Standard state free energies, not pKas, are ideal for describing small molecule protonation and tautomeric states

M R Gunner, Taichi Murakami, Ariën S. Rustenburg, Mehtap Işık, and John D. Chodera.
Journal of Computer Aided Molecular Design 34:561, 2020. [DOI] [PDF] [GitHub]

Here, we demonstrate how the physical nature of protonation and tautomeric state effects means that the standard state free energies of each microscopic protonation/tautomeric state at a single pH is sufficient to describe the complete pH-dependent microscopic and macroscopic populations. We introduce a new kind of diagram that uses this concept to illustrate a variety of pH-dependent phenomena, and show how it can be used to identify common issues with protonation state prediction algorithms. As a result, we recommend future blind prediction challenges utilize microstate free energies at a single reference pH as the minimal sufficient information for assessing prediction accuracy and utility.

Small-molecule targeting of MUSASHI RNA-binding activity in acute myeloid leukemia

Gerard Minuesa, Steven K Albanese, Arthur Chow, Alexandra Schurer, Sun-Mi Park, Christina Z. Rotsides, James Taggart, Andrea Rizzi, Levi N. Naden, Timothy Chou, Saroj Gourkanti, Daniel Cappel, Maria C Passarelli, Lauren Fairchild, Carolina Adura, Fraser J Glickman, Jessica Schulman, Christopher Famulare, Minal Patel, Joseph K Eibl, Gregory M Ross, Derek S Tan, Christina S Leslie, Thijs Beuming, Yehuda Goldgur, John D Chodera, Michael G Kharas
Nature Communications 10:2691, 2019. [DOI] [bioRxiv] [GitHub] [MSKCC blog post]

We use absolute alchemical free energy calculations to identify the likely interaction site for a small hydrophobic ligand that shows activity against MUSASHI in AML.

Toward learned chemical perception of force field typing rules

Camila Zanette, Caitlin C. Bannan, Christopher I. Bayly, Josh Fass, Michael K. Gilson, Michael R. Shirts, John Chodera, and David L. Mobley
Journal of Chemical Theory and Computation, 15:402, 2019. [DOI] [ChemRxiv] [GitHub]

We show how machine learning can learn typing rules for molecular mechanics force fields within a Bayesian statistical framework.

Overview of the SAMPL6 host-guest binding affinity prediction challenge

Andrea Rizzi, Steven Murkli, John N. McNeill, Wei Yao, Matthew Sullivan, Michael K. Gilson, Michael W. Chiu, Lyle Isaacs, Bruce C. Gibb, David L. Mobley*, John D. Chodera*
* denotes co-corresponding authors
Journal of Computer-Aided Molecular Design special issue on SAMPL6, 32:937, 2018. [DOI] [bioRxiv] [GitHub]

We present an overview of the host-guest systems and participant performance for the SAMPL6 host-guest blind affinity prediction challenges, assessing how well various physical modeling approaches were able to predict ligand binding affinities for simple ligand recognition problems where receptor sampling and protonation state effects are eliminated due to the simplicity of supramolecular hosts. We find that progress is now stagnated likely due to force field limitations.

pKa measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments

Mehtap Işık, Dorothy Levorse, Ariën S. Rustenburg, Ikenna E. Ndukwe, Heather Wang , Xiao Wang , Mikhail Reibarkh , Gary E. Martin , Alexey A. Makarov , David L. Mobley, Timothy Rhodes*, John D. Chodera*.
* co-corresponding authors
Journal of Computer-Aided Molecular Design special issue on SAMPL6 32:1117, 2018.
[DOI] [PDF] [bioRxiv] [Supplementary Tables and Figures] [Supplementary Data (includes Sirius T3 reports on all measurements)]

The SAMPL5 blind challenge exercises identified neglect of protonation state effects as a major accuracy-limiting factor in physical modeling of biomolecular interactions. In this study, we report the experimental measurements behind a SAMPL6 blind challenges in which we assess the ability of community codes to predict small molecule pKas for small molecule resembling fragments of selective kinase inhibitors.

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, Michael R. Shirts, Michael K. Gilson, Peter K. Eastman.
Journal of Chemical Theory and Computation 14:6076, 2018 [DOI] [bioRxiv]

We describe the philosophy behind a modern approach to molecular mechanics forcefield parameterization, and present initial results for the first SMIRNOFF-encoded forcefield: SMIRNOFF99Frosst.

Quantitative self-assembly prediction yields targeted nanomedicines

Yosi Shamay, Janki Shah, Mehtap Işık, Aviram Mizrachi, Josef Leibold, Darjus F. Tschaharganeh, Daniel Roxbury, Januka Budhathoki-Uprety, Karla Nawaly, James L. Sugarman, Emily Baut, Michelle R. Neiman, Megan Dacek, Kripa S. Ganesh, Darren C. Johnson, Ramya Sridharan, Karen L. Chu, Vinagolu K. Rajasekhar, Scott W. Lowe, John D. Chodera, and Daniel A. Heller. 
Nature Materials 17:361, 2018. [DOI] [PDF] [Supporting Info] [nano-drugbank]

In a collaboration with the Heller Lab at MSKCC, we show how indocyanine nanoparticles can package insoluble selective kinase inhibitors with high mass loadings and efficiently deliver them to tumors.

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

Samuel Gill, Nathan M. Lim, Patrick Grinaway, Ariën S. Rustenburg, Josh Fass, Gregory Ross, John D. Chodera, and David Mobley.
Journal of Physical Chemistry B 22:5579, 2018. [DOI] [ChemRxiv] [GitHub]

Nonequilibrium candidate Monte Carlo can be used to accelerate the sampling of ligand binding modes by orders of magnitude over instantaneous Monte Carlo.

Approaches for calculating solvation free energies and enthalpies demonstrated with an update of the FreeSolv database

Guilherme Duarte Ramos Matos, Daisy Y. Kyu, Hannes H. Loeffler, John D. Chodera, Michael R. Shirts, David Mobley
Journal of Chemical Engineering Data 62:1559, 2017. [DOI] [bioRxiv] [GitHub]

We review alchemical methods for computing solvation free energies and present an update (version 0.5) to the FreeSolv database of experimental and calculated hydration free energies of neutral compounds.

L-2-Hydroxyglutarate production arises from noncanonical enzyme function at acidic pH

Intlekofer A, Wang B, Liu H, Shah H, Carmona-Fontaine C, Rustenburg AS, Salah S, Gunner MR, Chodera JD, Cross JR, and Thompson CB.
Nature Chemical Biology 13:494, 2017. [DOI] [PDF] [GitHub]

At low pH, metabolic enzymes lactate dehydrogenase and malate dehydrogenase undergo shifts in substrate utilization that have high relevance to cancer metabolism due to surprisingly simple protonation state effects.

A water-mediated allosteric network governs activation of Aurora kinase A

Cyphers S, Ruff E, Behr JM, Chodera JD, and Levinson NM.
Nature Chemical Biology 13:402, 2017. [DOI] [PDF] [GitHub]

Over 50 microseconds of aggregate simulation data on Folding@home reveal a surprisingly stable hydrogen bond network underlies allosteric activation by Tpx2.