An open library of human kinase domain constructs for automated bacterial expression

kinome-expression-tree.jpg

Daniel L. Parton, Sonya M. Hanson, Lucelenie Rodríguez-Laureano, Steven K. Albanese, Scott Gradia, Chris Jeans, Markus Seeliger, and John D. Chodera.
Manuscript prior to publication: [bioRxiv]
Interactive data browser: [github.io]
Plasmids available via AddGene

Human kinase catalytic domains---the therapeutic target of selective kinase inhibitors used in the treatment of cancer and other diseases---are notoriously difficult and expensive to express in insect or human cells. Here, we utilize the phosphatase co-expression technology developed by Markus Seeliger (now at Stony Brook) to develop a library of human kinase catalytic domains for facile and inexpensive expression in bacteria.

OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics

Peter Eastman, Jason Swails, John D. Chodera, Robert T. McGibbon, Yutong Zhao, Kyle A. Beauchamp, Lee-Ping Wang, Andrew C. Simmonett, Matthew P. Harrigan, Bernard R. Brooks, Vijay S. Pande. PLoS Computational Biology 13:e1005659, 2017. [DOI] [bioRxiv] [website] [GitHub]

We describe the latest version of OpenMM, a GPU-accelerated framework for high performance molecular simulation applications.

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

Guilherme Duarte Ramos MatosDaisy Y. KyuHannes H. LoefflerJohn D. ChoderaMichael R. ShirtsDavid Mobley
Journal of Chemical Engineering Data, 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 conserved water-mediated hydrogen bond network governs allosteric activation in 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.
Solicited manuscript for special issue of the Journal of Computer Aided Molecular Design on the SAMPL5 Challenge.
preprint: [DOI] [bioRxiv] [PDF] // data: [GitHub]

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 Comput. Biol. 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.

Avoiding accuracy-limiting pitfalls in the study of protein-ligand interactions with isothermal titration calorimetry

Sarah E. Boyce, Joel Tellinghuisen, and John D. Chodera.
Manuscript prior to submission. [bioRxiv] [PDF]
Supplementary files: ITC worksheet [PDF] [XLSX] [ODS]
doi:10.1101/023796

We show how to avoid common accuracy-limiting mistakes in isothermal titration calorimetry, and provide a simple spreadsheet to aid in propagating the dominant source of uncertainty (titrant concentration errors) into the resulting thermodynamic parameters.

Keywords: isothermal titration calorimetry; ITC; propagation of error; entropy-enthalpy compensation

Towards Automated Benchmarking of Atomistic Forcefields: Neat Liquid Densities and Static Dielectric Constants from the ThermoML Data Archive

Kyle A. Beauchamp, Julie M. Behr, Ariën S. Rustenburg, Christopher I. Bayly, Kenneth Kroenlein, and John D. Chodera.
J. Phys. Chem. B 119:12912, 2015. [DOI] [PDF] // code: [GitHub] // preprint: [arXiv

Progress in forcefield validation and parameterization has been hindered by the availability of high-quality machine-readable physical property data for small organic molecules. We show how the NIST ThermoML dataset provides a solution to this problem, and demonstrate its utility in benchmarking the GAFF/AM1-BCC small molecule forcefield on neat liquid densities and static dielectric constants to uncover problems in the representation of low-dielectric environments.

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.

Time step rescaling recovers continuous-time dynamical properties for discrete-time Langevin integration of nonequilibrium systems

David A. Sivak, John D. Chodera, and Gavin E. Crooks.
J. Phys. Chem. B, 118:6466-6474, 2014. William C. Swope Festschrift issue. [DOI] [PDF]

We derive a simple, easy-to-implement Langevin integrator that has universally useful properties in molecular simulations.

Keywords: velocity Verlet with velocity randomization; VVVR; nonequilibrium integration

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.