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Towards simple kinetic models of functional dynamics for a kinase subfamily

Mohammad M. Sultan, Gert Kiss, Vijay Pande
doi: https://doi.org/10.1101/228528
Mohammad M. Sultan
1Department of Chemistry, Stanford University, 318 Campus Drive, Stanford, California 94305, USA.
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Gert Kiss
1Department of Chemistry, Stanford University, 318 Campus Drive, Stanford, California 94305, USA.
2Center for Molecular Analysis and Design, Stanford University, Stanford California 94305,USA.
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Vijay Pande
1Department of Chemistry, Stanford University, 318 Campus Drive, Stanford, California 94305, USA.
2Center for Molecular Analysis and Design, Stanford University, Stanford California 94305,USA.
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Abstract

Kinases are ubiquitous enzymes involved in the regulation of critical cellular pathways and have been implicated in several cancers. Consequently, the kinetics and thermodynamics of prototypical kinases are of interest and have been the subject of numerous experimental studies. In-silico modeling of the conformational ensembles of these enzymes, on the other hand, is lacking due to inherent computational limitations. Recent algorithmic advances combined with homology modeling and parallel simulations allow us to address this computational sampling bottleneck. Here, we present the results of molecular dynamics (MD) studies for seven Src family kinase (SFK) members Fyn, Lyn, Lck, Hck, Fgr, Yes, and Blk. We present a sequence invariant extension to Markov state models (MSMs), which allows us to quantitatively compare the structural ensembles of the seven kinases. Our findings indicate that in the absence of their regulatory partners, SFK members have similar in-silico dynamics with active state populations ranging from 4-40% and activation timescales in the hundreds of microseconds. Furthermore, we observe several potentially druggable intermediate states, including a pocket next to the ATP binding site that could be potentially targeted via a small molecule inhibitors. These results establish the utility of MSMs for studying protein families.

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Posted December 03, 2017.
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Towards simple kinetic models of functional dynamics for a kinase subfamily
Mohammad M. Sultan, Gert Kiss, Vijay Pande
bioRxiv 228528; doi: https://doi.org/10.1101/228528
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Towards simple kinetic models of functional dynamics for a kinase subfamily
Mohammad M. Sultan, Gert Kiss, Vijay Pande
bioRxiv 228528; doi: https://doi.org/10.1101/228528

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