pdb format file (optional)name.pdb 6 # Export all surface vertices to vtx.pdb in current folder (optional)2 # Export surface extrema as pdb file Maxima is presented as carbonMinima is presented as oxygen","link":"/2020/11/09/PyMol-Multiwfn-Electrostatic-Potential-ESP-Visualization/"},{"title":"PyMol Structure Amendment","text":"Note for protein crystal structural amendment using PyMol. Merge StructuresUse the alter command https://pymolwiki.org/index.php?title=Alter&redirect=no Merge objects by set parent values to the same alter (sele), chain='A', ...sortrebuild","link":"/2020/11/12/PyMol-Structure-Amendment/"},{"title":"PyMol Trajectory Visualization","text":"Visualize Amber nc trajectory in PyMolI used to convert everything into .dcd file but it is a little complex. Now I found PyMol actually can directly read prmtop & nc file but just need little adjustment. Rename .prmtop filerename .prmtop file into .top file.REF: https://wikis.ch.cam.ac.uk/ro-walesdocs/wiki/index.php/Loading_AMBER_prmtop_and_inpcrd_files_into_Pymol load top file and nc fileload AAA.topload_traj BBB.nc, AAA Note if want to use .mdcrd file from Amber, it needs be renamed as .trj before loading REF: https://pymolwiki.org/index.php/Load_trajhttps://sourceforge.net/p/pymol/mailman/message/36374096/https://sourceforge.net/p/pymol/mailman/message/35166151/","link":"/2022/08/03/PyMol-Trajectory-Visualization/"},{"title":"RefNote: AsiteDesign","text":"Hey, password is required here. 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","link":"/2023/04/14/RefNote-AsiteDesign/"},{"title":"RefNote: Code-99 Ref-3","text":"Hey, password is required here. 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","link":"/2020/07/05/RefNote-Code-99-Ref-3/"},{"title":"RefNote: Code-99 Ref-4 & 5 & 6","text":"Hey, password is required here. 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Code-99 Ref-1","text":"Hey, password is required here. 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Code-99 Ref-7","text":"Hey, password is required here. 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password is required here. 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Code-99 Ref-8 & 9","text":"Hey, password is required here. 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","link":"/2020/07/10/RefNote-Code-99-Ref-8/"},{"title":"RefNote: Experimental Thermodynamic data of Enzyme Interaction","text":"Misc about experimental thermodynamic data of enzyme interactions Method: Isothermal Titration Calorimetry (ITC)ExperimentIsothermal Titration drop in Sample Cell cause temperature change Reference Cell at given constant temperature. The feedback system transfer energy in/out the Sample Cell to keep the temperature constant after every drop. The monitor record the energy transfer as peak. Data AnalysisEnthalpy Integration of peak area directly gives the enthalpy($\\Delta H$). Entropy $\\Delta G = -RTlnK$$\\Delta G = \\Delta H - T\\Delta S$Modeling the curve around the end point gives the K.Dilution is required when the curve is too sharp to model. Data: Different System1BRS monomer ITC Barnase to Barstar (pH=8) No aggression One to One “independent of protein concentration or whether barnase is titrated with barstar or vice versa” Preventing the aggression and dimerization. “24 mM Hepes buffer (pH 8), 1 mM DTT because barstar tends to aggregate in the cell of the calorimeter in Tris buffer at pH 8.The DTT was added to the buffer to prevent oxidation and dimerization of barstar.” IBRS-2 is not the correct reference (Not the ITC method) The 1BRS-2 paper(Fersht,1995) used the Tris buffer. CRYSTAL SequenceC40A C82ADouble mutant due to possilbe RedOx.“Crystallographic studies involving wild-type barstar have been thwarted due to the unavoidable presence of a mixture of both oxidized and reduced species, thus necessitating the use of the double Cys—>Ala mutant. “ PolymerismNot really a trimer in the PDB, just the asymmetric section. / Chain AD was used in the analysis of the original referencemany problems in this part of PDB database(a polymer or monomers): Global Stoichiometry value to show what the author intended to get. Fits other data generation experiments for the most cases.(In solvent) But this value cannot always indicate which chains is the target result. (e.g. 1NTO) Quality Differences within the UnitChain C have much higher overall temperature factor.“This is most likely due to a lack of stabilizing crystal packing around this molecule, which is also less solvated than the other molecules in the asymmetric unit” ExceptionsMissing barnase residues 1 and 2 from the N-terminus. (A,C)This N-terminal disorder is a common feature in all barnase structures solved to dateThese residues are present, however, in the barnase B chain of the barnase-barstar complex as a result of stabilizing crystal packing interactionsMissing barstar residue 1 from the N-terminus. (E)There is no density for the N-terminal lysine residue of barstar chain E.Missing barstar residue 64-65. (E,D)It was impossible to build in residues 64 and 65 of barstar chains D and E because of relatively high disorder in this region of barstar. MD Model Use Chain B for barnase. (Fully Modeled) Use Chain F for barstar. (Partially Modeled)Fixed with Chain E. (K22 E28 S89)Fixed with tLEaP. (E64 N65)Mutate back to WT with the MutaGen. 1JTG monomer ITC TEM-1-beta-lactamase to BLIP (pH=7) “titrating 40 M TEM-1-beta-lactamase into 4 M BLIP mutant in PBS (50 mM phosphate, pH 7.0, 150 mM NaCl).” Minimal proton linkage effect The binding enthalpy in Tris buffer was identical to that in phosphate buffer CRYSTAL V59I A159V 1LFD ITC ???","link":"/2020/10/17/RefNote-Experimental-Thermodynamic-data-of-Enzyme-Interaction/"},{"title":"RefNote: Code-99 Ref-2","text":"Hey, password is required here. 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Code-99 RefM-0","text":"Hey, password is required here. 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","link":"/2020/07/06/RefNote-Code-99-RefM-0/"},{"title":"RefNote: The evolution of multiple active site configurations in a designed enzyme KE07 & Evolutionary Optimization of Computationally Designed Enzymes: Kemp Eliminases of the KE07 Series","text":"Evolutionary Optimization of Computationally Designed Enzymes: Kemp Eliminases of the KE07 Serieshttps://www.sciencedirect.com/science/article/pii/S0022283609015381?via%3Dihub The evolution of multiple active site configurations in a designed enzymehttps://www.nature.com/articles/s41467-018-06305-y Important experimental protocol reference (background reaction; Arrhenius kinetics) (JMB 2010) Evolutionary Optimization of Computationally Designed Enzymes: Kemp Eliminases of the KE07 SeriesThis work did following to understand the KE07 DE process: crystal structural based analysis pH optimum experiment Evolution change of KE07 The salt bridge between E101 and K222 influence the pKa of E101 I7D break this salt bridge to enhance the catalysis D7I in R7 cause kcat/Km decrease pH optimum after the mutation increased to ~6 