diff --git a/joss.04182/10.21105.joss.04182.crossref.xml b/joss.04182/10.21105.joss.04182.crossref.xml new file mode 100644 index 0000000000..186b31bc53 --- /dev/null +++ b/joss.04182/10.21105.joss.04182.crossref.xml @@ -0,0 +1,480 @@ + + + + 20220530T162257-94a8194942fe7f6683f29c8fe8d39e01b8455789 + 20220530162257 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org/ + + + + + 05 + 2022 + + + 7 + + 73 + + + + E2EDNA 2.0: Python Pipeline for Simulating DNA Aptamers +with Ligands + + + + Michael + Kilgour + https://orcid.org/0000-0001-6557-3297 + + + Tao + Liu + https://orcid.org/0000-0002-1082-5570 + + + Ilya S. + Dementyev + https://orcid.org/0000-0001-7171-1078 + + + Lena + Simine + https://orcid.org/0000-0002-8188-0550 + + + + 05 + 30 + 2022 + + + 4182 + + + 10.21105/joss.04182 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.6546661 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/4182 + + + + 10.21105/joss.04182 + https://joss.theoj.org/papers/10.21105/joss.04182 + + + https://joss.theoj.org/papers/10.21105/joss.04182.pdf + + + + + + E2EDNA: Simulation Protocol for DNA Aptamers +with Ligands + Kilgour + Journal of Chemical Information and +Modeling + 9 + 61 + 10.1021/acs.jcim.1c00696 + 1549-9596 + 2021 + Kilgour, M., Liu, T., Walker, B. D., +Ren, P., & Simine, L. (2021). E2EDNA: Simulation Protocol for DNA +Aptamers with Ligands. Journal of Chemical Information and Modeling, +61(9), 4139–4144. +https://doi.org/10.1021/acs.jcim.1c00696 + + + Aptamer Therapeutics in Cancer: Current and +Future + Morita + Cancers + 3 + 10 + 10.3390/cancers10030080 + 2072-6694 + 2018 + Morita, Y., Leslie, M., Kameyama, H., +Volk, D., & Tanaka, T. (2018). Aptamer Therapeutics in Cancer: +Current and Future. Cancers, 10(3), 80. +https://doi.org/10.3390/cancers10030080 + + + Real-time measurement of adenosine and ATP +release in the central nervous system + Dale + Purinergic Signalling + 1 + 17 + 10.1007/s11302-020-09733-y + 1573-9538 + 2021 + Dale, N. (2021). Real-time +measurement of adenosine and ATP release in the central nervous system. +Purinergic Signalling, 17(1), 109–115. +https://doi.org/10.1007/s11302-020-09733-y + + + Challenges and Opportunities for Nucleic Acid +Therapeutics + Corey + Nucleic Acid Therapeutics + 10.1089/nat.2021.0085 + 2159-3337 + 2021 + Corey, D. R., Damha, M. J., & +Manoharan, M. (2021). Challenges and Opportunities for Nucleic Acid +Therapeutics. Nucleic Acid Therapeutics, nat.2021.0085. +https://doi.org/10.1089/nat.2021.0085 + + + Nucleic Acid Aptamers for Molecular Therapy +of Epilepsy and Blood-Brain Barrier Damages + Zamay + Molecular Therapy - Nucleic +Acids + 19 + 10.1016/j.omtn.2019.10.042 + 2020 + Zamay, T. N., Zamay, G. S., Shnayder, +N. A., Dmitrenko, D. V., Zamay, S. S., Yushchenko, V., Kolovskaya, O. +S., Susevski, V., Berezovski, M. V., & Kichkailo, A. S. (2020). +Nucleic Acid Aptamers for Molecular Therapy of Epilepsy and Blood-Brain +Barrier Damages. 