{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T03:09:36Z","timestamp":1791774576903,"version":"4.3.4"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1011953","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2024,7,23]],"date-time":"2024-07-23T00:00:00Z","timestamp":1721692800000}}],"reference-count":129,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T00:00:00Z","timestamp":1720656000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000057","name":"nigms","doi-asserted-by":"crossref","award":["R35 GM145236"],"award-info":[{"award-number":["R35 GM145236"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>With recent methodological advances in the field of computational protein design, in particular those based on deep learning, there is an increasing need for frameworks that allow for coherent, direct integration of different models and objective functions into the generative design process. Here we demonstrate how evolutionary multiobjective optimization techniques can be adapted to provide such an approach. With the established Non-dominated Sorting Genetic Algorithm II (NSGA-II) as the optimization framework, we use AlphaFold2 and ProteinMPNN confidence metrics to define the objective space, and a mutation operator composed of ESM-1v and ProteinMPNN to rank and then redesign the least favorable positions. Using the two-state design problem of the foldswitching protein RfaH as an in-depth case study, and PapD and calmodulin as examples of higher-dimensional design problems, we show that the evolutionary multiobjective optimization approach leads to significant reduction in the bias and variance in RfaH native sequence recovery, compared to a direct application of ProteinMPNN. We suggest that this improvement is due to three factors: (i) the use of an informative mutation operator that accelerates the sequence space exploration, (ii) the parallel, iterative design process inherent to the genetic algorithm that improves upon the ProteinMPNN autoregressive sequence decoding scheme, and (iii) the explicit approximation of the Pareto front that leads to optimal design candidates representing diverse tradeoff conditions. We anticipate this approach to be readily adaptable to different models and broadly relevant for protein design tasks with complex specifications.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1011953","type":"journal-article","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T13:59:43Z","timestamp":1720706383000},"page":"e1011953","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":22,"title":["An integrative approach to protein sequence design through multiobjective optimization"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7812-0617","authenticated-orcid":true,"given":"Lu","family":"Hong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8494-680X","authenticated-orcid":true,"given":"Tanja","family":"Kortemme","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,7,11]]},"reference":[{"key":"pcbi.1011953.ref001","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1016\/j.cell.2023.12.028","article-title":"De novo protein design\u2014From new structures to programmable functions","volume":"187","author":"T. 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Moffat","year":"2021","journal-title":"bioRxiv"},{"key":"pcbi.1011953.ref065","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1162\/089976603321780317","article-title":"Laplacian Eigenmaps for Dimensionality Reduction and Data Representation.","volume":"15","author":"M Belkin","year":"2003","journal-title":"Neural Comput"},{"key":"pcbi.1011953.ref066","doi-asserted-by":"crossref","first-page":"e76630","DOI":"10.7554\/eLife.76630","article-title":"Structural and thermodynamic analyses of the \u03b2-to-\u03b1 transformation in RfaH reveal principles of fold-switching proteins.","volume":"11","author":"PK Zuber","year":"2022","journal-title":"eLife"},{"key":"pcbi.1011953.ref067","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1002\/pro.2869","article-title":"Boosting protein stability with the computational design of \u03b2-sheet surfaces","volume":"25","author":"DN Kim","year":"2016","journal-title":"Protein 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Seifi","year":"2021","journal-title":"Biopolymers"},{"key":"pcbi.1011953.ref071","doi-asserted-by":"crossref","first-page":"e1004379","DOI":"10.1371\/journal.pcbi.1004379","article-title":"Interdomain Contacts Control Native State Switching of RfaH on a Dual-Funneled Landscape.","volume":"11","author":"CA Ram\u00edrez-Sarmiento","year":"2015","journal-title":"PLOS Comput Biol."