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Center for Nonlinear Studies |
In this talk I will present a new bottom up approach to derive and analyze evolution of populations of viruses and bacteria using multiscale models based on fitness landscape which originates from fundamental biophysical requirement that in order to function structured proteins must be in their folded states. We model populations of living cells whose genomes explicitly encode proteins of known structure and effects of mutations on their stability and interactions with other proteins are determined using modern methods of computational Biophysics. We consider fitness (division and death rates for individual cells) to depend on abundance of folded proteins and toxicity caused by unfolded proteins each representing a continuous “Fermi-function” of folding free energy (G). We find that, under the conditions mutation/selection/drift balance, high mutation rates (m) lead to less stable proteins and a more dispersed Distribution of Fitness Effects of mutations, i.e. less mutational robustness. Small population size (N) also decreases stability and robustness. Compensatory mutations are more common and potent in small populations with high mutation rates. Further we uncover dependence of proteins evolutionary rates on their Biophysical properties such as stability and abundance and found that variability of evolution rates (‘’molecular clock’’) between different genes diminishes for highly diverged species due to interplay of factors of protein stability and abundance on fitness landscape.
Host: S. Gnanakaran, 5-1923, ghana@lanl.gov