Identification Of Novel Lead Compounds Research Articles

Discovery of 2-Aminothiazoles as Potent Antiprion Compounds

Prion diseases are fatal, untreatable neurodegenerative diseases caused by the accumulation of the misfolded, infectious isoform of the prion protein (PrP), termed PrP(Sc). In an effort to identify novel inhibitors of prion formation, we utilized a high-throughput enzyme-linked immunosorbent assay (ELISA) to evaluate PrP(Sc) reduction in prion-infected neuroblastoma cell lines (ScN2a). We screened a library of approximately 10,000 diverse small molecules in 96-well format and identified 121 compounds that reduced PrP(Sc) levels at a concentration of 5 microM. Four chemical scaffolds were identified as potential candidates for chemical optimization based on the presence of preliminary structure-activity relationships (SAR) derived from the primary screening data. A follow-up analysis of a group of commercially available 2-aminothiazoles showed this class as generally active in ScN2a cells. Our results establish 2-aminothiazoles as promising candidates for efficacy studies of animals and validate our drug discovery platform as a viable strategy for the identification of novel lead compounds with antiprion properties.

Novel Approach for Efficient Pharmacophore-Based Virtual Screening: Method and Applications

Virtual screening is emerging as a productive and cost-effective technology in rational drug design for the identification of novel lead compounds. An important model for virtual screening is the pharmacophore. Pharmacophore is the spatial configuration of essential features that enable a ligand molecule to interact with a specific target receptor. In the absence of a known receptor structure, a pharmacophore can be identified from a set of ligands that have been observed to interact with the target receptor. Here, we present a novel computational method for pharmacophore detection and virtual screening. The pharmacophore detection module is able to (i) align multiple flexible ligands in a deterministic manner without exhaustive enumeration of the conformational space, (ii) detect subsets of input ligands that may bind to different binding sites or have different binding modes, (iii) address cases where the input ligands have different affinities by defining weighted pharmacophores based on the number of ligands that share them, and (iv) automatically select the most appropriate pharmacophore candidates for virtual screening. The algorithm is highly efficient, allowing a fast exploration of the chemical space by virtual screening of huge compound databases. The performance of PharmaGist was successfully evaluated on a commonly used data set of G-Protein Coupled Receptor alpha1A. Additionally, a large-scale evaluation using the DUD (directory of useful decoys) data set was performed. DUD contains 2950 active ligands for 40 different receptors, with 36 decoy compounds for each active ligand. PharmaGist enrichment rates are comparable with other state-of-the-art tools for virtual screening.

Fragment Shuffling: An Automated Workflow for Three-Dimensional Fragment-Based Ligand Design

Fragment-based approaches display a promising alternative in lead discovery. Herein, we present the automated fragment shuffling workflow for the identification of novel lead compounds combining central elements from fragment-based lead identification and structure-based de novo design. Our method is based on sets of aligned 3D ligand structures binding to the same target or target family. The implementation comprises three different ligand fragmentation methods, a scoring scheme assigning individual scores to each fragment, and the incremental construction of novel ligands based on a greedy search algorithm guided by the calculated fragment scores. The validation of our 3D ligand design workflow is presented on the basis of two pharmaceutically relevant drug targets. A retrospective study based on a selected protein kinase data set revealed that the fragment shuffling approach realizes extended results compared to the well-known BREED technique. Furthermore, we applied our approach in a prospective study for the design of novel non-peptidic thrombin inhibitors. The designed ligand structures in both studies demonstrate the potential of the fragment shuffling workflow.

Molecular Modeling of Human Pentameric α7 Neuronal Nicotinic Acetylcholine Receptor and Its Interaction with its Agonist and Competitive Antagonist

The nicotinic Acetylcholine Receptor (nAChR) is the major class of neurotransmitter receptors that is involved in many neurodegenerative conditions such as schizophrenia, Alzheimer's and Parkinson's diseases. The N-terminal region or Ligand Binding Domain (LBD) of nAChR is located at pre- and post-synaptic nervous system, which mediates synaptic transmission. nAChR acts as the drug target for agonist and competitive antagonist molecules that modulate signal transmission at the nerve terminals. Based on Acetylcholine Binding Protein (AChBP) from Lymnea stagnalis as the structural template, the homology modeling approach was carried out to build three dimensional model of the N-terminal region of human α7nAChR. This theoretical model is an assembly of five α7 subunits with 5 fold axis symmetry, constituting a channel, with the binding pocket present at the interface region of the subunits. α-neurotoxin is a potent nAChR competitive antagonist that readily blocks the channel resulting in paralysis. The molecular interaction of α-Bungarotoxin, a long chain α-neurotoxin from (Bungarus multicinctus) and human α7nAChR was studied. Agonists such as acetylcholine, nicotine, which are used in a diverse array of biological activities, such as enhancements of cognitive performances, were also docked with the theoretical model of human α7nAChR. These docked complexes were analyzed further for identifying the crucial residues involved in interaction. These results provide the details of interaction of agonists and competitive antagonists with three dimensional model of the N-terminal region of human α7nAChR and thereby point to the design of novel lead compounds.

