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Assessing multiple score functions in Rosetta for drug discovery

Rosetta is a computational software suite containing algorithms for a wide variety of macromolecular structure prediction and design tasks including small molecule protocols commonly used in drug discovery or enzyme design. Here, we benchmark RosettaLigand score functions and protocols in comparison...

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Autores principales: Smith, Shannon T., Meiler, Jens
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7549810/
https://www.ncbi.nlm.nih.gov/pubmed/33044994
http://dx.doi.org/10.1371/journal.pone.0240450
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author Smith, Shannon T.
Meiler, Jens
author_facet Smith, Shannon T.
Meiler, Jens
author_sort Smith, Shannon T.
collection PubMed
description Rosetta is a computational software suite containing algorithms for a wide variety of macromolecular structure prediction and design tasks including small molecule protocols commonly used in drug discovery or enzyme design. Here, we benchmark RosettaLigand score functions and protocols in comparison to results of other software recently published in the Comparative Assessment of Score Functions (CASF-2016). The CASF-2016 benchmark covers a wide variety of tests including scoring and ranking multiple compounds against a target, ligand docking of a small molecule to a target, and virtual screening to extract binders from a compound library. Direct comparison to the score functions provided by CASF-2016 results shows that the original RosettaLigand score function ranks among the top software for scoring, ranking, docking and screening tests. Most notably, the RosettaLigand score function ranked 2/34 among other report score functions in CASF-2016. We additionally perform a ligand docking test with full sampling to mimic typical use cases. Despite improved performance of newer score functions in canonical protein structure prediction and design, we demonstrate here that more recent Rosetta score functions have reduced performance across all small molecule benchmarks. The tests described here have also been uploaded to the Rosetta scientific benchmarking server and will be run weekly to track performance as the code is continually being developed.
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spelling pubmed-75498102020-10-20 Assessing multiple score functions in Rosetta for drug discovery Smith, Shannon T. Meiler, Jens PLoS One Research Article Rosetta is a computational software suite containing algorithms for a wide variety of macromolecular structure prediction and design tasks including small molecule protocols commonly used in drug discovery or enzyme design. Here, we benchmark RosettaLigand score functions and protocols in comparison to results of other software recently published in the Comparative Assessment of Score Functions (CASF-2016). The CASF-2016 benchmark covers a wide variety of tests including scoring and ranking multiple compounds against a target, ligand docking of a small molecule to a target, and virtual screening to extract binders from a compound library. Direct comparison to the score functions provided by CASF-2016 results shows that the original RosettaLigand score function ranks among the top software for scoring, ranking, docking and screening tests. Most notably, the RosettaLigand score function ranked 2/34 among other report score functions in CASF-2016. We additionally perform a ligand docking test with full sampling to mimic typical use cases. Despite improved performance of newer score functions in canonical protein structure prediction and design, we demonstrate here that more recent Rosetta score functions have reduced performance across all small molecule benchmarks. The tests described here have also been uploaded to the Rosetta scientific benchmarking server and will be run weekly to track performance as the code is continually being developed. Public Library of Science 2020-10-12 /pmc/articles/PMC7549810/ /pubmed/33044994 http://dx.doi.org/10.1371/journal.pone.0240450 Text en © 2020 Smith, Meiler http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Smith, Shannon T.
Meiler, Jens
Assessing multiple score functions in Rosetta for drug discovery
title Assessing multiple score functions in Rosetta for drug discovery
title_full Assessing multiple score functions in Rosetta for drug discovery
title_fullStr Assessing multiple score functions in Rosetta for drug discovery
title_full_unstemmed Assessing multiple score functions in Rosetta for drug discovery
title_short Assessing multiple score functions in Rosetta for drug discovery
title_sort assessing multiple score functions in rosetta for drug discovery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7549810/
https://www.ncbi.nlm.nih.gov/pubmed/33044994
http://dx.doi.org/10.1371/journal.pone.0240450
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