from <4.5 K222 in R7 is important K222A in R7 cause 500-fold kcat/Km decrease K222A in KE07 cause ~3-fold kcat/Km increase didn’t give any reason that make sense The H-bonding network in 201-202-224 make H201 in a position of stabilizing TS N224D form H-bond with R202 and H201 that make them closer to the substrate the relationship between closer H201 and lower TS - R is not well explained (Nat. Comm.) The evolution of multiple active site configurations in a designed enzymeThis work did following to understand the KE07 DE process: crystal structural based analysis KIE kinetics (how did they used that) Arrhenius kinetics in 8 temperature PROPKA calculation of E101 fluorescence spectroscopy pf W50 (to probe the negative charge density on E101) HREX-MD enhanced sampling (for E101 conformation, modelled w/o ligand) EVB calcualtion of the reaction barrier of the 3 configs. Mechanism of KE07 If the pH value goes too high (too basic), the HIS tag will be deprotonated and bind into the pocket. After R4, present of product will break K222 salt bridge and form H bond with oxyanion of the product W50A signicantly reduce kcat Evolution change of KE07 R4: significantly lower Ea I7D lead to breaking of the salt bridge: better electrostatics but worse dynamics on E101 conformer (see the JMB paper) R5&R6: mainly the entropy part. Ea even increased from R5 to R6. (So it is actually reasonable) (???) based on 6DNJ they think R5 developed an additional catalytically competent conformation. (but it seems not a valid structure) And they can only observe conf. B when HIS tag is binding But HREX-MD sampled it and EVB suggests it works. really developed a new conformation C of W50 and is dominated. Conf. C is forming H-bond with E101 which pre-organize it for catalysis which is lower is activation barrier in this conformation comparing to A. (Prob due to organize E101) NOTEstudies related to KE07-R7-2 should use 6CT3 as the starting structure. (Use config )","link":"/2023/06/28/RefNote-The-evolution-of-multiple-active-site-configurations-in-a-designed-enzyme/"},{"title":"RefNote: Isotope Effect in the Activation of a Mechanophore","text":"An interesting paper about isotope effect in ambimodal ratio. The mechanochemistry driving force determined velocity distribution prominent the isotope effect on final ratio. more in:OneDrive\\文档\\Houk-2021\\1-19\\0119flashlit.pptx","link":"/2021/01/18/RefNote-Isotope-Effect-in-the-Activation-of-a-Mechanophore/"},{"title":"RefNote: mechanisms of oxygen resistance of enzyme","text":"Hey, password is required here. 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","link":"/2023/02/01/RefNote-code-O/"},{"title":"RefNote: Using High-Throughput Molecular Dynamics Simulation to Enhance the Computational Design of Kemp Elimination Enzymes","text":"Hey, password is required here. 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Density in NPA","text":"Note about how to read spin density from Gaussian pop=NBO output Gaussian use NBO version 3 by default that does not explictly print out the spin density in the out file. ref The .out file contains 3 segment of NPA table, the last two is treating alpha and beta orbitals seperately.The spin density can be calculated by:$TOTAL_{\\alpha} - TOTAL_{\\beta}$the two terms are from alpha and beta table. related post","link":"/2021/01/27/Spin-Density-in-NPA/"},{"title":"Rosetta Notes","text":"Hey, password is required here. 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9a3a8e0ba4581e976be1939a49dd4baac003cc288bf86f53022fe6c4ec2a619e76baaa952157961df3324201b3121c6a3501d69888c66939203642c39186b8374a41ecfb","link":"/2022/02/05/Rosetta-Notes/"},{"title":"TAO: 为蛋白质运行ONIOM计算","text":"本文为初次使用TAO运行ONIOM计算的杂记 A toolkit to assist ONIOM calculationshttps://doi.org/10.1002/jcc.21524http://chem.wayne.edu/schlegel/Software/oniomtoolTAO/TAOtutorial.html 制作输入文件初始文件： .pdb 包含溶剂和离子的蛋白质结构 .prep 通过LEaP生成的相应的力场参数文件（添加至ESPT/prepfiles） pdb2oniom 运行pdb2oniom -o NAME.gjf -resid corelist.txt -near 6 –i NAME.pdb 选择核心部分，制作corelist.txt (格式：[RES] “INDEX” ) 其中-near指定corelist周围几埃的原子可以在优化中移动教程里直接复制出来的命令里i前面的–不是正常的-，找问题找了半天，气死了 得到一段输出和两个文件.gjf .gjf.onb 输出文本： 部分配体和cofactor没有被识别 需要将相关的prep文件添加至ESPT/prepfiles文件夹 C端和N端残基以及一些离子没有被识别 需要手动添加 .gjf文件的修复 修复电荷：使用leap制作prmtop文件，利用脚本从对应的prmtop文件中读取电荷，进行整体的替换 修复名称： 配体和cofactor：WARNING 需将antechamber生成的prepin文件转化成旧版的prep文件（在每行结尾加原子序号,相关脚本(https://github.com/shaoqx/CalcKit/blob/master/Misc_scripts/TAO/prepin2prep.py)） 末端残基：手动修复，将UDF替换为对应的原子名称、类型 离子：手动修复，将UDF替换为对应的离子类型 （用什么标准的类型和名称？） .gjf文件补充信息 补充connectivity table: 使用GaussView读取再保存 设置QM层：使用GaussView设置高/低层 设置route行 .gjf文件的修复2 修复connectivity使用checkconnect检查连接数（输出超过-c设置的连接数的中心） checkconnect -g NAME.gjf -c 5之后手动在GaussView中修复 修复电荷使用chargesum检查电荷手动设置到gjf文件中 修复力场参数运行一次gjf文件 得到关于力场参数的报错使用pramlookup从Amber库中获取参数 parmlookup -g NAME.log -o NAME.txt重复多次直至不报错","link":"/2020/10/19/TAO-%E4%B8%BA%E8%9B%8B%E7%99%BD%E8%B4%A8%E8%BF%90%E8%A1%8CONIOM%E8%AE%A1%E7%AE%97/"},{"title":"Resonance Theory Notes","text":"Note for using WFRT/NRT methods. Analyze contribution of resonance structures. Understand different seperations of fragmental contribution to the structure. WFRT method https://mp.weixin.qq.com/s?__biz=MzU5NjMxNjkzMw==&mid=2247486121&idx=1&sn=c9a6cd8a7d245974cd4cc367822e05f3&chksm=fe65ccc3c91245d5ddde48eb7ac5775ce7b11c7b5c89b123ae5edc0717f6d4c16d780a1a7865&scene=21#wechat_redirect Quantitive resonance analysis can be carry out in two ways: Valance Bond calculation based Wavefunction based (DFT calculation) EzReson Installation git clone https://github.com/yangwangmadrid/EzReson check dependence: python >= 3.6 numpy >= 1.18.0 scipy >= 1.5.1 edit your_dir/EzReson/ezreson: change the value of EZREON_DIR to the real folder path chmod a+x ezreson edit ~/.bashrc: add export PATH=${PATH}:your_dir/EzReson source .bashrc and use general command python ezreson.py xxx.in > xxx.out Use EzReson 使用EzReson做化学共振分析https://mp.weixin.qq.com/s?__biz=MzU5NjMxNjkzMw==&mid=2247486139&idx=1&sn=b9f1550c4854b3632563a5aabc08600f&chksm=fe65ccd1c91245c735b535503f3a2aa288720ad2ae6cd222453a051c82b455539d6d06c8fdbc&scene=178&cur_album_id=1709622916134338560#rd 1. Gaussian NBO calculation optimize the geometry single point calculation with NAO (add pop=nboread and nbo section) and formchk %chk= $your_filename.chk%mem=8GB%nprocshared=4 # $method/$basisset pop=nboread...(after coordinate)$NBO NOBOND AONAO=W archive file= $your_filename$END now we have: xxx.33 xxx.fchk xxx.out 2. Select target LMOs and atomsEzReson do not support open shell system now Use NRT with Gaussian and NBO7 NRT example: https://nbo6.chem.wisc.edu/tut_nrt.htmNBO6 reference: http://bbs.keinsci.com/forum.php?mod=attachment&aid=NTQyfGFlZTY5MjZlfDE2MTc3OTI4NzF8MTM1NjR8MTAyNRT example (chinese): http://bbs.keinsci.com/thread-106-1-1.htmlE. D. Glendening, J. K. Badenhoop, and F. Weinhold, J. Comp. Chem. 19, 628-646 (1998). Install NBO >= 7.0Only NBO >= 7.0 contains the NRT function that works without the limitation of memory, so that standarded size of system Buy NBO7 from https://nbo6.chem.wisc.edu/new7_css.htm run NBO7 with their latest script /xxxdir/gennbo FILENAME N_CORE N_MEM Run Gaussianwith optimized structure Name.gjf...