EnGens: a computational framework for generation and analysis of representative protein conformational ensembles.
| العنوان: | EnGens: a computational framework for generation and analysis of representative protein conformational ensembles. |
|---|---|
| المؤلفون: | Conev A; Department of Computer Science, Rice University, Houston, TX 77005, USA., Rigo MM; Department of Computer Science, Rice University, Houston, TX 77005, USA., Devaurs D; MRC Institute of Genetics and Cancer, University of Edinburgh, EH4 2XU, UK., Fonseca AF; Department of Biology and Biochemistry, University of Houston, Houston, TX 77004, USA., Kalavadwala H; Department of Biology and Biochemistry, University of Houston, Houston, TX 77004, USA., de Freitas MV; Department of Biology and Biochemistry, University of Houston, Houston, TX 77004, USA., Clementi C; Department of Physics, Freie Universität Berlin, Berlin, 14195 Germany., Zanatta G; Department of Biophysics, Institute of Biosciences, Federal University of Rio Grande do Sul, Porto Alegre, 91501-970 Brazil., Antunes DA; Department of Biology and Biochemistry, University of Houston, Houston, TX 77004, USA., Kavraki L; Department of Computer Science, Rice University, Houston, TX 77005, USA. |
| المصدر: | BioRxiv : the preprint server for biology [bioRxiv] 2023 Apr 28. Date of Electronic Publication: 2023 Apr 28. |
| نوع المنشور: | Preprint |
| اللغة: | English |
| بيانات الدورية: | Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE |
| مستخلص: | Proteins are dynamic macromolecules that perform vital functions in cells. A protein structure determines its function, but this structure is not static, as proteins change their conformation to achieve various functions. Understanding the conformational landscapes of proteins is essential to understand their mechanism of action. Sets of carefully chosen conformations can summarize such complex landscapes and provide better insights into protein function than single conformations. We refer to these sets as representative conformational ensembles. Recent advances in computational methods have led to an increase in number of available structural datasets spanning conformational landscapes. However, extracting representative conformational ensembles from such datasets is not an easy task and many methods have been developed to tackle it. Our new approach, EnGens (short for ensemble generation), collects these methods into a unified framework for generating and analyzing protein conformational ensembles. In this work we: (1) provide an overview of existing methods and tools for protein structural ensemble generation and analysis; (2) unify existing approaches in an open-source Python package, and a portable Docker image, providing interactive visualizations within a Jupyter Notebook pipeline; (3) test our pipeline on a few canonical examples found in the literature. Representative ensembles produced by EnGens can be used for many downstream tasks such as protein-ligand ensemble docking, Markov state modeling of protein dynamics and analysis of the effect of single-point mutations. |
| التعليقات: | Update in: Brief Bioinform. 2023 Jul 07;:. (PMID: 37418278) |
