Biomedical subjects

A C Good

Publications and source records attributed to A C Good.

11 recordsLinked to original sources

PubMed2001

3-D pharmacophores in drug discovery.

In this chapter we review the use of 3-D pharmacophores in drug discovery. Recent advances are highlighted, including the application of pharmacophore descriptors generated both from ligands and protein binding sites. The application of 3-D pharmacophore fingerprints as molecular descriptors for similarity and diversity applications such as virtual screening, library design and QSAR is discussed. In addition, we highlight the quantification of structure-based diversity using site-derived fingerprints, and review virtual screening methods using both single refined hypotheses and the fingerprints of multiple potential hypotheses. Further, we discuss methods that take protein flexibility and molecular shape-into account. Each of the above techniques are reviewed with particular reference to the recent advances, advantages and challenges of each methodology.

Animals↗

PubMed1997

New methodology for profiling combinatorial libraries and screening sets: cleaning up the design process with HARPick.

Combinatorial chemistry is a tool of increasing importance in the field of ligand design, as it can yield huge increases in the number of compounds available for screening. Unfortunately, it is often the case that the number of molecules which could theoretically be constructed greatly exceeds potential synthesis and screening capacity. For this new technology to be fully exploited, it will become vital to design libraries with reference to the properties of compounds already in existence, if the added value of each new molecular collection is truly to be maximized. Similarly, if we are to take full advantage of the potential of combinatorial chemistry in lead optimization, it is important that our library design paradigms are flexible, with diversity scoring functions that can be modified to suit particular projects. Here these challenges are addressed through the introduction of a novel computer-aided library design tool known as HARPick (heuristic algorithm for reagent picking). The program is accessible to the bench chemist, and incorporates several significant advances over currently available approaches. These include product-based diversity calculations that can be constrained at the reagent level; diversity measures constructed from multiple descriptors; improved pharmacophore key information and full pharmacophore profiling of entire molecular databases. The potential of these improvements to aid in diversity profiling is illustrated through comparison with established methodology, and possible further enhancements are discussed.

Algorithms↗

PubMed1996

Engineering human immunodeficiency virus 1 protease heterodimers as macromolecular inhibitors of viral maturation.

Dimerization of human immunodeficiency virus type 1 protease (HIV-1 PR) monomers is an essential prerequisite for viral proteolytic activity and the subsequent generation of infectious virus particles. Disruption of the dimer interface inhibits this activity as does formation of heterodimers between wild-type and defective monomers. A structure-based approach was used to identify amino acid substitutions at the dimer interface of HIV-1 PR that facilitate preferential association of heterodimers and inhibit self-association of the defective monomers. Expression of the designed PR monomers inhibits activity of wild-type HIV-1 PR and viral infectivity when assayed in an ex vivo model system. These results show that it is possible to design PR monomers as macromolecular inhibitors that may provide an alternative to small molecule inhibitors for the treatment of HIV infection.

Amino Acid Sequence↗

PubMed1995

New molecular shape descriptors: application in database screening.

Geometric descriptors are becoming popular tools for encoding molecular shape, for use in database screening and clustering calculations. They provide condensed representations of complex objects and, as a consequence, can usually be compared quite rapidly. Here we present a number of new descriptors and methods for the quantification of molecular shape similarity. The techniques are tested using two different biological systems, with particular emphasis on their potential utility as methods for prescreening shape-based database searches. Results are compared with data sets produced using the DOCK program. We find that such similarity evaluations are useful for finding molecules with complementary shape, and that they contain an enriched number of potential DOCK hits when compared to the original databases. Significant limitations in the utility of such DOCK prescreens are discussed, and potential solutions are considered.

Binding Sites↗

PubMed1995

Investigating the extension of pairwise distance pharmacophore measures to triplet-based descriptors.

Distances between key functional groups have been used for some time as molecular descriptors in 3D database screening and clustering calculations. More recently, a number of groups have explored triplets of molecular centers to describe key ligand features in terms of the properties of triangles. Three-body distances are attractive, since they retain more information than pairwise representations. In most applications, the triangular descriptors have been used to detail molecular shape, using all the constituent atoms or molecular surface points as descriptor centers. As a consequence, the database keying times were such that only single conformers could be considered during molecular descriptor calculations. In this paper we reduce the points used in the molecular description down to the key functional centers, as applied in 3D pharmacophore database searches. Molecular triplets can then be calculated which describe the relative dispositions of differing functional groups, made up from multiple molecular conformations of a given molecule. The new triplet descriptors are compared with classical pairwise distance measures using a variety of pharmacophores, and their potential in database screening, clustering and pharmacophore identification is discussed.

