Application of high-throughput screening techniques to drug discovery.
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Biological Assay↗
Biomedical subjects
D V Green
Publications and source records attributed to D V Green.
Biaryl acids: novel non-nucleoside inhibitors of HIV reverse transcriptase types 1 and 2.
A series of biaryl acids has been found to show micromolar inhibition of the HIV reverse transcriptase (RT) from types 1 and 2 with IC50S in the micromolar range. The series was discovered by consideration of the polymerase active site and sub-structure searching of the company compound collection. Synthesis of analogues to investigate the SAR is described. Two of these compounds have shown inhibition of HIV-2 RT only.
Anti-HIV Agents↗
Benzophenone derivatives: a novel series of potent and selective inhibitors of human immunodeficiency virus type 1 reverse transcriptase.
A series of benzophenone derivatives has been synthesized and evaluated as inhibitors of HIV-1 reverse transcriptase (RT) and the growth of HIV-1 in MT-4 cells. Through the use of the structure-activity relationships within this series of compounds and computational chemistry techniques, a binding conformation is proposed. The SAR also indicated that the major interactions of 1h with the RT enzyme are through hydrogen bonding of the amide and benzophenone carbonyls and pi-orbital interactions with the benzophenone nucleus and an aromatic function separated from the benzophenone by a suitable spacer group. The crystal structure of compound 1h has been determined. A number of compounds with potent inhibitory activity against HIV-1 RT and HIV in cellular assays at levels comparable with AZT and our efforts to identify a metabolically stable analogue are described.
Benzophenones↗
Synthesis and anti-HIV-1 activity of a series of imidazo[1,5-b]pyridazines.
A series of substituted imidazo[1,5-b]pyridazines have been prepared and tested for inhibitory activity against the reverse transcriptase of HIV-1 (RT) and their ability to inhibit the growth of infected MT-4 cells. Crystal data are reported on two compounds, 15c and 33. From the structure-activity relationships developed within this and other series, it is proposed that key features of the interaction with RT include hydrogen-bond acceptor and aromatic pi-orbital bonding with the imidazopyridazine nucleus and a benzoyl function separated from the heterocycle by a suitable spacer group. Exceptional activity against the reverse transcriptase of HIV-1 (IC50 = 0.65 nM) was obtained with a 2-imidazolyl-substituted derivative, 7-[2-(1H-imidazol-1- yl)-5-methylimidazo-[1,5-b]pyridazin-7-yl]-1-phenyl-1-heptanone (33) which is attributed to additional binding of the imidazole sp2 nitrogen atom. A number of the compounds in this series also inhibit the replication of HIV-1 in vitro in MT-4 and C8166 cells at levels observed with the nucleoside AZT.
Antiviral Agents↗
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↗
PLUMS: a program for the rapid optimization of focused libraries.
PLUMS is a new method to perform rational monomer selection for combinatorial chemistry libraries. The algorithm has been developed to optimize focused libraries with specific two-dimensional and/or three-dimensional properties. A preliminary step is the identification of those molecules in the initial virtual library which satisfy the imposed property constraints; we define these molecules as the virtual hits. From the virtual hits, PLUMS generates a starting library, which is the true combinatorial library that includes all the virtual hits. Monomers are then removed in an iterative fashion, thus reducing the size of the library. At each iteration, the worst monomer is removed. Each sublibrary is selected using a global scoring function, which balances effectiveness and efficiency. The iterative process continues until one is left with a library that consists entirely of virtual hits. The optimal library, which is the best compromise between effectiveness and efficiency, can then be selected according to the score. During the iterative process, equivalent solutions may well occur and are taken into account by the algorithm, according to a user-defined parameter. The number of monomers for each substitution site and the size of the library are parameters that can be either optimized or used to constrain the selection. The results obtained on two test libraries are presented. PLUMS was compared with genetic algorithms (GA) and monomer frequency analysis (MFA), which are widely used for monomer selection. For the two test libraries, PLUMS and GA gave equivalent results. MFA is the fastest method, but it can give misleading solutions. Possible advantages and disadvantages of the different methods are discussed.
Journal Article↗
Prediction of biological activity for high-throughput screening using binary kernel discrimination.
High-throughput screening has made a significant impact on drug discovery, but there is an acknowledged need for quantitative methods to analyze screening results and predict the activity of further compounds. In this paper we introduce one such method, binary kernel discrimination, and investigate its performance on two datasets; the first is a set of 1650 monoamine oxidase inhibitors, and the second a set of 101 437 compounds from an in-house enzyme assay. We compare the performance of binary kernel discrimination with a simple procedure which we call "merged similarity search", and also with a feedforward neural network. Binary kernel discrimination is shown to perform robustly with varying quantities of training data and also in the presence of noisy data. We conclude by highlighting the importance of the judicious use of general pattern recognition techniques for compound selection.
Algorithms↗
Implementation of a system for reagent selection and library enumeration, profiling, and design.
We describe an integrated suite of computational tools which are used to assist in the selection of compounds for biological assays and the design of combinatorial libraries. These functions are delivered in a platform-independent manner via a corporate intranet and are used by computational experts and nonexperts alike. While the system was primarily designed to be used prior to synthesis, it can also be used to provide structural information for library registration and for decoding beads in tagged libraries. We describe a simple statistical method for monomer selection and compare it to computationally more demanding approaches.
Combinatorial Chemistry Techniques↗