Conference proceeding
HIV1-human protein-protein interaction prediction based on interface architecture similarity
2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), v 2017-, pp 97-100
Nov 2017
Abstract
In this paper, we computationally predicted the interactions between HIV-1 and human proteins, based on the hypothesis that proteins with similar interface architecture share similar interaction partners. Evolution - aware protein structural alignment method UniAlign was used to calculate the similarity between two protein interface architectures. Using experimentally verified HIV-1, human protein-protein interactions data, we first selected 12 features, including geometric similarity, conversion similarity etc.; then trained a support vector machine (SVM) with Gaussian kernel for the binary classification problem: whether a given protein pairs `interact' or `no interact'. We used the trained and tuned SVM classifier to discover potential novel HIV-1 interacting partners for human proteins. Many predicted interactions had significant literature support, and we modeled the novel 3D interacting complex for HIV-1 envelope gp120 and gp41 proteins. We provided the first structural evidence for those interactions.
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3 citations in Web of Science
5 citations in Scopus
Details
- Title
- HIV1-human protein-protein interaction prediction based on interface architecture similarity
- Creators
- Chunyu Zhao - Children's Hospital of PhiladelphiaYizhou Zang - Drexel UniversityWei Quan - Drexel UniversityXiaohua Hu - Drexel UniversityAhmet Sacan - Drexel University
- Publication Details
- 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), v 2017-, pp 97-100
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics); School of Biomedical Engineering, Science, and Health Systems
- Scopus ID
- 2-s2.0-85046002015
- Other Identifier
- 991019170348604721