Comparative Structure-Based Virtual Screening Utilizing Optimized AlphaFold Model Identifies Selective HDAC11 Inhibitor

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652036%3A_____%2F24%3A00582379" target="_blank" >RIV/86652036:_____/24:00582379 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/1422-0067/25/2/1358" target="_blank" >https://www.mdpi.com/1422-0067/25/2/1358</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/ijms25021358" target="_blank" >10.3390/ijms25021358</a>

Result language

angličtina

Original language name

Comparative Structure-Based Virtual Screening Utilizing Optimized AlphaFold Model Identifies Selective HDAC11 Inhibitor

Original language description

HDAC11 is a class IV histone deacylase with no crystal structure reported so far. The catalytic domain of HDAC11 shares low sequence identity with other HDAC isoforms, which makes conventional homology modeling less reliable. AlphaFold is a machine learning approach that can predict the 3D structure of proteins with high accuracy even in absence of similar structures. However, the fact that AlphaFold models are predicted in the absence of small molecules and ions/cofactors complicates their utilization for drug design. Previously, we optimized an HDAC11 AlphaFold model by adding the catalytic zinc ion and minimization in the presence of reported HDAC11 inhibitors. In the current study, we implement a comparative structure-based virtual screening approach utilizing the previously optimized HDAC11 AlphaFold model to identify novel and selective HDAC11 inhibitors. The stepwise virtual screening approach was successful in identifying a hit that was subsequently tested using an in vitro enzymatic assay. The hit compound showed an IC50 value of 3.5 mu M for HDAC11 and could selectively inhibit HDAC11 over other HDAC subtypes at 10 mu M concentration. In addition, we carried out molecular dynamics simulations to further confirm the binding hypothesis obtained by the docking study. These results reinforce the previously presented AlphaFold optimization approach and confirm the applicability of AlphaFold models in the search for novel inhibitors for drug discovery.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10608 - Biochemistry and molecular biology

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

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

Name of the periodical

International Journal of Molecular Sciences

ISSN

1661-6596

e-ISSN

—

Volume of the periodical

25

Issue of the periodical within the volume

2

Country of publishing house

CH - SWITZERLAND

Number of pages

29

Pages from-to

1358

UT code for WoS article

001151455500001

EID of the result in the Scopus database

2-s2.0-85183592255