# method/BSS pop=nboread...<coord section>$NBO archive file=Name$END This job result a Name.47 file as defined in archive file‘Since Gaussian use NBO3 in default so it cannot do the NRT in a embedded manner. Run NBO7 Edit .47 file Add NRT between $NBO and $END in the 2nd line. Add $NRTSTR section Name.47$NBO NRT $END$NRTSTR STR <1st resonance structure> END STR <2nd resonance structure> END ... STR <last resonance structure> END $END Note that NBO have a 132-character limitation. Line feed is needed if the STR is too long. Run NBO /xxxdir/gennbo FILENAME N_CORE N_MEM In FILENAME.nbo result will be shown as: STR ! Wgt = xx.xx% <1st resonance structure>END Grammer of NRTSTRLONE <atom_id> <number of lone pair> ... ENDBOND S <atom_id> <atom_id> D <atom_id> <atom_id> ... END S: single bond D: double bond","link":"/2021/03/27/Resonance%20Theory%20Notes/"},{"title":"RefNote: Screening of metagenomic imine reductases","text":"Screening and characterization of a diverse panel of metagenomic imine reductases for biocatalytic reductive aminationhttps://www.nature.com/articles/s41557-020-00606-w BackgroundDiscovery Approachof novel biocatalysisBuilding Block direct evolution in silico screening / computational design explore existing sequence space exploiting cofactor versatility Current Bottle Neck: HTS In silico: low in vitro “yield” (20/>500) expensive reactivity characterization: MS, microfluidic methods(fluorescence, absorbance)","link":"/2021/01/14/RefNote-Screening-of-metagenomic-imine-reductases/"},{"title":"Utilize Orbital Overlap with Multiwfn","text":"Using the overlap integral function in Multiwfn with some potential usages. http://sobereva.com/163 In GaussianPrepare the Input for fragment(pop=full) and complex(pop=full IOp(3/33=1)). The files are same for CDA analysis, so it’s convenient to do both. In MultiwfnInput the complex and fragments: [complex_path]10015[frag1_path][frag2_path][Orbital_frag1_Index],[Orbital_frag2_Index] This give the overlap integral(S) for multiplying wavefunction of Orbital_frag1 and Orbital_frag2 Potential usagesIn competing TSs: Spatial overlap difference (e.g. steric effect) Demo directly (e.g. steric effect and how it influence the electronic effect) Atomic coefficient difference A validation Utilize the $ \\frac{S^2}{d\\epsilon} $ to weight difference in different orbitals Overall Coefficient difference(Polarzation) affect the positional overlap (without internal positional difference) example: https://pubs.rsc.org/en/content/articlelanding/2020/sc/d0sc02901g#!divAbstract Above Fig. 2 in analysis.","link":"/2020/07/15/Utilize-Orbital-Overlap-with-Multiwfn/"},{"title":"VSCode Note","text":"VSCode notes, avoid redundant searching 远程环境使用remote ssh的功能可以连接到远程位置下进行开发此处可以连接到ACCRE等超算上利用超算的环境开发从而避免配置资源（Gaussian，Amber等）和编译耗时等一系列问题 遇到的问题git symlink support当打开的文件或者工作区的路径中包含软链接(symlink)的时候VSCode中的git会有很多功能难以正常运行。相关的issue具体体现为diff decoration不显示 同时资源管理器中也不显示修改的小标记 ACCRE case在ACCRE上这个问题尤其明显，因为ACCRE的/home路径本身是symlink [shaoq1@gw341 ~]$ ls -l /homelrwxrwxrwx 1 root root 12 Jan 20 2020 /home -> /gpfs52/home","link":"/2022/05/13/VSCode-Note/"},{"title":"pyGSM Notes","text":"Reference: GitHub repo from the developer (https://zimmermangroup.github.io/pyGSM/) Personal notes on using pyGSM. InstallationInstall pyGSMFollow README.md on GitHub. git clone https://github.com/ZimmermanGroup/pyGSM.gitconda create -n gsm_envsource activate gsm_envpython setup.py install --prefix ~/.local Install xtbFor some reason if xtb is not installed the program will abort.Install xtb by: conda install -c conda-forge xtb-python Usages References Examples from the wiki pageSome use case related issues: https://github.com/ZimmermanGroup/pyGSM/issues/22 https://github.com/ZimmermanGroup/pyGSM/issues/9A gsm --help information is attached at the end Make input geometry For DE-GSM, Place the geometry of reactant and product in a row in a xyz file. Note that the order of atom should be same in these geometries. Configure environmental resources export MKL_NUM_THREADS=###export OMP_NUM_THREADS=###export OMP_STACKSIZE=###G replace those ### with actual numbersThe are also flags like -mp_cores-nproc Configure pyGSM in the command lineExample: gsm -xyzfile scratch/initial0001.xyz \\ -mode DE_GSM \\ -num_nodes 15 \\ -package xTB_lot > TS-5-simp-gsm.log 2>&1 Frequent using options: xyzfileindicate the path of the input geometry packageSomehow Gaussian is not supported in pyGSM. xTB_lot is a good choice for fast searching for TS. modethe type of the calculation lot_inp_fileif the package is not xTB. A file that indicate the level of theory will be needed. num_nodesThis is the nnodes in the old GSM. Indicate how many nodes is used in the GSM method. restart_fileThe file used for restart the job. Not sure the specific protocol for using this. also there are 2 flags with just lower and upper case difference. This is confusing. In the old GSM, just use the original stringfile.xyz and state RESTART in the job config and run the job. max_gsm_itersDefault:100. Sometimes the GSM job reaches the iter limit and exit without converging. It’s useful to set it to a larger number like 1000. Options for xTB-GSM multiplicity charge xTB_Hamiltonian xTB_electronic_temperature RESTRAINT_FILE ResultThe result will be reported as opt_converged_000.xyz and the bottom of the log file. MiscThe output of gsm --help usage: gsm [-h] -xyzfile XYZFILE [-isomers ISOMERS] -mode {DE_GSM,SE_GSM,SE_Cross} [-only_drive] [-package {QChem,Orca,Molpro,PyTC,TeraChemCloud,OpenMM,DFTB,TeraChem,BAGEL,xTB_lot,ase}] [-lot_inp_file LOT_INP_FILE] [-ID ID] [-num_nodes NUM_NODES] [-pes_type {PES,Avg_PES,Penalty_PES}] [-adiabatic_index [ADIABATIC_INDEX ...]] [-multiplicity [MULTIPLICITY ...]] [-FORCE_FILE FORCE_FILE] [-RESTRAINT_FILE RESTRAINT_FILE] [-optimizer OPTIMIZER] [-opt_print_level OPT_PRINT_LEVEL] [-gsm_print_level GSM_PRINT_LEVEL] [-xTB_Hamiltonian {GFN2-xTB,GFN1-xTB}] [-xTB_accuracy XTB_ACCURACY] [-xTB_electronic_temperature XTB_ELECTRONIC_TEMPERATURE] [-xyz_output_format XYZ_OUTPUT_FORMAT] [-solvent SOLVENT] [-linesearch {NoLineSearch,backtrack}] [-coordinate_type {TRIC,DLC,HDLC}] [-ADD_NODE_TOL ADD_NODE_TOL] [-DQMAG_MAX DQMAG_MAX] [-BDIST_RATIO BDIST_RATIO] [-CONV_TOL CONV_TOL] [-growth_direction {0,1,2}] [-reactant_geom_fixed] [-product_geom_fixed] [-nproc NPROC] [-charge CHARGE] [-max_gsm_iters MAX_GSM_ITERS] [-max_opt_steps MAX_OPT_STEPS] [-only_climb] [-no_climb] [-optimize_mesx] [-optimize_meci] [-restart_file RESTART_FILE] [- MP_CORES] [-dont_analyze_ICs] [-hybrid_coord_idx_file HYBRID_COORD_IDX_FILE] [-frozen_coord_idx_file FROZEN_COORD_IDX_FILE] [-conv_Ediff CONV_EDIFF] [-conv_dE CONV_DE] [-conv_gmax CONV_GMAX] [-DMAX DMAX] [-sigma SIGMA] [-prim_idx_file PRIM_IDX_FILE] [-reparametrize] [-interp_method INTERP_METHOD] [-bonds_file BONDS_FILE] [-start_climb_immediately] [--ase-class ASE_CLASS] [--ase-kwargs ASE_KWARGS]Reaction path transition state and photochemistry