David L Mobley
Professor
School of Pharmacy & Pharmaceutical Sciences
School of Pharmacy & Pharmaceutical Sciences
Professor, Chemistry
School of Physical Sciences
School of Physical Sciences
B.S., University of California, Davis, 2000, Physics
M.S., University of California, Davis, 2002, Physics
Ph.D., University of California, Davis, 2004, Physics
M.S., University of California, Davis, 2002, Physics
Ph.D., University of California, Davis, 2004, Physics
University of California, Irvine
3134B Natural Sciences 1
Mail Code: 3958
Irvine, CA 92697
3134B Natural Sciences 1
Mail Code: 3958
Irvine, CA 92697
Research Interests
Computational techniques for drug discovery, free energy calculations, molecular simulations, solubility
Academic Distinctions
Hewlett-Packard Outstanding Junior Faculty Award, American Chemical Society, 2009
National Science Foundation CAREER Award, 2014
National Science Foundation CAREER Award, 2014
Appointments
2004-2008: Postdoctoral Researcher in Pharmaceutical Chemistry at the University of California, San Francisco, with Ken Dill.
Research Abstract
Our research focuses on applying computational and theoretical methods to understand and quantitatively predict fundamental biological processes such as protein-ligand binding, solvation, and solubility. We seek to provide an atomically detailed understanding of these processes at a level of accuracy that can be useful in industrial applications.
One major emphasis is binding prediction. A major focus is the binding of small-molecule ligands to proteins. While current computational methods see widespread use in the pharmaceutical industry in drug discovery applications, accuracy is limited and these approaches fall far short of the goal of using computers to suggest new drug candidates. Methods we recently developed and applied have achieved far greater accuracies at computing and even predicting binding affinities than previous methods, so we are working to begin applying these in more complicated and pharmaceutically relevant binding sites. Projects involve both applications to drug discovery problems, and methodological improvements. Our work in this area focuses on using so-called alchemical free energy techniques for predicting binding affinities using molecular simulations.
We have several more application-oriented problems of binding free energy techniques, and are also looking for new collaborations. In one of these projects, we are working in collaboration with experimentalists to guide discovery/development of new antibacterials targeting gram positive bacteria. The project here takes two tracks. One begins with an existing inhibitor of our target enzyme in E. Coli and modifies it to design around binding site changes in gram positive bacteria, screening potential new inhibitors with free energy techniques before synthesizing them. Another track uses virtual screening, docking, and finally free energy calculations to screen a large library of potential inhibitors and identify promising compounds for experimental testing. In another project, we are collaborating with a pharmaceutical company, using free energy calculations to help understand affinity trends in an existing lead series for another antibacterial target.
For more information, see the lab website at http://mobleylab.org.
One major emphasis is binding prediction. A major focus is the binding of small-molecule ligands to proteins. While current computational methods see widespread use in the pharmaceutical industry in drug discovery applications, accuracy is limited and these approaches fall far short of the goal of using computers to suggest new drug candidates. Methods we recently developed and applied have achieved far greater accuracies at computing and even predicting binding affinities than previous methods, so we are working to begin applying these in more complicated and pharmaceutically relevant binding sites. Projects involve both applications to drug discovery problems, and methodological improvements. Our work in this area focuses on using so-called alchemical free energy techniques for predicting binding affinities using molecular simulations.
We have several more application-oriented problems of binding free energy techniques, and are also looking for new collaborations. In one of these projects, we are working in collaboration with experimentalists to guide discovery/development of new antibacterials targeting gram positive bacteria. The project here takes two tracks. One begins with an existing inhibitor of our target enzyme in E. Coli and modifies it to design around binding site changes in gram positive bacteria, screening potential new inhibitors with free energy techniques before synthesizing them. Another track uses virtual screening, docking, and finally free energy calculations to screen a large library of potential inhibitors and identify promising compounds for experimental testing. In another project, we are collaborating with a pharmaceutical company, using free energy calculations to help understand affinity trends in an existing lead series for another antibacterial target.
For more information, see the lab website at http://mobleylab.org.
Publications
See Google Scholar Profile (https://scholar.google.com/citations?user=k4Q4JN8AAAAJ&hl=en) and Lab website (mobleylab.org) for updated lists of publications; the most-up-to-date info is always available on Google Scholar.
Grants
We appreciate funding from the NIH and NSF. Please see our website at mobleylab.org for details.
Professional Societies
American Chemical Society
Biophysical Society
Other Experience
Postdoctoral Researcher
University of California, San Francisco 2004—2008
University of California, San Francisco 2004—2008
Chief Science Officer
Simprota Corporation 2008—2008
Simprota Corporation 2008—2008
Assistant Professor, Chemistry
University of New Orleans 2008—2012
University of New Orleans 2008—2012
Adjunct Professor, Chemistry
University of New Orleans 2012—pres
University of New Orleans 2012—pres
Scientific Advisory Board
Schrödinger Software 2013—2017
Schrödinger Software 2013—2017
Scientific Advisory Board
OpenEye Scientific Software 2017
OpenEye Scientific Software 2017
Graduate Programs
Chemistry
Pharmacological Sciences
Link to this profile
https://faculty.uci.edu/profile/?facultyId=5908
https://faculty.uci.edu/profile/?facultyId=5908
Last updated
04/29/2019
04/29/2019