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Compound Library (compound + library)

Distribution by Scientific Domains

Chemistry	100%

Selected Abstracts

Enhancing molecular discovery using descriptor-free rearrangement clustering techniques for sparse data sets

AICHE JOURNAL, Issue 2 2010
Peter A. DiMaggio Jr.
Abstract This article presents a descriptor-free method for estimating library compounds with desired properties from synthesizing and assaying minimal library space. The method works by identifying the optimal substituent ordering (i.e., the optimal encoding integer assignment to each functional group on every substituent site of molecular scaffold) based on a global pairwise difference metric intended to capture smoothness of the compound library. The reordering can be accomplished via a (i) mixed-integer linear programming (MILP) model, (ii) genetic algorithm based approach, or (iii) heuristic approach. We present performance comparisons between these techniques as well as an independent analysis of characteristics of the MILP model. Two sparsely sampled data matrices provided by Pfizer are analyzed to validate the proposed approach and we show that the rearrangement of these matrices leads to regular property landscapes which enable reliable property estimation/interpolation over the full library space. An iterative strategy for compound synthesis is also introduced that utilizes the results of the reordered data to direct the synthesis toward desirable compounds. We demonstrate in a simulated experiment using held out subsets of the data that the proposed iterative technique is effective in identifying compounds with desired physical properties. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source]

Competition STD NMR for the detection of high-affinity ligands and NMR-based screening

MAGNETIC RESONANCE IN CHEMISTRY, Issue 6 2004
Yu-Sen Wang
Abstract The reported competition STD NMR method combines saturation transfer difference (STD) NMR with competition binding experiments to allow the detection of high-affinity ligands that undergo slow chemical exchange on the NMR time-scale. With this technique, the presence of a competing high-affinity ligand in the compound mixture can be detected by the disappearance or reduction of the STD signals of a low-affinity indicator ligand. This is demonstrated on a BACE1 (,-site amyloid precursor protein cleaving enzyme 1) protein,inhibitor system. This method can also be used to derive an approximate value, or a lower limit, for the dissociation constant of the potential ligand based on the reduction of the signal intensity of the STD indicator, which is illustrated on an HSA (human serum albumin) model system. This leads to important applications of the competition STD NMR method for lead discovery: it can be used (i) for compound library screening against a broad range of drug targets to identify both high- and low-affinity ligands and (ii) to rank order analogs rapidly and derive structure,activity relationships, which are used to optimize these NMR hits into viable drug leads. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Prospective Validation of a Comprehensive In silico hERG Model and its Applications to Commercial Compound and Drug Databases

CHEMMEDCHEM, Issue 5 2010
Munikumar
Abstract Ligand-based in silico hERG models were generated for 2,644 compounds using linear discriminant analysis (LDA) and support vector machines (SVM). As a result, the dataset used for the model generation is the largest publicly available (see Supporting Information). Extended connectivity fingerprints (ECFPs) and functional class fingerprints (FCFPs) were used to describe chemical space. All models showed area under curve (AUC) values ranging from 0.89 to 0.94 in a fivefold cross-validation, indicating high model consistency. Models correctly predicted 80,% of an additional, external test set; Y-scrambling was also performed to rule out chance correlation. Additionally models based on patch clamp data and radioligand binding data were generated separately to analyze their predictive ability when compared to combined models. To experimentally validate the models, 50 of the predicted hERG blockers from the Chembridge database and ten of the predicted non-hERG blockers from an in-house compound library were selected for biological evaluation. Out of those 50 predicted hERG blockers, tested at a concentration of 10,,M, 18 compounds showed more than 50,% displacement of [3H]astemizole binding to cell membranes expressing the hERG channel. Ki values of four of the selected binders were determined to be in the micromolar and high nanomolar range (Ki (VH01)=2.0,,M, Ki (VH06)=0.15,,M, Ki (VH19)=1.1,,M and Ki (VH47)=18 ,M). Of these four compounds, VH01 and VH47 showed also a second, even higher affinity binding site with Ki values of 7.4,nM and 36,nM, respectively. In the case of non-hERG blockers, all ten compounds tested were found to be inactive, showing less than 50,% displacement of [3H]astemizole binding at 10,,M. These experimentally validated models were then used to virtually screen commercial compound databases to evaluate whether they contain hERG blockers. 109,784 (23,%) of Chembridge, 133,175 (38,%) of Chemdiv, 111,737 (31,%) of Asinex and 11,116 (18,%) of the Maybridge database were predicted to be hERG blockers by at least two of the models, a prediction which could, for example, be used as a pre-filtering tool for compounds with potential hERG liabilities. [source]

Identification, SAR Studies, and X-ray Co-crystallographic Analysis of a Novel Furanopyrimidine Aurora Kinase,A Inhibitor

CHEMMEDCHEM, Issue 2 2010
Mohane Selvaraj Coumar Dr.
Abstract Herein we reveal a simple method for the identification of novel Aurora kinase,A inhibitors through substructure searching of an in-house compound library to select compounds for testing. A hydrazone fragment conferring Aurora kinase activity and heterocyclic rings most frequently reported in kinase inhibitors were used as substructure queries to filter the in-house compound library collection prior to testing. Five new series of Aurora kinase inhibitors were identified through this strategy, with IC50 values ranging from ,300,nM to ,15,,M, by testing only 133 compounds from a database of ,125,000 compounds. Structure,activity relationship studies and X-ray co-crystallographic analysis of the most potent compound, a furanopyrimidine derivative with an IC50 value of 309,nM toward Aurora kinase,A, were carried out. The knowledge gained through these studies could help in the future design of potent Aurora kinase inhibitors. [source]