tooloptional arguments: -h, --help show this help message and exit -xyzfile XYZFILE XYZ file containing reactant and, if DE-GSM, product. -isomers ISOMERS driving coordinate file -mode {DE_GSM,SE_GSM,SE_Cross} GSM Type (default: DE_GSM) -only_drive -package {QChem,Orca,Molpro,PyTC,TeraChemCloud,OpenMM,DFTB,TeraChem,BAGEL,xTB_lot,ase} Electronic structure theory package (default: QChem) -lot_inp_file LOT_INP_FILE external file to specify calculation e.g. qstart,gstart,etc. Highly package specific. -ID ID string identification number (default: 0) -num_nodes NUM_NODES number of nodes for string (defaults: 9 DE-GSM, 20 SE- GSM) -pes_type {PES,Avg_PES,Penalty_PES} Potential energy surface (default: PES) -adiabatic_index [ADIABATIC_INDEX ...] Adiabatic index (default: [0]) -multiplicity [MULTIPLICITY ...] Multiplicity (default: [1]) -FORCE_FILE FORCE_FILE Constant force between atoms in AU,e.g. [(1,2,0.1214)]. Negative is tensile, positive is compresive -RESTRAINT_FILE RESTRAINT_FILE Harmonic translational restraints -optimizer OPTIMIZER The optimizer object. (default: eigenvector_follow Recommend LBFGS for large molecules >1000 atoms) -opt_print_level OPT_PRINT_LEVEL Printout for optimization. 2 prints everything in opt. -gsm_print_level GSM_PRINT_LEVEL Printout for gsm. 1 prints ? -xTB_Hamiltonian {GFN2-xTB,GFN1-xTB} xTB hamiltonian -xTB_accuracy XTB_ACCURACY xTB accuracy -xTB_electronic_temperature XTB_ELECTRONIC_TEMPERATURE xTB electronic temperature -xyz_output_format XYZ_OUTPUT_FORMAT Format of the produced XYZ files -solvent SOLVENT Solvent to use (xTB calculations only) -linesearch {NoLineSearch,backtrack} default: NoLineSearch -coordinate_type {TRIC,DLC,HDLC} Coordinate system (default TRIC) -ADD_NODE_TOL ADD_NODE_TOL Convergence tolerance for adding new node (default: 0.01) -DQMAG_MAX DQMAG_MAX Maximum step size in single-ended mode (default: 0.8) -BDIST_RATIO BDIST_RATIO Reaction completion convergence in SE modes (default: 0.5) -CONV_TOL CONV_TOL Convergence tolerance for optimizing nodes (default: 0.0005) -growth_direction {0,1,2} Direction adding new nodes (default: 0) -reactant_geom_fixed Fix reactant geometry i.e. do not pre-optimize -product_geom_fixed Fix product geometry i.e. do not pre-optimize -nproc NPROC Processors for calculation. Python will detect OMP_NUM_THREADS, only use this if you want to force the number of processors -charge CHARGE Total system charge (default: 0) -max_gsm_iters MAX_GSM_ITERS The maximum number of GSM cycles (default: 100) -max_opt_steps MAX_OPT_STEPS The maximum number of node optimizations per GSM cycle (defaults: 3 DE-GSM, 20 SE-GSM) -only_climb Only use climbing image to optimize TS -no_climb Don't climb to the TS -optimize_mesx optimize to the MESX -optimize_meci optimize to the MECI -restart_file RESTART_FILE restart file -mp_cores MP_CORES Use python multiprocessing to parallelize jobs on a single compute node. Set OMP_NUM_THREADS, ncpus accordingly. -dont_analyze_ICs Don't post-print the internal coordinates primitives and values -hybrid_coord_idx_file HYBRID_COORD_IDX_FILE A filename containing a list of indices to use in hybrid coordinates. 0-Based indexed -frozen_coord_idx_file FROZEN_COORD_IDX_FILE A filename containing a list of indices to be frozen. 0-Based indexed -conv_Ediff CONV_EDIFF Energy difference convergence of optimization. -conv_dE CONV_DE State difference energy convergence -conv_gmax CONV_GMAX Max grad rms threshold -DMAX DMAX -sigma SIGMA The strength of the difference energy penalty in Penalty_PES -prim_idx_file PRIM_IDX_FILE A filename containing a list of indices to define fragments. 0-Based indexed -reparametrize Reparametrize restart string equally along path -interp_method INTERP_METHOD -bonds_file BONDS_FILE A file which contains the bond indices (0-based) -start_climb_immediately Start climbing immediately when restarting.ASE: ASE calculator options --ase-class ASE_CLASS ASE calculator import path, eg. "ase.calculators.lj.LennardJones" --ase-kwargs ASE_KWARGS ASE calculator keyword args, as JSON dictionary, eg. {"param_filename":"path/to/file.xml"}Example of use:--------------------------------gsm -mode DE_GSM -xyzfile yourfile.xyz -package QChem -lot_inp_file qstart -ID 1","link":"/2022/02/25/pyGSM-Notes/"},{"title":"免疫证明-天津国际旅行卫生保健中心","text":"Hey, password is required here. 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password is required here. 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password is required here. 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map)","text":"提了摩托车之后手机支架还没到，只用听的导航很没有安全感，想到小米手表或许可以辅助查看导航，于是查到了在MIUI for watch上安装第三方应用从而使用google map的方法 原教程链接 步骤下载adb工具和安装包在https://developer.android.google.cn/studio/releases/platform-tools 下载adb命令行工具 在play商店获得谷歌地图的页面链接通过apkDownloader下载apk包注意在商店直接下载的新版谷歌地图貌似无法在小米手表上使用(2022.7.6)使用文初教程链接中的安装包即可 使用adb工具安装apk包开启adb调试在设置-系统-关于中多次点击版本号开启开发者模式在设置-开发者选项中开启adb调试与wifi调试并记录ip地址与调试端口 安装apk包使用adb工具建立调试连接 {path-to-adb.exe} connect {ip:port} 安装软件包 {path-to-adb.exe} install {path-to-package.apk} 终止连接 {path-to-adb.exe} kill-server","link":"/2022/07/06/%E5%9C%A8%E5%B0%8F%E7%B1%B3%E6%89%8B%E8%A1%A8%E4%B8%8A%E5%AE%89%E8%A3%85apk-google-map/"},{"title":"动力与设想","text":"Hey, password is required here. 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password is required here. 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password is required here. 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password is required here. 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password is required here. 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不成熟的软件环境管理ACCRE上的软件看起来是用他们自己改的一个module完成的，其中涉及诸多问题 悄悄改环境在load charmm的时候module spider charmm/43b2只显示需要前置载入GCC/6.4.0-2.28 OpenMPI/2.1.1但是load完成之后module list中会多出Python/2.7.14以及numpy/1.13.1-Python-2.7.14等大量未说明的环境 库共存机制在编译软件时需要OpenMPI > 4.0但是module load 很多软件例如Amber都要求前置load一个低版本的OpenMPI和GCC 明明高版本的库可以向下兼容 导致需要反复调整库设置才能正常编译/运行 软件环境耦合在load amber的时候只能使用一个叫Amber/17-Python-2.7.14的版本这个版本会附带大量的过时的 耦合的 其他环境配置的改变就以python为例，正常的Amber安装中有些脚本需要python2.7来运行，并在这些脚本开头会指定使用amber内部附带的一个python环境ACCRE的安装中，首先先全局配置了一个python2.7，修改了默认的python路径到这个python2.7同时全局配置了一系列python2用的低版本的包（例如numpy）这导致即使使用conda虚拟环境更换了python的路径，numpy等包的传入路径还优先从ACCRE load的低版本目录中查找然后导致如下错误： ImportError:Importing the multiarray numpy extension module failed. Mostlikely you are trying to import a failed build of numpy.If you're working with a numpy git repo, try `git clean -xdf` (removes allfiles not under version control). Otherwise reinstall numpy. 这是如果unload这个numpy，Amber里的那些脚本就都不能用了。这无疑是软件环境管理的失败。并导致同时使用这些Amber脚本的python软件开发无法进行。 解决方案用自己装的Amber 不稳定的软件安装在ACCRE上用Gaussian和Amber总是能遇见从来没见过的不可重复的错误Amber: - Download failed an illegal memory access was encounteredGaussian: 有过 忘了 过时的软件支持@shone：singularity只有accre自己的tensorflow1.7的镜像，没有其他常用软件包镜像，且没有给制作镜像的节点 accre能够使用的多节点运算例子，我忘记那个软件是啥了，是一个他们压根就没装的软件 （xs） 吝啬不知道为什么软件不能让ACCRE买，每年交的钱和学校的funding包含这部分软件购置的钱吗？至少expanse是附带各种常用学术软件的access的@shone：还有，他们偷偷吞用户下的默认存储空间；就是我们买了10TB的空间，结果默认的40GB的home空间不见了 怠惰装软件@shone: 安装alphafold帮助他们写好了手把手的安装教程不愿意搞。帮他们装好了放在自己的目录底下，只要拷贝到公共目录就可以用。