{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T13:28:29Z","timestamp":1781530109386,"version":"3.54.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1013038","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T00:00:00Z","timestamp":1762992000000}}],"reference-count":78,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T00:00:00Z","timestamp":1760313600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007698","name":"University of Florida","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007698","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007698","name":"University of Florida","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007698","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Characterizing protein families\u2019 structural and functional diversity is essential for understanding their biological roles. Traditional analyses often focus on primary and secondary structures, which may not fully capture complex protein interactions. Here we introduce InteracTor, a novel toolkit that extracts multimodal features from protein three-dimensional (3D) structures, including interatomic interactions like hydrogen bonds, van der Waals forces, and hydrophobic contacts. By integrating eXplainable Artificial Intelligence (XAI) techniques, we quantified the importance of the extracted features in the classification of protein structural and functional families. InteracTor\u2019s interpref features enable mechanistic insights into the determinants of protein structure, function, and dynamics, offering a transparent means to assess their predictive power within machine learning models. Interatomic interaction features extracted by InteracTor demonstrated superior predictive power for protein family classification compared to features based solely on primary or secondary structure, revealing the importance of considering specific tertiary contacts in computational protein analysis. This work provides a robust framework for future studies aiming to enhance the capabilities of models for protein function prediction and drug discovery.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1013038","type":"journal-article","created":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T17:33:57Z","timestamp":1760376837000},"page":"e1013038","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":4,"title":["InteracTor: Feature engineering and explainable AI for profiling protein structure-interaction-function relationships"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5435-702X","authenticated-orcid":true,"given":"Jose Cleydson F.","family":"Silva","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Layla","family":"Schuster","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nick","family":"Sexson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2116-6970","authenticated-orcid":true,"given":"Melissa","family":"Erdem","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan","family":"Hulke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matias","family":"Kirst","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcio F. R.","family":"Resende","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5220-3704","authenticated-orcid":true,"given":"Raquel","family":"Dias","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,10,13]]},"reference":[{"key":"pcbi.1013038.ref001","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkab1061","article-title":"AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models","volume":"50","author":"M Varadi","year":"2022","journal-title":"Nucleic Acids Res"},{"issue":"6557","key":"pcbi.1013038.ref002","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1126\/science.abj8754","article-title":"Accurate prediction of protein structures and interactions using a three-track neural network","volume":"373","author":"M Baek","year":"2021","journal-title":"Science"},{"issue":"2","key":"pcbi.1013038.ref003","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbac031","article-title":"ASPIRER: a new computational approach for identifying non-classical secreted proteins based on deep learning","volume":"23","author":"X Wang","year":"2022","journal-title":"Brief Bioinform"},{"issue":"3","key":"pcbi.1013038.ref004","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1093\/bioinformatics\/btz629","article-title":"PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins","volume":"36","author":"Y Zhang","year":"2020","journal-title":"Bioinformatics"},{"issue":"11","key":"pcbi.1013038.ref005","doi-asserted-by":"crossref","first-page":"2100","DOI":"10.1002\/prot.24928","article-title":"Different