How Does the Methodology of 3D Structure Preparation Influence the Quality of pK(a) Prediction?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F15%3A00082988" target="_blank" >RIV/00216224:14740/15:00082988 - isvavai.cz</a>

Výsledek na webu

<a href="http://pubs.acs.org/doi/pdf/10.1021/ci500758w" target="_blank" >http://pubs.acs.org/doi/pdf/10.1021/ci500758w</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1021/ci500758w" target="_blank" >10.1021/ci500758w</a>

Jazyk výsledku

angličtina

Název v původním jazyce

How Does the Methodology of 3D Structure Preparation Influence the Quality of pK(a) Prediction?

Popis výsledku v původním jazyce

The acid dissociation constant is an important molecular property, and it can be successfully predicted by Quantitative Structure-Property Relationship (QSPR) models, even for in silico designed molecules. We analyzed how the methodology of in silico 3Dstructure preparation influences the quality of QSPR models. Specifically, we evaluated and compared QSPR models based on six different 3D structure sources (DTP NCI, Pubchem, Balloon, Frog2, OpenBabel, and RDKit) combined with four different types of optimization. These analyses were performed for three classes of molecules (phenols, carboxylic acids, anilines), and the QSPR model descriptors were quantum mechanical (QM) and empirical partial atomic charges. Specifically, we developed 516 QSPR models and afterward systematically analyzed the influence of the 3D structure source and other factors on their quality. Our results confirmed that QSPR models based on partial atomic charges are able to predict pK(a) with high accuracy.

Název v anglickém jazyce

How Does the Methodology of 3D Structure Preparation Influence the Quality of pK(a) Prediction?

Popis výsledku anglicky

The acid dissociation constant is an important molecular property, and it can be successfully predicted by Quantitative Structure-Property Relationship (QSPR) models, even for in silico designed molecules. We analyzed how the methodology of in silico 3Dstructure preparation influences the quality of QSPR models. Specifically, we evaluated and compared QSPR models based on six different 3D structure sources (DTP NCI, Pubchem, Balloon, Frog2, OpenBabel, and RDKit) combined with four different types of optimization. These analyses were performed for three classes of molecules (phenols, carboxylic acids, anilines), and the QSPR model descriptors were quantum mechanical (QM) and empirical partial atomic charges. Specifically, we developed 516 QSPR models and afterward systematically analyzed the influence of the 3D structure source and other factors on their quality. Our results confirmed that QSPR models based on partial atomic charges are able to predict pK(a) with high accuracy.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

CE - Biochemie

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Chemical Information and Modeling

ISSN

1549-9596

e-ISSN

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Svazek periodika

55

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

1088-1097

Kód UT WoS článku

000356903200002

EID výsledku v databázi Scopus

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