结果他们不用 物理学不存在了 （随时间变化的bug）有一次跑EnzyHTP发现跑到PDBMin一步提交任务时直接失败而且不产生slurm-xxx.out文件手动尝试提交也是相同的情况过了一个小时后就好了","link":"/2022/04/25/%E8%AE%BAACCRE%E4%B8%BA%E4%BB%80%E4%B9%88%E6%9C%89%E7%BD%AA/"},{"title":"Amber MD关键字","text":"之前了解了一遍Amber动力学输入文件中关键字的含义，但是几个月不用再一看又不熟悉了。为此做一个方便快速检索参考的中文笔记。 MD模拟 输入关键字这是我使用的production步的输入文件 prod.inEquilibration:constant pressure &cntrl imin = 0, ntx = 5, irest = 1, # 工作类型、读取设置 ntf = 2, ntc = 2, # SHAKE束缚 nstlim= 50000000, dt= 0.002, # 模拟时长 cut = 10.0, # 截断 temp0 = 300.0, # 温度 ntt = 3, gamma_ln = 5.0, # 温度控制 ntb = 2, ntp = 1, # 周期性边界的类型，系综 ntpr = 25000, ntwx = 5000, # 输出：写入频率 iwrap = 1, # 输出：坐标居中 ig = -1, # 随机化 / 其中功能相关的设置被放置在相近的位置 imin选择任务类型1（最小化）2（MD）5（读取轨线进行再次计算） ntx坐标（-c指定）读取方式1（仅读取笛卡尔坐标）5（读取坐标和速度以进行重启） irest读取rst文件（-c指定）的行为0 （不重启模拟，不读取速度，时间设置为0，开始新的模拟）1 （重启模拟，从rst文件中读取坐标和速度，时间继续，不开始新的模拟） ntprout和mdinfo文件的写入频率每ntpr步写入一次，默认为50 ntwx轨线文件的写入频率每ntwx步写入一次，默认是0（不写入） ntwrrst文件的更新频率，减少任务崩溃的损失每ntwr步更新一次，任务结束后也更新一次，默认值等于nstlim（只在任务结束写入一次） iwrap写入到轨线和rst文件中时分子的绝对位置和相对位置：1 （写入每个分子在初始盒子中对应的等价分子，利用平移对称性只用初始盒子的大小描述体系）0 （写入每个分子的绝对位置，往往用于扩散分析，在1的情况下无法分析扩散）类似贪吃蛇*不涉及扩散分析的任务都建议使用iwarp=1 ntf与ntcSHAKE键振动限制，往往设置NTF=NTC目的：MD的基础步长受体系中最快的运动限制，限制最快的X-H振动以获取更大的步长TIP3P也是在限制X-H振动的情况下拟合的，使用该力场需要加对应限制1 （不使用SHAKE）2 （所有含H的键被限制，在dt=0.002时必用）3 （所有键长都被固定） nstlimMD的步数 dtMD的步长，单位：ps，默认为0.001，加氢SHAKE往往使用0.002 cut描述nonbonded截断的范围 单位：埃范围内静电作用使用精确的 QQ/r^2 范围外用Particle Mesh Ewald (PME)方法近似有文献指出需要大于等于10.0，尤其是计算蛋白相互作用时 ntt温度控制0 （体系能量固定，绝热，NVE系综）1 （恒定温度，使用weak-coupling算法：只保证总动能不变，将超出的动能重新分配。不能保证温度在分子各处一致，往往导致低频自由度能量过高，无法保证各自由度间的能量关系）2 （恒定温度，使用Anderson-like算法：每隔vrand步就模拟碰撞，随机的重置体系中的速度以符合设定温度。会导致轨线没有绝对时间相关的意义，只有在vrand步之内可以进行绝对时间相关的分析，vrand值太小会导致构象空间的探索变慢(默认1000)）3 （恒定温度，使用Langevin算法：使用gamma_ln设置的$\\gamma$值，有时会崩溃？）9 （恒定温度，使用优化的Isokinetic Nose-Hoover chain ensemble (OIN)方法：貌似是为了使用一些加速步进的方法？）10（恒定温度，使用Stochastic Isokinetic Nose-Hoover RESPA integrator方法：貌似是为了使用一些加速步进的方法？Tuckerman组开发）11（Berendsen控温器，之后用到了再补充） nmropt0 (默认)无nmr分析1 读入NMR限制和权重变化 （控制恒温器温度变化）2 读入NMR限制、权重变化、NOESY volumes、化学位移、残基偶极限制 temp0设定恒定温度值，大于300时需要降低步长 tempi初始温度，用于heat步，初始速度使用maxwellian分布可增加温度控制段，设置在不同阶段温度的变化，如： heat.in >folded&wt type = 'TEMP0', istep1= 0, istep2=18000, value1= 0.0, value2=300.0, #在前18000步升温至300K/&wt type = 'TEMP0', istep1= 18001, istep2=20000, value1= 300.0, value2=300.0, #在后2000步保持恒温/&wt type = 'END',/ ig决定初始速度的随机种子，也决定了Langevin和Anderson-like方法中的伪随机值-1 （时间相关的随机种子）默认其他值 （固定种子，一般只在调试时使用） ntp压力控制，逐渐调整cell体积以达到设定压力0 （无压力控制，默认）1 （使用各向同性位置修正）2 （使用各向异性位置修正，只能用于正交盒子，一般用于膜系统的模拟）3 （使用半各向异性位置修正，只能用于正交盒子和恒定表面张力体系，将表面切向的两个压力耦合在一起） pres0恒定压力值，单位bar，默认为 1.0 ntb周期性边界的类型, Amber20中不需要单独设置0 （无周期性边界 关闭PME 微观系综）1 （定容）2 （定压） ntr用简谐势在笛卡尔空间中限制原子位置需要指定参考结构-ref 目标原子 和 力常数0 （不限制）1 （限制） restraint_wt位置限制的权重，单位：$kcal·mol^{−1}·Å^{−2}$设置$k(\\Delta x)^2$ 中的k值 restraintmask描述目标原子，语法： 描述基元起始符: 起始选择残基@ 起始描述原子序号/名称选择可以用 , 分隔和 - 连接的序号描述 例：:1-10,12 和 @12,54-85可以用残基/原子名称描述 例：:ARG,ALA 和 @CA,C,O可以用原子类型描述 但是需要在 @ 后加 % 例： @%N*,N3可以用 :* 描述所有结构，注意！不是通配符，貌似是由于有些原子类型里包含星号如C*可以用 = 充当通配符，但是只能在字符之后 例:@H= 描述所有H原子 描述基元间逻辑关系& 或 | 与 ! 非距离关系<:数字 与 >:数字 在数字范围之内/之外的所有残基<@数字 与 >@数字 在数字范围之内/之外的所有原子*可以用()描述结合的优先级 可以用ambmask测试ambmask -p prmtop -c inpcrd -out [short| pdb| amber] -find [maskstr]会输出选中原子到stdout 施加基于内坐标的constraintNMR restraint的方案 Amber tutorialhttp://ambermd.org/Questions/constraints.html 在.in文件中加入nmropt=1关键字，在结尾添加DISANG={path-to-rs-file} 制作.rs文件描述restraint &rst iat={atom_idx},{atom_idx}, r1=抛物线势左起点, r2=抛物线势左终点, r3=抛物线势右起点, r4=抛物线势右终点, rk2=左边抛物线力常数, rk3=右边抛物线力常数,ir6={指定一组原子时确定中心的方式}, ialtd={在势极大时的行为/是否将偏离过大的结构拖回}&end 验证MD结果是否有效查看out文件中的参数随轨线步数变化使用process_mdout.perl脚本处理 perl process_mdout.pl 文件名 用cpptraj查看RMSD cpptraj.inparm *prmtoptrajin *ncrms ToFirst out 名称.rmsd @CA,C,N #restraintmask描述的目标原子run 如果在prod步之前密度、温度、能量、rmsd都收敛，同时prod中这几项稳定则认为prod产生的数据可以用于采样 关于提升GPU下的计算效率Amber文档中给出的最大化GPU加速效率的建议： 避免使用过高的写入频率（小的NTPR, NTWX, NTWV, NTWE, NTWR） 避免$ntave \\neq 0$ 避免在不必要时使用NPT系综，考虑使用Monte Carlo barostat (barostat=2) 使用gbsa=3而不是gbsa=1，前者适合GPU 使用langevin温度控制会稍微降低速度 MMPBSA 与 MMGBSA将结合自由能拆分成气相的结合自由能和三个物种各自的溶剂化自由能$\\Delta G_{solv,bind}^0 = \\Delta G_{bind,vacuum}^0+\\Delta G_{solv,complex}^0−(\\Delta G_{solv,ligand}^0+\\Delta G_{solv,receptor}^0)$GB（Generalized Born）和PB（Poisson-Boltzman）描述不同的求解溶剂化自由能中静电部分的方法使用LCPO方法求解疏水部分的贡献J. Comput. Chem., 2016, 37, 2436–2446关于参数选取 准备文件需要准备三部分文件： 轨线（.nc） 描述配体、受体、复合物和溶剂化复合物的拓扑文件（.prmtop） 为PB/GB设置合适的PBRadii该设置(只作用用隐式溶剂模型)不影响常规(即使用显式溶剂)MD计算 相关讨论可以通过set修改leap的全局设置之后生成新的prmtop文件 set default PBRadii mbondi2 也可以通过ParmEd修改现有的prmtop文件 parmed -p <your_prmtop> -i input_file input_file中为 parmed.inchangeRadii mbondi2parmout new_radii.prmtop 参数参考 值 igb值 bondi 7 mbondi 1 mbondi2 2 or 5 mbondi3 8 分别为三部分结构生成不含溶剂的拓扑文件 同时需要了解体系的离子强度 设置输入文件（.in）格式类似MD的输入文件$AMBERHOME/bin/MMPBSA.py --input-file-help可以查询可设置选项 MMPBSA.inSample input file for GB and PB calculation&general startframe=5, endframe=100, interval=5, verbose=2, keep_files=0,/&gb igb=5, saltcon=实际离子浓度,/&pb istrng=实际离子浓度, fillratio=4.0,/ startframe & endframe 描述开始和结束的帧interval 步长keep_files 默认是1（保留所有轨迹文件和mdout）0（删除所有）2（保留所有）(*关于巨大的reference.frc 重编译有些时候不太显示，希望之后amber能给个选项)verbose 0（只输出差值部分）1（也输出组分的数据）2（增加bonded terms） saltcon 盐浓度（单位：M） istrng 离子强度（单位：M） fillratio 矩形有限差分网格的最长维度与溶质的最长维度之比。对于与水尺度类似的溶剂一般不用改 gb和pb部分设置对应的参数 运行$AMBERHOME/bin/MMPBSA.py -O -i MMPBSA.in -o FINAL_RESULTS_MMPBSA.dat -sp complex_solvated.prmtop -cp complex.prmtop -rp receptor.prmtop -lp ligand.prmtop -y *.mdcrd 或者使用并行版 mpirun -np 核数 $AMBERHOME/bin/MMPBSA.py.MPI -O -i MMPBSA.in -o FINAL_RESULTS_MMPBSA.dat -sp complex_solvated.prmtop -cp complex.prmtop -rp receptor.prmtop -lp ligand.prmtop -y *.mdcrd TIPS for COMET USER在comet上没有直接的MMPBSA.py.MPI文件 经过咨询了解到可以直接讲MMPBSA.py复制到自己目录下为MMPBSA.py.MPI参考的提交脚本： RunMMPBSA.sh >folded> #!/usr/bin/env bash> #SBATCH --job-name=name> #SBATCH --partition=compute> #SBATCH -N 1> #SBATCH --ntasks-per-node=24> #SBATCH --mem=100GB> #SBATCH -t 48:00:00> #SBATCH --signal=B:SIGUSR1@60> #SBATCH --verbose> #SBATCH --hint=nomultithread> #SBATCH --mail-user=mail> #SBATCH --mail-type=all> > #Run MMPBSA> module purge> module load amber> module load intel> module load mpi4py> > ibrun python3 /path/to/MMPBSA.py.MPI .... options ...> 计算结果计算会在当前目录下输出 *.mdcrd GB和PB计算过程中分析过的坐标 *.mdout 所有指定帧的能量 –> 并行按后缀依次合并即可 *.pdb 平均结构的PDB文件,可进行准简谐熵计算 FINAL_RESULTS_MMPBSA.dat 结果输出文件 其中结果输出文件中会输出组分能量项： VDWAALS $H_{MM,vdw}$分子力场能的vdw部分 EEL $H_{MM,ele}$分子力场能的静电部分 (不包含周期性边界条件cut=999.0) EPB/EGB $E_{solv,ele}$溶剂化自由能的静电部分，由PB或GB计算 ESURF $E_{solv,nonpolar}$ ？？有什么区别 (GB only) ENPOLAR $E_{solv,nonpolar}$ 非极化作用的空穴部分 // 在mdout文件里也被写做ECAVITY (PB only) EDISPER $E_{solv,nonpolar,disper}$ 非极化作用的色散部分 (PB only) 其中并行相关的帧分配方式：将所有帧连续的分成MPI.COMM_WORLD.get_size()块之后，块的大小通过平均后渐进的方式决定 MMPBSA_mods.make_trajs.py >folded# Sanity checkif traj.processed_frames < size: raise MMPBSA_Error('Must have at least as many frames as processors!')# We now know how many frames we have in total, so make a list that lists the# number of frames found for each rank, and assign extra frames incrementallyframes_per_rank = traj.processed_frames // sizeextras = traj.processed_frames - frames_per_rank * sizeframe_count = [frames_per_rank for i in range(size)]for i in range(size): if i < extras: frame_count[i] += 1# Dump our complex trajectoriesif INPUT['full_traj'] or INPUT['entropy']: traj.Outtraj(pre + 'complex.