Descriptor pharmacophore-based

PharmPrint descriptors substructure descriptors ( pharmacophore-based descriptors) phase capacity ratio = capacity factor —> chromatographic descriptors... 

Apart from pharmacophore-based approaches, a variety of methods were applied to decipher important ligand features of PXR activation. VolSurf descriptor-based partial least squares (PLS) regression-based models pointed toward amide responsive regions that implicated good acceptor abilities as key variables [33]. 

Fig. 4.1 Virtual screening tools can be categorized by the compound data to be screened (compound collection, combinatorial library, chemistry space) and the query type (structure-based, ligand-based, descriptor-based, pharmacophore-based). The output is always a list of compounds together with a score quantifying the fit to the query.

Quantitative Structure-Activity Relationship models are used increasingly in chemical data mining and combinatorial library design [5, 6]. For example, three-dimensional (3-D) stereoelectronic pharmacophore based on QSAR modeling was used recently to search the National Cancer Institute Repository of Small Molecules [7] to find new leads for inhibiting HIV type 1 reverse transcriptase at the nonnucleoside binding site [8]. A descriptor pharmacophore concept was introduced by us recently [9] on the basis of variable selection QSAR the descriptor pharmacophore is defined as a subset of... 

This surface area classification notion naturally can be extended to other properties. For example, a collection of pharmacophore-type VS A descriptors can be calculated by summing the V, contribution of each in a molecule of a specific type. For example, if the atom classes are donor, acceptor, polar, hydrophobe, anion, and cation, then six VSA descriptors can be calculated such that for any given molecule the sum of the six descriptors is the VSA of the entire molecule and each descriptor is the VSA of all atoms one of the six classes. Such descriptors can be used for rough pharmacophore-based similarity measures. 

Schuffenhauer et al. have used Similog keys in molecular complexity studies,1301 and other groups have used pharmacophore-based descriptors.1281... 

Often, all alignment-based methods and molecular field and potential calculations are classified as pharmacophore perception techniques. We will include most of these methods in this review however, when using the term pharmacophore model, we will be referring mainly to one specific type of perception, namely three-dimensional feature-based pharmacophore models represented by geometry or location constraints, qualitative or quantitative. An extrapolation of the pharmacophore approach to a set of multi-dimensional descriptors (pharmacophore fingerprints) has been developed mostly for library design and focusing purposes [3-8]. 

According to these definitions, each atom of a molecule is assigned to no, one or two PPPs. Since the descriptor is based on atom pairs, a pharmacophore matrix is built up. The entries py of the pharmacophore matrix P hold the PPP pair of vertex i and vertex j. If an atom is not a member of any PPP group, the row and column that correspond to the atom remain empty. A single atom can also belong to more than one PPP group. In this case, the entry py of the pharmacophore matrix P holds more than one PPP pair. All possible pairing combinations of the five PPPs result in 15 pairs (DD, DA, DP, DN, DL, AA, AP, AN, AL, PP, PN, PL, NN, NL, LL). 

The descriptors developed to characterize the substrate chemotypes are obtained from a mixture of molecular orbital calculations and GRID probe-pharmacophore recognition. Molecular orbital calculations to compute the substrate s electron density distribution are the first to be performed. All atom charges are determined using the AMI Hamiltonian. Then the computed charges are used to derive a 3D pharmacophore based on the molecular electrostatic potential (MEP) around the substrate molecules. 

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