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For: Zhou Y, Duan Y, Yang Y, Faraggi E, Lei H. Trends in template/fragment-free protein structure prediction. Theor Chem Acc 2011;128:3-16. [PMID: 21423322 PMCID: PMC3030773 DOI: 10.1007/s00214-010-0799-2] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2010] [Accepted: 08/15/2010] [Indexed: 12/13/2022]
Number Cited by Other Article(s)
1
Zhou Y, Litfin T, Zhan J. 3 = 1 + 2: how the divide conquered de novo protein structure prediction and what is next? Natl Sci Rev 2023;10:nwad259. [PMID: 38033736 PMCID: PMC10684263 DOI: 10.1093/nsr/nwad259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 09/18/2023] [Indexed: 12/02/2023]  Open
2
Broz M, Jukič M, Bren U. Naive Prediction of Protein Backbone Phi and Psi Dihedral Angles Using Deep Learning. Molecules 2023;28:7046. [PMID: 37894526 PMCID: PMC10609058 DOI: 10.3390/molecules28207046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/06/2023] [Accepted: 10/09/2023] [Indexed: 10/29/2023]  Open
3
Machine learning approaches demonstrate that protein structures carry information about their genetic coding. Sci Rep 2022;12:21968. [PMID: 36539476 PMCID: PMC9767929 DOI: 10.1038/s41598-022-25874-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022]  Open
4
Ismi DP, Pulungan R, Afiahayati. Deep learning for protein secondary structure prediction: Pre and post-AlphaFold. Comput Struct Biotechnol J 2022;20:6271-6286. [PMID: 36420164 PMCID: PMC9678802 DOI: 10.1016/j.csbj.2022.11.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 11/05/2022] [Accepted: 11/05/2022] [Indexed: 11/13/2022]  Open
5
Mckenna A, P N Dubey S. Machine Learning Based Predictive Model for the Analysis of Sequence Activity Relationships Using Protein Spectra and Protein Descriptors. J Biomed Inform 2022;128:104016. [PMID: 35143999 DOI: 10.1016/j.jbi.2022.104016] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 12/13/2021] [Accepted: 02/03/2022] [Indexed: 11/26/2022]
6
Newton MAH, Mataeimoghadam F, Zaman R, Sattar A. Secondary structure specific simpler prediction models for protein backbone angles. BMC Bioinformatics 2022;23:6. [PMID: 34983370 PMCID: PMC8728911 DOI: 10.1186/s12859-021-04525-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 12/07/2021] [Indexed: 11/10/2022]  Open
7
Accurate prediction of protein torsion angles using evolutionary signatures and recurrent neural network. Sci Rep 2021;11:21033. [PMID: 34702851 PMCID: PMC8548351 DOI: 10.1038/s41598-021-00477-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/27/2021] [Indexed: 11/08/2022]  Open
8
Mayer-Bacon C, Agboha N, Muscalli M, Freeland S. Evolution as a Guide to Designing xeno Amino Acid Alphabets. Int J Mol Sci 2021;22:ijms22062787. [PMID: 33801827 PMCID: PMC8000707 DOI: 10.3390/ijms22062787] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/01/2021] [Accepted: 03/05/2021] [Indexed: 02/02/2023]  Open
9
Enhancing protein backbone angle prediction by using simpler models of deep neural networks. Sci Rep 2020;10:19430. [PMID: 33173130 PMCID: PMC7655839 DOI: 10.1038/s41598-020-76317-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 10/23/2020] [Indexed: 11/09/2022]  Open
10
Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning. J Comput Biol 2020;27:796-814. [DOI: 10.1089/cmb.2019.0193] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]  Open
11
Cai Y, Li X, Sun Z, Lu Y, Zhao H, Hanson J, Paliwal K, Litfin T, Zhou Y, Yang Y. SPOT-Fold: Fragment-Free Protein Structure Prediction Guided by Predicted Backbone Structure and Contact Map. J Comput Chem 2019;41:745-750. [PMID: 31845383 DOI: 10.1002/jcc.26132] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 10/07/2019] [Accepted: 12/01/2019] [Indexed: 02/01/2023]
12
Fang C, Shang Y, Xu D. A deep dense inception network for protein beta-turn prediction. Proteins 2019;88:143-151. [PMID: 31294886 DOI: 10.1002/prot.25780] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 06/17/2019] [Accepted: 07/06/2019] [Indexed: 12/13/2022]
13