Discovery and Structure–Activity Relationship Studies of a Unique Class of HIV‐1 Integrase Inhibitors

HIV-1 integrase (IN) is an essential enzyme for viral replication and a validated target for the development of drugs against AIDS. Currently there are no approved drugs that target IN. However, new IN inhibitors are under clinical investigation. As more IN inhibitors enter human drug trials, there is a growing need for the design of novel lead compounds with diverse structural scaffolds and promising pharmacokinetic properties to counteract the difficulties observed with first-generation IN inhibitors. We have identified a novel class of IN inhibitors through the systematic exploration of structure-activity relationships in a series of linomide analogues. The predicted bound conformation of the most active analogues inside the IN active site also supports the observed structure-activity correlation in this new compound class.

Efficient method for high-throughput virtual screening based on flexible docking: discovery of novel acetylcholinesterase inhibitors.

A method of easily finding ligands, with a variety of core structures, for a given target macromolecule would greatly contribute to the rapid identification of novel lead compounds for drug development. We have developed an efficient method for discovering ligand candidates from a number of flexible compounds included in databases, when the three-dimensional (3D) structure of the drug target is available. The method, named ADAM&EVE, makes use of our automated docking method ADAM, which has already been reported. Like ADAM, ADAM&EVE takes account of the flexibility of each molecule in databases, by exploring the conformational space fully and continuously. Database screening has been made much faster than with ADAM through the tuning of parameters, so that computational screening of several hundred thousand compounds is possible in a practical time. Promising ligand candidates can be selected according to various criteria based on the docking results and characteristics of compounds. Furthermore, we have developed a new tool, EVE-MAKE, for automatically preparing the additional compound data necessary for flexible docking calculation, prior to 3D database screening. Among several successful cases of lead discovery by ADAM&EVE, the finding of novel acetylcholinesterase (AChE) inhibitors is presented here. We performed a virtual screening of about 160 000 commercially available compounds against the X-ray crystallographic structure of AChE. Among 114 compounds that could be purchased and assayed, 35 molecules with various core structures showed inhibitory activities with IC(50) values less than 100 microM. Thirteen compounds had IC(50) values between 0.5 and 10 microM, and almost all their core structures are very different from those of known inhibitors. The results demonstrate the effectiveness and validity of the ADAM&EVE approach and provide a starting point for development of novel drugs to treat Alzheimer's disease.

Potential for antiviral treatment of severe acute respiratory syndrome

Severe acute respiratory syndrome is a new, sometimes lethal disease of humans that is caused by a novel coronavirus. To date there have been over 750 related deaths and there is clearly an urgent need to develop specific antiviral drugs to combat this disease. In this review, the authors shall focus on the molecular biology of the coronavirus and suggest how this information can be used to identify possible targets for antiviral drugs. Within a remarkably short period of time, the severe acute respiratory syndrome coronavirus has been isolated, its genome has been sequenced and the structure of at least one key viral enzyme has been deduced. In addition, bioinformatic analysis has predicted a number of enzymatic activities associated with proteins of the viral replicase-transcriptase complex. In some cases, these functions have been confirmed by biochemical analysis. Thus, there has been significant progress in the rational approach to anti-severe acute respiratory syndrome coronavirus drug design. This approach, combined with the random screening of licensed compounds or existing compound libraries, should result in the identification of novel lead compounds and the expeditious development of antiviral drugs. Although the initial severe acute respiratory syndrome epidemic has been controlled by conventional measures, the animal reservoir for the coronavirus progenitor has not been identified. It is therefore likely that the virus will be reintroduced into the human population in the future. When this happens, the most economical and effective way to contain the virus will be the therapeutic use of antiviral drugs.

Development of test systems for the discovery of selective human aldosterone synthase (CYP11B2) and 11β-hydroxylase (CYP11B1) inhibitors.: Discovery of a new lead compound for the therapy of congestive heart failure, myocardial fibrosis and hypertension

Two key players in adrenal steroid hormone biosynthesis are the human mitochondrial cytochrome P450 enzymes CYP11B1 and CYP11B2 that catalyze the final steps in the biosynthesis of cortisol and aldosterone, respectively. Overproduction of both hormones contributes to a number of severe diseases, as illustrated by the association of elevated aldosterone levels with hypertension and higher mortality in congestive heart failure, and by Cushing’s syndrome as the clinical correlate of chronic hypercortisolism. Thus, CYP11B1 and CYP11B2 comprise new targets for drug treatment and selective inhibitors of both enzymes are of high pharmacological interest. To facilitate the search for such compounds, we have established novel test procedures using recombinant fission yeast strains that stably express these enzymes. The aim of this study was to compare the inhibition profiles displayed by these enzymes in established mammalian cell culture test systems to those obtained with the new fission yeast assays, and to evaluate the usefulness of the Schizosaccharomyces pombe strains as screening systems for the identification of novel lead compounds. Using these test systems, we were able to identify a new and very selective CYP11B2 inhibitor (SIAS-1) that displayed no detectable interference with CYP11B1 activity.