[Apologies for multiple postings]



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*    GRAND Seminar

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*    http://cs.gmu.edu/~robotics/Main/GrandSeminar

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*Title*

An algorithm for discovering steric influences on

protein-ligand binding specificity



*Time/Venue*

CS conference room, ENGR 4201

Noon, October 11, Tue.



*Speaker*



Brian Chen

http://www.cse.lehigh.edu/~chen/

Assistant Professor

Dept. of Computer Science and Engineering

Lehigh University



*Host*



Amarda Shehu

http://www.cs.gmu.edu/~ashehu



*Abstract*



Living things are composed of interacting and nested systems

that exhibit symptoms of health and disease at all levels.

At the most fundamental level, understanding the correct

behavior of healthy systems, and resolving the breakdowns

that occur in disease, requires a precise understanding of

how proteins function and malfunction. Building such an

understanding is much like the examination of a complex

machine: the analysis of protein shape can yield many

insights, especially at functional sites, where biochemical

activity actually occurs.



Many algorithms have been designed to gather structural

observations, especially about the functional site, that

point to functional hypotheses that can be ultimately tested

on the bench. In every case, these methods employ a "guilt

by association" approach by assigning biological function

based on functional site similarity or a resemblance to

established norms. This talk asserts that more informative

approaches are possible and presents VASP, a new method that

dissects functional sites to isolate individual components

that play influential functional roles. VASP enables these

new capabilities by exploiting a novel connection to

concepts from computer graphics and computer aided design.



The results presented in this talk describe a case study

where VASP was applied to the analysis of the major serine

proteases. VASP isolated individual amino acids and regions

of functional sites that enable the serine proteases to

preferentially bind specific molecules. None of these

observations are possible with existing unsupervised

methods. These results point to applications in molecular

bioengineering, where the identification of individual

functional components is essential for the rational

engineering of active biomolecules, and to applications in

structure-based drug design, where important functional

components could be exploited to mitigate side effects or

evade drug resistance.







-- 

*Jyh-Ming Lien*

Assistant Professor, George Mason University

+1-703-993-9546

http://cs.gmu.edu/~jmlien