Rational design of small molecules

alchemical free energy calculation of abl:imatinib

alchemical free energy calculation of abl:imatinib

The discovery and development of a new small molecule drug currently takes a decade and over $1B, with overall success rates below 3%. To meet the dire need for new small molecule inhibitors for use as chemical probes and potential therapeutics, we are developing physical modeling techniques to rapidly accelerate this process and allow better decisions to be made earlier in the process to anticipate and avoid ADME-Tox issues later in the program.


To enable truly rational computational design of small molecules, we are developing new algorithms and open source tools for alchemical free energy calculations that provide a rigorous but practical approach to the quantitative prediction of small molecule binding affinities and other physicochemical properties of relevance to ADME-Tox (such as partition coefficients, serum binding, and off-target affinities).

Our open source code YANK, built on the GPU-accelerated OpenMM molecular simulation library, automates best practices (such as heterogeneous dispersion corrections, restraints, automated equilibration detection, and optimal estimation) and allows us to explore new algorithms for enhanced sampling (such as Gibbs sampling replica-exchange and self-adjusted mixture sampling) and increased chemical detail (including dynamic treatment of protonation states and counterions).


YANK: An open, extensible GPU-accelerated code for alchemical free energy calculations
perses: Relative free energy calculations for ligand design [experimental]

openmmtools: Toolkit layer and alchemical factories for OpenMM
protons: Constant-pH dynamics for OpenMM  [experimental]
saltswap: Grand-canonical Monte Carlo (GCMC) treatment of counterions for OpenMM  [experimental]


alchemistry.org - a community-oriented resource for alchemical free energy calculations


Michael R. Shirts (University of Colorado): Best practices in alchemical free energy calculations
David L. Mobley (University of California, Irvine): Best practices in alchemical free energy calculations
Paul Czodrowski (Merck KGaA): Automation of best practices in alchemical free energy calculations for drug discovery; benchmarking of accuracy
Vijay S. Pande (Stanford University): Development of the GPU-accelerated OpenMM simulation framework


Levi N. Naden (postdoctoral fellow)
Andrea Rizzi (CBM Graduate Student)
Patrick Grinaway (PBSB Graduate Student):
Relative free energy calculations


Identifying ligand binding sites and poses using GPU-accelerated Hamiltonian replica exchange molecular dynamics
Kai Wang K, John D. Chodera, Yanzhi Yang, and Michael R. Shirts. 
J. Comput. Aid. Mol. Des. 27:989, 2013. [DOI] [PDF]

Free energy methods in drug discovery and design: Progress and challenges
John D. Chodera, David L. Mobley, Michael R. Shirts, Richard W. Dixon, Kim M. Branson, and Vijay S. Pande.
Curr. Opin. Struct. Biol. 21:150, 2011. [DOI] [PDF]

Alchemical free energy calculations: Ready for prime time?
Michael R. Shirts, David L. Mobley, and John D. Chodera.
Annu. Rep. Comput. Chem. 3:41, 2007. [DOI] [PDF]

Predicting absolute ligand binding free energies to a simple model site
David L. Mobley, Alan P. Graves, John D. Chodera, Andrea C. McReynolds, Brian K. Shoichet, and Ken A. Dill.
J. Mol. Biol. 371:1118, 2007. [DOI] [PDF]

Confine-and-release method: Obtaining correct binding free energies in the presence of protein conformational change
David L. Mobley, John D. Chodera, and Ken A. Dill.
J. Chem. Theor. Comput. 3:1231, 2007. [DOI] [PDF]

On the use of orientational restraints and symmetry corrections in alchemical free energy calculations
David L. Mobley, John D. Chodera, and Ken A. Dill.
J. Chem. Phys. 125:084902, 2006. [DOI] [PDF]


Merck Kgga

Merck Kgga



Gerstner Young investigator award

Gerstner Young investigator award