combinations of atomic interactions predict protein-small molecule and protein-DNA\/RNA affinities with similar accuracy","volume":"83","author":"R Dias","year":"2015","journal-title":"Proteins"},{"issue":"9","key":"pcbi.1013038.ref006","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1002\/prot.26503","article-title":"An updated dataset and a structure-based prediction model for protein-RNA binding affinity","volume":"91","author":"X Hong","year":"2023","journal-title":"Proteins"},{"issue":"12","key":"pcbi.1013038.ref007","doi-asserted-by":"crossref","first-page":"4691","DOI":"10.3390\/molecules28124691","article-title":"DeepBindGCN: Integrating Molecular Vector Representation with Graph Convolutional Neural Networks for Protein-Ligand Interaction Prediction","volume":"28","author":"H Zhang","year":"2023","journal-title":"Molecules"},{"issue":"1","key":"pcbi.1013038.ref008","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1186\/s12859-017-1702-0","article-title":"3D deep convolutional neural networks for amino acid environment similarity analysis","volume":"18","author":"W Torng","year":"2017","journal-title":"BMC Bioinformatics"},{"issue":"11","key":"pcbi.1013038.ref009","doi-asserted-by":"crossref","first-page":"2927","DOI":"10.1021\/acssynbio.0c00345","article-title":"Discovery of novel gain-of-function mutations guided by structure-based deep learning","volume":"9","author":"R Shroff","year":"2020","journal-title":"ACS Synth Biol"},{"key":"pcbi.1013038.ref010","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkac351","article-title":"iFeatureOmega: an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets","volume":"50","author":"Z Chen","year":"2022","journal-title":"Nucleic Acids Res"},{"issue":"2","key":"pcbi.1013038.ref011","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1089\/cmb.2022.0241","article-title":"Pfeature: A Tool for Computing Wide Range of Protein Features and Building Prediction Models","volume":"30","author":"A Pande","year":"2023","journal-title":"J Comput Biol"},{"key":"pcbi.1013038.ref012","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1016\/j.csbj.2022.12.044","article-title":"ProFeatX: A parallelized protein feature extraction suite for machine learning","volume":"21","author":"D Guevara-Barrientos","year":"2022","journal-title":"Comput Struct Biotechnol J"},{"issue":"1","key":"pcbi.1013038.ref013","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s12559-023-10179-8","article-title":"Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence","volume":"16","author":"V Hassija","year":"2024","journal-title":"Cogn Comput"},{"issue":"7","key":"pcbi.1013038.ref014","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1038\/nsmb.1610","article-title":"Localized thermodynamic coupling between hydrogen bonding and microenvironment polarity substantially stabilizes proteins","volume":"16","author":"J Gao","year":"2009","journal-title":"Nat Struct Mol Biol"},{"issue":"11","key":"pcbi.1013038.ref015","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1016\/j.biochi.2007.07.020","article-title":"Hydrogen bonds in protein-DNA complexes: where geometry meets plasticity","volume":"89","author":"SA Coulocheri","year":"2007","journal-title":"Biochimie"},{"issue":"06","key":"pcbi.1013038.ref016","doi-asserted-by":"crossref","first-page":"164","DOI":"10.6026\/97320630013164","article-title":"Protein-protein interfaces are vdW dominant with selective H-bonds and (or) electrostatics towards broad functional specificity","volume":"13","author":"S Irulan","year":"2017","journal-title":"Bioinformation"},{"issue":"1","key":"pcbi.1013038.ref017","doi-asserted-by":"crossref","first-page":"16273","DOI":"10.1038\/s41598-017-16322-4","article-title":"Rama: a machine learning approach for ribosomal protein prediction in plants","volume":"7","author":"TFM Carvalho","year":"2017","journal-title":"Sci Rep"},{"issue":"20","key":"pcbi.1013038.ref018","doi-asserted-by":"crossref","first-page":"12176","DOI":"10.3390\/ijms232012176","article-title":"RLPredictiOme, a Machine Learning-Derived Method for High-Throughput Prediction of Plant Receptor-like Proteins, Reveals Novel Classes of Transmembrane Receptors","volume":"23","author":"JCF Silva","year":"2022","journal-title":"Int J Mol Sci"},{"issue":"1","key":"pcbi.1013038.ref019","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1186\/s12859-017-1839-x","article-title":"Fangorn Forest (F2): a machine learning approach to classify genes and genera in the family Geminiviridae","volume":"18","author":"JCF