Computational design of carbohydrate-binding proteins
报告人:
David F. Green
Stony Brook University
报告时间:
2012-10-18 14:00
报告地点:
FIT 1-222
主办单位:
交叉信息研究院
简介:
Abstract: ---------------------------------------------------- The ability to rationally engineer novel functionality into carbohydrate-binding proteins could find use in a wide range of potential applications, including diagnostic identification of microbes, prevention of retroviral infection, and targeted delivery of protein-therapeutics to specific tissue-types. However, the design of carbohydrate binding interfaces is challenging both due to the intrinsic conformational flexibility of carbohydrate targets and to the highly polar nature of the binding interface, which necessitates accurate treatments of solvation effects. Here, we will highlight some of the methodological advances we have made in order to make the computational design of carbohydrate-binding proteins tractable; these include the use of optimized models for the computational of carbohydrate binding energies, the application of statistically-derived rules for hierarchical screening methods, and the combination of molecular dynamic simulation with the Dead-End Eliminat ion and A* algorithms for discrete conformational search. The applicability of these methods will be presented using examples from the engineering of a number of algal lectins with potent virucidal activity against the Human Immunodeficiency Virus (HIV).
