Wei Zhang

• Lead molecular modeling studies, including MD simulation/analysis, FEP, cryptic pocket identification, covalent docking/screening, SAR analysis, QM calculation, supporting ferroptosis-based drug discovery projects • Explore/build computational chemistry platform incorporates machine learning/AI-based methods, including generative chemistry and active learning

• Established computational chemistry platform (hardware, software, compound libraries, databases, etc.) supporting drug discovery and development • Provide structural insights and hypothesis to help understand SAR and design/prioritize compound synthesis for lead optimization • Identified novel chemical series through SBVS, and further extended them into new leads for optimization/development • Evaluate the druggability of potential targets, and propose/apply computational strategies, including VS, scaffold hopping, for hit identification • Explore computational methods for their potential applications on discovery projects, including FEP, ML/DL, generative-AI, Covalent Docking, etc. • Train scientists on computational chemistry, cheminformatics, database management methods/strategies, and supervise their applications on drug discovery projects

• Established structure-based drug discovery platform of the department of discovery science • Identified multiple hits with different novel chemical scaffolds by targeting GPCR through molecular modeling and virtual screening • Explore/develop/apply various structure/ligand-based computational strategies, including MD simulation, virtual screening, FEP, etc. and work closely with medicinal chemists, pharmacologists, toxicologists, to facilitate drug discovery and development efforts targeting GPCRs and ion channels • Explore the potential structural mechanisms of specie difference and selectivity among targets and off-targets through molecular modeling and mutagenesis studies. • Manage computational chemistry and chemoinformatic facilities • Work with CROs to solve the cryo-EM structures of target proteins (GPCRs)

• Apply CADD strategies to discover and develop PROTAC (Proteolysis-Targeting Chimera) protein degraders for a variety of drug targets • Develop computational methods to explore protein-protein interactions and the mechanism of action of PROTACs • Conduct virtual screening to identify novel ligands of target proteins and E3 ligases

• Responsible for the development of computational methods, including machine learning and QSAR modeling, to explore drug induced toxic effects and predict different toxicity endpoints. • Work with system biologists, toxicologists, biochemists and cell biologists to explore the potential off-targets of drug candidates. • Manage in vitro safety profiling, explore structural details of potential interactions between screen identified off-targets and drug candidates

• Lead the molecular modeling group and conduct independent drug discovery research. • Apply computational methods, including molecular dynamics simulation, computer-aided drug design and cheminformatics analysis for a variety of drug discovery projects related to cancer, CNS diseases and infectious diseases • Explore and initiate computer-aided drug discovery projects • Work closely with medicinal chemists, biologists and HTS team at different drug discovery stages to identify/optimize hit/lead compounds on various drug targets, including kinases, kinesins, GPCRs, and transporters, etc. • Lead anti-cancer drug discovery projects (identified lead compounds with IC50 values < 10 nM through computational methods) • Develop and apply molecular simulation based computational methods to explore unknown allosteric sites of drug targets • Design and assemble focused/diverse compound libraries • Maintain computational chemistry and chemoinformatic facilities and provide supports to the drug discovery division • Responsible for project report, research proposal, and publication • Train scientists on molecular modeling and cheminformatics applications