| References: | Nucleic Acids Res. 2019 Jan 8;47(D1):D520-D528. (PMID: 30357364) Bioinformatics. 2009 Jun 1;25(11):1422-3. (PMID: 19304878) Cell. 2013 Apr 11;153(2):293-305. (PMID: 23582321) Nat Struct Biol. 1996 Apr;3(4):364-74. (PMID: 8599763) Science. 1991 Dec 13;254(5038):1598-603. (PMID: 1749933) J Mol Biol. 2020 Nov 6;432(22):5849-5859. (PMID: 32918948) Structure. 2021 Jan 7;29(1):6-14. (PMID: 33176159) Ann Med. 2014 Sep;46(6):372-83. (PMID: 24897931) J Chem Phys. 2020 Nov 21;153(19):194101. (PMID: 33218238) Int J Mol Sci. 2016 Nov 10;17(11):. (PMID: 27834926) J Chem Theory Comput. 2015 Nov 10;11(11):5525-42. (PMID: 26574340) Science. 2023 Mar 17;379(6637):1123-1130. (PMID: 36927031) Comput Biol Med. 2021 Dec;139:104943. (PMID: 34717233) J Struct Biol. 2021 Dec;213(4):107800. (PMID: 34600140) Sci Signal. 2011 Oct 18;4(195):re2. (PMID: 22009150) Nature. 2007 Dec 13;450(7172):964-72. (PMID: 18075575) J Chem Phys. 2011 May 7;134(17):174105. (PMID: 21548671) Proc Natl Acad Sci U S A. 2020 Dec 1;117(48):30610-30618. (PMID: 33184174) J Mol Biol. 1976 May 15;103(2):227-49. (PMID: 985660) Science. 2021 Aug 20;373(6557):871-876. (PMID: 34282049) J Biol Chem. 1998 Nov 13;273(46):30199-203. (PMID: 9804776) BMC Bioinformatics. 2011 Feb 15;12 Suppl 1:S32. (PMID: 21342563) Trends Biochem Sci. 2002 Aug;27(8):419-26. (PMID: 12151227) Protein Sci. 2000 Jan;9(1):10-9. (PMID: 10739242) PLoS One. 2014 Jan 31;9(1):e87520. (PMID: 24498124) Nucleic Acids Res. 2021 Jan 8;49(D1):D437-D451. (PMID: 33211854) J Am Chem Soc. 2018 Feb 21;140(7):2386-2396. (PMID: 29323881) J Phys Chem B. 2020 Oct 22;124(42):9354-9364. (PMID: 32955887) Annu Rev Phys Chem. 1997;48:545-600. (PMID: 9348663) J Chem Phys. 2020 Jul 28;153(4):044130. (PMID: 32752662) iScience. 2022 Sep 22;25(10):105181. (PMID: 36248733) Bioinformatics. 2011 Jun 1;27(11):1575-7. (PMID: 21471012) Nature. 2021 Aug;596(7873):583-589. (PMID: 34265844) J Chem Theory Comput. 2015 Feb 10;11(2):600-8. (PMID: 26528090) Nucleic Acids Res. 2022 Jan 7;50(D1):D439-D444. (PMID: 34791371) J Comput Chem. 2009 Jul 30;30(10):1545-614. (PMID: 19444816) Biochemistry. 2017 Jun 20;56(24):2971-2984. (PMID: 28570055) J Mol Model. 2020 Aug 12;26(9):231. (PMID: 32789582) Biophys J. 2015 Oct 20;109(8):1528-32. (PMID: 26488642) PLoS Comput Biol. 2017 Jul 26;13(7):e1005659. (PMID: 28746339) Oncotarget. 2014 Jul 30;5(14):5198-208. (PMID: 25105564) Bioinformatics. 2021 Oct 25;37(20):3657-3659. (PMID: 33822884) J Phys Chem B. 2021 May 20;125(19):5022-5034. (PMID: 33973773) Chem Rev. 2021 Aug 25;121(16):9722-9758. (PMID: 33945269) Curr Opin Struct Biol. 2022 Jun;74:102380. (PMID: 35561475) ACS Chem Biol. 2018 Jun 15;13(6):1438-1446. (PMID: 29787234) J Chem Theory Comput. 2013 Jan 8;9(1):461-469. (PMID: 23316124) J Chem Theory Comput. 2022 Aug 9;18(8):4983-4994. (PMID: 35621307) Chem Sci. 2020 Feb 26;11(13):3511-3515. (PMID: 34703536) Biophys J. 2017 Dec 5;113(11):2396-2405. (PMID: 29211993) J Chem Phys. 2019 Jun 7;150(21):214114. (PMID: 31176319) Ann N Y Acad Sci. 1998 Dec 13;864:1-8. (PMID: 9928078) J Chem Theory Comput. 2019 Oct 8;15(10):5689-5702. (PMID: 31436987) J Chem Phys. 2013 Jul 7;139(1):015102. (PMID: 23822324) BMC Struct Biol. 2010 Oct 29;10:39. (PMID: 21034466) |
| معلومات مُعتمدة: | U01 CA258512 United States CA NCI NIH HHS |
| تواريخ الأحداث: | Date Created: 20230510 Latest Revision: 20230720 |
| رمز التحديث: | 20240628 |
| مُعرف محوري في PubMed: | PMC10168271 |
| DOI: | 10.1101/2023.04.24.538094 |
| PMID: | 37163076 |
| قاعدة البيانات: | MEDLINE |
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