The SAMPL6 SAMPLing challenge: Assessing the reliability and efficiency of binding free energy calculations

Andrea Rizzi, Travis Jensen, David R. Slochower, Matteo Aldeghi, Vytautas Gapsys, Dimitris Ntekoumes, Stefano Bosisio, Michail Papadourakis, Niel M. Henriksen, Bert L. de Groot, Zoe Cournia, Alex Dickson, Julien Michel, Michael K. Gilson, Michael R. Shirts, David L. Mobley, and John D. Chodera
Preprint ahead of publication. [bioRxiv] [GitHub]

To assess the relative efficiencies of alchemical binding free energy calculations, the SAMPL6 SAMPLing challenge asked participants to submit predictions as a function of computer effort for the same force field and charge model. Surprisingly, we found that most molecular simulation codes cannot agree on the binding free energy was, even for the same force field.

A novel small-molecule pan-Id antagonist inhibits pathologic ocular neovascularization


Paulina M. Wojnarowicz, Raquel Lima e Silva, Masayuki Ohanka, Sang Bae Lee, Yvette Chin, Anita Kulukian, Sung-Hee Chang, Bina Desai, Marta Garcia Escolano, Riddhi Shah, Marta Garcia-Cao, Sijia Xu, Rashmi Thakar, Yehuda Goldgur, Meredith A. Miller, Ouathek Ouerfelli, Guangli Yang, Tsutomu Arakawa, Steven K. Albanese, William A. Garland, Glenn Stoller, Jaideep Chaudhary, Rajesh Soni, John Philip, Ronald C. Hendrickson, Antonio Iavarone, Andrew J. Dannenberg, John D. Chodera, Nikola Pavletich, Anna Lasorella, Peter A. Campochiaro, and Robert Benezra
Cell Reports 29:62, 2019 [DOI] [PDF]

We report the discovery and characterization of a small molecule, AGX51, with the surprising ability to inhibit the interaction of Id1 with E47, which leads to ubiquitin-mediated degradation of Ids.

Graph nets for partial charge prediction

Yuanqing Wang, Josh Fass, Chaya D. Stern, Kun Luo, and John D. Chodera.
Preprint ahead of publication.
[arXiv] [GitHub]

Graph convolutional and message-passing networks can be a powerful tool for predicting physical properties of small molecules when coupled to a simple physical model that encodes the relevant invariances. Here, we show the ability of graph nets to predict partial atomic charges for use in molecular dynamics simulations and physical docking.

Sharing data from molecular simulations

Abraham MJ, Apostolov R, Barnoud J, Bauer P, Blau C, Bonvin AMJJ, Chavent M, Chodera JD, Condic-Jurkic K, Delemotte L, Grubmüller H, Howard RJ, Lindahl E, Ollila S, Salent J, Smith D, Stansfeld PJ, Tiemann J, Trellet M, Woods C, and Zhmurov A.
Journal of Chemical Information and Modeling ASAP. [chemRxiv] [DOI] [PDF]

There is a dire need to establish standards for sharing data in the molecular sciences. Here, we review the findings of a workshop held in Stockholm in Nov 2018 to discuss this need.

Octanol-water partition coefficient measurements for the SAMPL6 Blind Prediction Challenge


Mehtap Işık, Dorothy Levorse, David L. Mobley, Timothy Rhodes, and John D. Chodera.
Preprint ahead of publication.
[bioRxiv] [data] [GitHub]

We describe the design and data collection (and associated challenges) for the SAMPL6 part II logP octanol-water blind prediction challenge, where the goal was to benchmark the accuracy of force fields for druglike molecules (here, molecules resembling kinase inhibitors).

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.

Overview of the SAMPL6 host-guest binding affinity prediction challenge

Andrea RizziSteven MurkliJohn N. McNeillWei YaoMatthew SullivanMichael K. Gilson, Michael W. Chiu, Lyle IsaacsBruce C. GibbDavid 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.