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Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe

[Image: see text] The small molecule universe (SMU) is defined as a set of over 10(60) synthetically feasible organic molecules with molecular weight less than ∼500 Da. Exhaustive enumerations and evaluation of all SMU molecules for the purpose of discovering favorable structures is impossible. We t...

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Autores principales: Rupakheti, Chetan, Virshup, Aaron, Yang, Weitao, Beratan, David N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2015
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4372820/
https://www.ncbi.nlm.nih.gov/pubmed/25594586
http://dx.doi.org/10.1021/ci500749q
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author Rupakheti, Chetan
Virshup, Aaron
Yang, Weitao
Beratan, David N.
author_facet Rupakheti, Chetan
Virshup, Aaron
Yang, Weitao
Beratan, David N.
author_sort Rupakheti, Chetan
collection PubMed
description [Image: see text] The small molecule universe (SMU) is defined as a set of over 10(60) synthetically feasible organic molecules with molecular weight less than ∼500 Da. Exhaustive enumerations and evaluation of all SMU molecules for the purpose of discovering favorable structures is impossible. We take a stochastic approach and extend the ACSESS framework (Virshup et al. J. Am. Chem. Soc.2013, 135, 7296–730323548177) to develop diversity oriented molecular libraries that can generate a set of compounds that is representative of the small molecule universe and that also biases the library toward favorable physical property values. We show that the approach is efficient compared to exhaustive enumeration and to existing evolutionary algorithms for generating such libraries by testing in the NKp fitness landscape model and in the fully enumerated GDB-9 chemical universe containing 3 × 10(5) molecules.
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spelling pubmed-43728202015-03-31 Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe Rupakheti, Chetan Virshup, Aaron Yang, Weitao Beratan, David N. J Chem Inf Model [Image: see text] The small molecule universe (SMU) is defined as a set of over 10(60) synthetically feasible organic molecules with molecular weight less than ∼500 Da. Exhaustive enumerations and evaluation of all SMU molecules for the purpose of discovering favorable structures is impossible. We take a stochastic approach and extend the ACSESS framework (Virshup et al. J. Am. Chem. Soc.2013, 135, 7296–730323548177) to develop diversity oriented molecular libraries that can generate a set of compounds that is representative of the small molecule universe and that also biases the library toward favorable physical property values. We show that the approach is efficient compared to exhaustive enumeration and to existing evolutionary algorithms for generating such libraries by testing in the NKp fitness landscape model and in the fully enumerated GDB-9 chemical universe containing 3 × 10(5) molecules. American Chemical Society 2015-01-16 2015-03-23 /pmc/articles/PMC4372820/ /pubmed/25594586 http://dx.doi.org/10.1021/ci500749q Text en Copyright © 2015 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
spellingShingle Rupakheti, Chetan
Virshup, Aaron
Yang, Weitao
Beratan, David N.
Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe
title Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe
title_full Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe
title_fullStr Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe
title_full_unstemmed Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe
title_short Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe
title_sort strategy to discover diverse optimal molecules in the small molecule universe
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4372820/
https://www.ncbi.nlm.nih.gov/pubmed/25594586
http://dx.doi.org/10.1021/ci500749q
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