Avner Schlessinger

Dr. Avner Schlessinger is a Professor of Pharmacological Sciences at the Icahn School of Medicine at Mount Sinai in New York City. He serves as Associate Director of Mt. Sinai Center for Therapeutics Discovery and Co-Director of the Disease Mechanisms and Therapeutics (DMT) Training Area. His work integrates computational chemistry and artificial intelligence to advance drug discovery and characterize disease pathways.

Dr. Schlessinger's educational background includes a BSc in Biology and Chemistry from Tel Aviv University, a PhD from Columbia University in the Department of Biochemistry and Molecular Biophysics, and postdoctoral training at the Department of Bioengineering and Therapeutic Sciences at UCSF as an NIH NRSA fellow.

His research focuses on two major areas: structure-based drug design for membrane transporters and structural bioinformatics. The Schlessinger Lab develops computational tools to annotate protein function, with specific emphasis on predicting protein structure and function using machine learning, studying Solute Carrier (SLC) transporters, and designing tool compounds for clinically relevant drug targets. His work spans chemical biology, bioinformatics, drug discovery, precision medicine, and pharmacogenomics.

Analysis of Dr. Schlessinger's recent publications reveals a strong focus on membrane transporters, particularly SLC family proteins, and the application of AI and machine learning to drug discovery. His work increasingly integrates structural biology with genomics to understand disease mechanisms and identify novel therapeutic targets, with growing emphasis on cancer metabolism pathways and neurological disorders.

Dr. Schlessinger serves on the Editorial Boards of PLOS Computational Biology and Trends in Pharmacological Sciences, as well as on advisory boards of biotechnology companies and international consortia. He is also the Founder/Co-Founder of KINaiZ.

His lab employs an integrated computational and experimental approach, collaborating with experimental labs to rationally design chemical tools for studying transporters' role in disease pathways. The lab has developed numerous computational methods and resources including PyVOL, Structural Signatures, and KinAce, which are available on GitHub for the scientific community.