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LightDock goes information-driven. +Bioinformatics, 36(3), 950–952. +https://doi.org/10.1093/bioinformatics/btz642 + + + Fast Flexible Modeling of RNA Structure Using +Internal Coordinates + Flores + IEEE/ACM Transactions on Computational +Biology and Bioinformatics + 5 + 8 + 10.1109/TCBB.2010.104 + 1545-5963 + 2011 + Flores, S. C., Sherman, M. A., Bruns, +C. M., Eastman, P., & Altman, R. B. (2011). Fast Flexible Modeling +of RNA Structure Using Internal Coordinates. IEEE/ACM Transactions on +Computational Biology and Bioinformatics, 8(5), 1247–1257. +https://doi.org/10.1109/TCBB.2010.104 + + + APTANI: A computational tool to select +aptamers through sequence-structure motif analysis of HT-SELEX +data + Caroli + Bioinformatics + 2 + 32 + 10.1093/bioinformatics/btv545 + 1367-4803 + 2016 + Caroli, J., Taccioli, C., De La +Fuente, A., Serafini, P., & Bicciato, S. (2016). APTANI: A +computational tool to select aptamers through sequence-structure motif +analysis of HT-SELEX data. Bioinformatics, 32(2), 161–164. +https://doi.org/10.1093/bioinformatics/btv545 + + + APTANI2: Update of aptamer selection through +sequence-structure analysis + Caroli + Bioinformatics + 7 + 36 + 10.1093/bioinformatics/btz897 + 1367-4803 + 2020 + Caroli, J., Forcato, M., & +Bicciato, S. (2020). APTANI2: Update of aptamer selection through +sequence-structure analysis. Bioinformatics, 36(7), 2266–2268. +https://doi.org/10.1093/bioinformatics/btz897 + + + G-quadruplex DNA Aptamers and their Ligands: +Structure, Function and Application + Tucker + Current Pharmaceutical Design + 14 + 18 + 10.2174/138161212799958477 + 2012 + Tucker, W. O., Shum, K. T., & +Tanner, J. A. (2012). G-quadruplex DNA Aptamers and their Ligands: +Structure, Function and Application. 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Aptamers and Synthetic Antibodies, +1(1), 12–16. + + + Systematic Evolution of Ligands by +Exponential Enrichment: RNA Ligands to Bacteriophage T4 DNA +Polymerase + Tuerk + Science + 4968 + 249 + 10.1126/science.2200121 + 0036-8075 + 1990 + Tuerk, C., & Gold, L. (1990). +Systematic Evolution of Ligands by Exponential Enrichment: RNA Ligands +to Bacteriophage T4 DNA Polymerase. Science, 249(4968), 505–510. +https://doi.org/10.1126/science.2200121 + + + A chronocoulometric aptamer sensor for +adenosine monophosphate + Shen + Chemical Communications + 21 + 10.1039/b618909a + 1359-7345 + 2007 + Shen, L., Chen, Z., Li, Y., Jing, P., +Xie, S., He, S., He, P., & Shao, Y. (2007). A chronocoulometric +aptamer sensor for adenosine monophosphate. Chemical Communications, 21, +2169. https://doi.org/10.1039/b618909a + + + Aptamer-Based Sensor Arrays for the Detection +and Quantitation of Proteins + Kirby + Analytical Chemistry + 14 + 76 + 10.1021/ac049858n + 0003-2700 + 2004 + Kirby, R., Cho, E. 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Journal of Biosciences, 45(1), 44. +https://doi.org/10.1007/s12038-020-0017-x + + + + + + diff --git a/joss.04182/10.21105.joss.04182.jats b/joss.04182/10.21105.joss.04182.jats new file mode 100644 index 0000000000..b30916daa3 --- /dev/null +++ b/joss.04182/10.21105.joss.04182.jats @@ -0,0 +1,822 @@ + + +
+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +4182 +10.21105/joss.04182 + +E2EDNA 2.0: Python Pipeline for Simulating DNA Aptamers +with Ligands + + + +0000-0001-6557-3297 + +Kilgour +Michael + + + + +0000-0002-1082-5570 + +Liu +Tao + + + + +0000-0001-7171-1078 + +Dementyev +Ilya S. + + + + +0000-0002-8188-0550 + +Simine +Lena + + +* + + + +Department of Chemistry, McGill University, Montreal, +Quebec, Canada + + + + +* E-mail: + + +31 +1 +2022 + +7 +73 +4182 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Python +simulation pipeline +DNA aptamers + + + + + + Summary +

