Bar-Ilan University Supervisors

Prof. Hanoch Senderowitz completed his PhD studies in computational organic chemistry with Prof. Benzion Fuchs at Tel Aviv University in 1993.  His main research subjects were in the field of steric and stereoelectronic effects, their mutual interplay and their influence on structure and reactivity in organic compounds. Between 1993 and 1997, he was a Post Doctorate Fulbright Fellow with Professor Clark Still in the MacroModel development team at Columbia University where his research focused on the development of a new smart Monte Carlo algorithm to accelerate convergence on multi-minima potential energy surfaces, on the integration of this method with Molecular Dynamics into a combined MC/MD simulation algorithm and on the development and QM-based parameterized of carbohydrate force fields. In 1997, Prof. Senderowitz returned to Israel and joined the pharmaceutical industry first at Peptor Ltd., where he worked on theoretical and modeling aspects related to the development of peptide-based drugs and latter at EPIX Pharmaceutical, a drug discovery company focused on the development of drugs targeting GPCRs and ion channels, where he headed the computational development group. Since 2009 he is a Professor at the Department of Chemistry at Bar-Ilan University where he heads the laboratory of molecular modeling, computer aided drug design and chemo-informatics. His research at BIU focuses on the development of new computational methods (algorithms and workflows) and on their application in chemoinformatics and materials informatics to study the factors that govern molecular energies, structures, and properties. Understanding the interplay between these factors could subsequently be used for the design of new compounds with improved characteristics for various purposes. The lab applies a multi-disciplinary approach consisting of various levels of theory, different computational techniques and different machine learning algorithms. Professor Senderowitz’s research is funded by grants from multiple resources.