Sandor Vajda, Ph.D.

Professor (BME, SE)

Office ERB 221
Email vajda@bu.edu
Phone (617) 353-4757
Fax (617) 353-6766
Website Vajda Lab
Alternate Website Biomolecular Research Center

Honors and Awards

Fellow, American Institute for Medical and Biological Engineering, 2014
Member, American Chemical Society, 1997
Member, Biophysical Society, 1996
Member, Protein Society, 1992
Member, American Association for the Advancement of Science, 1990

Areas of Interest

The research in my lab focuses on molecular recognition using computational bioengineering approaches. Studying protein-protein interactions is crucial for understanding metabolic control, signal transduction, and gene regulation, whereas the ability to dock small ligands to proteins is the key to rational drug and vaccine design strategies. Accordingly, we develop computational methods and software for protein engineering and drug discovery, both for academic use and industrial applications.

Research Areas

Computational methods have the potential for substantially improving the efficiency and reducing the costs of biomedical and pharmaceutical research. Our goal is developing reliable and robust methods based on rigorous biophysical and engineering principles, and to implement them as free web-based servers to be used for academic and governmental institutions. The programs are also licensed for commercial applications.
We have developed methodologies for predicting the structure of protein complexes that have consistently been among the best performers in the worldwide protein docking experiment called CAPRI (see https://www.ebi.ac.uk/pdbe/complex-pred/capri/). Some of the methods are implemented in our protein docking server ClusPro (http://cluspro.bu.edu/), which was the first automated server. ClusPro has over 25,000 registered users, and we run over 10,000 docking jobs each month. Structures of complexes, generated by the server, have been reported in thousands of research papers. Recently ClusPro has been combined by machine learning tools to substantially improve performance. In particular, the combined method yields much better results for predicting antibody-antigen interactions than any other computational tool currently available.
For the analysis of interactions between proteins and small ligands our main contribution has been the development of the FTMap algorithm (http://ftmap.bu.edu/) for computational solvent mapping. The method places molecular probes – small molecules and functional groups – on a protein surface for the identification and characterization of binding sites. Since mapping provides very useful information for drug design, we have been developing and testing modeling and design tools for the pharmaceutical industry, in collaboration with academic labs and companies. Our main goal is to build an in-silico methodology that substantially reduces the very high costs of early-stage drug discovery.
Since we work on problems that are very important to the pharmaceutical and biotechnology industries, our Ph.D. students always have generous offers for research scientist positions even before graduating from the lab, without the need for postdoctoral training. However, we also offer such training to researchers from different backgrounds moving into our research field, or to scientist who are interested in academic positions.

Sandor Vajda, Ph.D.

Professor (BME, SE)

Publications