Ancestral reconstruction reveals mechanisms of ERK regulatory evolution


Dajun Sang, Sudarshan Pinglay, Rafal P Wiewiora, Myvizhi E Selvan, Hua Jane Lou, John D Chodera, Benjamin E Turk, Zeynep H Gümüş, and Liam J Holt. eLife 2019;8:e38805 [DOI] [eLife] [PDF] [Folding@home data]

To understand how kinase regulation by phosphorylation emerged, we reconstruct the common ancestor of CDKs and MAPKs, using biochemical experiments and massively parallel molecular simulations to study how a few mutations were sufficient to switch ERK-family kinases from high- to low-autophosphorylation.

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.

The dynamic conformational landscapes of the protein methyltransferase SETD8


Rafal P. Wiewiora*, Shi Chen*, Fanwang Meng, Nicolas Babault, Anqi Ma, Wenyu Yu, Kun Qian, Hao Hu, Hua Zou, Junyi Wang, Shijie Fan, Gil Blum, Fabio Pittella-Silva, Kyle A. Beauchamp, Wolfram Tempel, Hualing Jiang, Kaixian Chen, Robert Skene, Y. George Zheng, Peter J. Brown, Jian Jin, John D. Chodera+, and Minkui Luo+.
eLife 8:e45403, 2019. [DOI] [bioRxiv] [GitHub] [OSF] [movies] [MSKCC blog post]
* These authors contributed equally to this work
+ Co-corresponding authors

In this work, we show how targeted X-ray crystallography using covalent inhibitors and depletion of native ligands to reveal structures of low-population hidden conformations can be combined with massively distributed molecular simulation to resolve the functional dynamic landscape of the protein methyltransferase SETD8 in unprecedented atomistic detail. Using an aggregate of six milliseconds of fully atomistic simulation from Folding@home, we use Markov state models to illuminate the conformational dynamics of this important epigenetic protein.

All Folding@home simulation trajectories for this paper are available on the Open Science Framework.

The trajectories generated for this project were used as the source for a unique musical composition 'Metastable' by George Holloway, performed by the Ligeti String Quartet with visual accompaniment from Robert Arbon.

Quantitative self-assembly prediction yields targeted nanomedicines

Yosi ShamayJanki Shah, Mehtap Işık, Aviram MizrachiJosef LeiboldDarjus F. TschaharganehDaniel RoxburyJanuka Budhathoki-UpretyKarla NawalyJames L. SugarmanEmily BautMichelle R. NeimanMegan DacekKripa S. GaneshDarren C. JohnsonRamya SridharanKaren L. ChuVinagolu K. RajasekharScott 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.

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.

Mechanistically distinct cancer-associated mTOR activation clusters predict sensitivity to rapamycin

Xu Jianing, Pham CG, Albanese SK, Dong Yiyu, Oyama T, Lee CH, Rodrik-Outmezguine V, Yao Z, Han S, Chen D, Parton DL, Chodera JD, Rosen N, Cheng EH, and Hsieh J. Journal of Clinical Investigation 126:3526, 2016. [DOI] [PDF]

In work with the James Hsieh lab at MSKCC, we examine the surprising origin of how different clinically-identified cancer-associated mutations in MTOR activate the kinase through distinct mechanisms.

Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge

Ariën S. Rustenburg, Justin Dancer, Baiwei Lin, Jianweng A. Feng, Daniel F. Ortwine, David L. Mobley, and John D. Chodera.
Journal of Computer-Aided Molecular Design 30:945, 2016. [DOI] [bioRxiv] [PDF] // data: [GitHub]
Solicited manuscript for special issue of the Journal of Computer Aided Molecular Design on the SAMPL5 Challenge.

The SAMPL Challenges have driven predictive physical modeling for ligand:protein binding forward by focusing the community on a series of blind challenges that evaluate performance on blind datasets, focus attention on current challenges for physical modeling techniques, and provide high-quality experimental datasets to the community after the challenge is over. For many years, challenges focused around hydration free energies have proven to be extremely useful, with theory now able to determine when experiment is wrong. To replace these challenges, since no more hydration free energy data is being measured, we proposed to use the partition or distribution coefficients of small druglike molecules between aqueous and apolar phases. We report the collection of cyclohexane-water partition data for a set of compounds used to drive the SAMPL5 distribution coefficient challenge, providing the experimental data, methodology, and insight for future iterations of this challenge.

