Computational Approaches to Understanding the Evolution of Molecular Function

Yana Bromberg1, Matthew W. Hahn2,3, Predrag Radivojac3


1Department of Biochemistry and Microbiology, Rutgers University
2Department of Biology, Indiana University
3Department of Computer Science and Informatics, Indiana University

Pacific Symposium on Biocomputing 22:1-2(2017)

© 2017 World Scientific
Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution (CC BY) 4.0 License.


Abstract

Understanding the function of biological macromolecules and their interactions is a grand challenge of modern biology, and a key foundation for biomedical research. It is now evident that the function of these molecules, in isolation or in groups, can be productively studied in the context of evolution. Therefore, understanding how these molecules and their functions evolve is an important step in understanding the specific events that lead to observable changes in molecular and biological processes. With the advent of high-throughput technologies and the rapid accumulation of molecular data over the past several decades, the evolution of molecular function can be systematically studied at multiple levels. This includes the evolution of protein structure, 3D organization and dynamics, protein and gene expression, as well as the higher-level organization of function contained within pathways. New experiments using the latest gene-editing technologies (such as CRISPR-Cas9) have also made it possible to directly test hypotheses about function in almost any organism. Combining these data with theory and computational tools taken from evolutionary biology and related fields has led to an explosion in the study of how function evolves.


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