AlQuraishi M. End-to-End Differentiable Learning of Protein Structure. Cell Syst 2019;8:292-301.e3. [PMID: 31005579 PMCID: PMC6513320 DOI: 10.1016/j.cels.2019.03.006] [Citation(s) in RCA: 183] [Impact Index Per Article: 36.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 02/01/2019] [Accepted: 03/11/2019] [Indexed: 12/11/2022]
14
Hanson J, Paliwal K, Litfin T, Yang Y, Zhou Y. Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks. Bioinformatics 2018;35:2403-2410. [DOI: 10.1093/bioinformatics/bty1006] [Citation(s) in RCA: 115] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 11/02/2018] [Accepted: 12/06/2018] [Indexed: 11/14/2022]  Open
15
Fang C, Shang Y, Xu D. Improving Protein Gamma-Turn Prediction Using Inception Capsule Networks. Sci Rep 2018;8:15741. [PMID: 30356073 PMCID: PMC6200818 DOI: 10.1038/s41598-018-34114-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 10/06/2018] [Indexed: 01/17/2023]  Open
16
Heffernan R, Paliwal K, Lyons J, Singh J, Yang Y, Zhou Y. Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning. J Comput Chem 2018;39:2210-2216. [PMID: 30368831 DOI: 10.1002/jcc.25534] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 05/11/2018] [Accepted: 06/14/2018] [Indexed: 02/01/2023]
17
Yang Y, Gao J, Wang J, Heffernan R, Hanson J, Paliwal K, Zhou Y. Sixty-five years of the long march in protein secondary structure prediction: the final stretch? Brief Bioinform 2018;19:482-494. [PMID: 28040746 PMCID: PMC5952956 DOI: 10.1093/bib/bbw129] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 11/15/2016] [Indexed: 11/13/2022]  Open
18
Fang C, Shang Y, Xu D. Prediction of Protein Backbone Torsion Angles Using Deep Residual Inception Neural Networks. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2018;16:10.1109/TCBB.2018.2814586. [PMID: 29994074 PMCID: PMC6592781 DOI: 10.1109/tcbb.2018.2814586] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
19
Wang T, Yang Y, Zhou Y, Gong H. LRFragLib: an effective algorithm to identify fragments for de novo protein structure prediction. Bioinformatics 2017;33:677-684. [PMID: 27797773 DOI: 10.1093/bioinformatics/btw668] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2016] [Accepted: 10/18/2016] [Indexed: 11/13/2022]  Open
20
Heffernan R, Yang Y, Paliwal K, Zhou Y. Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility. Bioinformatics 2017;33:2842-2849. [DOI: 10.1093/bioinformatics/btx218] [Citation(s) in RCA: 234] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Accepted: 04/15/2017] [Indexed: 11/14/2022]  Open
21
Lampros C, Papaloukas C, Exarchos T, Fotiadis DI. HMMs in Protein Fold Classification. Methods Mol Biol 2017;1552:13-27. [PMID: 28224488 DOI: 10.1007/978-1-4939-6753-7_2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
22
Gao J, Yang Y, Zhou Y. Predicting the errors of predicted local backbone angles and non-local solvent- accessibilities of proteins by deep neural networks. Bioinformatics 2016;32:3768-3773. [DOI: 10.1093/bioinformatics/btw549] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Revised: 07/29/2016] [Accepted: 08/18/2016] [Indexed: 11/14/2022]  Open
23
Hoque MT, Yang Y, Mishra A, Zhou Y. s DFIRE : Sequence‐specific statistical energy function for protein structure prediction by decoy selections. J Comput Chem 2016;37:1119-24. [DOI: 10.1002/jcc.24298] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2015] [Revised: 12/06/2015] [Accepted: 12/13/2015] [Indexed: 12/15/2022]
24
Ru X, Song C, Lin Z. A genetic algorithm encoded with the structural information of amino acids and dipeptides for efficient conformational searches of oligopeptides. J Comput Chem 2016;37:1214-22. [DOI: 10.1002/jcc.24311] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2015] [Revised: 11/19/2015] [Accepted: 01/06/2016] [Indexed: 01/10/2023]
25
Yang Y, Zhou Y. Effective protein conformational sampling based on predicted torsion angles. J Comput Chem 2015;37:976-80. [DOI: 10.1002/jcc.24285] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Revised: 11/01/2015] [Accepted: 11/27/2015] [Indexed: 11/09/2022]
26
Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning. Sci Rep 2015;5:11476. [PMID: 26098304 PMCID: PMC4476419 DOI: 10.1038/srep11476] [Citation(s) in RCA: 218] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Accepted: 05/19/2015] [Indexed: 11/09/2022]  Open