DNA aptamers are short sequences of single-stranded DNA with + untapped potential in molecular medicine, drug design, and materials + design due to their strong and selective and most importantly tunable + binding affinity to target molecules + (Tucker + et al., 2012; + Zhou + & Rossi, 2017). For instance, DNA aptamers can be used as + therapeutics + (Corey + et al., 2021) for a wide range of diseases such as epilepsy + (Zamay + et al., 2020) and cancer + (Morita + et al., 2018). They can also be used to detect a wide variety + of molecular ligands, including antibiotics + (Mehlhorn + et al., 2018), neurotransmitters + (Sinha + & Das Mukhopadhyay, 2020), metals + (Qu + et al., 2016), proteins + (Kirby + et al., 2004), nucleotides + (Shen + et al., 2007) and metabolites + (Dale, + 2021; + Dauphin-Ducharme + et al., 2022) in real time, even in harsh environments + (McConnell + et al., 2020).

+

We present E2EDNA 2.0: End-2-End DNA 2.0, a python simulation + pipeline which offers a unified and automated solution to + computational modeling of DNA aptamers with molecular ligands. It is + broadly aimed at researchers developing therapeutics and sensors based + on DNA aptamers who require detailed atomistic information on the + behavior of aptamers and ligands in realistic media. Similar to its + predecessor E2EDNA + (Kilgour + et al., 2021), E2EDNA 2.0 predicts DNA aptamers’ secondary and + tertiary structures, and if a ligand is present, the configuration of + the solvated aptamer-ligand complex.

+ + + Statement of Need +

With E2EDNA 2.0 our goal is to create a python-interfacing + simulation package for single-stranded DNA with small ligands that is + easy to install and use in python-based workflows. The pipeline is + automated, yet flexible, taking us from DNA aptamer sequence to folded + aptamer, and aptamer-ligand complex. Currently, available software + packages designed for computationally studying DNA aptamers + predominantly focus on partial feature analyses of RNA and DNA + aptamers. For example, APTANI + (Caroli + et al., 2016) and APTANI2 + (Caroli + et al., 2020), commonly used by the aptamer community, select + potentially relevant aptamers from SELEX (Systematic Evolution of + Ligands by EXponential + enrichment)(McKeague + & DeRosa, 2014; + Tuerk + & Gold, 1990) experimental data sets through a + sequence-structure analysis, and AEGIS, a platform equipped with a + generative deep learning model to propose novel aptamer sequences + (Biondi + & Benner, 2018). These approaches are aimed at fast + black-box analysis of large numbers of sequences. A detailed analysis + of a small number of high-promise candidate sequences is often + required but no automated and easy-to-use simulation package exists in + the computational space aside from E2EDNA + (Kilgour + et al., 2021) and E2EDNA 2.0, with the latter preferable for + ease of installation and user-friendly implementations of eight modes + of simulation.

+

The gap that the E2EDNA family of programs addresses is the absence + of a non-black-box one-stop-shop aptamer simulation package, which is + capable of providing in silico predictions of 2D structure, 3D + structure, and aptamer-ligand binding simulation while keeping + methodology flexible and analysis open-ended. E2EDNA 2.0 achieves this + in two key ways: a python-interfacing implementation which makes + installation and access easier for users than the original E2EDNA + package, and the automation of the dozens of tasks required in setting + up, running, and interpreting atomistic aptamer-ligand + simulations.

+ +

Schematic workflow of E2EDNA 2.0 + pipeline.

+ + + + + Components and Features +

As shown in + Figure 1, + the complete simulation pipeline in E2EDNA 2.0 consists of the + following main steps: 1. Secondary structure prediction, 2. Tertiary + structure prediction, 3. Molecular dynamics simulation, and 4. + Aptamer-ligand docking. The key inputs into E2EDNA 2.0 are the DNA + sequence in the FASTA format, the structure of the ligand in the pdb + format (optional), and the choice of simulation mode. The output + includes secondary structure in dot-bracket notation, tertiary + structures in pdb format of free aptamer and aptamer-ligand complex + (optional), and simulation trajectories in the dcd format. It is worth + noting that there are other parameters besides “key inputs” that can + be customized, such as solvent ionic strength. Detailed analysis of + the generated trajectories is not performed by E2EDNA 2.0, though is + straightforward to set up for a particular workflow using built-in or + user-specified functions.

