New York University · ChemistryCenter for Protein-Protein Interaction Design
Yingkai Zhang · New York, New York
Research Focus
Yingkai Zhang's research lab focuses on using advanced computational techniques and machine learning to design new drugs that can specifically target protein-protein interactions (PPIs). These interactions are crucial for controlling cellular activities, and misregulations can lead to diseases. The lab combines innovative design strategies with experimental collaborations to create and optimize molecular 'modulators' that can help treat various medical conditions.
protein-protein interactionsmachine learningdrug discoverymolecular modelingmodulator designbiomolecular interactionstherapeutic developmentcomputational toolsdeep learning
Research Aims
5AIM 01Develop new computational tools to enhance drug design.
AIM 02Optimize molecular modulators for targeting protein-protein interactions.
AIM 03Integrate machine learning with structural biology for drug discovery.
AIM 04Collaborate with experimental labs to validate computational predictions.
AIM 05Explore chemical space for discovering potent therapeutic leads.
Skills the Lab Values
computational modelingmachine learningprotein-ligand dockingmolecular dynamics simulationsvirtual screeningPython programmingaffinity measurement techniquesdeep learning model developmentprotein design
Output against the department
Publications196bottom 47% of dept.115th of 216
this lab
most publishedleast published
Citations12ktop 43% of dept.92nd of 216
this lab
most citedleast cited
Career totals from OpenAlex, compared against labs that share a department. A department spans everything from one paper to tens of thousands, so bar heights are on a log scale — otherwise the largest lab would flatten every other bar to a line.