Application of computational methods for predicting protein interactions

Protein interactions with other proteins or small molecules are critical to most physiological processes. These interactions may be characterized experimentally, but this can be time consuming and expensive; computational methods for predicting how two proteins interact, or which regions of a protei...

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Main Author: Yueh, Christine
Language:en_US
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/2144/27450
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spelling ndltd-bu.edu-oai-open.bu.edu-2144-274502019-01-08T15:43:36Z Application of computational methods for predicting protein interactions Yueh, Christine Biomedical engineering Protein interactions with other proteins or small molecules are critical to most physiological processes. These interactions may be characterized experimentally, but this can be time consuming and expensive; computational methods for predicting how two proteins interact, or which regions of a protein are most favorable for binding, are thus valuable tools for understanding how proteins of interest function, and have applications in drug discovery and identifying proteins of therapeutic interest. The ClusPro and FTMap algorithms for docking or solvent mapping, respectively, model protein-protein and protein-small molecule interactions, and can be used to identify the most likely orientations of a protein complex or the regions on a protein surface with the greatest propensity for binding. Here we describe three applications of ClusPro and FTMap. ClusPro was used to develop a method for determining whether a protein-protein interface is biologically relevant, by docking the proteins and comparing the results to the given interface; a larger number of near-native structures--which have interfaces similar to that of the given complex--was found to correspond to a greater probability that an interface is biological. In another project, ClusPro was used to predict whether a mutation in a multimeric complex would trigger the formation of a supramolecular assembly, based on how often that mutated residue appeared in the interfaces of the docking results; if a mutation caused such a residue to be present in the docked interfaces more often, in comparison to those of the wild-type structure, then it was likely to induce self-assembly. FTMap was used to detect and analyze the druggability of potential allosteric sites in kinases, with mapping performed on all available kinase structures to identify and determine the potential binding affinity of binding hot spots located outside of the active site. Discrimination of proteins as dimers or monomers was implemented as an addition to the ClusPro server, ClusPro-DC, and the results of the druggability analysis of kinases were organized into an online resource, the Kinase Atlas. 2019-02-20T00:00:00Z 2018-03-12T15:47:59Z 2018 2018-02-20T23:27:00Z Thesis/Dissertation https://hdl.handle.net/2144/27450 en_US
collection NDLTD
language en_US
sources NDLTD
topic Biomedical engineering
spellingShingle Biomedical engineering
Yueh, Christine
Application of computational methods for predicting protein interactions
description Protein interactions with other proteins or small molecules are critical to most physiological processes. These interactions may be characterized experimentally, but this can be time consuming and expensive; computational methods for predicting how two proteins interact, or which regions of a protein are most favorable for binding, are thus valuable tools for understanding how proteins of interest function, and have applications in drug discovery and identifying proteins of therapeutic interest. The ClusPro and FTMap algorithms for docking or solvent mapping, respectively, model protein-protein and protein-small molecule interactions, and can be used to identify the most likely orientations of a protein complex or the regions on a protein surface with the greatest propensity for binding. Here we describe three applications of ClusPro and FTMap. ClusPro was used to develop a method for determining whether a protein-protein interface is biologically relevant, by docking the proteins and comparing the results to the given interface; a larger number of near-native structures--which have interfaces similar to that of the given complex--was found to correspond to a greater probability that an interface is biological. In another project, ClusPro was used to predict whether a mutation in a multimeric complex would trigger the formation of a supramolecular assembly, based on how often that mutated residue appeared in the interfaces of the docking results; if a mutation caused such a residue to be present in the docked interfaces more often, in comparison to those of the wild-type structure, then it was likely to induce self-assembly. FTMap was used to detect and analyze the druggability of potential allosteric sites in kinases, with mapping performed on all available kinase structures to identify and determine the potential binding affinity of binding hot spots located outside of the active site. Discrimination of proteins as dimers or monomers was implemented as an addition to the ClusPro server, ClusPro-DC, and the results of the druggability analysis of kinases were organized into an online resource, the Kinase Atlas. === 2019-02-20T00:00:00Z
author Yueh, Christine
author_facet Yueh, Christine
author_sort Yueh, Christine
title Application of computational methods for predicting protein interactions
title_short Application of computational methods for predicting protein interactions
title_full Application of computational methods for predicting protein interactions
title_fullStr Application of computational methods for predicting protein interactions
title_full_unstemmed Application of computational methods for predicting protein interactions
title_sort application of computational methods for predicting protein interactions
publishDate 2018
url https://hdl.handle.net/2144/27450
work_keys_str_mv AT yuehchristine applicationofcomputationalmethodsforpredictingproteininteractions
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