The overarching goal of the proposed research is to study evolution of structure, Biophysical properties and function of proteins in the context of Darwinian evolution of their carrier organisms. In the past budget period we significantly advanced towards that goal by introducing rich, powerful yet tractable multiscale models of protein evolution which derive organismal fitness from genomic sequences via intuitive yet realistic Genotype- Phenotype relationships which relate biophysical and functional properties of proteins to important phenotypic traits such cell division. Here we will further develop this approach by adding more realism to the models including treatment of proteins in sequence-based multiscale model at atomic resolution, prototypical E.coli glycolytic pathway, effect of misfolding on fitness and effect of protein abundances. Specific problems that will be addressed include the effect of ecology of the population on key Biophysical properties of proteins such as distribution of their stabilities, abundances and strengths of protein-protein interactions in the proteome; reconstruction of ancestor sequences and molecular phylogenies from genomics data within physically realistic models, relationship between protein stability, abundance in cytoplasm, and rate of their evolution. Predictions and insights from multiscale models will be vigorously tested against high-throughput Bioinfiomatic analyses and experiment. Experimental studies proposed here include measurements of stabilities of statistically representative sets of proteins in several proteomes, of bacteria having various ecological parameters (e.g population sizes and/or mutation rates). Successful completion of these studies will advance our ability to extract functionally relevant signals from genomic sequences by putting their analysis on firm evolutionary and Biophysical ground.
This research aims to establish the relation between ecological properties of bacterial populations and molecular properties of their proteomes. It will provide foundation to determine effective tools to fight adverse effect of infection and address such unmet medical needs as development of novel medicines and treatment protocols to overcome bacterial resistance.
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| Manhart, Michael; Shakhnovich, Eugene I (2018) Growth tradeoffs produce complex microbial communities on a single limiting resource. Nat Commun 9:3214 |
| Jacobs, William M; Shakhnovich, Eugene I (2018) Accurate Protein-Folding Transition-Path Statistics from a Simple Free-Energy Landscape. J Phys Chem B : |
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| Gilson, Amy I; Marshall-Christensen, Ahmee; Choi, Jeong-Mo et al. (2017) The Role of Evolutionary Selection in the Dynamics of Protein Structure Evolution. Biophys J 112:1350-1365 |
| Choi, Jeong-Mo; Gilson, Amy I; Shakhnovich, Eugene I (2017) Graph's Topology and Free Energy of a Spin Model on the Graph. Phys Rev Lett 118:088302 |
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| Rodrigues, João V; Bershtein, Shimon; Li, Anna et al. (2016) Biophysical principles predict fitness landscapes of drug resistance. Proc Natl Acad Sci U S A 113:E1470-8 |
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