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Overview

One of the most powerful tools for designing drug molecules is an understanding of the target protein's binding site. Identifying key amino acids and understanding the electronic, steric, and solvation properties of the site enables the design of potent ligands. Of equal importance for the success of a drug discovery program is the evaluation of binding site druggability. Determining, a priori, if a particular binding site has the appropriate character to bind drug-like ligands saves research time and money.While there are a variety of experimental and computational techniques to identify and characterize binding sites, the focus of this chapter is on Binding Site Analysis (BSA) using virtual fragment simulations. The methodology of the technique is described, along with examples of successful application to drug discovery programs. BSA both indicates if a protein is a viable target for drug discovery and provides a roadmap for designing ligands. Using a computational fragment-based method is a effective means of understanding of a binding site.

01 Dec 2009·AIDS Research and TherapyQ4 · MEDICINE

Comparison of metal-dependent catalysis by HIV-1 and ASV integrase proteins using a new and rapid, moderate throughput assay for joining activity in solution

Q4 · MEDICINE

ArticleOA

Author: Andrake, Mark D ; Merkel, George ; Zhao, Xue Zhi ; Skalka, Anna Marie ; Burke, Terrence R ; Ramcharan, Joseph

AbstractBackgroundHIV-1 integrase (IN) is an attractive target for the development of drugs to treat AIDS, and inhibitors of this viral enzyme are already in the clinic. Nevertheless, there is a continuing need to devise new approaches to block the activity of this viral protein because of the emergence of resistant strains. To facilitate the biochemical analysis of wild-type IN and its derivatives, and to measure the potency of prospective inhibitory compounds, a rapid, moderate throughput solution assay was developed for IN-catalyzed joining of viral and target DNAs, based on the detection of a fluorescent tag.ResultsA detailed, step-by-step description of the new joining assay is provided. The reactions are run in solution, the products captured on streptavidin beads, and activity is measured by release of a fluorescent tag. The procedure can be scaled up for the analysis of numerous samples, and is substantially more rapid and sensitive than the standard radioactive gel methods. The new assay is validated and its utility demonstrated via a detailed comparison of the Mg++- and Mn++-dependent activities of the IN proteins from human immunodeficiency virus type 1 (HIV-1) and the avian sarcoma virus (ASV). The results confirm that ASV IN is considerably more active than HIV-1 IN, but with both enzymes the initial rates of joining, and the product yields, are higher in the presence of Mn++ than Mg++. Although the pH optima for these two enzymes are similar with Mn++, they differ significantly in the presence of Mg++, which is likely due to differences in the molecular environment of the binding region of this physiologically relevant divalent cation. This interpretation is strengthened by the observation that a compound that can inhibit HIV-1 IN in the presence of either metal cofactors is only effective against ASV in the presence of Mn++.ConclusionA simplified, assay for measuring the joining activity of retroviral IN in solution is described, which offers several advantages over previous methods and the standard radioactive gel analyses. Based on comparisons of signal to background ratios, the assay is 10–30 times more sensitive than gel analysis, allows more rapid and accurate biochemical analyses of IN catalytic activity, and moderate throughput screening of inhibitory compounds. The assay is validated, and its utility demonstrated in a comparison of the metal-dependent activities of HIV-1 and ASV IN proteins.

01 Jun 2009·Current Computer Aided-Drug Design

Computational Models for Central Nervous System Penetration

Author: Klon, Anthony E.

A review.As the population of the elderly increases, there is a growing need for drugs to treat a variety of neurol. diseases, such as Alzheimer's disease, Parkinson's disease, brain cancer, stroke, and infections in the central nervous system (CNS).Conversely, there is a need to identify brain penetration, and therefore potentially adverse events, from drugs acting on non-CNS targets.Late-stage clin. failures are costly in the drug discovery process, giving rise to the need for models to predict blood-brain barrier (BBB) penetration.In vivo and ex vivo models are expensive, time-consuming, and labor-intensive, giving rise to the development of in vitro and in silico models to aid in drug development early in the discovery process.Recent years have seen an increased emphasis on predictive computational models of CNS penetration.We review the progress in computational models of CNS penetration over the last five years.Computational models reported in the literature usually model the ratio of brain to blood levels for a mol.These models can be broken down into logBB models, which attempt to predict a discrete value for the logarithm of the brain:blood ratio, and binary classifiers, which classify mols. as either brain-penetrant or non-penetrant according to an arbitrary cutoff.We also discuss whether the brain:blood ratio is an appropriate metric to use in predicting CNS penetration and the need for alternative endpoints that measure the information medicinal chem. teams are actually interested in, such as the permeability-surface (PS) product and the fraction unbound (f_u) in the brain.

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Pipeline

Pipeline Snapshot as of 28 Nov 2024

The statistics for drugs in the Pipeline is the current organization and its subsidiaries are counted as organizations,Early Phase 1 is incorporated into Phase 1, Phase 1/2 is incorporated into phase 2, and phase 2/3 is incorporated into phase 3

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