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Modeling of protein binary complexes using structural mass spectrometry data
Author(s) -
Kamal J.K. Amisha,
Chance Mark R.
Publication year - 2008
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1110/ps.073071808
Subject(s) - docking (animal) , footprinting , chemistry , homology modeling , searching the conformational space for docking , protein data bank (rcsb pdb) , threading (protein sequence) , macromolecular docking , protein structure , dna footprinting , crystallography , biological system , stereochemistry , biology , biochemistry , transcription factor , dna binding protein , gene , medicine , nursing , enzyme
In this article, we describe a general approach to modeling the structure of binary protein complexes using structural mass spectrometry data combined with molecular docking. In the first step, hydroxyl radical mediated oxidative protein footprinting is used to identify residues that experience conformational reorganization due to binding or participate in the binding interface. In the second step, a three‐dimensional atomic structure of the complex is derived by computational modeling. Homology modeling approaches are used to define the structures of the individual proteins if footprinting detects significant conformational reorganization as a function of complex formation. A three‐dimensional model of the complex is constructed from these binary partners using the ClusPro program, which is composed of docking, energy filtering, and clustering steps. Footprinting data are used to incorporate constraints—positive and/or negative—in the docking step and are also used to decide the type of energy filter—electrostatics or desolvation—in the successive energy‐filtering step. By using this approach, we examine the structure of a number of binary complexes of monomeric actin and compare the results to crystallographic data. Based on docking alone, a number of competing models with widely varying structures are observed, one of which is likely to agree with crystallographic data. When the docking steps are guided by footprinting data, accurate models emerge as top scoring. We demonstrate this method with the actin/gelsolin segment‐1 complex. We also provide a structural model for the actin/cofilin complex using this approach which does not have a crystal or NMR structure.