{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T23:18:42Z","timestamp":1783811922012,"version":"3.55.0"},"reference-count":42,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,2,5]],"date-time":"2024-02-05T00:00:00Z","timestamp":1707091200000},"content-version":"vor","delay-in-days":4,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Dutch Research Organisation"},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NWO Vidi scheme"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Many membrane peripheral proteins have evolved to transiently interact with the surface of (curved) lipid bilayers. Currently, methods to quantitatively predict sensing and binding free energies for protein sequences or structures are lacking, and such tools could greatly benefit the discovery of membrane-interacting motifs, as well as their de novo design.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we trained a transformer neural network model on molecular dynamics data for &amp;gt;50 000 peptides that is able to accurately predict the (relative) membrane-binding free energy for any given amino acid sequence. Using this information, our physics-informed model is able to classify a peptide\u2019s membrane-associative activity as either non-binding, curvature sensing, or membrane binding. Moreover, this method can be applied to detect membrane-interaction regions in a wide variety of proteins, with comparable predictive performance as state-of-the-art data-driven tools like DREAMM, PPM3, and MODA, but with a wider applicability regarding protein diversity, and the added feature to distinguish curvature sensing from general membrane binding.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>We made these tools available as a web server, coined Protein-Membrane Interaction predictor (PMIpred), which can be accessed at https:\/\/pmipred.fkt.physik.tu-dortmund.de.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae069","type":"journal-article","created":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T16:06:05Z","timestamp":1706803565000},"source":"Crossref","is-referenced-by-count":32,"title":["PMIpred: a physics-informed web server for quantitative protein\u2013membrane interaction prediction"],"prefix":"10.1093","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1204-2489","authenticated-orcid":false,"given":"Niek","family":"van Hilten","sequence":"first","affiliation":[{"name":"Leiden Institute of Chemistry, Leiden University , Leiden 2333 CC, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2464-6896","authenticated-orcid":false,"given":"Nino","family":"Verwei","sequence":"additional","affiliation":[{"name":"Leiden Institute of Chemistry, Leiden University , Leiden 2333 CC, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeroen","family":"Methorst","sequence":"additional","affiliation":[{"name":"Leiden Institute of Chemistry, Leiden University , Leiden 2333 CC, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carsten","family":"Nase","sequence":"additional","affiliation":[{"name":"Department of Physics, Technical University Dortmund , Dortmund 44227, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrius","family":"Bernatavicius","sequence":"additional","affiliation":[{"name":"Leiden Institute of Advanced Computer Science, Leiden University , Leiden 2333 CA, Netherlands"},{"name":"Leiden Academic Centre for Drug Research, Leiden University , Leiden 2333 CC, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Herre Jelger","family":"Risselada","sequence":"additional","affiliation":[{"name":"Leiden Institute of Chemistry, Leiden University , Leiden 2333 CC, Netherlands"},{"name":"Department of Physics, Technical University Dortmund , Dortmund 44227, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,2,5]]},"reference":[{"key":"2024062814445421200_btae069-B1","doi-asserted-by":"crossref","first-page":"15452","DOI":"10.1038\/srep15452","article-title":"Structural insights into the cooperative remodeling of membranes by amphiphysin\/bin1","volume":"5","author":"Adam","year":"2015","journal-title":"Sci Rep"},{"key":"2024062814445421200_btae069-B5","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1038\/nature02108","article-title":"Lipid packing sensed by ArfGAP1 couples COPI coat disassembly to membrane bilayer curvature","volume":"426","author":"Bigay","year":"2003","journal-title":"Nature"},{"key":"2024062814445421200_btae069-B7","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1021\/ja907936c","article-title":"Curvature sensing by the epsin n-terminal homology domain measured on cylindrical lipid membrane tethers","volume":"132","author":"Capraro","year":"2010","journal-title":"J Am Chem Soc"},{"key":"2024062814445421200_btae069-B8","doi-asserted-by":"crossref","first-page":"5449","DOI":"10.1093\/bioinformatics\/btac680","article-title":"DREAMM: a web-based server for drugging protein-membrane interfaces as a novel workflow for targeted drug design","volume":"38","author":"Chatzigoulas","year":"2022","journal-title":"Bioinformatics"},{"key":"2024062814445421200_btae069-B9","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbab518","article-title":"Predicting protein-membrane interfaces of peripheral membrane proteins using ensemble machine learning","volume":"23","author":"Chatzigoulas","year":"2022","journal-title":"Brief. 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