Description:FIELD OF INVENTION

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

BACKGROUND

[0002]A field of drug discovery has evolved significantly in recent years, with computational methods and artificial intelligence (AI) technologies playing an increasingly prominent role. The computational methods and AI technologies aim to enhance efficiency in identifying and developing new therapeutic compounds. Computer-aided drug discovery (CADD) has emerged as a promising area, leveraging computational resources to accelerate various stages of a drug development pipeline.

[0003]Traditional drug discovery workflows involve iterative Design-Make-Test-Analyse (DMTA) cycles, which may be resource-intensive. The DTMA cycles include multiple rounds of molecular construction, synthesis, and experimental testing, , Claims:I/We Claim:
1. An artificial intelligence-based (AI-based) method (300) for generating one or more drug like molecules, comprising:
obtaining (302), by one or more hardware processors (106) through a data-obtaining subsystem (206), one of: biological target data and therapeutic information from a user;
generating (304), by the one or more hardware processors (106) through a generative molecule devising subsystem (208), one or more molecular structures through one or more machine learning (ML) models,
the one or more machine learning (ML) models configured to perform at least one of: binding affinity optimization, structural conformity and feasibility, chemical space exploration, and iterative feedback loop based on the obtained one of: biological target data and therapeutic information;
evaluating (306), by the one or more hardware processors (106) through a virtual screening subsystem (210), the generated one or more molecular structures for at least one of: binding affinity, pharmacological relevance, and s