Databases, Factual↗

PubMed1993

QSAR's from similarity matrices. Technique validation and application in the comparison of different similarity evaluation methods.

It has recently been shown that good quantitative structure-activity relationships can be obtained through statistical analysis of molecular similarity matrices. Here we extend the technique to seven additional molecular series, previously studied using Comparative Molecular Field Analysis (CoMFA) methodology. The results are used to confirm technique applicability across a wider range of QSAR problems and to compare quantitatively the ability of various similarity indices to describe biological systems. The relative merits of this technique in comparison to CoMFA are discussed.

Carbolines↗

PubMed1993

Structure-activity relationships from molecular similarity matrices.

An alternative method for determining structure-activity correlations is presented. Ligand molecules are described using data matrices derived from the results of N by N (each molecule compared to every other) molecular similarity calculations. The matrices were analyzed using a neural network pattern recognition technique and partial least squares statistics, with the results obtained compared to those achieved using comparative molecular field analysis (CoMFA). The molecular series used in the study comprised 31 steroids. The resultant pattern recognition analysis showed clustering of compounds with high, intermediate, and low affinity into separate regions of the neuron output plots. The cross-validated correlation coefficients obtained from statistical analyses of the matrices against steroid binding data compared well with those achieved using CoMFA. These results show that data matrices derived from molecular similarity calculations can provide the basis for rapid elucidation of both qualitative and quantitative structure-activity relationships.

Computer Simulation↗

PubMed1992

Similarity screening of molecular data sets.

Three-dimensional (3D)-database searches are now being widely applied to determine potential new active molecules. Many structural data sets obtained as a result of these searches are still large in size. In this paper we apply molecular similarity calculations as a rapid method to screen two such data sets. In the first investigation, synthetic candidates, produced as a result of a tendamistat beta-turn mimic search, were tested for their ability to imitate the beta-turn backbone. In the second study, structures extracted through a histamine pharmacophore query search were examined on the basis of their electronic similarity to histamine. Molecular similarity is shown to provide a rapid means of gaining insight into the composition of molecular data sets, with possible implications for future full 3D-database searches.

Databases, Factual↗

PubMed1992

The calculation of molecular similarity: alternative formulas, data manipulation and graphical display.

The use of electrostatic potential comparisons between molecules for the elucidation of structure activity relationships is now a well-established modeling technique. The Carbo and Hodgkin similarity indices are used extensively to make quantitative comparisons of this nature; yet their roots are found in the overlap of electron density distribution, with both formulas utilizing a product-based numerator. Two new similarity indices are suggested that calculate the electrostatic potential similarity using a difference-based numerator. The form of the new indices allows the creation of additional software functions that enhance the flexibility of similarity calculations and permit the creation of similarity maps. The general properties of these software functions and all indices are discussed and applied to a series of dopamine D2 receptor agonists.

Computer Simulation↗

PubMedDate not supplied

Molecular docking towards drug discovery.

Fueled by advances in molecular structure determination, tools for structure-based drug design are proliferating rapidly. Lead discovery through searching of ligand databases with molecular docking techniques represents an attractive alternative to high-throughout random screening. The size of commercial databases imposes severe computational constraints on molecular docking, compromising the level of calculational detail permitted for each putative ligand. We describe alternative philosophies for docking which effectively address this challenge. With respect to the dynamic aspects of molecular recognition, these strategies lie along a spectrum of models bounded by the Lock-and-Key and Induced-Fit theories for ligand binding. We explore the potential of a rigid model in exploiting species specificity and of a tolerant model in predicting absolute ligand binding affinity. Current molecular docking methods are limited primarily by their ability to rank docked complexes; we therefore place particular emphasis on this aspect of the problem throughout our validation of docking strategies.

Animals↗

PubMedDate not supplied

Where are the GaPs? A rational approach to monomer acquisition and selection.

Gridding and partitioning (GaP) is a computational method for the classification and selection of monomers for combinatorial libraries. The molecules are described in terms of the pharmacophoric groups they contain and where those pharmacophoric groups can be located in three-dimensional space. The approach involves a detailed conformational analysis of each molecule. This conformational analysis is done within a common coordinate frame, thus enabling the monomers to be compared. The use of a partitioned space is central to this particular application as it facilitates the identification of regions of space which are not well represented by existing compounds. Several ways to extend the use of partitioned pharmacophore spaces are described. Applications of the approach in monomer acquisition and in library design are outlined.

Algorithms↗