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Unbiased Molecular Dynamics of 11 min Timescale Drug Unbinding Reveals Transition State Stabilizing Interactions

Lotz, Samuel; Dickson, Alex

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  <identifier identifierType="DOI">10.5281/zenodo.1021565</identifier>
      <creatorName>Lotz, Samuel</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0001-6159-615X</nameIdentifier>
      <affiliation>Michigan State University</affiliation>
      <creatorName>Dickson, Alex</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-9640-1380</nameIdentifier>
      <affiliation>Michigan State University</affiliation>
    <title>Unbiased Molecular Dynamics of 11 min Timescale Drug Unbinding Reveals Transition State Stabilizing Interactions</title>
    <date dateType="Issued">2017-10-30</date>
  <resourceType resourceTypeGeneral="JournalArticle"/>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsSupplementTo">10.1021/jacs.7b08572</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1021564</relatedIdentifier>
    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;Abstract: Ligand (un)binding kinetics is being recognized as a determinant of drug specificity and efficacy&lt;br&gt;
in an increasing number of systems. However, the calculation of kinetics and the simulation of&lt;br&gt;
drug unbinding is more difficult than computing thermodynamic quantities, such as binding free&lt;br&gt;
energies. Here we present the first full simulations of an unbinding process at pharmacologi-&lt;br&gt;
cally relevant timescales (11 min), without the use of biasing forces, detailed prior knowledge, or&lt;br&gt;
specialized processors using the weighted ensemble based algorithm, WExplore. These simula-&lt;br&gt;
tions show the inhibitor TPPU unbinding from its enzyme target soluble epoxide hydrolase (sEH),&lt;br&gt;
which is a clinically relevant target that has attracted interest in kinetics optimization in order&lt;br&gt;
to increase efficacy. We make use of conformation space networks (CSNs) that allow us to con-&lt;br&gt;
ceptualize unbinding not just as a linear process, but as a network of interconnected states that&lt;br&gt;
connect the bound and unbound states. This allows us to visualize patterns in hydrogen-bonding,&lt;br&gt;
solvation, and non-equilibrium free energies, without projection onto progress coordinates. The&lt;br&gt;
topology and layout of the network reveal multiple unbinding pathways, and other rare events,&lt;br&gt;
such as the reversal of ligand orientation within the binding site. Furthermore, we make a pre-&lt;br&gt;
diction of the transition state ensemble, using transition path theory, and identify protein-ligand&lt;br&gt;
interactions which are stabilizing to the transition state. Additionally, we uncover trends in ligand&lt;br&gt;
and binding site solvation that corroborate experimental evidence from more classical structure&lt;br&gt;
kinetics relationships (SKRs) and generates new questions as to the role of drug modifications in&lt;br&gt;
kinetics optimization. Finally, from the 75 observed unbinding events we calculate a residence&lt;br&gt;
time, 42 s, within 2 orders of magnitude from the experimental residence time of 11 min, which&lt;br&gt;
is just outside the standard error of the calculation.&lt;/p&gt;

&lt;p&gt;Contents: This data repository contains the trajectories as well as the WExplore data used to keep track of cloning and merging, initial structures, clustering results, and key tables of results from the analysis. A full analysis &amp;quot;notebook&amp;quot; is also provided in the org-mode format.&lt;/p&gt;</description>
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