Bulletin of the American Physical Society
APS March Meeting 2023
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session T13: Physics of biological computation across scales
11:30 AM–2:30 PM,
Thursday, March 9, 2023
Room: Room 238
Sponsoring Unit: DBIO
Chair: Shenshen Wang, University of California, Los Angeles
Abstract: T13.00003 : Optimization and historical contingency in protein sequences*
12:42 PM–1:18 PM
Correlations arising from phylogeny often confound coevolution signal from functional or structural optimization, impairing the inference of structural contacts from sequences. However, inferred Potts models are more robust than local statistics to these effects, which may explain their success . Dedicated corrections can further increase this robustness . Moreover, phylogenetic correlations can in fact provide useful information for some inference tasks, especially to infer interaction partners from sequences among the paralogs of two protein families. In this case, signal from phylogeny and signal from constraints combine constructively , and explicitly exploiting both further improves inference performance .
Protein language models have recently been applied to sequence data, greatly advancing structure, function and mutational effect prediction. Language models trained on multiple sequence alignments capture coevolution and structural contacts, but also phylogenetic relationships . They are able to disentangle signal from structural constraints and from phylogeny more efficiently than Potts models , and they have promising generative properties .
*This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 851173, to A.-F. B.).
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