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Identifying positively selected amino acid residues in hiv-1 envelope protein: a dynamic simulation approach

PI(s): Yi Mao (University of Tennessee-Knoxville (Knoxville,TN))
Start Date: 8-Nov-2010
End Date: 27-Nov-2010
Keywords: evolutionary computation, computational modeling, natural selection
HIV-1 envelope protein is responsible for the invasion of the HIV virus into the host cell, and is also involved in suppressing the immune system after HIV infection. It has the potential to evolve at a high rate, and escapes the attacks of host immune systems. In the past, the identification of positively selected amino acid residue sites in HIV-1 envelope gene has been successful by developing statistical tools to analyze the evolution of protein-coding DNA sequence. However, the nature of these selected residues remains unclear. Here I propose to use computational modeling based on the protein structure of HIV-1 envelope to predict these residue sites where positive selection may take place. Dynamic modeling of the protein generates correlation information of the whole molecular system, which is then further analyzed by mathematical analysis tools to yield its inner functional organization. Those residue sites with great functional relevance would be mostly likely selected during the evolution process. In the meantime, the simulations will investigate the molecular mechanisms of virus entry and infection as well. This project will be done in collaboration with Dr. Allen Rodrigo at NESCent. The primary goal of collaboration is to explore the parallels between physical approach and population genetics approach in molecular evolutionary theory.