{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T19:05:12Z","timestamp":1790276712623,"version":"4.1.0"},"reference-count":49,"publisher":"American Chemical Society (ACS)","issue":"7","license":[{"start":{"date-parts":[[2023,3,30]],"date-time":"2023-03-30T00:00:00Z","timestamp":1680134400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/S022848\/1"],"award-info":[{"award-number":["EP\/S022848\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,4,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Recent advances in machine learning methods have had a significant impact on protein structure prediction, but accurate generation and characterization of protein-folding pathways remains intractable. Here, we demonstrate how protein folding trajectories can be generated using a directed walk strategy operating in the space defined by the residue-level contact-map. This double-ended strategy views protein folding as a series of discrete transitions between connected minima on the potential energy surface. Subsequent reaction-path analysis for each transition enables thermodynamic and kinetic characterization of each protein-folding path. We validate the protein-folding paths generated by our discretized-walk strategy against direct molecular dynamics simulations for a series of model coarse-grained proteins constructed from hydrophobic and polar residues. This comparison demonstrates that ranking discretized paths based on the intermediate energy barriers provides a convenient route to identifying physically sensible folding ensembles. Importantly, by using directed walks in the protein contact-map space, we circumvent several of the traditional challenges associated with protein-folding studies, namely, long time scales required and the choice of a specific order parameter to drive the folding process. As such, our approach offers a useful new route for studying the protein-folding problem.<\/jats:p>","DOI":"10.1021\/acs.jcim.3c00023","type":"journal-article","created":{"date-parts":[[2023,3,30]],"date-time":"2023-03-30T12:27:42Z","timestamp":1680179262000},"page":"2181-2195","source":"Crossref","is-referenced-by-count":8,"title":["Generating Protein\nFolding Trajectories Using Contact-Map-Driven\nDirected Walks"],"prefix":"10.1021","volume":"63","author":[{"given":"Ziad","family":"Fakhoury","sequence":"first","affiliation":[{"name":"University of Warwick , , ,","place":["Coventry, United\nKingdom, CV4 7AL"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6156-7399","authenticated-orcid":true,"given":"Gabriele C.","family":"Sosso","sequence":"additional","affiliation":[{"name":"University of Warwick , , ,","place":["Coventry, United\nKingdom, CV4 7AL"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5932-6011","authenticated-orcid":true,"given":"Scott","family":"Habershon","sequence":"additional","affiliation":[{"name":"University of Warwick , , ,","place":["Coventry, United\nKingdom, CV4 7AL"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2023,3,30]]},"reference":[{"key":"2026081804440219000_cit1","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-00882-0","volume-title":"Protein Folding:\nAn Introduction","author":"Gomes","year":"2019"},{"key":"2026081804440219000_cit2","first-page":"22","article-title":"How to Fold\nGraciously","author":"Levinthal","year":"1969","journal-title":"Mossbauer Spectroscopy in Biological\nSystems"},{"key":"2026081804440219000_cit3","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1038\/s41586-021-03819-2","article-title":"Highly accurate protein structure prediction\nwith AlphaFold","volume":"596","author":"Jumper","year":"2021","journal-title":"Nature"},{"key":"2026081804440219000_cit4","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/d41586-020-03348-4","article-title":"\u2018It\nwill change everything\u2019: DeepMind\u2019s AI makes gigantic\nleap in solving protein structures","volume":"588","author":"Callaway","year":"2020","journal-title":"Nature"},{"key":"2026081804440219000_cit5","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1126\/science.1079589","article-title":"Prevention of transthyretin\namyloid disease by changing protein misfolding energetics","volume":"299","author":"Hammarstrom","year":"2003","journal-title":"Science"},{"key":"2026081804440219000_cit6","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.sbi.2013.12.006","article-title":"Assessing the accuracy of physical\nmodels used in protein-folding simulations: quantitative evidence\nfrom long molecular dynamics simulations","volume":"24","author":"Piana","year":"2014","journal-title":"Curr.\nOpin. 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