%s' % trj_suffix, filetype=INPUT['netcdf'])traj.Outtraj(pre + 'complex.pdb', frames='1', filetype='pdb')traj.Outtraj(pre + 'dummycomplex.inpcrd',frames='1',filetype='restart')# Now dump thread-specific trajectorieslast_frame = 1for i in range(size): frame_string = '%d-%d' % (last_frame, last_frame+frame_count[i]-1) traj.Outtraj(pre + 'complex.%s.%d' % (trj_suffix, i), frames=frame_string, filetype=INPUT['netcdf']) last_frame += frame_count[i] 根据mdout文件的逐帧分析/作图脚本https://github.com/shaoqx/CalcKit/tree/master/Misc_scripts/MMPBSA提取每一帧各能量项的数值，可以容易的分析和作图 MMPBSA中包含的熵分子力场项 - 不包含熵溶剂静电PB项 - 不包含熵溶剂非极性部分(inp=2) - 1. 形成空穴（溶剂内聚能破坏，溶剂熵减）2. 溶质溶剂吸引（VDW作用） MMPBSA中的周期性边界条件查看具体的模块发现计算MM部分能量时使用的是无周期性边界条件(igb>0时默认关闭周期性边界条件ntb=0，cut=999.0)这就意味着盒子的大小和形状会对结果产生影响（离子的位置？）！！如果用长方形盒子必然会导致GPU在equi步报错！！ 关于各种选项根据Expert Opin Drug Discov. 2015 May 4; 10(5): 449–461.一文，总结一些在用MMPBSA研究新体系的思考： 一般可选择的有： PB/GB 3A/1A 关键水的处理 计算熵的方法根据文中的建议，这些选择和对研究的具体体系有一定的依赖性，最好在研究之前benchmark 采样方法：文中建议使用多次短模拟合并采样的方法，以降低SD为标准，正在测试其可靠性使用循环多次跑prod步for i in {1..20}; do pmemd.cuda -O -i ./MD/prod.in -o ./MD/prod${i}.out -p *.prmtop -c ./MD/equi.rst -ref ./MD/equi.rst -r ./MD/prod_${i}.rst -x ./MD/prod_${i}.nc; done 之后用cpptraj合并parm ../*.prmtoptrajin prod*.nc 200 lastautoimagetrajout prod.ncgo 对比； 跑100ns取后90ns，每10ps一帧取9000帧分析 （结果比较接近实验值） 跑100ns取后90ns，每30ps一帧取3000帧分析 （结果比较接近实验值） 跑20条5ns 每个轨迹取后4.5ns，每10ps一帧合起来共9000帧 （结果很差） 跑20条5ns 每个轨迹取后4.5ns，每30ps一帧合起来共3000帧 （结果很差） 非标准残基的参数化 相关参考教程例子 http://ambermd.org/antechamber/pro4.html 从PDB中复制非天然氨基酸的几行保存为新文件(每类一个即可) 注意需要把空缺的化合价补全，一般最后是一个独立氨基酸的结构，否则antechamber难以正确判断原子类型 使用antechamber生成ac文件 antechamber -fi pdb -i {输入路径.pdb} -fo ac -o {输出路径.ac} -c bcc -at amber -nc {净电荷数} “Note that antechamber is mostly set up to use gaff atom types, so it occasionally makes a mistake with the Amber atom types.” 这要怎么自动化啊，问题看起来是随机的，要怎么确定什么原子类型是正确的？貌似每次都会把N给错 *注意生成的ac文件会修改原子名称，会将所有数字开头的原子名称修改 制作描述和蛋白其他部分连接方式的mc文件(mianchain) XXX.mc >foldedHEAD_NAME {连接前一个氨基酸的原子名，如N1}TAIL_NAME {连接后一个氨基酸的原子名，如C3}MAIN_CHAIN {从head到tail依次的原子名}MAIN_CHAIN {...}MAIN_CHAIN {...}MAIN_CHAIN {...}OMIT_NAME {需要从最终结构中删除的原子，如某些构建方式中会多出来的H}OMIT_NAME {...}OMIT_NAME {...}OMIT_NAME {...}PRE_HEAD_TYPE {前一个氨基酸用来连接改氨基酸的原子类型，如C}POST_TAIL_TYPE {后一个氨基酸用来连接改氨基酸的原子类型，如N}CHARGE {净电荷数} 使用prepgen生成prepin文件 prepgen -i {输入路径.ac} -o {输出路径.prepin} -m {mc文件路径.mc} -rn {残基名} 使用frcmod第一次使用天然氨基酸的参数(ff14SB)参数化 parmchk2 -i {输入路径.prepin} -f prepi -o {输出路径.frcmod} -a Y -p $AMBERHOME/dat/leap/parm/parm10.dat 将没有参数化的部分用gaff生成的参数补全 grep -v "ATTN" {路径.frcmod} > {路径.frcmod1} # Strip out ATTN linesparmchk2 -i {路径.prepin} -f prepi -o {路径.frcmod2} 最后得到两个参数文件 使用prepin和两个frcmod文件通过tleap完成最后的参数整合 MCPB.py的使用 参考官网教程http://ambermd.org/tutorials/advanced/tutorial20/mcpbpy.htm相关教程http://bbs.keinsci.com/thread-26531-1-1.html MCPB.py [flags] [options]-i 输入文件-s 步骤数 目标参数化金属中心(MetalUnit)以及附近的配体残基（非标准质子态）（非标准连接方式） 流程大致流程是： 制作目标蛋白模型 从目标模型中提取出各种参数化相关的组件(mol2格式) 使用MCPB.py根据提供的组件自动生成Gaussian输入文件 Gaussian计算，利用MCPB.py自动读取输出文件中的信息完成参数化 I. 制作目标蛋白模型(preparation)根据研究需求制作目标蛋白的MD-ready模型要求： 无原子缺失(蛋白，cofactor，底物，水 的轻重原子) 正确的质子态(确定配体、水的质子朝向合理) cofactor处于合理的binding位置 底物处于合理的binding位置 包含必要的active site water 转换为amber格式的pdb并重置index pdb4amber -i {输入路径} -o {输出路径} II. 提取目标蛋白模型组件(mol2文件)以及非天然氨基酸和配体的frcmod参数文件“MCPB.py uses mol2 files based on the residue names” - 只要保证各组件残基名称和PDB中保持一致即可“You need to create different mol2 files for different TYPES of metals, water, and NCAA in the PDB file” - 每类组件只需要一个mol2文件 金属离子 从蛋白的PDB中，复制金属离子的一行保存为新文件(一个原子即可) 运行metalpdb2mol2.py脚本，指定电荷，并生成mol2文件python metalpdb2mol2.py -i {输入路径} -o {输出路径} -c {电荷数} Active site water 水 从PDB中复制水的几行保存为新文件(一个水即可)(*需要氢和朝向正确) 使用antechamber生成mol2文件antechamber -fi pdb -fo mol2 -i WAT_H.pdb -o WAT.mol2 -at amber -c bcc -pf y 将mol2中的原子类型从oh和ho修改为OW和HW (例) 配体（cofactor和底物） 从PDB中复制配体的几行保存为新文件(每类一个配体即可) 使用antechamber生成mol2文件antechamber -fi pdb -fo mol2 -i {输入路径} -o {输出路径} -c bcc -pf y -nc {配体净电荷数} *注意最后保存的mol2文件的名称要和PDB中配体的残基名一致 生成frcmod文件parmchk2 -i {输入路径} -o {输出路径} -f mol2 非天然氨基酸(modified AA) 参考”非标准残基的参数化”一节生成prepin,frcmod1,frcmod2文件 将prepin文件转换为mol2文件 antechamber -fi prepi -i {输入路径.prepin} -fo mol2 -o {输出路径.mol2} -nc {净电荷数} *注意最后保存的mol2文件的名称要和PDB中配体的残基名一致*检查mol2中的原子类型名称和prepin中的是否一致 III. 使用MCPB.py生成Gaussian输入文件 配置MCPB计算制作.in配置文件 mcpb.in >foldedoriginal_pdb {完整模型路径.pdb}group_name {自定义一个名字}cut_off {参数化区域选择范围，默认填2.8}ion_ids {金属的原子序号 (空格分隔可以多个,但是只能是一个金属complex里的多个)}ion_mol2files {金属的mol2文件 (空格分隔可以多个,但是只能是一个金属complex里的多个)}naa_mol2files {非天然氨基酸的mol2文件 *配体、水、cofactor、modified AA (空格分隔可以多个)}frcmod_files {补充的参数文件 *配体、cofactor、modified AA (空格分隔可以多个)}large_opt {是否优化大模型，默认填1 (1：只优化H、0：不优化)}software_version {g16或g09} 不在金属中心附近的mol2和frcmod文件影响什么 我不小心没加上但是也没有报错？ 不在目标金属中心附近的NCAA的mol2和frcmod文件貌似不影响结果，测试了在mcpb.in中加和不加两种情况得到的最终的mol2文件和frcmod文件没有区别貌似只影响最后生成的tleap.in文件 运行MCPB生成com文件 MCPB.py -i {路径.in} -s 1 此步会生成小模型、标准模型和大模型的PDB和fingerprint文件。还会生成小模型和大模型的高斯输入文件。 大模型 的高斯输入文件将首先对氢原子进行优化，以纠正任何放置不当的氢原子。 标准模型fingerprint文件（1mlw_standard.fingerprint）包含标准模型中原子的原子类型信息（第3列是原始原子类型，最后一列是最终分配的原子类型）。金属离子的原子类型（名称以 M 开头）和连接原子（名称以 Y/Z 开头）会自动重命名，以将它们与 AMBER 力场中的其他原子类型区分开来。(为了参数化后的识别) 可以将 step_number 设为 1n 来强制不重命名任何原子类型并生成fingerprint文件，然后手动修改（在此之前，请检查 AMBER force field parm*.dat 文件以确保金属离子和连接原子类型 不与amber已有的原子类型冲突）。 fingerprint文件在文件末尾还包含金属离子与周围原子之间的链接信息，开头字母为“LINK”。用户还可以根据自己的需要手动修改它们（例如，如果 QM 几何优化后有任何连接更改） 运行Gaussian计算 MCPB.py生成的输入文件默认用的是B3LYP/6-31G*、2核、3000MB。建议至少改为B3LYP-D3并根据实际资源修改核数和内存设置 g16 < 1OKL_small_opt.com > 1OKL_small_opt.logg16 < 1OKL_small_fc.com > 1OKL_small_fc.logformchk 1OKL_small_opt.chk 1OKL_small_opt.fchkg09 < 1OKL_large_mk.com > 1OKL_large_mk.log 这步得到的3个log文件和fchk文件需要被放置在与第一次运行MCPB.py相同的路径 *需要检查优化得到的结构中配位键是否断裂，如果断裂需尝试： 更换理论层级 先固定优化其他坐标之后放开优化配位键 IV. 使用MCPB.py读取Gaussian输出文件并生成参数 生成frcmod参数文件在运行第一步的目录运行 MCPB.py -i 1OKL.in -s 2 *注意运行该步的时候目录下不能存在temp文件夹，该脚本貌似会生成一个temp文件 拟合电荷并生成mol2文件 MCPB.py -i 1OKL.in -s 3 默认使用charge model B 生成tleap输入文件和修改残基名后的PDB MCPB.py -i 1OKL.in -s 4 获得 {名称}_mcpbpy.pdb {名称}_tleap.in V. 运行tleap.in完成参数化tleap -s -f {名称}_tleap.in 需要在tleap.in文件中加入所有非天然氨基酸、配体的参数对应命令 可以改为用protein.ff14SB和water.TIP3P吗？为什么会报错Residues lacking connect0/connect1？ 