Silva","year":"2017","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"pcbi.1013038.ref020","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/s42256-019-0138-9","article-title":"From Local Explanations to Global Understanding with Explainable AI for Trees","volume":"2","author":"SM Lundberg","year":"2020","journal-title":"Nat Mach Intell"},{"issue":"3","key":"pcbi.1013038.ref021","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1016\/j.jmb.2011.02.053","article-title":"Contribution of hydrophobic interactions to protein stability","volume":"408","author":"CN Pace","year":"2011","journal-title":"J Mol Biol"},{"issue":"9","key":"pcbi.1013038.ref022","doi-asserted-by":"crossref","first-page":"1383","DOI":"10.1002\/pro.2710","article-title":"Peptide folding driven by Van der Waals interactions","volume":"24","author":"S-S Sung","year":"2015","journal-title":"Protein Sci"},{"issue":"1","key":"pcbi.1013038.ref023","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/s11340-008-9154-0","article-title":"Protein Mechanics: A New Frontier in Biomechanics","volume":"49","author":"G Bao","year":"2009","journal-title":"Exp Mech"},{"issue":"24","key":"pcbi.1013038.ref024","doi-asserted-by":"crossref","first-page":"3338","DOI":"10.1021\/acs.biochem.8b00217","article-title":"Hydrogen bonds: simple after all?","volume":"57","author":"D Herschlag","year":"2018","journal-title":"Biochemistry"},{"issue":"26","key":"pcbi.1013038.ref025","doi-asserted-by":"crossref","first-page":"6690","DOI":"10.1021\/acs.jpcb.8b02814","article-title":"Evaluating the London Dispersion Coefficients of Protein Force Fields Using the Exchange-Hole Dipole Moment Model","volume":"122","author":"ET Walters","year":"2018","journal-title":"J Phys Chem B"},{"issue":"1","key":"pcbi.1013038.ref026","article-title":"How sticky are our proteins? Quantifying hydrophobicity of the human proteome","volume":"2","author":"JHM van Gils","year":"2022","journal-title":"Bioinform Adv"},{"key":"pcbi.1013038.ref027","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/978-94-011-3780-5_38","article-title":"The Role of Protein Structure in Surface Tension Kinetics.","volume-title":"From Clone to Clinic [Internet]","author":"AP Wei","year":"1990"},{"issue":"33","key":"pcbi.1013038.ref028","doi-asserted-by":"crossref","first-page":"4595","DOI":"10.1021\/acs.biochem.6b00500","article-title":"Dispersion Forces and the Molecular Origin of Internal Friction in Protein","volume":"55","author":"P Sashi","year":"2016","journal-title":"Biochemistry"},{"issue":"2","key":"pcbi.1013038.ref029","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/0022-2836(73)90011-9","article-title":"Environment and exposure to solvent of protein atoms. Lysozyme and insulin","volume":"79","author":"A Shrake","year":"1973","journal-title":"J Mol Biol"},{"key":"pcbi.1013038.ref030","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1007\/978-1-4939-3743-1_14","article-title":"Gene Ontology: Pitfalls, Biases, and Remedies.","volume-title":"The Gene Ontology Handbook [Internet]","author":"P Gaudet","year":"2017"},{"key":"pcbi.1013038.ref031","first-page":"103054","article-title":"Protein sequence classification with improved extreme learning machine algorithms","volume":"2014","author":"J Cao","year":"2014","journal-title":"Biomed Res Int"},{"issue":"6553","key":"pcbi.1013038.ref032","doi-asserted-by":"crossref","DOI":"10.1126\/science.abf8761","article-title":"Revealing enzyme functional architecture via high-throughput microfluidic enzyme kinetics","volume":"373","author":"CJ Markin","year":"2021","journal-title":"Science"},{"issue":"3","key":"pcbi.1013038.ref033","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1038\/s41580-023-00673-0","article-title":"The molecular basis for cellular function of intrinsically disordered protein regions","volume":"25","author":"AS Holehouse","year":"2024","journal-title":"Nat Rev Mol Cell Biol"},{"issue":"4","key":"pcbi.1013038.ref034","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1038\/nrg3414","article-title":"Emerging methods in protein co-evolution","volume":"14","author":"D de Juan","year":"2013","journal-title":"Nat Rev Genet"},{"issue":"3","key":"pcbi.1013038.ref035","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1007\/s10989-012-9338-4","article-title":"Synthesis and Biological Activity of N-Sulfonyltripeptides with C-Terminal Arginine as Potential Serine Proteases Inhibitors","volume":"19","author":"A Markowska","year":"2013","journal-title":"Int J Pept Res