Artificial intelligence-based system for generating drug like molecules and method thereof

An artificial intelligence-based (AI-based) system for generating one or more drug like molecules, comprising:

• one or more servers, comprising:
• one or more hardware processors;
• and
• a memory unit coupled to the one or more hardware processors, wherein the memory unit comprises a plurality of subsystems in form of one or more instructions executable by the one or more hardware processors, and wherein the plurality of subsystems comprises:
• a data-obtaining subsystem configured to obtain one of:
• biological target data and therapeutic information from a user;
• a generative molecule devising subsystem configured to generate 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;
• a virtual screening subsystem configured to evaluate the generated one or more molecular structures for at least one of:
• binding affinity, pharmacological relevance, and structural validity via one or more virtual screening models to compute a multi-parametric scoring;
• a prediction subsystem configured to predict one or more properties associated with absorption, distribution, metabolism, excretion, and toxicity (ADMET) of the evaluated one or more molecular structures by one or more generative artificial intelligence (AI) models trained on diverse datasets consisting at least one of:
• pharmacokinetic data and toxicology data;
• a retrosynthesis planning subsystem configured to determine one or more feasible synthesis pathways for the selected one or more molecular structures through one or more retrosynthesis models based on at least one of:
• analysing reaction pathways and integration of one or more chemical reaction databases enabled by reaction informatics;
• and
• an iterative refinement subsystem configured to optimise the one or more molecular structures for generating the one or more drug like molecules with a validated synthetic feasibility and drug-like properties based on one or more feedback from at least one of:
• the generative molecule devising subsystem, the virtual screening subsystem, the prediction subsystem, and the retrosynthesis planning subsystem.