Mobley Lab, UCI

Free energy methods for pharmaceutical drug discovery

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.

Github

Github

Publications

Publications

Research

Research

AlchemistryWiki

AlchemistryWiki

Papers

Escaping Atom Types in Force Fields Using Direct Chemical Perception

David L. Mobley , Caitlin C. Bannan , Andrea Rizzi, Christopher I. Bayly, John D. Chodera , Victoria T. Lim, Nathan M. Lim, Kyle A. Beauchamp, David R. Slochower, Michael R. Shirts, Michael K. Gilson, and Peter K. Eastman

 

Traditional approaches to specifying a molecular mechanics force field encode all the information needed to assign force field parameters to a given molecule into a discrete set of atom types. [More…]

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News

Mobley lab highlights since Spring

There’s lots of great news since my last update in April.

Lab news and events:

  • New graduate student Hannah Baumann recently joined the lab, coming to us from Germany after an internship at Merck Group doing free energy calculations. She’s probably done more such calculations than anyone in the lab!
  • Rotation students Martin Amezcua, Oanh Tran, Chris Zhang and Ellie Frank are spending time in the lab this quarter
  • Caitlin Bannan received an NSF MolSSI Phase II Fellowship for her work on direct chemical perception with the Open Force Field Initiative
  • Nathan Lim was awarded an NSF MolSSI Phase I Fellowship for his work on our BLUES software package.
[More…]

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News, Our science

The Open Force Field Consortium launches; check out a webinar

We’re very excited about the Open Force Field Initiative, a new effort to help build better force fields and improve the infrastructure for developing them. And we’re especially excited that a pharmaceutical industry consortium has come together to help fund and guide this work. Check out our announcement for more details!

If you’d like to know more about our longer-term plans, check out graduate student Caitlin Bannan’s upcoming BioExcel Webinar Oct. [More…]

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Papers, Our science

Challenges in the use of atomistic simulations to predict solubilities of drug-like molecules

Guilherme Duarte Ramos Matos, David L. Mobley

Background: Solubility is a physical property of high importance to the pharmaceutical industry, the prediction of which for potential drugs has so far been a hard task. We attempted to predict the solubility of acetylsalicylic acid (ASA) by estimating the absolute chemical potentials of its most stable polymorph and of solutions with different concentrations of the drug molecule.
[More…]

Papers, Our science

SAMPL6 challenge results from pKa predictions based on a general Gaussian process model

Caitlin C. Bannan, David L. Mobley, A. Geoffrey Skillman

A variety of fields would benefit from accurate pKa predictions, especially drug design due to the affect a change in ionization state can have on a molecules physiochemical properties. Participants in the recent SAMPL6 blind challenge were asked to submit predictions for microscopic and macroscopic pKas of 24 drug like small molecules.  [More…]

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Contact

David L. Mobley
dmobley@mobleylab.org
phone: 949.385.2436
office: 3134B Nat. Sci. I

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