27
Lyons J, Dehzangi A, Heffernan R, Sharma A, Paliwal K, Sattar A, Zhou Y, Yang Y. Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network. J Comput Chem 2014;35:2040-6. [PMID: 25212657 DOI: 10.1002/jcc.23718] [Citation(s) in RCA: 110] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2014] [Revised: 07/12/2014] [Accepted: 08/09/2014] [Indexed: 11/09/2022]
28
Lampros C, Simos T, Exarchos TP, Exarchos KP, Papaloukas C, Fotiadis DI. Assessment of optimized Markov models in protein fold classification. J Bioinform Comput Biol 2014;12:1450016. [PMID: 25152041 DOI: 10.1142/s0219720014500164] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
29
Zhao H, Yang Y, Janga SC, Kao CC, Zhou Y. Prediction and validation of the unexplored RNA-binding protein atlas of the human proteome. Proteins 2014;82:640-7. [PMID: 24123256 PMCID: PMC3949140 DOI: 10.1002/prot.24441] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2013] [Revised: 09/13/2013] [Accepted: 09/26/2013] [Indexed: 12/13/2022]
30
Noid WG. Perspective: Coarse-grained models for biomolecular systems. J Chem Phys 2014;139:090901. [PMID: 24028092 DOI: 10.1063/1.4818908] [Citation(s) in RCA: 540] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]  Open
31
Liang S, Zhang C, Zhou Y. LEAP: highly accurate prediction of protein loop conformations by integrating coarse-grained sampling and optimized energy scores with all-atom refinement of backbone and side chains. J Comput Chem 2014;35:335-41. [PMID: 24327406 PMCID: PMC4125323 DOI: 10.1002/jcc.23509] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2013] [Revised: 10/06/2013] [Accepted: 11/24/2013] [Indexed: 11/11/2022]
32
Yang Y, Zhao H, Wang J, Zhou Y. SPOT-Seq-RNA: predicting protein-RNA complex structure and RNA-binding function by fold recognition and binding affinity prediction. Methods Mol Biol 2014;1137:119-30. [PMID: 24573478 PMCID: PMC3937850 DOI: 10.1007/978-1-4939-0366-5_9] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
33
Mirzaie M, Sadeghi M. Delaunay-based nonlocal interactions are sufficient and accurate in protein fold recognition. Proteins 2013;82:415-23. [DOI: 10.1002/prot.24407] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2013] [Revised: 08/12/2013] [Accepted: 08/21/2013] [Indexed: 01/05/2023]
34
Jiang F, Han W, Wu YD. The intrinsic conformational features of amino acids from a protein coil library and their applications in force field development. Phys Chem Chem Phys 2013;15:3413-28. [PMID: 23385383 DOI: 10.1039/c2cp43633g] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
35
Hansen N, Allison JR, Hodel FH, van Gunsteren WF. Relative free enthalpies for point mutations in two proteins with highly similar sequences but different folds. Biochemistry 2013;52:4962-70. [PMID: 23802564 DOI: 10.1021/bi400272q] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
36
Shao Q, Zhu W, Gao YQ. Robustness in Protein Folding Revealed by Thermodynamics Calculations. J Phys Chem B 2012;116:13848-56. [DOI: 10.1021/jp307684h] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
37
Evolutionary decision rules for predicting protein contact maps. Pattern Anal Appl 2012. [DOI: 10.1007/s10044-012-0297-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
38
Maadooliat M, Gao X, Huang JZ. Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles. Brief Bioinform 2012;14:724-36. [PMID: 22926831 DOI: 10.1093/bib/bbs052] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]  Open
39
Yu W, Wu Z, Chen H, Liu X, MacKerell AD, Lin Z. Comprehensive conformational studies of five tripeptides and a deduced method for efficient determinations of peptide structures. J Phys Chem B 2012;116:2269-83. [PMID: 22260814 DOI: 10.1021/jp207807a] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
40
Yang Y, Faraggi E, Zhao H, Zhou Y. Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templates. Bioinformatics 2011;27:2076-82. [PMID: 21666270 DOI: 10.1093/bioinformatics/btr350] [Citation(s) in RCA: 241] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]  Open
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