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From Protein Structure to Function with Bioinformatics.pdf

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9 <strong>Protein</strong> Dynamics: <strong>From</strong> <strong>Structure</strong> <strong>to</strong> <strong>Function</strong> 2399.4.3 CONCOORDCONCOORD (de Groot et al. 1997) uses a geometry-based approach <strong>to</strong> predictprotein flexibility. The three-dimensional structure of a protein is determined byvarious interactions such as covalent bonds, hydrogen bonds and non-polar interactions.Most of these interactions remain intact during functionally relevantconformational changes. This notion lies at the heart of the CONCOORD simulationmethod: based on an input structure, alternative structures are generated thatshare the large majority of interactions found in the original configuration. To thisend, in the first step of a CONCOORD simulation (Fig. 9.11) interactions in asingle input structure are analyzed and turned in<strong>to</strong> geometrical constraints,mainly distance constraints <strong>with</strong> upper and lower bounds for a<strong>to</strong>mic distances butalso angle constraints and information about planar and chiral groups. This geometricaldescription of the structure can be compared <strong>to</strong> a construction plan of theprotein. In the second step, starting from random a<strong>to</strong>mic coordinates, the structureis iteratively rebuilt based on the predefined construction plan, commonlyseveral hundreds of times. As each run starts from random coordinates, themethod does not suffer from sampling problems like MD simulations and theresulting ensemble covers the whole conformational space that is available <strong>with</strong>inthe predefined constraints. However, the method does not provide informationabout the path between two conformational substates or about timescales andenergies (Fig. 9.12).9.4.3.1 ApplicationsCONCOORD and the newly developed extension tCONCOORD (t stands fortransition) (Seeliger et al. 2007) have been applied <strong>to</strong> diverse proteins. Adenylatekinase displays a distinct domain-closing motion upon binding <strong>to</strong> its substrate(ATP/AMP) or an inhibi<strong>to</strong>r (see Fig. 9.13 left) <strong>with</strong> a C α-RMSD of 7.6 Åbetween the ligand-bound and the ligand-free conformation. Two tCONCOORDsimulations were carried out using a closed conformation (PDB 1AKE) as input.In one simulation the ligand (Ap 5A) was removed. Fig. 9.13 (right) shows theresult of a principal components analysis (PCA) applied <strong>to</strong> the experimentalstructures. The first eigenvec<strong>to</strong>r (x-axis) corresponds <strong>to</strong> the domain-openingmotion indicated by the arrow in Fig. 9.13 (left). Every dot in the plot representsa single structure. Red dots represent the ensemble that has been generated usingthe closed conformation of adenylate kinase <strong>with</strong>out ligand as input. Green dotsrepresent the ensemble that has been generated using the ligand-bound structureas input. Whereas the simulation <strong>with</strong> inhibi<strong>to</strong>r basically samples closed conformationsaround the ligand-bound state, the ligand-free simulation samples both,open and closed conformations, thereby reaching the experimentally determinedopen conformations <strong>with</strong> RMSD’s of 2.4, 2.6, and 3.1 Å for 1DVR, 1AK2, and4AKE, respectively. In structure-based drug design, often the reverse problem,

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