Biophysical and computational methods to analyze amino acid interaction networks in proteins.
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A number of different structural and computational methods have been developed to interrogate amino acid networks, including analyses of X-ray crystallographic data and structures, computer simulations, NMR data, and covariation among protein sequences, and the critical insights that such methods provide into protein function are described.Abstract:
Globular proteins are held together by interacting networks of amino acid residues. A number of different structural and computational methods have been developed to interrogate these amino acid networks. In this review, we describe some of these methods, including analyses of X-ray crystallographic data and structures, computer simulations, NMR data, and covariation among protein sequences, and indicate the critical insights that such methods provide into protein function. This information can be leveraged towards the design of new allosteric drugs, and the engineering of new protein function and protein regulation strategies.read more
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References
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Journal ArticleDOI
A Set of Measures of Centrality Based on Betweenness
TL;DR: A family of new measures of point and graph centrality based on early intuitions of Bavelas (1948) is introduced in this paper, which define centrality in terms of the degree to which a point falls on the shortest path between others and there fore has a potential for control of communication.
Journal ArticleDOI
Secondary-structure matching (SSM), a new tool for fast protein structure alignment in three dimensions
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Random graphs with arbitrary degree distributions and their applications.
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