We introduce PHASE, a highly flexible system for common pharmacophore identification and assessment, 3D QSAR model development, and 3D database creation and searching. The primary workflows and tasks supported by PHASE are described, and details of the underlying scientific methodologies are provided. Using results from previously published investigations, PHASE is compared directly to other ligand-based software for its ability to identify target pharmacophores, rationalize structure-activity data, and predict activities of external compounds.

Pharmacophore modeling and 3D database searching are now recognized as integral components of lead discovery and lead optimization, and the continuing need for improved pharmacophorebased tools has driven the development of PHASE. By employing a novel, tree-based partitioning algorithm, PHASE exhaustively identifies spatial arrangements of functional groups that are common and essential to the biologic activity of a set of high affinity ligands. These pharmacophore hypotheses are validated in a number of ways, including their ability to: (i) rationalize the binding affinities of a training set of molecules of varying activity, (ii) successfully predict the affinities of a test set of molecules, and (iii) selectively retrieve known actives from a database of drug-like molecules. In addition, PHASE uniquely offers the ability to distinguish multiple binding modes through a bi-directional clustering approach applied to bit string representations of the ligand/hypothesis space.Pharmacophore Perception and 3D Quantitative Structure-activity relationship (QSAR) Development A collection of 49 glycoprotein (GP)IIb/IIIa antagonists (RGD mimics) of varying affinity and spanning two distinct chemotypes was used to define a 23-member training set and a 26-member test set for the generation and validation of 3D pharmacophore models that rationalize the associated fibrinogen receptor-binding data (1,2). Activity thresholds of 100 nM and 1 lM were used to identify nine actives and five inactives, respectively, within the training set. A maximum of 500 conformations were generated for each molecule using MacroModel torsional sampling with OPLS_2005 postprocessing (MacroModel 9.1 Reference Manual, Copyright ª 2005, Schrçdinger, L.L.C., New York, USA; http://www.schrodinger.com/). Pharmacophores with four features (including positive and negative ionic centers) common to all nine training set actives were identified then scored according to superposition of pharmacophore site points, alignment of vector characteristics, overlap of molecular

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A systematic virtual screening study on 11 pharmaceutically relevant targets has been conducted to investigate the interrelation between 8 two-dimensional (2D) fingerprinting methods, 13 atom-typing schemes, 13 bit scaling rules, and 12 similarity metrics using the new cheminformatics package Canvas. In total, 157 872 virtual screens were performed to assess the ability of each combination of parameters to identify actives in a database screen. In general, fingerprint methods, such as MOLPRINT2D, Radial, and Dendritic that encode information about local environment beyond simple linear paths outperformed other fingerprint methods. Atom-typing schemes with more specific information, such as Daylight, Mol2, and Carhart were generally superior to more generic atom-typing schemes. Enrichment factors across all targets were improved considerably with the best settings, although no single set of parameters performed optimally on all targets. The size of the addressable bit space for the fingerprints was also explored, and it was found to have a substantial impact on enrichments. Small bit spaces, such as 1024, resulted in many collisions and in a significant degradation in enrichments compared to larger bit spaces that avoid collisions.

Articles you may be interested inModel derived reduced density matrix restrictions for correlated fermions Details are provided for the implementation of a density matrix divide-and-conquer approximation into the framework of molecular orbital theory on nonperiodic systems. Originally developed for density functional theory, the divide-and-conquer procedure is one of the most promising in a growing list of techniques that exhibit linear scaling with respect to the number of basis functions in the system. The key to linear scaling is the division of the electronic structure calculation into a series of calculations over a set of small, overlapping subsystems. A semiempirical molecular orbital program designed around the divide-and-conquer approach has been written and a number of tests are carried out on polyglycine structures in order to evaluate its performance. For the systems examined, linear scaling is indeed observed, and the accuracy of the calculations can be controlled quite readily by the manner in which the system is divided into its component subsystems. For very large structures, the expense associated with the computation of two-center interactions will ultimately dominate the calculation, and quadratic scaling will become apparent. Techniques to linearize this aspect of the calculation are investigated and discussed.