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Allosteric pathway formation in globin proteins explored with network analysis models

  • Carnegie Mellon University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the context of drug design and protein engineering, understanding the nature of allosteric networks is of particular interest. A pre-condition for successfully developing a rational design of proteins that incorporates allostery is the capability of understanding the structure and dynamics of protein internal communication pathways and networks. In this article, we compare computational approaches utilizing network analysis models and methods with results from THz time-scale spectroscopy experiments. We are able to show that community detection applied on network models of coevolution within a protein family can provide insight about the signal propagation pathways in protein subfamilies. Experimental results connect these communities with protein dynamics. We deduce that different routes of communication may be linked with the discrimination and dynamics of ligand binding.

Original languageEnglish
Title of host publicationTechnical Proceedings of the 2014 NSTI Nanotechnology Conference and Expo, NSTI-Nanotech 2014
PublisherNano Science and Technology Institute
Pages271-274
Number of pages4
ISBN (Print)9781482258271
StatePublished - 2014
Externally publishedYes
EventNanotechnology 2014: MEMS, Fluidics, Bio Systems, Medical, Computational and Photonics - 2014 NSTI Nanotechnology Conference and Expo, NSTI-Nanotech 2014 - Washington, DC, United States
Duration: 15 Jun 201418 Jun 2014

Publication series

NameTechnical Proceedings of the 2014 NSTI Nanotechnology Conference and Expo, NSTI-Nanotech 2014
Volume2

Conference

ConferenceNanotechnology 2014: MEMS, Fluidics, Bio Systems, Medical, Computational and Photonics - 2014 NSTI Nanotechnology Conference and Expo, NSTI-Nanotech 2014
Country/TerritoryUnited States
CityWashington, DC
Period15/06/1418/06/14

Keywords

  • Allostery
  • Coevolution networks
  • Community detection
  • Protein engineering

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