Verfahren und System für Strukturbasierten Arzneimittelentwurf unter Verwendung eines Multimodalen Tiefenlernmodells

Details

Veröffentlichungs-Nr.

EP4181145

Aktenzeichen

EP22202493

Anmeldetag

19. Oktober 2022

Veröffentlichung

13. August 2025

Erteilung

13. August 2025

Rechtsraum

EP

IPC

G16B15/30G16B20/30G16B40/20G16B40/30

Abstract

This disclosure relates generally to method and system for structure-based drug design using a multi-modal deep learning model. The method processes a target protein for designing at least one optimized molecule by using a multi-modal deep learning model. The GAT-VAE module obtains a latent vector of at least one active site graph comprising of key amino acid residues from the target protein. The SMILES-VAE module obtains at least one latent vector from the target protein. Further, the conditional molecular generator concatenates the active site graph with the latent vector to generate a set of molecules. The RL framework is iteratively performed on the concatenated latent vector to optimize at least one molecule by using the drug-target affinity (DTA) predictor module to predict an affinity value for the set of molecules towards the target protein. Further, at least one optimized molecule is designed with an affinity of the target protein.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien

Fachgebiete