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Dynamic profile analysis to characterize dynamics-driven allosteric sites in enzymes.

ABSTRACT: We examine the dynamic features of non-trivial allosteric binding sites to elucidate potential drug binding sites. These allosteric sites were previously found to be allosteric after determination of the protein-drug co-crystal structure. After comprehensive search in the Protein Data Bank, we identify 10 complex structures with allosteric ligands whose structures are very similar to their functional forms. Then, possible pockets on the protein surface are searched as potential ligand binding sites. To mimic ligand binding to the pocket, complex models are generated to fill out each pocket with pseudo ligand blocks consisting of spheres. Normal mode analysis of the elastic network model is performed for the complex models and unbound structures to assess the change of protein dynamics induced by ligand binding. We examine nine profiles to describe the dynamic and positional characteristics of the pockets, and identify the change of fluctuation around the ligand, ?MSFbs , as the best profile for distinguishing the allosteric sites from the other sites in 8 structures. These cases should be considered as examples of dynamics-driven allostery, which accompanies significant changes in protein dynamics. ?MSFbs is suggested to be used for the search of potential dynamics-driven allosteric sites in proteins for drug discovery.

SUBMITTER: Taguchi J

PROVIDER: S-EPMC5042162 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Dynamic profile analysis to characterize dynamics-driven allosteric sites in enzymes.

Taguchi Junko J Kitao Akio A

Biophysics and physicobiology 20160714

We examine the dynamic features of non-trivial allosteric binding sites to elucidate potential drug binding sites. These allosteric sites were previously found to be allosteric after determination of the protein-drug co-crystal structure. After comprehensive search in the Protein Data Bank, we identify 10 complex structures with allosteric ligands whose structures are very similar to their functional forms. Then, possible pockets on the protein surface are searched as potential ligand binding si ...[more]

PMID: 27924265

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Project description:Kinesin motor domains couple cycles of ATP hydrolysis to cycles of microtubule binding and conformational changes that result in directional force and movement on microtubules. The general principles of this mechanochemical coupling have been established; however, fundamental atomistic details of the underlying allosteric mechanisms remain unknown. This lack of knowledge hampers the development of new inhibitors and limits our understanding of how disease-associated mutations in distal sites can interfere with the fidelity of motor domain function. Here, we combine unbiased molecular-dynamics simulations, bioinformatics analysis, and mutational studies to elucidate the structural dynamic effects of nucleotide turnover and allosteric inhibition of the kinesin-5 motor. Multiple replica simulations of ATP-, ADP-, and inhibitor-bound states together with network analysis of correlated motions were used to create a dynamic protein structure network depicting the internal dynamic coordination of functional regions in each state. This analysis revealed the intervening residues involved in the dynamic coupling of nucleotide, microtubule, neck-linker, and inhibitor binding sites. The regions identified include the nucleotide binding switch regions, loop 5, loop 7, ?4-?5-loop 13, ?1, and ?4-?6-?7. Also evident were nucleotide- and inhibitor-dependent shifts in the dynamic coupling paths linking functional sites. In particular, inhibitor binding to the loop 5 region affected ?-sheet residues and ?1, leading to a dynamic decoupling of nucleotide, microtubule, and neck-linker binding sites. Additional analyses of point mutations, including P131 (loop 5), Q78/I79 (?1), E166 (loop 7), and K272/I273 (?7) G325/G326 (loop 13), support their predicted role in mediating the dynamic coupling of distal functional surfaces. Collectively, our results and approach, which we make freely available to the community, provide a framework for explaining how binding events and point mutations can alter dynamic couplings that are critical for kinesin motor domain function.

Dataset Information

Dynamic profile analysis to characterize dynamics-driven allosteric sites in enzymes.

Publications

Dynamic profile analysis to characterize dynamics-driven allosteric sites in enzymes.

Similar Datasets

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