A new method for induced fit docking (GENIUS) and its application to virtual screening of novel HCV NS3-4A protease inhibitors

Computational Approaches for the Discovery of Novel Hepatitis C Virus NS3/4A and NS5B Inhibitors

Nonstructural 5B (NS5B) polymerase and Nonstructural 3/4A (NS3/4A) protease have proven to be promising targets for the development of anti-HCV (Hepatitis C Virus) agents. The NS5B polymerase is of paramount importance in HCV viral replication; therefore, employing NS5B inhibitors was considered an effective way for the treatment of HCV. Identifying inhibitors against NS3/4A serine protease represents another attractive approach applied in anti-HCV drug discovery, which is evidenced by its crucial role of in the biogenesis of the viral replication activity. In this chapter, many different computational approaches including Quantitative Structure-Activity Relationship (QSAR) and virtual screening in anti-HCV drug discovery were considered and discussed in detail. Virtual Screening (VS) techniques, including ligand-based and structure-based, and QSAR have been utilized for the discovery of NS5B inhibitors. Moreover, using various in silico protocols and workflows, a number of studies have been conducted with an aim of identifying potential NS3/4A blockage agents.

4,5-Disubstituted 6-Aryloxy-1,3-dihydrobenzo[c][1,2]oxaboroles Are Broad-Spectrum Serine β-Lactamase Inhibitors

Bacterially expressed β-lactamases are rapidly eroding the clinical utility of the important β-lactam class of antibacterials, significantly impairing our ability to fight serious bacterial infections. This paper describes a study of oxaborole-derived β-lactamase inhibitors in which crystal structures and computational modeling aided in the rational design of analogues with improved spectrum of activity against class A, C, and D enzymes. Crystal structures of two of these inhibitors covalently bound to two different serine β-lactamases, class C Pseudomonas aeruginosa AmpC and class D OXA-10, are described herein. Improved physicochemical properties as well as increased activity against an array of β-lactamases resulted in substantial restoration of susceptibility to ceftazidime in Escherichia coli and Klebsiella pneumoniae.

Biological and medicinal significance of benzofuran

This article emphasizes on the importance of benzofuran as a biologically relevant heterocycle. It covers most of the physiologically as well as medicinally important compounds containing benzofuran rings. This article also covers clinically approved drugs containing benzofuran scaffold.

Receptor-ligand molecular docking

Docking methodology aims to predict the experimental binding modes and affinities of small molecules within the binding site of particular receptor targets and is currently used as a standard computational tool in drug design for lead compound optimisation and in virtual screening studies to find novel biologically active molecules. The basic tools of a docking methodology include a search algorithm and an energy scoring function for generating and evaluating ligand poses. In this review, we present the search algorithms and scoring functions most commonly used in current molecular docking methods that focus on protein-ligand applications. We summarise the main topics and recent computational and methodological advances in protein-ligand docking. Protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction are important and interconnected challenges to be overcome by further methodological developments in the docking field.

Identification of novel small molecules as inhibitors of hepatitis C virus by structure-based virtual screening

Hepatitis C virus (HCV) NS3/NS4A serine protease is essential for viral replication, which is regarded as a promising drug target for developing direct-acting anti-HCV agents. In this study, sixteen novel compounds with cell-based HCV replicon activity ranging from 3.0 to 28.2 μM (IC₅₀) were successfully identified by means of structure-based virtual screening. Compound 5 and compound 11, with an IC₅₀ of 3.0 μM and 5.1 μM, respectively, are the two most potent molecules with low cytotoxicity.

In silico virtual screening approaches for anti-viral drug discovery

Despite the considerable advances in medical and pharmaceutical research during the past years, diseases caused by viruses have remained a major burden to public health. Virtual in silico screening has repeatedly proven to be useful to meet the special challenges of antiviral drug discovery. Large virtual compound libraries are filtered by different computational screening methods such as docking, ligand-based similarity searches or pharmacophore-based screening, reducing the number of candidate molecules to a smaller set of promising candidates that are then tested biologically. This rational approach makes the drug discovery process more goal-oriented and saves resources in terms of time and money. In this review we discuss how different virtual screening techniques can be applied to antiviral drug discovery, present recent success stories in this field and finally address the main differences between the methods.: