Chemical space exploration with Molpher: Generating and assessing a glucocorticoid receptor ligand library

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378050%3A_____%2F23%3A00604437" target="_blank" >RIV/68378050:_____/23:00604437 - isvavai.cz</a>

Výsledek na webu

<a href="https://onlinelibrary.wiley.com/doi/10.1002/minf.202300316" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/minf.202300316</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.26434/chemrxiv-2023-4jm5t" target="_blank" >10.26434/chemrxiv-2023-4jm5t</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Chemical space exploration with Molpher: Generating and assessing a glucocorticoid receptor ligand library

Popis výsledku v původním jazyce

Computational exploration of chemical space is important in modern cheminformatics research as it can accelerate the discovery of new biologically active compounds. In this study, we present a detailed analysis of a chemical library generated by one of the available molecular generators, Molpher. A targeted library of potential glucocorticoid receptor (GR) ligands was generated, and its composition was compared with a reference library randomly sampling chemical space. A random forest was used to determine the biological activity of ligands, and its applicability domain, which is essential to consider when predicting the biological activity of newly designed compounds, was incorporated using conformal prediction. It was demonstrated that the GR ligand library is significantly enriched with GR ligands compared to the random library. Moreover, through prospective analysis, it was shown that Molpher could design compounds that were later experimentally verified as active on the GR. Finally, a set of 34 potential GR ligands was proposed.

Název v anglickém jazyce

Chemical space exploration with Molpher: Generating and assessing a glucocorticoid receptor ligand library

Popis výsledku anglicky

Computational exploration of chemical space is important in modern cheminformatics research as it can accelerate the discovery of new biologically active compounds. In this study, we present a detailed analysis of a chemical library generated by one of the available molecular generators, Molpher. A targeted library of potential glucocorticoid receptor (GR) ligands was generated, and its composition was compared with a reference library randomly sampling chemical space. A random forest was used to determine the biological activity of ligands, and its applicability domain, which is essential to consider when predicting the biological activity of newly designed compounds, was incorporated using conformal prediction. It was demonstrated that the GR ligand library is significantly enriched with GR ligands compared to the random library. Moreover, through prospective analysis, it was shown that Molpher could design compounds that were later experimentally verified as active on the GR. Finally, a set of 34 potential GR ligands was proposed.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10601 - Cell biology

Projekt

<a href="/cs/project/LM2023052" target="_blank" >LM2023052: Národní infrastruktura chemické biologie</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

ChemRxiv

ISSN

2573-2293

e-ISSN

2573-2293

Svazek periodika

43

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

24

Strana od-do

e202300316

Kód UT WoS článku

001268141400001

EID výsledku v databázi Scopus

2-s2.0-85197786625