{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T14:38:39Z","timestamp":1786113519473,"version":"build-2736575974"},"posted":{"date-parts":[[2026,8,4]]},"group-title":"Bioengineering","reference-count":29,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.biorxiv.org\/about\/FAQ#license"}],"funder":[{"id":[{"id":"https:\/\/ror.org\/044fk6795","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Rutgers Health BMIHAI Pilot Grant Program"},{"name":"National Institutes of Health, National Institute of General Medical Sciences","award":["T32 GM135141"],"award-info":[{"award-number":["T32 GM135141"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,8,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                <jats:p>\n                  Machine learning-guided protein sequence redesign is now routinely used to optimize multiple properties relevant for protein engineering, most prominently thermostability and recombinant expression levels. Salt tolerance is a valuable property for \u201dblue-biotechnology\u201d- enabled biomanufacturing, yet no generative computational method exists to redesign proteins for increased salt tolerance. We hypothesized that a training dataset heavily biased toward salt-adapted proteomes would yield a model capable of designing proteins with halophilic properties. To test this, we retrained the sequence redesign model ProteinMPNN on proteins from \u201csalt-in\u201d extreme halophiles such as\n                  <jats:italic>Haloarcula marismortui<\/jats:italic>\n                  , a Dead Sea archaeon that grows optimally near 3\u20134 M NaCl, roughly six times the salinity of seawater, and accumulates molar concentrations of salts in its cytoplasm. Our model, HaloMPNN, redesigns non-halophilic proteins so that their properties shift towards those of natural halophilic proteins: lower predicted isoelectric point, greater surface acidity, and reduced surface and core hydrophobicity. Redesigning a broad range of non-halophilic proteins with SolubleMPNN, ProteinMPNN, and HyperMPNN shows that this shift is specific to HaloMPNN rather than a generic consequence of sequence redesign. HaloMPNN therefore offers both a route to designing candidate salt-tolerant enzymes and a means of identifying the characteristics that underlie halophilic adaptation.\n                <\/jats:p>","DOI":"10.64898\/2026.08.02.742362","type":"posted-content","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T12:00:29Z","timestamp":1785844829000},"source":"Crossref","is-referenced-by-count":0,"title":["HaloMPNN: retraining ProteinMPNN on halophilic proteomes for salt-tolerant enzyme design"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-4407-6853","authenticated-orcid":false,"given":"Alyssa Lu","family":"Lee","sequence":"first","affiliation":[{"name":"Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6824-0428","authenticated-orcid":false,"given":"Austin","family":"Seamann","sequence":"additional","affiliation":[{"name":"Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gwendolyn","family":"Chung","sequence":"additional","affiliation":[{"name":"Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ 08854, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Clairie","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Rutgers, The State University of New Jersey, 110 Frelinghuysen Road, Piscataway, NJ 08854, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3370-092X","authenticated-orcid":false,"given":"Rohan","family":"Maddamsetti","sequence":"additional","affiliation":[{"name":"Department of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, 76 Lipman Drive, New Brunswick, New Jersey 08901, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2255-0543","authenticated-orcid":false,"given":"Sagar D.","family":"Khare","sequence":"additional","affiliation":[{"name":"Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, United States"},{"name":"Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 123 Bevier Road, Piscataway, New Jersey 08854, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026080512400794000_2026.08.02.742362v1.1","doi-asserted-by":"publisher","DOI":"10.1126\/science.add2187"},{"key":"2026080512400794000_2026.08.02.742362v1.2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-024-07601-y"},{"key":"2026080512400794000_2026.08.02.742362v1.3","doi-asserted-by":"crossref","unstructured":"M. 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