EdaFold: An Evolutionary Algorithm based Fragment Assembly Method for De Novo Protein Structure Prediction

2019-07-04 23:37:09 2

Kam Y. J. Zhang


Zhang Initiative Research Unit,

Advanced Science Institute  实验室网址:
http://www.asi.riken.jp/en/laboratories/irunits/zhang/index.html

 


 

报告时间:2013年4月23日(星期二)下午13:00

 

地点:北京大学定量生物学中心老化学楼东配楼102会议室(理教路西/老光华楼北侧)

 

 

摘要

Fragment assembly is a powerful method of protein structure prediction that builds protein models from a pool of candidate fragments taken from known structures. Stochastic sampling is subsequently used to refine the models. We have developed a new method for fragment-based protein structure prediction based on an Estimation of Distribution Algorithm called EdaFold. This algorithm learns from previously generated decoys and steers the search toward native-like regions. A comparison with Rosetta AbInitio protocol shows that EdaFold is able to generate models with lower energies and to enhance the percentage of near-native decoys on a benchmark of 20 proteins.

We have used this EdaFold method to participate in the recent “10th Community Wide Experiment on theCritical Assessment of Techniques for Protein Structure Prediction (CASP10)”. Our method was ranked No. 1 out of 143 groups from world-wide participants in the template-free modeling category as judged by the average Z-score on GDT_TS. This prospective exercise has further validated the utility of method.


主持人:来鲁华教授