+

Next we briefly discuss the external software packages engaged in + the E2EDNA 2.0 pipeline. For developers we point out that the pipeline + is modular and any of these packages may be drop-in replaced with any + equivalent or competing software. The first module, NUPACK + (Zadeh + et al., 2011), generates a predicted secondary structure given + DNA FASTA sequence, temperature, and ionic strength. It can output + explicit probability of observing the most likely secondary structure + for a given sequence, as well as suboptimal structures and their + probabilities. The second module, MacroMoleculeBuilder (MMB) + (Flores + et al., 2011) is a multifunctional software from simTK which + allows for rapid directed folding of oligonucleotides and peptides via + straightforward inputs on various platforms. MMB initializes a given + ssDNA sequence in a single-helix configuration, and folds it according + to user-specified base-pairing conditions via simulation with + ficticious forces which pull the respective bases together. E2EDNA 2.0 + includes scripts which automatically take in secondary structure + instructions from NUPACK in the form of a list of paired bases, and + generate MMB command files accordingly. The MMB outputs, as initial + structures, are then passed to MD simulation for relaxation. The third + module, OpenMM + (Eastman + et al., 2017), is the molecular dynamics engine powering E2EDNA + 2.0. OpenMM is used to sample 3D structures of both the ‘free’ aptamer + and its aptamer-target complex. The representative DNA aptamer + structure is chosen from the MD trajectory via a principal component + analysis on backbone dihedrals: a free energy is constructed in the + space of top-ranked principal components (5) as reaction coordinates + and the lowest free energy structure is passed on to the docking with + ligand step. The fourth module, LightDock + (Jiménez-García + et al., 2018; + Roel-Touris + et al., 2020), automates the docking between a free DNA aptamer + and a given target ligand. LightDock uses a glowworm swarm algorithm; + we compute the number of swarms required as being proportional to the + approximate surface area of the aptamer and use the best-scored + glowworm as the docked complex structure.

+

We conclude the presentation of E2EDNA 2.0 by listing the available + simulation modes. We refer the reader to the documentation for more + details on the modes, as well as for installation and running the + simulation instructions.

+ + +

Mode: ‘2d structure’; Description: predicts secondary + structure.

+ + +

Mode: ‘3d coarse’; Description: ‘2d structure’ + quick folding + into a 3D structure.

+ + +

Mode: ‘3d smooth’; Description: ‘3d coarse’ + MD + relaxation.

+ + +

Mode: ‘coarse dock’; Description: ‘3d coarse’ structure + + molecular docking.

+ + +

Mode: ‘smooth dock’; Description: ‘3d smooth’ structure + + molecular docking.

+ + +

Mode: ‘free aptamer’; Description: ‘3d coarse’ + MD sampling + search for representative aptamer folded conformation.

+ + +

Mode: ‘full dock’; Description: ‘free aptamer’ + molecular + docking.

+ + +

Mode: ‘full binding’; Description: ‘full dock’ + MD sampling of + aptamer-ligand complex.

+ + + + + Acknowledgements +

Funding from the NSERC Discovery grant RGPIN-201924734 and an NSERC + PDF for M.K. is greatly appreciated. Computations were made on the + supercomputer Beluga, managed by Calcul Quebec + (https://www.calculquebec.ca/) and Compute Canada + (https://www.computecanada.ca/). The operation of this supercomputer + is funded by the Canada Foundation for Innovation (CFI).

