{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T19:03:24Z","timestamp":1790622204691,"version":"4.1.0"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1014778","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T00:00:00Z","timestamp":1790553600000}}],"reference-count":29,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"\n Machine learning (ML) methods for proteins and RNAs rely on multiple sequence alignments (MSAs) and related datasets such as experimental mutagenesis libraries, yet the amount of usable information they contain remains unclear. Here, a spectral measure of information is recast into an interpretable quantity for MSAs, denoted\n \n \n \n \n \n \n L<\/mml:mi>\n \n e<\/mml:mi>\n f<\/mml:mi>\n f<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msub>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n , defined as the number of fully independent alignment positions that reproduce the observed sequence diversity. Applied to RNA MSAs, this measure shows that evolutionary constraints nearly halve diversity relative to the secondary structure alone, quantifying functional and phylogenetic restrictions beyond base pairing. The same analysis indicates even lower effective diversity in proteins, reflecting tighter packing and coevolutionary constraints.\n \n \n \n \n \n \n L<\/mml:mi>\n \n e<\/mml:mi>\n f<\/mml:mi>\n f<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msub>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n further correlates with protein structure prediction accuracy, anticipating cases with insufficient evolutionary signal. When applied to experimentally and computationally generated libraries, it measures both produced diversity and cross-library overlap, quantifying novelty rather than redundant sampling. Together, these results establish\n \n \n \n \n \n \n L<\/mml:mi>\n \n e<\/mml:mi>\n f<\/mml:mi>\n f<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msub>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n as an operational tool to estimate effective information in MSAs, anticipate modeling difficulties, and guide protein and RNA design.\n <\/jats:p>","DOI":"10.1371\/journal.pcbi.1014778","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T17:49:40Z","timestamp":1790185780000},"page":"e1014778","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["A spectral framework for measuring diversity in multiple sequence alignments"],"prefix":"10.1371","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8364-5098","authenticated-orcid":true,"given":"Vaitea","family":"Opuu","sequence":"first","affiliation":[{"name":"PSL University","place":["Paris, France"],"department":["Laboratoire de Biophysique et Evolution, UMR CNRS-ESPCI 8231 Chimie Biologie Innovation"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"pcbi.1014778.ref001","doi-asserted-by":"crossref","first-page":"64331","DOI":"10.52202\/075280-2810","article-title":"Proteingym: Large-scale benchmarks for protein fitness prediction and design","volume":"36","author":"P Notin","year":"2023","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"1","key":"pcbi.1014778.ref002","doi-asserted-by":"crossref","first-page":"7836","DOI":"10.1038\/s41467-025-63151-5","article-title":"Exploring the space of self-reproducing ribozymes using generative models","volume":"16","author":"CN Lambert","year":"2025","journal-title":"Nat Commun"},{"key":"pcbi.1014778.ref003","first-page":"29287","article-title":"Language models enable zero-shot prediction of the effects of mutations on protein function","volume":"34","author":"J Meier","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"7873","key":"pcbi.1014778.ref004","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1038\/s41586-021-03819-2","article-title":"Highly accurate protein structure prediction with AlphaFold","volume":"596","author":"J Jumper","year":"2021","journal-title":"Nature"},{"issue":"15","key":"pcbi.1014778.ref005","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2016239118","article-title":"Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences","volume":"118","author":"A Rives","year":"2021","journal-title":"Proc Natl Acad Sci U S A"},{"key":"pcbi.1014778.ref006","doi-asserted-by":"crossref","unstructured":"Ding F, Steinhardt J. 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