Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388963%3A_____%2F24%3A00581097" target="_blank" >RIV/61388963:_____/24:00581097 - isvavai.cz</a>

Alternative codes found

RIV/61989592:15310/24:73627556

Result on the web

<a href="https://doi.org/10.1039/D3RA08147H" target="_blank" >https://doi.org/10.1039/D3RA08147H</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1039/d3ra08147h" target="_blank" >10.1039/d3ra08147h</a>

Result language

angličtina

Original language name

Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets

Original language description

This study introduces the PocketCFDM generative diffusion model, aimed at improving the prediction of small molecule poses in the protein binding pockets. The model utilizes a novel data augmentation technique, involving the creation of numerous artificial binding pockets that mimic the statistical patterns of non-bond interactions found in actual protein-ligand complexes. An algorithmic method was developed to assess and replicate these interaction patterns in the artificial binding pockets built around small molecule conformers. It is shown that the integration of artificial binding pockets into the training process significantly enhanced the model's performance. Notably, PocketCFDM surpassed DiffDock in terms of non-bond interaction and steric clash numbers, and the inference speed. Future developments and optimizations of the model are discussed. The inference code and final model weights of PocketCFDM are accessible publicly via the GitHub repository: https://github.com/vtarasv/pocket-cfdm.git.

Czech name

—

Czech description

—

Type

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

CEP classification

—

OECD FORD branch

10403 - Physical chemistry

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

RSC Advances

ISSN

2046-2069

e-ISSN

2046-2069

Volume of the periodical

14

Issue of the periodical within the volume

2

Country of publishing house

GB - UNITED KINGDOM

Number of pages

13

Pages from-to

1341-1353

UT code for WoS article

001135725900001

EID of the result in the Scopus database

2-s2.0-85183320570