Ensembler: Enabling high-throughput molecular simulations at the superfamily scale

Daniel L. Parton, Patrick B. Grinaway, Sonya M. Hanson, Kyle A. Beauchamp, and John D. Chodera
PLoS Computational Biology 12:e1004728, 2016. [DOI] [PDF] [bioRxiv] / data: [Dryad] / code: [GitHub]

We demonstrate a new tool that enables---for the first time---massively parallel molecular simulation studies of biomolecular dynamics at the superfamily scale, illustrating its application to protein tyrosine kinases, an important class of drug targets in cancer.

A simple method for automated equilibration detection in molecular simulations

John D. Chodera.
J. Chem. Theor. Comput. 12:1799, 2016. [DOI[PDF] / code to reproduce manuscript: [GitHub] / preprint: [bioRxiv] / available in pymbar.timeseries

We present a simple scheme for automatically selecting how much initial simulation data to discard to equilibration or burn-in based on maximizing the number of statistically uncorrelated samples in the dataset.

Keywords: molecular simulation; molecular dynamics; burn-in; equilibration; production; analysis

Modeling error in experimental assays using the bootstrap principle: Understanding discrepancies between assays using different dispensing technologies

Sonya M. Hanson, Sean Ekins, and John D. Chodera.
Journal of Computer Aided Molecular Design 29:1073, 2015. [DOI] [PDF] // IPython notebook [GitHub] // preprint: [bioRxiv]
Inspired by this In the Pipeline blog post

The drug development community faced a puzzling challenge when a disturbing paper published in PLoS One demonstrated results from the same assay performed with different dispensing technologies both varied wildly and significantly different in magnitude of reported potencies. Inspired by a talk given at the 2014 CADD GRC by Cosma Shalizi on bootstrapping to model error, we show how this simple idea can help explain a large amount of the discrepancy in this assay, and provide simple mathematical tools and an IPython notebook illustrating how easy it is to model the error and bias in experimental assays even when other information about assay reliability is unavailable.

Spectral rate theory for two-state kinetics

Jan-Hendrik Prinz, John D. Chodera, and Frank Noé.
Phys. Rev. X 4:011020, 2014. [DOI] [PDF]

We present a new mathematical framework for unifying various two-state rate theories presented in the physical chemistry literature over many decades, and provide a quantitative way to measure reaction coordinate quality.

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]

We show how bound ligand poses can be identified even when the location of the binding sites are unknown using the machinery of alchemical modern free energy calculations on graphics processors. 

Systematic improvement of a classical molecular model of water

Lee-Ping Wang, Teresa L. Head-Gordon, Jay W. Ponder, Pengyu Ren, John D. Chodera, Peter K. Eastman, Todd J. Martinez, and Vijay S. Pande.
J. Phys. Chem. B 117:9956, 2013. [DOI] [PDF]

A new inexpensive polarizable model of liquid water for next-generation forcefields is derived using an automated parameterization engine.


Using nonequilibrium fluctuation theorems to understand and correct errors in equilibrium and nonequilibrium discrete Langevin dynamics simulations

David A. Sivak, John D. Chodera, and Gavin E. Crooks.
Phys. Rev. X 3:011007, 2013. [DOI] [PDF]

The finite-timestep errors in molecular dynamics simulations can be interpreted as a form of nonequilibrium work.  We show how this leads to straightforward schemes for correcting for these errors or assessing their impact.

Keywords: velocity verlet with Velocity randomization; VVVR; nonequilibrium free energy; integrator error; nonequilibrium integration

OpenMM 4: A reusable, extensible, hardware independent library for high performance molecular simulation

Peter Eastman, Mark S. Friedrichs, John D. Chodera, Randy J. Radmer, Chris M. Bruns, Joy P. Ku, Kyle A. Beauchamp, T. J. Lane, Lee-Ping Wang, Diwakar Shukla, Tony Tye, Mike Houston, Timo Stich, Christoph Klein, Michael R. Shirts, and Vijay S. Pande.
J. Chem. Theor. Comput. 9:461, 2013. [DOI] [PDF]

We describe the latest version of an open-source, GPU-accelerated library and toolkit for molecular simulation.

The limitations of constant-force-feedback experiments

Phillip J. Elms, John D. Chodera, Carlos J. Bustamante, and Susan Marqusee.
Biophys. J. 103:1490, 2012. [DOI] [PDF]

Popular constant-force-feedback single-molecule experiments can cause severe artifacts in single-molecule force spectroscopy data.  We demonstrate a simple alternative that eliminates these artifacts.