From rxpgnews.com
NYU chemist wins Watson Young Investigator award
By New York University
Apr 15, 2005, 18:49
New York University's Yingkai Zhang, an assistant professor in the Department of Chemistry, has been awarded a $200,000 James D. Watson Young Investigator Award from the New York State Office of Science, Technology, and Academic Research (NYSTAR). The award was announced by New York Gov. George Pataki.
Funds for the award come from the Generating Employment through New York State Science (Gen*NY*sis) initiative, a $225-million program that was created to maximize the potential of the world-class life sciences research being conducted at New York State's public, not-for-profit, and private academic research institutions. The Watson award is designed to "recognize and support outstanding scientists and engineers who, early in their careers, show potential for leadership and scientific discovery in the field of biotechnology."
Zhang's research is in the area of computational chemical biology. He is developing and applying novel computational and theoretical methods to gain a better understanding of the chemical mechanisms of important biological processes. Zhang, who received a National Science Foundation Career Award earlier this year, has extensive experience ranging from theoretical chemistry and methodology development to computational modeling of biological systems.
This marks the third Watson Young Investigator Award in four years for NYU. Kent Kirshenbaum (2004) and Paramjit S. Arora (2002), both assistant professors in the Department of Chemistry, previously received $200,000 grants.
The research to be conducted under the NYSTAR grant will develop an innovative computational strategy for the rational redesign of enzymes. Scientists have long sought to develop biocatalysts for applications in medicine, food, and chemical synthesis, as well as for degrading hazardous materials. The key obstacle is a detailed understanding of enzyme function and an innovative and practical design strategy. Zhang intends to address this challenge by employing the emerging capabilities of modern computational methods, which would allow a greater understanding of the inner workings of enzymes.
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