Thomas
Ferrin, Ph.D.
Professor of Pharmaceutical Chemistry

Contact Information:
tef@cgl.ucsf.edu
Tel: (415) 476-2299
Fax: (415) 502-1755
Box 2240, Genentech Hall N472

Links:
home page
UCSF Computer Graphics Lab
Biological and Medical Informatics
PIBS

Publications

Computer-aided drug design, emphasizing application of 3-D interactive computer graphics for studying macromolecules and small molecule interactions

Our work focuses on computational approaches for comprehending the structure and function of large biological molecules using three-dimensional computer graphics and data mining techniques. Interactive visualization and manipulation of nucleic acids, proteins, and protein-ligand complexes is a highly effective research tool, especially when coupled to fast computers employing numerical analysis techniques. Complementary to these structure-based approaches to studying macromolecular function, the vast quantities of genomic data now available requires new theoretical constructs and computational approaches for turning this data into scientific understanding. Innovative computational methods such as genetic algorithms, neural networks, and hidden Markov models are providing powerful new software paradigms to relate sequence, structure, and functional information on a genomic scale.

Making this information available to the scientific community through facile web-based interfaces is a considerable challenge, but crucial if others are to benefit from and build on our work, and hence constructing searchable and extensible databases using, for example, object-oriented programming techniques are required. We are incorporating these approaches and others into integrated systems for molecular recognition in applications such as drug design, protein engineering, biomaterials design, and bioremediation.

We encourage collaborative interdisciplinary research projects with scientists at UCSF, other academic institutions, and industry. Research is conducted by a diverse group whose backgrounds range from computer science to bioinformatics to structural biology and molecular biology.