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BIOMOLECULAR DYNAMICS REVEALED BY ELASTIC NETWORK MODELS AND THE STUDY OF MECHANICAL KEY SITES FOR LIGAND BINDING

Yang, Lee-Wei (2005) BIOMOLECULAR DYNAMICS REVEALED BY ELASTIC NETWORK MODELS AND THE STUDY OF MECHANICAL KEY SITES FOR LIGAND BINDING. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

The Gaussian network model (GNM) can be used as a first approximation for describing the fluctuation dynamics of proteins, the limits of applicability and the range of validity of the model parameters need to be established. A systematic analysis of the GNM predictions is done within the scope of this thesis, and the potential utility of GNM for elucidating structure-dynamics-function relations in enzymes is explored. The application of the GNM to a set of 183 non-homologous proteins shows that it can predict the X-ray crystallographic temperature factors more precisely than full-atomic normal mode analysis (NMA) does. Furthermore, the application to 1250 non-redundant proteins indicates that the GNM predictions agree better with NMR solution data, than X-ray crystallographic, and measurements taken at high diffraction temperatures. A systematic study of 98 enzymes that belong to different enzyme classes (EC) shows that catalytic residues are distinguished by their restricted mobilities in the global modes. The amplitudes of their fluctuations rank in the lowest 7% range amongst the rank-ordered mobilities of all residues. Catalytic residues also bear more restricted mobilities than their 4 flanked neighbors in sequence and this feature holds for more than 70% of the examined catalytic residues, suggesting a communication between chemical activity and molecular mechanics. The observed restricted mobility of catalytic residues is used as a criterion for identifying active sites of enzymes in a newly developed algorithm (COMPACT). The method shows a high sensitivity and a moderate-to-low specificity for a set of representative monomeric enzymes. All the false-positives predicted by COMPACT are found to be highly conserved, suggesting that their finely tuned dynamics results from evolutionary pressure. These particular sites are proposed to serve as alternative drug binding targets. We have implemented this tool in iGNM, a database of protein dynamics. Protein dynamics stored in iGNM or computed from the online calculation server (oGNM) have assisted in identifying possible silver ion binding residue in creatinase and describing the loop mobilities of low-fidelity DNA polymerase. Over all, this dissertation supports the view that protein structures have been designed to undergo conformational changes that are required for their biological functions.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Yang, Lee-Weilwy1@pitt.eduLWY1
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairBahar, Ivetbahar@ccbb.pitt.eduBAHAR
Committee MemberRussell, Alanrussellaj@upmc.edu
Committee MemberMeirovitch, Hagaihagaim@pitt.eduHAGAIM
Committee MemberMadura, Jeffrymadura@duq.edu
Committee MemberCascio, Michaelcascio@pitt.eduCASCIO
Date: 9 December 2005
Date Type: Completion
Defense Date: 13 June 2005
Approval Date: 9 December 2005
Submission Date: 1 December 2005
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: School of Medicine > Biochemistry and Molecular Genetics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: active site prediction; elastic network model; hinge; PDB; PolQ
Other ID: http://etd.library.pitt.edu/ETD/available/etd-12012005-104746/, etd-12012005-104746
Date Deposited: 10 Nov 2011 20:07
Last Modified: 15 Nov 2016 13:52
URI: http://d-scholarship.pitt.edu/id/eprint/9908

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