Prediction of protein structure and AI

Anfinsen CB. Principles that govern the folding of protein chains. Science. 1973;181:223–30.

Article  CAS  PubMed  Google Scholar 

Levinthal C. Are there pathways for protein folding? J Chim Phys. 1968;65:44–45.

Article  Google Scholar 

Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021;596:583–89.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Applying and improving AlphaFold at CASP14. Proteins. 2021;89:1711–21.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Varadi M, Anyango S, Deshpande M, Nair S, Natassia C, Yordanova G, et al. AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res. 2021;50:D439–D44.

Article  PubMed Central  Google Scholar 

Consortium TU. UniProt: the Universal Protein Knowledgebase in 2023. Nucleic Acids Res. 2022;51:D523–D31.

Article  Google Scholar 

Burley SK, Bhikadiya C, Bi C, Bittrich S, Chao H, Chen L, et al. RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning. Nucleic Acids Res. 2023;51:D488–D508.

Article  CAS  PubMed  Google Scholar 

Mariani V, Biasini M, Barbato A, Schwede T. lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests. Bioinformatics. 2013;29:2722–28.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wilson CJ, Choy WY, Karttunen M. AlphaFold2: a role for disordered protein/region prediction? Int J Mol Sci. 2022;23:4591.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Guo H-B, Perminov A, Bekele S, Kedziora G, Farajollahi S, Varaljay V, et al. AlphaFold2 models indicate that protein sequence determines both structure and dynamics. Sci Rep. 2022;12:10696.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Akdel M, Pires DEV, Pardo EP, Jänes J, Zalevsky AO, Mészáros B, et al. A structural biology community assessment of AlphaFold2 applications. Nat Struct Mol Biol. 2022;29:1056–67.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bludau I, Willems S, Zeng WF, Strauss MT, Hansen FM, Tanzer MC, et al. The structural context of posttranslational modifications at a proteome-wide scale. PLoS Biol. 2022;20:e3001636.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang Y, Skolnick J. Scoring function for automated assessment of protein structure template quality. Proteins: Struct, Funct, Bioinforma. 2004;57:702–10.

Article  CAS  Google Scholar 

Evans R, O’Neill M, Pritzel A, Antropova N, Senior A, Green T, et al. Protein complex prediction with AlphaFold-Multimer. bioRxiv. 2022:2021.10.04.463034.

Buel GR, Walters KJ. Can AlphaFold2 predict the impact of missense mutations on structure? Nat Struct Mol Biol. 2022;29:1–2.

Article  CAS  PubMed  Google Scholar 

Pak MA, Markhieva KA, Novikova MS, Petrov DS, Vorobyev IS, Maksimova ES, et al. Using AlphaFold to predict the impact of single mutations on protein stability and function. PLoS One. 2023;18:e0282689.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Keskin Karakoyun H, Yuksel SK, Amanoglu I, Naserikhojasteh L, Yesilyurt A, Yakicier C, et al. Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer. Front Genet. 2023;14:1052383.

Article  PubMed  PubMed Central  Google Scholar 

Hekkelman ML, de Vries I, Joosten RP, Perrakis A. AlphaFill: enriching AlphaFold models with ligands and cofactors. Nat Methods. 2023;20:205–13.

Article  CAS  PubMed  Google Scholar 

Bryant P, Pozzati G, Elofsson A. Improved prediction of protein-protein interactions using AlphaFold2. Nat Commun. 2022;13:1265.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bryant P, Pozzati G, Zhu W, Shenoy A, Kundrotas P, Elofsson A. Predicting the structure of large protein complexes using AlphaFold and Monte Carlo tree search. Nat Commun. 2022;13:6028.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Drake ZC, Seffernick JT, Lindert S. Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling. Nat Commun. 2022;13:7846.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bryant P. Deep learning for protein complex structure prediction. Curr Opin Struct Biol. 2023;79:102529.

Article  CAS  PubMed  Google Scholar 

Gao M, Nakajima An D, Parks JM, Skolnick J. AF2Complex predicts direct physical interactions in multimeric proteins with deep learning. Nat Commun. 2022;13:1744.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Konc J, Janežič D. ProBiS-fold approach for annotation of human structures from the alphafold database with no corresponding structure in the PDB to discover new druggable binding sites. J Chem Inf Model. 2022;62:5821–29.

Article  CAS  PubMed  Google Scholar 

Ruffolo JA, Chu L-S, Mahajan SP, Gray JJ. Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies. Nat Commun. 2023;14:2389.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ruffolo JA, Sulam J, Gray JJ. Antibody structure prediction using interpretable deep learning. Patterns. 2022;3:100406.

Article  CAS  PubMed  Google Scholar 

Yin R, Pierce BG Evaluation of AlphaFold Antibody-Antigen Modeling with Implications for Improving Predictive Accuracy. bioRxiv. 2023.

Ittisoponpisan S, Islam SA, Khanna T, Alhuzimi E, David A, Sternberg MJE. Can predicted protein 3D structures provide reliable insights into whether missense variants are disease associated? J Mol Biol. 2019;431:2197–212.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Iqbal S, Ge F, Li F, Akutsu T, Zheng Y, Gasser RB, et al. PROST: AlphaFold2-aware sequence-based predictor to estimate protein stability changes upon missense mutations. J Chem Inf Model. 2022;62:4270–82.

Article  CAS  PubMed  Google Scholar 

Cheng J, Novati G, Pan J, Bycroft C, Zemgulyte A, Applebaum T, et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science. 2023;381:eadg7492.

Article  CAS  PubMed  Google Scholar 

Landrum MJ, Chitipiralla S, Brown GR, Chen C, Gu B, Hart J, et al. ClinVar: improvements to accessing data. Nucleic Acids Res. 2020;48:D835–d44.

Article  CAS  PubMed  Google Scholar 

Vacic V, Iakoucheva LM. Disease mutations in disordered regions-exception to the rule? Mol Biosyst. 2012;8:27–32.

Article  CAS  PubMed  Google Scholar 

Meyer K, Kirchner M, Uyar B, Cheng JY, Russo G, Hernandez-Miranda LR, et al. Mutations in disordered regions can cause disease by creating dileucine motifs. Cell. 2018;175:239–53.e17.

Article  CAS  PubMed  Google Scholar 

Pentony MM, Ward J, Jones DT. Computational resources for the prediction and analysis of native disorder in proteins. Methods Mol Biol. 2010;604:369–93.

Article  CAS  PubMed  Google Scholar 

Vacic V, Markwick PR, Oldfield CJ, Zhao X, Haynes C, Uversky VN, et al. Disease-associated mutations disrupt functionally important regions of intrinsic protein disorder. PLoS Comput Biol. 2012;8:e1002709.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Mort M, Evani US, Krishnan VG, Kamati KK, Baenziger PH, Bagchi A, et al. In silico functional profiling of human disease-associated and polymorphic amino acid substitutions. Hum Mutat. 2010;31:335–46.

Article  PubMed  PubMed Central  Google Scholar 

Zhou JB, Xiong Y, An K, Ye ZQ, Wu YD. IDRMutPred: predicting disease-associated germline nonsynonymous single nucleotide variants (nsSNVs) in intrinsically disordered regions. Bioinformatics. 2020;36:4977–83.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ragonis-Bachar P, Landau M. Functional and pathological amyloid structures in the

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