},{"key":"pcbi.1011953.ref072","doi-asserted-by":"crossref","first-page":"3802","DOI":"10.1038\/s41467-022-31532-9","article-title":"Many dissimilar NusG protein domains switch between \u03b1-helix and \u03b2-sheet folds.","volume":"13","author":"LL Porter","year":"2022","journal-title":"Nat Commun"},{"key":"pcbi.1011953.ref073","doi-asserted-by":"crossref","first-page":"6052","DOI":"10.1128\/jb.171.11.6052-6058.1989","article-title":"PapD, a periplasmic transport protein in P-pilus biogenesis","volume":"171","author":"F Lindberg","year":"1989","journal-title":"J Bacteriol"},{"key":"pcbi.1011953.ref074","doi-asserted-by":"crossref","first-page":"5551","DOI":"10.1111\/febs.12296","article-title":"Structural diversity of calmodulin binding to its target sites.","volume":"280","author":"H Tidow","year":"2013","journal-title":"FEBS J"},{"key":"pcbi.1011953.ref075","doi-asserted-by":"crossref","first-page":"e164","DOI":"10.1371\/journal.pcbi.0030164","article-title":"Design of Multi-Specificity in Protein Interfaces.","volume":"3","author":"EL Humphris","year":"2007","journal-title":"PLOS Comput Biol."},{"key":"pcbi.1011953.ref076","doi-asserted-by":"crossref","first-page":"e1007339","DOI":"10.1371\/journal.pcbi.1007339","article-title":"Multi-state design of flexible proteins predicts sequences optimal for conformational change","volume":"16","author":"MF Sauer","year":"2020","journal-title":"PLOS Comput Biol"},{"key":"pcbi.1011953.ref077","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s42004-023-01029-7","article-title":"Peptide 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Ye","year":"2006","journal-title":"Biochemistry"},{"key":"pcbi.1011953.ref081","doi-asserted-by":"crossref","first-page":"e4653","DOI":"10.1002\/pro.4653","article-title":"De novo protein design by inversion of the AlphaFold structure prediction network","volume":"32","author":"CA Goverde","year":"2023","journal-title":"Protein Sci"},{"key":"pcbi.1011953.ref082","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1038\/s42256-020-0217-y","article-title":"Ensemble deep learning in bioinformatics","volume":"2","author":"Y Cao","year":"2020","journal-title":"Nat Mach Intell"},{"key":"pcbi.1011953.ref083","article-title":"Structured Denoising Diffusion Models in Discrete State-Spaces.","author":"J Austin","year":"2021"},{"key":"pcbi.1011953.ref084","article-title":"Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning.","author":"S 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Sauer","year":"1999","journal-title":"Science"},{"key":"pcbi.1011953.ref088","doi-asserted-by":"crossref","first-page":"8178","DOI":"10.1073\/pnas.96.14.8178","article-title":"Structural basis of chaperone self-capping in P pilus biogenesis","volume":"96","author":"DL Hung","year":"1999","journal-title":"Proc Natl Acad Sci"},{"key":"pcbi.1011953.ref089","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1038\/nsb0995-768","article-title":"Solution structure of calcium-free calmodulin","volume":"2","author":"H Kuboniwa","year":"1995","journal-title":"Nat Struct Biol"},{"key":"pcbi.1011953.ref090","doi-asserted-by":"crossref","first-page":"12320","DOI":"10.1021\/bi9908235","article-title":"NMR Solution Structure of a Complex of Calmodulin with a Binding Peptide of the Ca2+","volume":"38","author":"B Elshorst","year":"1999","journal-title":"Pump. Biochemistry"},{"key":"pcbi.1011953.ref091","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1038\/12271","article-title":"A novel target recognition revealed by calmodulin in complex with Ca2+-calmodulin-dependent kinase kinase\u2014Nature Structural & Molecular Biology","volume":"6","author":"M Osawa","year":"1999","journal-title":"Nat Struct Biol"},{"key":"pcbi.1011953.ref092","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.1016\/0022-2836(92)90324-D","article-title":"Calmodulin structure refined at 1.7 \u00c5 resolution","volume":"228","author":"R Chattopadhyaya","year":"1992","journal-title":"J Mol Biol"},{"key":"pcbi.1011953.ref093","doi-asserted-by":"crossref","first-page":"1599","DOI":"10.1016\/S0969-2126(97)00308-0","article-title":"Motions of calmodulin characterized using both Bragg and diffuse X-ray scattering","volume":"5","author":"ME Wall","year":"1997","journal-title":"Structure"},{"key":"pcbi.1011953.ref094","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1038\/35074145","article-title":"Structure of the gating domain of a Ca2+-activated K+ channel complexed with Ca2+\/calmodulin","volume":"410","author":"MA Schumacher","year":"2001","journal-title":"Nature"},{"key":"pcbi.1011953.ref095","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1093\/emboj\/cdg078","article-title":"Structural basis for endothelial nitric oxide synthase binding to calmodulin","volume":"22","author":"M Aoyagi","year":"2003","journal-title":"EMBO J"},{"key":"pcbi.1011953.ref096","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/S0022-2836(03)00271-7","article-title":"Structural Basis for Simultaneous Binding of Two Carboxy-terminal Peptides of Plant Glutamate Decarboxylase to Calmodulin","volume":"328","author":"KL