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.

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.