貌似是使用mol2和bond组合的正常表现 V-1. （对于多聚体）修改pdb和tleap以适配其他金属中心对于多聚体，其他对称的金属中心可以使用其中一个金属中心MCPB得到的参数 但是需要修改tleap.in和PDB使tleap可以讲其识别到对应的参数 修改_mcpbpy.pdb中其他金属中心的残基名参考MCPB.py第四步中输出的改名位点，例： XXX.mc >foldedRenamed residues includes: 519-HIDRenamed residues includes: 521-HIDRenamed residues includes: 684-HIERenamed residues includes: 1441-CURenamed residues includes: 1445-WAT 修改其他链中对应的名称 修改_tleap.in中的bond语句为其他链的金属中心和配体添加对应的键，例： XXX.mc >foldedbond mol.519.NE2 mol.1441.CUbond mol.521.NE2 mol.1441.CUbond mol.684.ND1 mol.1441.CUbond mol.1441.CU mol.1445.Obond mol.518.C mol.519.Nbond mol.519.C mol.520.Nbond mol.520.C mol.521.Nbond mol.521.C mol.522.Nbond mol.683.C mol.684.Nbond mol.684.C mol.685.Nbond mol.1239.NE2 mol.1446.CUbond mol.1241.NE2 mol.1446.CUbond mol.1404.ND1 mol.1446.CUbond mol.1446.CU mol.1450.Obond mol.1238.C mol.1239.Nbond mol.1239.C mol.1240.Nbond mol.1240.C mol.1241.Nbond mol.1241.C mol.1242.Nbond mol.1403.C mol.1404.Nbond mol.1404.C mol.1405.N V-2. （对于多个不同金属中心）修改pdb和tleap.in MCPB.py新加的原子类型名称都使用默认名称导致重复，需要更改重复的原子类型名称以适配多次MCBP生成的mol2和frcmod文件 将重复的M1,Y1等原子类型重命名之后合并到tleap.in中 在frcmod, mol2文件中查找替换成修改后的原子类型名称 将mol2文件和frcmod文件合并至tleap.in中在此步注意如果有重复的残基名（例如有两个不同的Ca2+中心时都会被命名为CA1）需要在mol2文件和tleap.in都更改为彼此独特的残基名（如CA2）**注意 CA2 = loadmol2 xxxx.mol中等号左边的名字符合和pdb配对 一定要修改 将bond指令合并至tleap.in中 将更新后的残基名合并到同一个pdb文件中 如果两个不同的金属中心彼此比较接近/有共享的配体则难以以此方式合并参数，会引起一系列的参数确实错误有些时候对于辅助折叠的金属中心可以使用nonbonded model来描述 Misc注意antechameber生成的mol2文件中的原子类型可能不规范 pymol可能会不识别从而转存的时候将原子名称搞错 教程中提到需要修复原子序号的问题，但是没有修复也不怎么影响模拟，跑了100ns都没问题 轨线输出文件格式 mdcrd： ASCII编码的纯坐标 每帧由中心的三个坐标组成的一行分割 帧内由连续的每个原子的xyz坐标组成（每行10个数值）amber.mdcrd >foldedCpptraj Generated trajectory 17.357 12.865 14.673 17.869 12.805 13.804 16.361 12.909 14.514 17.650 12.025 15.151 17.683 14.091 15.410 17.493 14.988 14.820 17.057 14.204 ... 33.227 24.489 1.071 33.789 24.515 1.846 32.350 24.321 1.417 58.637 58.637 58.637 ... [next frame] NetCrd(.nc/.crd): 二进制的坐标文件可以通过cpptraj将这些格式以及pdb相互转换 Umbrella Sampling模拟与分析 目标沿某个预定义的“路径坐标”采样从而得到体系沿该路径变化对应的自由能变化（有平均力势得出；Potential Mean Force） 路径坐标的定义由研究的问题决定并定义了得到的数据的意义 原理将“路径坐标”划分为多个窗口，用势函数约束该窗口的坐标值进行采样（例如：简谐势） 如果在采样后各窗口间采样得到的几何结构在“路径坐标”上有足够重叠，则可以使用WHAM方法去除“约束势函数”带来的bias从而得到自由能曲线 流程 官方教程 官方教程中文版 1. 平衡初始结构与一般的MD模拟相同，参数化并运行min heat equi等步骤 2. 定义路径坐标根据研究的问题定义路径坐标 除明确的几何坐标如二面角之外也可以定义一些近似的路径例如用口袋氨基酸骨架质心与配体质心的距离角度等近似binding的路径坐标 3. 选择Umbrella Sampling的窗口原则 窗口之间在路径坐标上必须重叠（这要求力常数不能太大，间隔不能太大） 窗口要尽可能少 使用简谐势的话 力常数（也就是约束强度）需要足够大来保证采样足够充分（如果路径的内禀势能非常大，例如断强键，力常数需要匹配地大从而保证每个窗口各不相同） 如何先验地得到合适的力常数？ 4. 在每个窗口进行MD模拟以带几何约束的模拟相同，见施加基于内坐标的constraint 每个窗口进行 min，equi，prod 模拟 可以在.in文件中增加 &wt type='DUMPFREQ', istep1=50, # istep1 用于指定记录频率&end 与 DUMPAVE=dihedral_60.dat 部分从而直接输出采样得到的constraint的值 貌似不进行heating了，不过heating本身的必要性也不明确 (https://github.com/openmm/openmm/issues/4240) 运行时长 需要模拟足够长时间从而保证该约束条件下的采样收敛 理想情况下被约束的坐标自己往往涉及较大时间尺度的变化而其余的坐标可以在可接受的模拟时间尺度内收敛 *官方教程建议采样完成后随机去除20%的数据再计算一次PMF来验证其收敛 初始结构 初始结构在路径坐标上的值不宜与约束的目标值相差太大（例如：初始结构为1A 约束在10A） 但是也需要尽可能地平行提交计算任务 常用的策略是手动创建一些中间点的初始结构之后从这些结构开始 或者使顺序运行逐步改变初始结构 验证采样结果 可以做出采样结果在路径坐标上的histogram来判断设置是否有效 重叠是否充分 采样是否全面 5. 用WHAM分析结果 使用 Alan Grossfield 开发的WHAM程序 http://membrane.urmc.rochester.edu/?page_id=126 5.1 安装WHAM 从Alan Grossfield的官网上下载源代码(http://membrane.urmc.rochester.edu/?page_id=126/) 参考manual安装 tar -xvf wham-release-#####.tgz cd wham/whammake cleanmake 注意截至2.0.11版本，WHAM的编译仍不支持GCC 10.2.0，调整环境至GCC 8.2.0方编译成功 5.2 运行WHAM {dir_of_wham}/wham [P|Ppi|Pval] hist_min hist_max num_bins tol temperature numpad metadatafile freefile [num_MC_trials randSeed] P|Ppi|Pval指定反应坐标是周期性的（用于角度坐标）其中P指定360，Ppi指定2pi，Pval指定val的具体值（如P180.0）为一个周期 hist_min hist_max设置目标坐标的分布范围，所有范围外的点都被忽略 num_bins设置窗口数，对应最后自由能图上的点数 tol设置WHAM计算的收敛PMF阈值，单位为kcal/mol temperature指定输入的采样数据对应的温度 numpad指定padding数据点的数量，对于周期性目标坐标起作用，该设置与非周期性目标坐标的计算无关 metadatafile指定输入的数据文件路径 freefile指定输出文件的路径 num_MC_trials randSeed如果指定，错误分析不进行，并使用Monte Carlop bootstrap 错误分析，分别指定fake data的数量和随机种子 用例 wham 14.3 35.7 84 0.01 300.0 0 meta.dat result.dat 其中meta.dat的格式为 /path/to/timeseries/file loc_win_min spring [correl time] [temperature] 其中 /path/to/timeseries/file为数据文件路径 loc_win_min为该窗口的势函数的极小值点 spring为V = 0.5k(x-x0)^2定义下的力常数 correl time只在Monte Carlop bootstrap 错误分析时使用指定该采样集合的相关时间 temperature如果指定覆盖命令行指定的温度 5.3 分析WHAM结果 WHAM的结果为坐标和自由能，直接作图分析 Misctleaptleap自动加氢甚至不会考虑周围的金属离子(如Zn2+等配位中心)，会把旁边的残基质子化而不考虑配位 prepin格式 https://ambermd.org/doc/prep.html利用树和LOOP的方式描述连接 GPU在equi步报错用solvatebox的话就会用solvateOct则不会 迷惑的内存错误Error: an illegal memory access was encountered launching kernel kClearForcescudaMemcpy GpuBuffer::Download failed an illegal memory access was encountered 参考 https://blog.csdn.net/Litedg/article/details/124230876http://archive.ambermd.org/202203/0149.html 说了部分原理 主要的原因： GPU相关的MD精度有限，在涉及巨大的数值的时候会出现该问题 往往意味着结构中有bad contact从而存在巨大力 解决方案： 用CPU跑min步可以解决大部分问题 有一次遇到CPU跑20000步min还遇到这个问题改成100000步就好了","link":"/2020/11/16/Amber-MD%E5%85%B3%E9%94%AE%E5%AD%97/"},{"title":"Python Notes","text":"Python notes, avoid redundant searching 大量变量赋值有时会想到建很多变量之后给他们赋值操作，但是发现这种方式本身无法批量写出，代码又不好写又不可读 结论任何管理大量变量并利用其名称的需求都可以利用自建的字典完成（而不是内建的变量空间！）相关例子 不使用 a = xxxb = xxx... 而是用 dict={}for i in list: dict[i] = xxx 失败的尝试 尝试过使用exec()函数，但是其中完成的变量赋值都在其自己的local字典中，如果写在函数里就和没执行一样。详细 尝试过写一个生成脚本的脚本之后执行生成的脚本。可行是可行，但是又慢又麻烦 程序的命令行选项 argparsepython标准库提供了非常方便的argparse库来完成这部分需求。计划在下个版本的CrestSub用用。相关教程 在使用包含该库的API时可以用parse_args()方法生成需要的命名空间对象。ArgumentParser.parse_args(args=None, namespace=None)其默认值从sys.argv获取，此处通过手动传入arg列表参数完成命名空间对象的创建 例： use_api.py >foldedfrom package import package_main, build_parser #import the ArgumentParser building funcdef use_package(): package_parser = build_parser() args = package_parser.parse_args(['--help','...']) #list of input arguments package_main(args) 选项值语法选项和它的值是作为两个单独参数传入 parser.parse_args(['--foo', 'FOO']) 对于长选项（名称长度超过一个字符的选项），选项和值也可以作为单个命令行参数传入，使用 = 分隔它们即可 parser.parse_args(['--foo=FOO']) 对于短选项（长度只有一个字符的选项），选项和它的值可以拼接在一起 parser.parse_args(['-xX']) 有些短选项可以使用单个 - 前缀来进行合并，如果仅有最后一个选项（或没有任何选项）需要值的话 >>> ...>>> parser.parse_args(['-xyzZ'])Namespace(x=True, y=True, z='Z') pip 直接安装的pdb2pqr是不能用的版本 20/12/21 列表排序sort()方法相关例子参考 列表取随机元素random.choice(list_i)参考 屏蔽函数的标准输出参考 串行中执行系统指令的方案 subprocess.run()在串行中需要执行某个系统语句，执行结束后再继续运行剩余的脚本古老的解决方案是os.system() 仅仅在一个子终端运行系统命令，而不能获取命令执行后的返回信息相对新的os.popen() 可以返回输出结果，但是难以方便的做到运行结束后再执行下一句,需要使用.wait()方法确保串行时执行结束3.5之后加入的subprocess.run()函数看起来是目前最优的方案参考 [文档] (https://docs.python.org/zh-cn/3/library/subprocess.html)常用选项 run('command', check=True, text=True, shell=True, capture_output=True) is 和 == 的区别is是判断id()的返回值是否相同（是否指向同一对象）==是判断值本身是否相同 python中的缓冲输入输出stdout & stderr在测试程序的时候发现自己的日志输出没有及时出现 调查之后发现需要修改export PYTHONUNBUFFERED=1 或在运行是加-u详解 关于命令行参数 f.write()发现使用write写入文件是也会被缓冲，无法及时输出通过在打开文件时设置缓存为0同时用二进制方法写入参考 原地动态输出（覆盖旧内容）print(f'Working on {i}/100', end='\\r', flush=1) end='\\r'使得光标回到行首 flush刷新输出 使得缓存的输出被写出 x +=1 和 x = x + 1可变元素的类型中，x +=1与x = x+1作用不同，区别如下：x +=1，修改x自身的值x = x+1，创建一个新的”同名”对象x，并将x+1，赋值给新创建的同名变量x（它的含义和y = x + 1相同，只不过这里将y取名为x了），x + 1赋值给新x后，旧x的指向就会被释放 给类实现多个构造函数关键理解： init 是所有构造函数的交集参考class_structure 以及 网页 使用点解析类中的信息getattr,setattr,getattribute getattribute访问类中的任何属性的时候触发，全面的控制属性的访问方法注意！由于它拦截了对任何属性的访问，所以想要在其中使用类内的属性而不造成无线循环(被访问的属性又会先调用getattribute)，唯一有效的使用情景必须包含基类的getattribute方法 getattr访问类中没有被定义的属性时触发。（在抛出AttributeError时）相比前者可以实用的构建解析类中信息的方法 setattr尝试通过点解析并给其赋值时注意！类内自己给对象赋值也会出发这个方法，所以如果在该方法内给对象赋值就会导致无限循环往往通过dict属性完成赋值避免这个问题参考 文档 类对象在迭代器中实现有限次迭代（迭代有限个元素）根据python的迭代器原理迭代器遇到对象返回StopIteration异常之后会终止于是可以在getitem方法中，在迭代次数超过设定值后抛出StopIteration异常 class A: def __init__(self, a, b): self.a = a self.b = b def __getitem__(self, id): if id == 0: return self.a if id == 1: return self.b if id > 1: raise StopIterationx = A('1','2')for i in x: print(i) 读取文件时判断文件结尾可以使用 while True: line = f.readline() ... if line = '': break ... 的结构 Numpy 的高级索引https://numpy.org/doc/stable/reference/arrays.indexing.html#advanced-indexinghttps://www.runoob.com/numpy/numpy-advanced-indexing.html 按值删除列表里所有符合的对象需要通过倒序遍历来避免删除后序号变化带来的问题 for i in range(len(self.residues)-1,-1,-1): if self.residue[i].name == name: del self.residues[i] *基本所有涉及迭代中删除列表元素的问题都要这样遍历 记忆化搜索问题：“建立的树想要在操作某个最儿子对象的时候遍历所有最儿子对象，是直接.