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The next Data Science seminar will be on Friday, February 17th,
12:00-1:00pm at the MRB Seminar Room (1st floor).<br>
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**** Pizza and refreshments will be provided ****<br>
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To keep track of the number of attendees, please *register* at:<br>
<a class="moz-txt-link-freetext" href="https://www.eventbrite.com/e/data-science-talk-tickets-544627033117">https://www.eventbrite.com/e/data-science-talk-tickets-544627033117</a></div>
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<div class="moz-forward-container">The talk will be given by <b>Prof.
Chia-en Chang</b>, Department of Chemistry, UCR<br>
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<b>Title:</b><br>
Machine Learning Guided Modeling of Ligand-Protein Binding
Energy Landscape: Applications in Small Molecule and
Protein-based Drug Design.<br>
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<b>Abstract:</b><br>
Molecules in cells constantly move. The motions of proteins in
living cells can be simple fluctuations or functional.
Therefore, investigating protein dynamics is crucial for
understanding protein function and for accurately compute
ligand-protein binding free energy landscape. Because
experimental structures are static conformations, classical or
enhanced molecular dynamics (MD) simulations are commonly used
for conformational sampling. Machine/deep learning approaches
can then be used to analyze MD results and assist conformational
sampling and energy calculations.<br>
<br>
In this presentation, we will focus on modeling ligand-receptor
binding/unbinding pathways to compute protein-drug binding
thermodynamics and kinetics for drug development. We will show
the binding free energy landscape constructed by Binding
Kinetics Toolkit (BKiT), a program using post-analysis,
principal component analysis and milestoning theory to predict
drug binding kinetics. We will also discuss use of machine
learning and deep learning to enhance protein conformational
sampling to model protein conformational transition and other
applications.<br>
<br>
<br>
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Sponsored by the UCR Data Science Center, the purpose of the
Data Science Seminars is to foster collaborations between "core"
Data Science faculty (from CSE/ECE/Stat Departments) and
faculty/visitors from other sciences that face Data Science
problems in their research. These informal gatherings are open
to interested faculty and graduate students. Each meeting will
start with a talk describing research problems and then a
discussion will follow for questions, open problems, ideas for
possible collaborations etc.<br>
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A full list of previous seminars appears at:<br>
<a class="moz-txt-link-freetext"
href="http://datascience.ucr.edu/seminars"
moz-do-not-send="true">http://datascience.ucr.edu/seminars</a><br>
<br>
Forward this email to other colleagues or graduate students in
your lab that may be interested. Moreover, if you are interested
in giving a Data Science related talk, please contact me (<a
class="moz-txt-link-abbreviated moz-txt-link-freetext"
href="mailto:tsotras@cs.ucr.edu" moz-do-not-send="true">tsotras@cs.ucr.edu</a>).<br>
<br>
Sincerely,<br>
Vassilis Tsotras<br>
Professor, CSE Department<br>
Director, Data Science Major<br>
<br>
<br>
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