Teague Sterling

TL;DR: The database contains over twenty million commercially available molecules in biologically relevant representations that may be downloaded in popular ready-to-dock formats and subsets and is freely available at zinc.docking.org.

TL;DR: A suite of ligand annotation, purchasability, target, and biology association tools, incorporated into ZINC and meant for investigators who are not computer specialists, offer new analysis tools that are easy for nonspecialists yet with few limitations for experts.

TL;DR: This study investigates an approach that uses lipophilicity, affinity, and similarity to known aggregators to advise on the likelihood that a candidate compound is an aggregator, and finds that 85% of the ligands acting in the 0.1 to 10 μM range in the medicinal chemistry literature are at least 85% similar to a known aggregator with these physical properties and may aggregate at relevant concentrations.

TL;DR: In this article, the authors explore sampling techniques that eliminate stochastic behavior in DOCK3.6, allowing a focused effort to optimize the code for efficiency, with a threefold increase in the speed of the program.

TL;DR: There appears to be no single pattern-matching "code" for identifying binding sites in unrelated proteins that bind identical ligands, though modeling suggests that there might be a limited number of different patterns that suffice to recognize different ligand functional groups.