Strategies for small molecule library design.

Compilation of an appropriate set of compounds is essential for the success of a small molecule screen. When very little is known about the target and when no or few ligands have been identified, the screening file is often made as diverse as possible. When structural information on the target or target family is available or ligands of the target are known, it is more efficient to apply a ligand- or target-focused bias, so as to predominantly screen compounds that can be expected to modulate the target.

Optimization of highly selective 2,4-diaminopyrimidine-5-carboxamide inhibitors of Sky kinase.

Optimization of the ADME properties of a series of 2,4-diaminopyrimidine-5-carboxamide inhibitors of Sky kinase resulted in the identification of highly selective compounds with properties suitable for use as in vitro and in vivo tools to probe the effects of Sky inhibition.

Highly selective 2,4-diaminopyrimidine-5-carboxamide inhibitors of Sky kinase.

We report the SAR around a series of 2,4-diaminopyrimidine-5-carboxamide inhibitors of Sky kinase. 2-Aminophenethyl analogs demonstrate excellent potency but moderate kinase selectivity, while 2-aminobenzyl analogs that fill the Ala571 subpocket exhibit good inhibition activity and excellent kinase selectivity.

Novel and selective spiroindoline-based inhibitors of Sky kinase.

We report the discovery of a novel series of spiroindoline-based inhibitors of Sky kinase that bind in the ATP-binding site and exhibit high levels of kinome selectivity through filling the Ala571-subpocket. These inhibitors exhibit moderate oral bioavailability in the rat due to low absorption across the gut wall.

Simple idea to generate fragment and pharmacophore descriptors and their implications in chemical informatics.

Using a well-defined set of fragments/pharmacophores, a new methodology to calculate fragment/ pharmacophore descriptors for any molecule onto which at least one fragment/pharmacophore can be mapped is presented. To each fragment/pharmacophore present in a molecule, we attach a descriptor that is calculated by identifying the molecule's atoms onto which it maps and summing over its constituent atomic descriptors. The attached descriptors are named C-fragment/pharmacophore descriptors, and this methodology can be applied to any descriptors defined at the atomic level, such as the partition coefficient, molar refractivity, electrotopological state, etc.

Novel, customizable scoring functions, parameterized using N-PLS, for structure-based drug discovery.

The ability to accurately predict biological affinity on the basis of in silico docking to a protein target remains a challenging goal in the CADD arena. Typically, "standard" scoring functions have been employed that use the calculated docking result and a set of empirical parameters to calculate a predicted binding affinity. To improve on this, we are exploring novel strategies for rapidly developing and tuning "customized" scoring functions tailored to a specific need.

Inhibition of protein-protein interactions: the discovery of druglike beta-catenin inhibitors by combining virtual and biophysical screening.

The interaction between beta-catenin and Tcf family members is crucial for the Wnt signal transduction pathway, which is commonly mutated in cancer. This interaction extends over a very large surface area (4800 A(2)), and inhibiting such interactions using low molecular weight inhibitors is a challenge. However, protein surfaces frequently contain "hot spots," small patches that are the main mediators of binding affinity.

Potent and selective Aurora inhibitors identified by the expansion of a novel scaffold for protein kinase inhibition.

Potent and selective Aurora kinase inhibitors were identified from the combinatorial expansion of the 1,4,5,6-tetrahydropyrrolo[3,4-c]pyrazole bi-cycle, a novel and versatile scaffold designed to target the ATP pocket of protein kinases. The most potent compound reported in this study had an IC(50) of 0.027 microM in the enzymatic assay for Aur-A inhibition and IC(50)s between 0.

Linear and nonlinear methods in modeling the aqueous solubility of organic compounds.

Solubility data for 930 diverse compounds have been analyzed using linear Partial Least Square (PLS) and nonlinear PLS methods, Continuum Regression (CR), and Neural Networks (NN). 1D and 2D descriptors from MOE package in combination with E-state or ISIS keys have been used. The best model was obtained using linear PLS for a combination between 22 MOE descriptors and 65 ISIS keys.

Novel scoring functions comprising QXP, SASA, and protein side-chain entropy terms.

Novel scoring functions that predict the affinity of a ligand for its receptor have been developed. They were built with several statistical tools (partial least squares, genetic algorithms, neural networks) and trained on a data set of 100 crystal structures of receptor-ligand complexes, with affinities spanning 10 log units. The new scoring functions contain both descriptors generated by the QXP docking program and new descriptors that were developed in-house.