Yap","year":"2003","journal-title":"J Mol Biol"},{"key":"pcbi.1011953.ref097","doi-asserted-by":"crossref","first-page":"5962","DOI":"10.1021\/acs.biochem.6b00821","article-title":"Structural Studies of a Complex Between Endothelial Nitric Oxide Synthase and Calmodulin at Physiological Calcium Concentration","volume":"55","author":"M Piazza","year":"2016","journal-title":"Biochemistry"},{"key":"pcbi.1011953.ref098","doi-asserted-by":"crossref","first-page":"e1000426","DOI":"10.1371\/journal.pbio.1000426","article-title":"Structure of the CaMKII\u03b4\/Calmodulin Complex Reveals the Molecular Mechanism of CaMKII Kinase Activation","volume":"8","author":"P Rellos","year":"2010","journal-title":"PLOS Biol"},{"key":"pcbi.1011953.ref099","doi-asserted-by":"crossref","first-page":"1604","DOI":"10.1107\/S1399004714006919","article-title":"Structural insights into the mechanism of calmodulin binding to death receptors","volume":"70","author":"P Cao","year":"2014","journal-title":"Acta Crystallogr D Biol Crystallogr"},{"key":"pcbi.1011953.ref100","doi-asserted-by":"crossref","first-page":"3558","DOI":"10.1073\/pnas.1114748109","article-title":"Crystallographic basis for calcium regulation of sodium channels","volume":"109","author":"MF Sarhan","year":"2012","journal-title":"Proc Natl Acad Sci"},{"key":"pcbi.1011953.ref101","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1093\/bioinformatics\/btq007","article-title":"PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta","volume":"26","author":"S Chaudhury","year":"2010","journal-title":"Bioinformatics"},{"key":"pcbi.1011953.ref102","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1016\/j.jmb.2010.11.008","article-title":"Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping","volume":"405","author":"MD Tyka","year":"2011","journal-title":"J Mol Biol"},{"key":"pcbi.1011953.ref103","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1002\/pro.2389","article-title":"Relaxation of backbone bond geometry improves protein energy landscape modeling","volume":"23","author":"P Conway","year":"2014","journal-title":"Protein Sci"},{"key":"pcbi.1011953.ref104","doi-asserted-by":"crossref","first-page":"e1008103","DOI":"10.1371\/journal.pcbi.1008103","article-title":"Efficient consideration of coordinated water molecules improves computational protein-protein and protein-ligand docking discrimination.","volume":"16","author":"RE Pavlovicz","year":"2020","journal-title":"PLOS Comput Biol"},{"key":"pcbi.1011953.ref105","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1002\/(SICI)1096-987X(199802)19:3<319::AID-JCC6>3.0.CO;2-W","article-title":"Exact and efficient analytical calculation of the accessible surface areas and their gradients for macromolecules","volume":"19","author":"R Fraczkiewicz","year":"1998","journal-title":"J Comput Chem"},{"key":"pcbi.1011953.ref106","doi-asserted-by":"crossref","first-page":"89497","DOI":"10.1109\/ACCESS.2020.2990567","article-title":"Pymoo: Multi-Objective Optimization in Python.","volume":"8","author":"J Blank","year":"2020","journal-title":"IEEE Access"},{"key":"pcbi.1011953.ref107","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1109\/MCSE.2021.3083216","article-title":"mpi4py: Status Update After 12 Years of Development.","volume":"23","author":"L Dalcin","year":"2021","journal-title":"Comput Sci Eng"},{"key":"pcbi.1011953.ref108","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1109\/TEVC.2013.2281535","article-title":"An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints.","volume":"18","author":"K Deb","year":"2014","journal-title":"IEEE Trans Evol Comput"},{"key":"pcbi.1011953.ref109","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1109\/TEVC.2020.2992387","article-title":"Generating Well-Spaced Points on a Unit Simplex for Evolutionary Many-Objective Optimization","volume":"25","author":"J Blank","year":"2021","journal-title":"IEEE Trans Evol Comput"},{"key":"pcbi.1011953.ref110","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1002\/prot.20264","article-title":"Scoring function for automated assessment of protein structure template quality","volume":"57","author":"Y Zhang","year":"2004","journal-title":"Proteins Struct Funct Bioinforma"},{"key":"pcbi.1011953.ref111","article-title":"Prediction of multiple conformational states by combining sequence clustering with AlphaFold2.","author":"HK Wayment-Steele","year":"2022","journal-title":"bioRxiv"},{"key":"pcbi.1011953.ref112","doi-asserted-by":"crossref","first-page":"e75751","DOI":"10.7554\/eLife.75751","article-title":"Sampling alternative conformational states of transporters and receptors with AlphaFold2.","volume":"11","author":"D del Alamo","year":"2022","journal-title":"eLife"},{"key":"pcbi.1011953.ref113","article-title":"Conditioned Protein Structure Prediction.","author":"T