Algorithms for Reticulate Network Construction, Protein Binding Sites Prediction and Protein Complex Prediction
Project: Research
Researcher(s)
- Lusheng WANG (Principal Investigator / Project Coordinator)Department of Computer Science
- Tao Jiang (Co-Investigator)
Description
Computational biology is a rapidly developing area that plays a crucial role in some biological research. Our project aims at the design and analysis of efficient and effective algorithms and heuristics for three important problems in computational biology: the reticulate network construction problem, the protein binding site prediction problem and the protein complex prediction problem.Constructing the evolutionary history of a set of species is a basic problem in the study of biological evolution. When reticulate events occur, the evolutionary history should be described as a reticulate network. The problem of constructing reticulate networks based on a set of input trees has attracted lots of attention. Here we will design efficient and effective algorithms for several variations of the problem.Identifying the location of binding sites on proteins is of fundamental importance for a wide range of applications including molecular docking, de novo drug design, structural identification and comparison of functional sites. Here we propose a brand new approach to solve this problem. The main ideas of our approach are finding surface substructures as candidate binding sites by including the volume of protein molecules and compute rigid transformations for protein 3D structures to see if a pair of surface substructures match.Protein complexes are clusters of multiple proteins, and they often play a crucial part in basal cellular mechanism. Thus, computational methods to predict protein complexes are becoming important. In this project, we propose a new approach for protein complex prediction. We will try to join a set of 3D structures of proteins in a complex in 3D space to see if they fit together based on the known binding sites. This is the first time that 3D structure transformations are used for protein complex prediction. We expect that our new approach will initialize a new research area.This project will provide a solid theoretical foundation for the implementation of the much needed software packages for the three problems. We will also implement those algorithms to form software packages for the three proposed problems.Detail(s)
Project number | 9041683 |
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Grant type | GRF |
Status | Finished |
Effective start/end date | 1/01/12 → 16/12/15 |