+ + + + + + + + KilgourMichael + LiuTao + WalkerBrandon D. + RenPengyu + SimineLena + + E2EDNA: Simulation Protocol for DNA Aptamers with Ligands + Journal of Chemical Information and Modeling + 202109 + 20211115 + 61 + 9 + 1549-9596 + https://pubs.acs.org/doi/10.1021/acs.jcim.1c00696 + 10.1021/acs.jcim.1c00696 + 4139 + 4144 + + + + + + MoritaYoshihiro + LeslieMacall + KameyamaHiroyasu + VolkDavid + TanakaTakemi + + Aptamer Therapeutics in Cancer: Current and Future + Cancers + 201803 + 20220127 + 10 + 3 + 2072-6694 + https://www.mdpi.com/2072-6694/10/3/80 + 10.3390/cancers10030080 + 80 + + + + + + + DaleNicholas + + Real-time measurement of adenosine and ATP release in the central nervous system + Purinergic Signalling + 202103 + 20220127 + 17 + 1 + 1573-9538 + https://link.springer.com/10.1007/s11302-020-09733-y + 10.1007/s11302-020-09733-y + 109 + 115 + + + + + + CoreyDavid R. + DamhaMasad J. + ManoharanMuthiah + + Challenges and Opportunities for Nucleic Acid Therapeutics + Nucleic Acid Therapeutics + 202112 + 20220127 + 2159-3337 + https://www.liebertpub.com/doi/10.1089/nat.2021.0085 + 10.1089/nat.2021.0085 + nat.2021.0085 + + + + + + + ZamayTatiana N. + ZamayGalina S. + ShnayderNatalia A. + DmitrenkoDiana V. + ZamaySergey S. + YushchenkoVictoria + KolovskayaOlga S. + SusevskiVanessa + BerezovskiMaxim V. + KichkailoAnna S. + + Nucleic Acid Aptamers for Molecular Therapy of Epilepsy and Blood-Brain Barrier Damages + Molecular Therapy - Nucleic Acids + 202003 + 20220127 + 19 + https://linkinghub.elsevier.com/retrieve/pii/S2162253119303543 + 10.1016/j.omtn.2019.10.042 + 157 + 167 + + + + + + Dauphin-DucharmePhilippe + PloenseKyle L. + Arroyo-CurrásNetzahualcóyotl + KippinTod E. + PlaxcoKevin W. + + Electrochemical Aptamer-Based Sensors: A Platform Approach to High-Frequency Molecular Monitoring In Situ in the Living Body + Biomedical Engineering Technologies + Springer US + New York, NY + 2022 + 20220127 + 2393 + 978-1-07-161803-5 + https://link.springer.com/10.1007/978-1-0716-1803-5_25 + 10.1007/978-1-0716-1803-5_25 + 479 + 492 + + + + + + BiondiElisa + BennerSteven + + Artificially Expanded Genetic Information Systems for New Aptamer Technologies + Biomedicines + 201805 + 20220127 + 6 + 2 + 2227-9059 + http://www.mdpi.com/2227-9059/6/2/53 + 10.3390/biomedicines6020053 + 53 + + + + + + + ZadehJoseph N. + SteenbergConrad D. + BoisJustin S. + WolfeBrian R. + PierceMarshall B. + KhanAsif R. + DirksRobert M. + PierceNiles A. + + NUPACK: Analysis and design of nucleic acid systems + Journal of Computational Chemistry + 201101 + 20220127 + 32 + 1 + https://onlinelibrary.wiley.com/doi/10.1002/jcc.21596 + 10.1002/jcc.21596 + 170 + 173 + + + + + + EastmanPeter + SwailsJason + ChoderaJohn D. + McGibbonRobert T. + ZhaoYutong + BeauchampKyle A. + WangLee-Ping + SimmonettAndrew C. + HarriganMatthew P. + SternChaya D. + WiewioraRafal P. + BrooksBernard R. + PandeVijay S. + + OpenMM 7: Rapid development of high performance algorithms for molecular dynamics + PLOS Computational Biology + + GentlemanRobert + + 201707 + 20220127 + 13 + 7 + 1553-7358 + https://dx.plos.org/10.1371/journal.pcbi.1005659 + 10.1371/journal.pcbi.1005659 + e1005659 + + + + + + + Jiménez-GarcíaBrian + Roel-TourisJorge + Romero-DuranaMiguel + VidalMiquel + Jiménez-GonzálezDaniel + Fernández-RecioJuan + + LightDock: A new multi-scale approach to protein–protein docking + Bioinformatics + + ValenciaAlfonso + + 201801 + 20220127 + 34 + 1 + 1367-4803 + https://academic.oup.com/bioinformatics/article/34/1/49/4103399 + 10.1093/bioinformatics/btx555 + 49 + 55 + + + + + + Roel-TourisJorge + BonvinAlexandre M J J + Jiménez-GarcíaBrian + + LightDock goes information-driven + Bioinformatics + + PontyYann + + 202002 + 20220127 + 36 + 3 + 1367-4803 + https://academic.oup.com/bioinformatics/article/36/3/950/5550626 + 10.1093/bioinformatics/btz642 + 950 + 952 + + + + + + FloresS. 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