[ds-undergrads] Data Science talk by Prof. Chia-en Chang, tomorrow Friday February 17th, 12-1pm, MRB Seminar Room

[tsotras at cs.ucr.edu]

Dear DS majors,
please find below info about tomorrow's Data Science seminar; it is about
using ML techniques for structural biology problems. Please use the link
below to register if you plan to attend.

best,
V. Tsotras


---------------------------- Original Message ----------------------------
Subject: [UCR_DataScience] Data Science talk by Prof. Chia-en Chang,
Friday February 17th, 12-1pm, MRB Seminar Room
From:    "Vassilis Tsotras" <tsotras at cs.ucr.edu>
Date:    Mon, February 13, 2023 5:07 pm
To:      datascience at lists.ucr.edu
--------------------------------------------------------------------------

The next Data Science seminar will be on Friday, February 17th,
12:00-1:00pm at the MRB Seminar Room (1st floor).

**** Pizza and refreshments will be provided ****

To keep track of the number of attendees, please *register* at:
https://www.eventbrite.com/e/data-science-talk-tickets-544627033117

The talk will be given by *Prof. Chia-en Chang*, Department of
Chemistry, UCR

*Title:*
Machine Learning Guided Modeling of Ligand-Protein Binding Energy
Landscape: Applications in Small Molecule and Protein-based Drug Design.

*Abstract:*
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.

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.


------------------------------------
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.

A full list of previous seminars appears at:
http://datascience.ucr.edu/seminars

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 (tsotras at cs.ucr.edu).

Sincerely,
Vassilis Tsotras
Professor, CSE Department
Director, Data Science Major

_______________________________________________
DataScience mailing list
DataScience at lists.ucr.edu
https://lists.ucr.edu/mailman/listinfo/datascience