回去然后遍历好呢还是给最爸爸做个get所有最儿子的方法好呢”这是平衡 时间 和 空间 资源的消耗。如果重用的次数比较多（或者其中子部分重用次数多），单次耗时长就时间优先，选择记忆。反之空间优先，选择不记忆。如果都不重要（往往是迷惑的来源），就以可读性，可扩展性，编写难度优先。（例：Class_Structure.Structure.get_all_protein_atom()） 类变量只有只属于这个类的抽象概念，一定不能是受类对象的具体性决定的变量 初始化函数中初始化对象值对于python，不需要在构造函数里清理变量，因为是引用传递，会被重复访问的只有类变量。只有在必需要有初始值时(比如之后要append，或者检查是否为0)，建议一起初始化。如果有些变量只有在某个方法里用到，那么通过方法被访问的频率决定要不要在构造函数里初始化。平衡逻辑和资源。 关于拷贝浅拷贝：大部分函数给出新的对象时默认是浅拷贝，即用于构建新对象的其他对象的成员可变对象以引用形式传递只有最外层的对象是新对象深拷贝：深拷贝的目的是构建一个全新的对象，即递归地将对象内的所有成员可变对象以拷贝的形式传递到新对象中。在深拷贝中往往存在两种问题：1）对象的成员对象直接或间接地包含自己（直接递归地拷贝的话会引起无限循环）2）全部拷贝的话会拷贝不需要的额外内容（例如：每次拷贝应该共享的administrative data structure）python的copy标准库中的deepcopy函数解决这两个问题的方法分别是：1）建立一个备忘录临时字典（memo）存储所有拷贝过的对象，对于相同原对象的拷贝请求直接给出已经拷贝过对象的引用。通过这种方法，深拷贝后的对象内部保有原本对象的拓扑结构（即包含关系）。2）允许用户自定义deepcopy方法 也可以通过在调用deepcopy时向memo中添加{原对象内存id：值}来改写deepcopy的行为。（例：deepcopy(self, memo = {id(self.parent):None})来实现不拷贝祖先节点） 自定义类deepcopy的默认逻辑copy.py >folded#简化后的函数定义def deepcopy(x, memo=None, _nil=[]): # 递归第一个的情况 if memo is None: memo = {} # 判断是否被拷贝过 d = id(x) y = memo.get(d, _nil) if y is not _nil: return y # 被拷贝过就直接给出引用 # 没有被拷贝过则使用reduce+重建来拷贝自身 reductor = getattr(self, "__reduce_ex__", None) # 这个b函数在哪定义的啊！！ rv = reductor(4) y = _reconstruct(x, memo, *rv) memo[d] = y _keep_alive(x, memo) # Make sure x lives at least as long as d return ydef _reconstruct(x, memo, func, args, state=None, listiter=None, dictiter=None, deepcopy=deepcopy): if args: args = (deepcopy(arg, memo) for arg in args) y = func(*args) memo[id(x)] = y if state is not None: state = deepcopy(state, memo) if isinstance(state, tuple) and len(state) == 2: state, slotstate = state else: slotstate = None if state is not None: y.__dict__.update(state) if slotstate is not None: for key, value in slotstate.items(): setattr(y, key, value) if listiter is not None: for item in listiter: item = deepcopy(item, memo) y.append(item) if dictiter is not None: for key, value in dictiter: key = deepcopy(key, memo) value = deepcopy(value, memo) y[key] = value return y 关于赋值 变量赋值： python中对于不可变对象是变量赋值，直接将一个新对象索引到标识符 引用赋值： python中对于可变对象是引用赋值，新标识符和原标识符指向同一个对象，通过任何一个标识符改变该对象的值都会使另一个标识符能访问到的值相应变化（同一物）（所以直接传self的双向链表是可行的）参考 关于bound method的赋值注意如果将一个bound method复制给另一个实例的bound method标识符的时，python的行为很反直觉 如下例： class A: def __init__(self, v) -> None: self.v = v def report_v(self): print(self.v)a = A(1)b = A(2)a.report_v()b.report_v()b.report_v = a.report_vb.report_v() 输出为 121 这里在最后b.report_v()实际调用了a.report_v然后用a的值给出了输出(所以是1而不是2) 这是因为report_v本身带有a作为第一个预载参数而没有换成b 解决方案: b.report_v = a.report_v.__func__.__get__(b) 使用.__func__.__get__()来重新绑定实例 构造函数的行参默认值被无意修改（！重要的例子！）在通过在构造函数中使用可变对象作为形参默认值时，之后对默认初始化的类对象的该变量进行操作时由于是引用赋值，会直接作用在形参默认值那个对象上 导致没法通过构造函数完成彻底初始化 class A: def __init__(self, x=None, y=[]): self.x = x self.y = y #.copy() for i in range(10): data = A() data.x = i data.y.append(i) print(data.x, data.y)>>>> 0 [0]>>>> 1 [0, 1]>>>> 2 [0, 1, 2]>>>> 3 [0, 1, 2, 3]>>>> 4 [0, 1, 2, 3, 4]>>>> 5 [0, 1, 2, 3, 4, 5]>>>> 6 [0, 1, 2, 3, 4, 5, 6]>>>> 7 [0, 1, 2, 3, 4, 5, 6, 7]>>>> 8 [0, 1, 2, 3, 4, 5, 6, 7, 8]>>>> 9 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] 这里A()本来应该生成一个x，y都是空对象的新类对象 但是由于y默认形参内存中的对象被改变了，所以上一次循环中y的值被保留了 class A: def __init__(self, x=None, y=[]): self.x = x self.y = y #.copy() print(y, id(y), id(self.y)) for i in range(10): data = A() data.x = i data.y.append(i)>>>> [] 2010413471752 2010413471752>>>> [0] 2010413471752 2010413471752>>>> [0, 1] 2010413471752 2010413471752>>>> [0, 1, 2] 2010413471752 2010413471752>>>> [0, 1, 2, 3] 2010413471752 2010413471752>>>> [0, 1, 2, 3, 4] 2010413471752 2010413471752>>>> [0, 1, 2, 3, 4, 5] 2010413471752 2010413471752>>>> [0, 1, 2, 3, 4, 5, 6] 2010413471752 2010413471752>>>> [0, 1, 2, 3, 4, 5, 6, 7] 2010413471752 2010413471752>>>> [0, 1, 2, 3, 4, 5, 6, 7, 8] 2010413471752 2010413471752 如果使用拷贝复制则不会出现这个问题 self.y = y.copy()>>>> 0 [0]>>>> 1 [1]>>>> 2 [2]>>>> 3 [3]>>>> 4 [4]>>>> 5 [5]>>>> 6 [6]>>>> 7 [7]>>>> 8 [8]>>>> 9 [9] ！重要结论！在使用可变对象时需要注意辨析需求是拷贝还是引用注意对于形参默认值的引用引发的问题 一个解决方案Class A: def __init__( self, **kwargs ): self.x = kwargs.get('x', None) self.y = kwargs.get('y',list()) kwargs 返回一个字典，get()方法在字典中搜索给定的键，如果没有找到则返回一个默认值kwarg 还可以用来判断哪些参数没有被输入**可以用字典的方式批量提供关键参数 一些架构的思想系统学习前的一些想法 可以把大函数分解增加可读性，即使分解出的小函数几乎不会被重用，但可以做成内部函数增加逻辑性 （看别人代码所得）同时这种策略可以在处理复杂问题时“自上而下”的完成，先假装这些内部函数写好了把上层的函数先写好再慢慢写下层函数 （有什么好处？至少思路更清晰）（很有效） 不要刻意的想着使用某种语法（比如修饰器）思路最重要 有些语言函数只能依托于类存在 类不一定要依托于某种具体的对象，只是为了归类将函数和变量放进类里也是可以的 区分数据结构和继承关系：继承是从一般到特殊，而不是从属关系！数据结构用节点和链表的概念理解很有帮助，在class structure中从atom对象访问蛋白就可以通过一级一级的双向链表结合访问函数来实现。 遇到哪些不确定的，不普遍的，可能扩展的，最好能整合起来放在独立的函数、类、模块里 核心还是减少重用，但是是在各个层级的，同时维持逻辑的一致性 关于之后建立图，可以建立新的类：边（连接性） 和 节点（原子） 关于访问url中的内容/从数据库中获取数据关于各种库的区别目前来讲urllib3是最好用的 而requests中使用了urllib3并优化了用户体验 参考request.get()获取对象 对象.text获取文本 对象.content获取byte request 官方文档https://docs.python-requests.org/en/latest/ 关于BeautifulSoup4该库解析html为树结构从而便于访问具体内容obj.标签名 访问子标签obj.attrs 访问标签内属性列表obj.find_all()/find() 返回该节点下所有满足条件的节点 （如何只搜索一级？） 关于string和textobj.string 当tag及其子tag内有唯一的文本是返回该文本 否则返回Noneobj.text 返回tag中所有文本 以换行按顺序分割各节点文本 关于previous/next_sibling返回空行使用obj.find_previous/next_sibling() next_sibling does not necessarily return the next html tag but instead the next “soup element”. usually that is a only a newline but can be more. find_next_sibling() on the other hand return the next html tag ignoring whitespace and other crud between the tags. 参考 关于类中的各种方法实例方法类方法：用来做和所有general类对象相关的一些通用函数静态方法：用来做用来分解内部流程用的内部函数 Q:实例方法中能调用类方法吗？？ 关于类嵌套 父类 子类在EnzyHTP.Config和autodE中使用类嵌套的方式存储参数 子类中访问父类的方式在子类的类变量的定义中无法访问父类的变量但是子类的类方法可以访问父类中的成员 可以借此完成层级化的参数配置初始化 class A: xxx = 1 class B: yyy=2 # xyy = A.xxx ---> NameError: name 'A' is not defined @classmethod def p_p(cls): # print(cls.yyy, A.xxx) ---> 2 1 cls.xyy = A.xxx print(cls.yyy, cls.xyy, A.xxx) # ---> 2 1 1 A.B.p_p() 直接在bash shell命令行使用运行python语句注意区分引号https://stackoverflow.com/questions/30702519/python-c-vs-python-heredocexample: bash:~$ python -c "import argparseparser = argparse.ArgumentParser()parser.add_argument('--file_name', type=str, required=True, help='name of python file to be created')parser.parse_args()" --file_name test 函数兼容不同输入类型执行不同逻辑使用plum包的dispatch装饰器从而根据类型注释中的类型决定使用的逻辑https://blog.csdn.net/weixin_36376765/article/details/113961245 在抽象类中定义接口https://stackoverflow.com/questions/2736255/abstract-attributes-in-python pylint输出信息控制https://pylint.pycqa.org/en/latest/user_guide/messages/message_control.html 为什么要使用namedtuplehttps://zhuanlan.zhihu.com/p/33446228 logging中logger的架构和层级关系_LOGGER = logging.getLogger(name) 会给出一个名称是name的logger 该logger默认是root logger (logging.getLogger("")) 的子logger, 默认继承任何root的行，这样会出现一个潜在问题： 别的使用logging的包如果配置了root logger的行为，就会影响每一个这个包之外的logger 设置_LOGGER.propagate = False可以禁用此行为 相关讨论：https://github.com/python/cpython/issues/80374, https://github.com/ChemBioHTP/EnzyHTP/issues/126 [logging.getLogger("")] + [j for i, j in logging.Logger.manager.loggerDict.items()]可以给出一个包含所有logger的列表","link":"/2020/12/12/Python-Notes/"},{"title":"[Exp] Kinetic Assay KE","text":"Hey, password is required here. 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