Ther"},{"issue":"7","key":"pcbi.1013038.ref036","doi-asserted-by":"crossref","first-page":"2269","DOI":"10.1021\/jp207807a","article-title":"Comprehensive conformational studies of five tripeptides and a deduced method for efficient determinations of peptide structures","volume":"116","author":"W Yu","year":"2012","journal-title":"J Phys Chem B"},{"issue":"1","key":"pcbi.1013038.ref037","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1186\/s13068-021-01964-4","article-title":"Identification and characterization of proteins of unknown function (PUFs) in Clostridium thermocellum DSM 1313 strains as potential genetic engineering targets","volume":"14","author":"S Poudel","year":"2021","journal-title":"Biotechnol Biofuels"},{"issue":"3","key":"pcbi.1013038.ref038","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1006\/jmbi.2001.4526","article-title":"Mapping protein family interactions: intramolecular and intermolecular protein family interaction repertoires in the PDB and yeast","volume":"307","author":"J Park","year":"2001","journal-title":"J Mol Biol"},{"issue":"1","key":"pcbi.1013038.ref039","doi-asserted-by":"crossref","first-page":"1060","DOI":"10.1038\/s41467-024-44988-8","article-title":"Engineering stringent genetic biocontainment of yeast with a protein stability switch","volume":"15","author":"SA Hoffmann","year":"2024","journal-title":"Nat Commun"},{"issue":"10","key":"pcbi.1013038.ref040","doi-asserted-by":"crossref","first-page":"12761","DOI":"10.3390\/ijms131012761","article-title":"Proteins of unknown function in the protein data bank (PDB): An inventory of true uncharacterized proteins and computational tools for their analysis","volume":"13","author":"N Nadzirin","year":"2012","journal-title":"Int J Mol Sci"},{"issue":"2","key":"pcbi.1013038.ref041","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s12033-023-00765-4","article-title":"Quantum Computing in the Next-Generation Computational Biology Landscape: From Protein Folding to Molecular Dynamics","volume":"66","author":"S Pal","year":"2024","journal-title":"Mol Biotechnol"},{"issue":"1","key":"pcbi.1013038.ref042","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1038\/s41526-023-00319-7","article-title":"Bisphosphonate conjugation enhances the bone-specificity of NELL-1-based systemic therapy for spaceflight-induced bone loss in mice","volume":"9","author":"P Ha","year":"2023","journal-title":"NPJ Microgravity"},{"issue":"9","key":"pcbi.1013038.ref043","doi-asserted-by":"crossref","first-page":"3359","DOI":"10.1021\/acs.jctc.4c00067","article-title":"A perspective on protein structure prediction using quantum computers","volume":"20","author":"H Doga","year":"2024","journal-title":"J Chem Theory Comput"},{"issue":"102","key":"pcbi.1013038.ref044","doi-asserted-by":"crossref","first-page":"20140715","DOI":"10.1098\/rsif.2014.0715","article-title":"Towards synthetic biological approaches to resource utilization on space missions","volume":"12","author":"AA Menezes","year":"2015","journal-title":"J R Soc Interface"},{"issue":"2","key":"pcbi.1013038.ref045","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbae074","article-title":"New classifications for quantum bioinformatics: Q-bioinformatics, QCt-bioinformatics, QCg-bioinformatics, and QCr-bioinformatics","volume":"25","author":"M Mokhtari","year":"2024","journal-title":"Brief Bioinform"},{"issue":"1","key":"pcbi.1013038.ref046","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1038\/s41580-021-00407-0","article-title":"A guide to machine learning for biologists","volume":"23","author":"JG Greener","year":"2022","journal-title":"Nat Rev Mol Cell Biol"},{"key":"pcbi.1013038.ref047","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.plantsci.2019.03.020","article-title":"Machine learning approaches and their current application in plant molecular biology: A systematic review","volume":"284","author":"JCF Silva","year":"2019","journal-title":"Plant Sci"},{"issue":"2","key":"pcbi.1013038.ref048","doi-asserted-by":"crossref","first-page":"0017","DOI":"10.1038\/s41570-017-0017","article-title":"Competition of van der Waals and chemical forces on gold\u2013sulfur surfaces and nanoparticles","volume":"1","author":"JR Reimers","year":"2017","journal-title":"Nat Rev Chem"},{"issue":"4","key":"pcbi.1013038.ref049","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1124\/mol.114.097014","article-title":"Structural and biophysical characterization of human cytochromes P450 2B6 and 2A6 bound to volatile hydrocarbons: analysis and comparison","volume":"87","author":"MB Shah","year":"2015","journal-title":"Mol