UM  > 科技學院  > 電機及電腦工程系
Predicting favorable protein docking poses on a solid surface by particle swarm optimization
Ngai J.C.F.; Mak P.-I.; Siu S.W.I.
2015-09-10
Conference NameIEEE Congress on Evolutionary Computation (CEC)
Source Publication2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
Pages2745-2752
Conference DateMAY 25-28, 2015
Conference PlaceSendai, JAPAN
Abstract

Protein adsorption at solid surfaces has received intense focus due to its high relevance to biotechnological applications. In alternative to experimental approaches, computational methods such as molecular dynamics (MD) simulations are frequently employed to simulate the protein adsorption process and to study molecular interactions at the interfacial region. However, a successful simulation of the adsorption process depends largely on the initial adsorbed protein orientation on the surface. To avoid sampling protein trajectory which will eventually fail to adsorb, a workaround is to first determine the preferred orientations of the protein relative to the surface and use them as starting structures in MD simulations. Here, we present the first application of particle swarm optimization (PSO) to search for the low energy docking poses of a protein molecule on a solid surface. Performing rigid-body translation and rotation of the protein with energy minimization and empirical scoring function, our search algorithm successfully located the low energy orientations of the lysozyme molecule on a hydrophobic PTFE surface. Nine out of ten predicted docking poses are energetically more favorable than all poses sampled using a brute-force search. Three sets of major adsorption sites are identified for the lysozyme and they are in good agreement to results obtained by long MD simulations; novel adsorption sites are also identified from the lowest energy docking pose. Our method provides a reliable way to predict the optimal protein orientations useful for computational studies of protein-surface interactions.

KeywordHydrophobic Solid Surface Lysozyme Particle Swarm Optimization Protein Adsorption Ptfe
DOIhttp://doi.org/10.1109/CEC.2015.7257229
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000380444802103
Fulltext Access
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Ngai J.C.F.,Mak P.-I.,Siu S.W.I.. Predicting favorable protein docking poses on a solid surface by particle swarm optimization[C],2015:2745-2752.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Ngai J.C.F.]'s Articles
[Mak P.-I.]'s Articles
[Siu S.W.I.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Ngai J.C.F.]'s Articles
[Mak P.-I.]'s Articles
[Siu S.W.I.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Ngai J.C.F.]'s Articles
[Mak P.-I.]'s Articles
[Siu S.W.I.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.