Description:FIELD OF INVENTION

[0001]Embodiments of the present invention relate to computational drug discovery and more particularly relate to an artificial intelligence-based (AI-based) system for generating one or more pocket-conditioned molecules and an artificial intelligence-based (AI-based) method thereof.

BACKGROUND

[0002]Field of drug discovery relies heavily on identification of small one or more molecular structures that may effectively bind to specific protein targets. Traditional drug development methods involve extensive laboratory testing and computational docking simulations, both of which require significant time and resources. Advances in artificial intelligence (AI) and machine learning (ML) have enabled the use of one or more predictive models to accelerate this process, allowing researchers to screen vast molecular libraries for potential one or more pocket-conditioned molecules. AI-driven molecular modelling techniques have demonstrated promise in identifying the one or more pocket-conditioned m , Claims:I/ We Claim:
1. An artificial intelligence-based (AI-based) method (300) for generating one or more pocket-conditioned molecules, comprising:
obtaining (302), by one or more hardware processors (106) through a data obtaining subsystem (206), at least one of: ligand data comprises at least one of: two-dimensional (2D) molecular representations and three-dimensional (3D) molecular conformations and protein pocket data comprises at least one of: two-dimensional (2D) sequences and three-dimensional (3D) coordinates to generate molecular interactions;
aligning (304), by the one or more hardware processors (106) through a data pre-processing subsystem (208), at least one of: the two-dimensional (2D) molecular representations with the three-dimensional (3D) molecular conformations and the two-dimensional (2D) sequences with the three-dimensional (3D) coordinates to verify at least one of: a spatial consistency and a structural consistency;
encoding (306), by the one or more hardware processors (106) through a data