Xie","year":"2023","journal-title":"bioRxiv"},{"key":"pcbi.1011953.ref114","first-page":"1","article-title":"Computational scoring and experimental evaluation of enzymes generated by neural networks","author":"SR Johnson","year":"2024","journal-title":"Nat Biotechnol"},{"key":"pcbi.1011953.ref115","article-title":"Generating novel protein sequences using Gibbs sampling of masked language models.","author":"SR Johnson","year":"2021","journal-title":"bioRxiv"},{"key":"pcbi.1011953.ref116","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.artint.2012.09.005","article-title":"Approximation quality of the hypervolume indicator.","volume":"195","author":"K Bringmann","year":"2013","journal-title":"Artif Intell"},{"key":"pcbi.1011953.ref117","doi-asserted-by":"crossref","first-page":"2338","DOI":"10.21105\/joss.02338","article-title":"A parallel global multiobjective framework for optimization: pagmo.","volume":"5","author":"F Biscani","year":"2020","journal-title":"J Open Source Softw"},{"key":"pcbi.1011953.ref118","doi-asserted-by":"crossref","first-page":"10915","DOI":"10.1073\/pnas.89.22.10915","article-title":"Amino acid substitution matrices from protein blocks","volume":"89","author":"S Henikoff","year":"1992","journal-title":"Proc Natl Acad Sci"},{"key":"pcbi.1011953.ref119","doi-asserted-by":"crossref","first-page":"1422","DOI":"10.1093\/bioinformatics\/btp163","article-title":"Biopython: freely available Python tools for computational molecular biology and bioinformatics","volume":"25","author":"PJA Cock","year":"2009","journal-title":"Bioinformatics"},{"key":"pcbi.1011953.ref120","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python.","volume":"12","author":"F Pedregosa","year":"2011","journal-title":"J Mach Learn Res."},{"key":"pcbi.1011953.ref121","author":"Eric Jones","year":"2001","journal-title":"SciPy: Open Source Scientific Tools for Python"},{"key":"pcbi.1011953.ref122","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","article-title":"SciPy 1.0: fundamental algorithms for scientific computing","volume":"17","author":"P Virtanen","year":"2020","journal-title":"Python. Nat Methods"},{"key":"pcbi.1011953.ref123","doi-asserted-by":"crossref","first-page":"2272","DOI":"10.1093\/bioinformatics\/btz921","article-title":"Logomaker: beautiful sequence logos in Python","volume":"36","author":"A Tareen","year":"2020","journal-title":"Bioinformatics"},{"key":"pcbi.1011953.ref124","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1186\/s13059-017-1287-y","article-title":"Non-base-contacting residues enable kaleidoscopic evolution of metazoan C2H2 zinc finger DNA binding","volume":"18","author":"HS Najafabadi","year":"2017","journal-title":"Genome Biol"},{"key":"pcbi.1011953.ref125","doi-asserted-by":"crossref","first-page":"D523","DOI":"10.1093\/nar\/gkac1052","article-title":"UniProt: the Universal Protein Knowledgebase in 2023","volume":"51","author":"The UniProt Consortium","year":"2023","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1011953.ref126","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1038\/msb.2011.75","article-title":"Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega","volume":"7","author":"F Sievers","year":"2011","journal-title":"Mol Syst Biol"},{"key":"pcbi.1011953.ref127","doi-asserted-by":"crossref","first-page":"W276","DOI":"10.1093\/nar\/gkac240","article-title":"Search and sequence analysis tools services from EMBL-EBI in 2022","volume":"50","author":"F Madeira","year":"2022","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1011953.ref128","doi-asserted-by":"crossref","first-page":"e4428","DOI":"10.1002\/pro.4428","article-title":"Stabilizing proteins, simplified: A Rosetta-based webtool for predicting favorable mutations","volume":"31","author":"DF Thieker","year":"2022","journal-title":"Protein Sci"},{"key":"pcbi.1011953.ref129","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1002\/pro.2187","article-title":"A comparison of successful and failed protein interface designs highlights the challenges of designing buried hydrogen bonds","volume":"22","author":"PB Stranges","year":"2013","journal-title":"Protein Sci"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1011953","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2024,7,23]],"date-time":"2024-07-23T00:00:00Z","timestamp":1721692800000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1011953","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,23]],"date-time":"2024-07-23T15:11:48Z","timestamp":1721747508000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1011953"}},"subtitle":[],"editor":[{"given":"Alexey","family":"Onufriev","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2024,7,11]]},"references-count":129,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,7,11]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1011953","relation":{},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,11]]}}}