Pharmacol"},{"issue":"12","key":"pcbi.1013038.ref050","doi-asserted-by":"crossref","first-page":"1859","DOI":"10.1124\/dmd.115.068981","article-title":"Cytochrome P450 organization and function are modulated by endoplasmic reticulum phospholipid heterogeneity","volume":"44","author":"LM Brignac-Huber","year":"2016","journal-title":"Drug Metabol Dispos"},{"issue":"6","key":"pcbi.1013038.ref051","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1002\/prot.25666","article-title":"The Short-chain Dehydrogenase\/Reductase Engineering Database (SDRED): A classification and analysis system for a highly diverse enzyme family","volume":"87","author":"M Gr\u00e4ff","year":"2019","journal-title":"Proteins"},{"issue":"17","key":"pcbi.1013038.ref052","doi-asserted-by":"crossref","first-page":"9498","DOI":"10.3390\/ijms22179498","article-title":"Genome-Wide Identification and Characterization of Short-Chain Dehydrogenase\/Reductase (SDR) Gene Family in Medicago truncatula","volume":"22","author":"S Yu","year":"2021","journal-title":"Int J Mol Sci"},{"issue":"10","key":"pcbi.1013038.ref053","doi-asserted-by":"crossref","first-page":"1383","DOI":"10.1016\/S0969-2126(02)00851-1","article-title":"The structural basis for catalysis and specificity of the X-prolyl dipeptidyl aminopeptidase from Lactococcus lactis","volume":"10","author":"P Rigolet","year":"2002","journal-title":"Structure"},{"issue":"24","key":"pcbi.1013038.ref054","doi-asserted-by":"crossref","first-page":"3895","DOI":"10.1007\/s00018-008-8588-y","article-title":"Medium- and short-chain dehydrogenase\/reductase gene and protein families\u00a0: the SDR superfamily: functional and structural diversity within a family of metabolic and regulatory enzymes","volume":"65","author":"KL Kavanagh","year":"2008","journal-title":"Cell Mol Life Sci"},{"key":"pcbi.1013038.ref055","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.73913","article-title":"SDR enzymes oxidize specific lipidic alkynylcarbinols into cytotoxic protein-reactive species","volume":"11","author":"P Demange","year":"2022","journal-title":"eLife"},{"issue":"19","key":"pcbi.1013038.ref056","doi-asserted-by":"crossref","first-page":"3957","DOI":"10.1021\/bi1020748","article-title":"Uncovering the Role of Hydrophobic Residues in Cytochrome P450\u2212Cytochrome P450 Reductase Interactions","volume":"50","author":"C Kenaan","year":"2011","journal-title":"Biochemistry"},{"issue":"6","key":"pcbi.1013038.ref057","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.3390\/ijms19061617","article-title":"Ligand access channels in cytochrome P450 enzymes: A review","volume":"19","author":"P Urban","year":"2018","journal-title":"Int J Mol Sci"},{"issue":"5","key":"pcbi.1013038.ref058","doi-asserted-by":"crossref","DOI":"10.1128\/spectrum.02054-22","article-title":"The Repertoire of Solute-Binding Proteins of Model Bacteria Reveals Large Differences in Number, Type, and Ligand Range","volume":"10","author":"\u00c1 Ortega","year":"2022","journal-title":"Microbiol Spectr"},{"key":"pcbi.1013038.ref059","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1007\/978-1-4757-2065-5_8","article-title":"Pores, Channels and Transporters.","volume-title":"Biomembranes [Internet]","author":"RB Gennis","year":"1989"},{"issue":"9","key":"pcbi.1013038.ref060","doi-asserted-by":"crossref","first-page":"1806","DOI":"10.1002\/pro.5560060902","article-title":"Crystal structures of bovine chymotrypsin and trypsin complexed to the inhibitor domain of Alzheimer\u2019s amyloid beta-protein precursor (APPI) and basic pancreatic trypsin inhibitor (BPTI): engineering of inhibitors with altered specificities","volume":"6","author":"AJ Scheidig","year":"1997","journal-title":"Protein Sci"},{"issue":"1","key":"pcbi.1013038.ref061","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/19382014.2021.1982325","article-title":"Identification of protease serine S1 family member 53 as a mitochondrial protein in murine islet beta cells","volume":"14","author":"N Mizusawa","year":"2022","journal-title":"Islets"},{"issue":"4","key":"pcbi.1013038.ref062","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1042\/ETLS20180094","article-title":"Pyrrolysine in archaea: a 22nd amino acid encoded through a genetic code expansion. Robinson NP, editor","volume":"2","author":"JF Brug\u00e8re","year":"2018","journal-title":"Emerg Top Life Sci"},{"issue":"5911","key":"pcbi.1013038.ref063","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1126\/science.1164748","article-title":"Genetic Code Supports Targeted Insertion of Two Amino Acids by One Codon","volume":"323","author":"AA