Jinjiang Guo

Do Larger Models Really Win in Drug Discovery?A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction

The paper benchmarks model scaling in AI-driven drug discovery, finding that compact models often outperform larger ones across various molecular property and activity prediction tasks.

DCBK: A Fragment-Based Hybrid Simulation and Machine Learning Framework for Predicting Ligand Dissociation Kinetics

DCBK predicts ligand dissociation kinetics by combining simulation and machine learning, achieving strong agreement with experiments and offering mechanistic insights.

GenVS TBDB: A Target-Aware AI-Generated and Virtual Screened Small-Molecule Library for Tuberculosis Drug Discovery

This paper introduces GenVS-TBDB, an AI-generated and virtual-screened small-molecule library targeting Mycobacterium tuberculosis, identifying bioactive compounds with potential for tuberculosis drug discovery.