Utilization of an optimized AlphaFold protein model for structure-based design of a selective HDAC11 inhibitor with anti-neuroblastoma activity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652036%3A_____%2F24%3A00617017" target="_blank" >RIV/86652036:_____/24:00617017 - isvavai.cz</a>

Výsledek na webu

<a href="https://onlinelibrary.wiley.com/doi/epdf/10.1002/ardp.202400486" target="_blank" >https://onlinelibrary.wiley.com/doi/epdf/10.1002/ardp.202400486</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/ardp.202400486" target="_blank" >10.1002/ardp.202400486</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Utilization of an optimized AlphaFold protein model for structure-based design of a selective HDAC11 inhibitor with anti-neuroblastoma activity

Popis výsledku v původním jazyce

AlphaFold is an artificial intelligence approach for predicting the three-dimensional (3D) structures of proteins with atomic accuracy. One challenge that limits the use of AlphaFold models for drug discovery is the correct prediction of folding in the absence of ligands and cofactors, which compromises their direct use. We have previously described the optimization and use of the histone deacetylase 11 (HDAC11) AlphaFold model for the docking of selective inhibitors such as FT895 and SIS17. Based on the predicted binding mode of FT895 in the optimized HDAC11 AlphaFold model, a new scaffold for HDAC11 inhibitors was designed, and the resulting compounds were tested in vitro against various HDAC isoforms. Compound 5a proved to be the most active compound with an IC50 of 365 nM and was able to selectively inhibit HDAC11. Furthermore, docking of 5a showed a binding mode comparable to FT895 but could not adopt any reasonable poses in other HDAC isoforms. We further supported the docking results with molecular dynamics simulations that confirmed the predicted binding mode. 5a also showed promising activity with an EC50 of 3.6 mu M on neuroblastoma cells.

Název v anglickém jazyce

Utilization of an optimized AlphaFold protein model for structure-based design of a selective HDAC11 inhibitor with anti-neuroblastoma activity

Popis výsledku anglicky

AlphaFold is an artificial intelligence approach for predicting the three-dimensional (3D) structures of proteins with atomic accuracy. One challenge that limits the use of AlphaFold models for drug discovery is the correct prediction of folding in the absence of ligands and cofactors, which compromises their direct use. We have previously described the optimization and use of the histone deacetylase 11 (HDAC11) AlphaFold model for the docking of selective inhibitors such as FT895 and SIS17. Based on the predicted binding mode of FT895 in the optimized HDAC11 AlphaFold model, a new scaffold for HDAC11 inhibitors was designed, and the resulting compounds were tested in vitro against various HDAC isoforms. Compound 5a proved to be the most active compound with an IC50 of 365 nM and was able to selectively inhibit HDAC11. Furthermore, docking of 5a showed a binding mode comparable to FT895 but could not adopt any reasonable poses in other HDAC isoforms. We further supported the docking results with molecular dynamics simulations that confirmed the predicted binding mode. 5a also showed promising activity with an EC50 of 3.6 mu M on neuroblastoma cells.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30104 - Pharmacology and pharmacy

Projekt

<a href="/cs/project/GA24-12155S" target="_blank" >GA24-12155S: Studium funkce histon deacetylázy 11 napříč říšemi života</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Archiv der Pharmazie

ISSN

0365-6233

e-ISSN

1521-4184

Svazek periodika

357

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

—

Kód UT WoS článku

001266632400001

EID výsledku v databázi Scopus

2-s2.0-85198365123