Turanov","year":"2009","journal-title":"Science"},{"key":"pcbi.1013038.ref064","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1107\/S2052252514009324","article-title":"The PDB_REDO server for macromolecular structure model optimization","volume":"1","author":"RP Joosten","year":"2014","journal-title":"IUCrJ"},{"key":"pcbi.1013038.ref065","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1186\/1758-2946-3-33","article-title":"Open Babel: An open chemical toolbox","volume":"3","author":"NM O\u2019Boyle","year":"2011","journal-title":"J Cheminform"},{"key":"pcbi.1013038.ref066","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkaa1100","article-title":"UniProt: the universal protein knowledgebase in 2021","volume":"49","author":"UniProt Consortium","year":"2021","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"pcbi.1013038.ref067","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/75556","article-title":"Gene ontology: tool for the unification of biology. The Gene Ontology Consortium","volume":"25","author":"M Ashburner","year":"2000","journal-title":"Nat Genet"},{"issue":"1","key":"pcbi.1013038.ref068","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1093\/nar\/28.1.235","article-title":"The Protein Data Bank","volume":"28","author":"HM Berman","year":"2000","journal-title":"Nucleic Acids Res"},{"issue":"6","key":"pcbi.1013038.ref069","doi-asserted-by":"crossref","first-page":"066138","DOI":"10.1103\/PhysRevE.69.066138","article-title":"Estimating mutual information","volume":"69","author":"A Kraskov","year":"2004","journal-title":"Phys Rev E"},{"issue":"2065","key":"pcbi.1013038.ref070","doi-asserted-by":"crossref","first-page":"20150202","DOI":"10.1098\/rsta.2015.0202","article-title":"Principal component analysis: a review and recent developments","volume":"374","author":"IT Jolliffe","year":"2016","journal-title":"Phil Trans R Soc A"},{"issue":"1","key":"pcbi.1013038.ref071","doi-asserted-by":"crossref","first-page":"5415","DOI":"10.1038\/s41467-019-13055-y","article-title":"Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets","volume":"10","author":"AC Belkina","year":"2019","journal-title":"Nat Commun"},{"key":"pcbi.1013038.ref072","volume-title":"Orange: Data Mining Toolbox in Python","author":"J Demsar"},{"issue":"6","key":"pcbi.1013038.ref073","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1016\/j.jbi.2007.03.010","article-title":"FreeViz--an intelligent multivariate visualization approach to explorative analysis of biomedical data","volume":"40","author":"J Demsar","year":"2007","journal-title":"J Biomed Inform"},{"key":"pcbi.1013038.ref074","article-title":"Scikit-learn: Machine Learning in Python [Internet]","author":"F Pedregosa","year":"2018","journal-title":"arXiv"},{"key":"pcbi.1013038.ref075","article-title":"A Unified Approach to Interpreting Model Predictions [Internet]","author":"S Lundberg","year":"2017","journal-title":"arXiv"},{"key":"pcbi.1013038.ref076","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1080\/15502724.2018.1533851","article-title":"Power analysis, sample size, and assessment of statistical assumptions\u2014improving the evidential value of lighting research","volume":"15","author":"J Uttley","year":"2019","journal-title":"LEUKOS"},{"key":"pcbi.1013038.ref077","doi-asserted-by":"crossref","first-page":"1658","DOI":"10.1007\/978-3-642-04898-2_616","article-title":"Wilcoxon-Signed-Rank Test.","volume-title":"International Encyclopedia of Statistical Science [Internet]","author":"D Rey","year":"2011"},{"issue":"1","key":"pcbi.1013038.ref078","doi-asserted-by":"crossref","first-page":"59","DOI":"10.22271\/maths.2021.v6.i1a.636","article-title":"Multiple comparison test by Tukey\u2019s honestly significant difference (HSD): Do the confident level control type I error","volume":"6","author":"A Nanda","year":"2021","journal-title":"Int J Stat Appl Math"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1013038","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T00:00:00Z","timestamp":1762992000000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1013038","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T19:02:06Z","timestamp":1763060526000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1013038"}},"subtitle":[],"editor":[{"given":"Fei","family":"Guo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2025,10,13]]},"references-count":78,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,10,13]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1013038","relation":{},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,13]]}}}