Reoptimized UNRES potential for protein model quality assessment

Eshel Faraggi , Paweł Krupa , Magdalena Mozolewska , Józef Adam Liwo , Andrzej Kloczkowski

Abstract

Ranking protein structure models is an elusive problem in bioinformatics. These models are evaluated on both the degree of similarity to the native structure and the folding pathway. Here, we simulated the use of the coarse-grained UNited RESidue (UNRES) force field as a tool to choose the best protein structure models for a given protein sequence among a pool of candidate models, using server data from the CASP11 experiment. Because the original UNRES was optimized for Molecular Dynamics simulations, we reoptimized UNRES using a deep feed-forward neural network, and we show that introducing additional descriptive features can produce better results. Overall, we found that the reoptimized UNRES performs better in selecting the best structures and tracking protein unwinding from its native state. We also found a relatively poor correlation between UNRES values and the model’s Template Modeling Score (TMS). This is remedied by reoptimization. We discuss some cases where our reoptimization procedure is useful.
Author Eshel Faraggi
Eshel Faraggi,,
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, Paweł Krupa
Paweł Krupa,,
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, Magdalena Mozolewska
Magdalena Mozolewska,,
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, Józef Adam Liwo (FCh / DTCh / LMM)
Józef Adam Liwo,,
- Laboratory of Molecular Modeling
, Andrzej Kloczkowski
Andrzej Kloczkowski,,
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Journal seriesGenes, ISSN 2073-4425, (A 25 pkt)
Issue year2018
Vol9
No12
Pages1-17
Publication size in sheets0.8
Keywords in Englishprotein energy; optimization; model ranking; UNRES; Seder; GENN; OUNRES
DOIDOI:10.3390/genes9120601
URL https://doi.org/10.3390/genes9120601
Languageen angielski
LicenseJournal (articles only); published final; Uznanie Autorstwa (CC-BY); with publication
Score (nominal)25
ScoreMinisterial score = 25.0, ArticleFromJournal
Ministerial score (2013-2016) = 25.0, ArticleFromJournal
Publication indicators WoS Impact Factor: 2017 = 3.191 (2) - 2017=3.286 (5)
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