Assessment of Structural Basis for Thiazolopyridine Derivatives as DNA Gyrase-B Inhibitors.

Background: Tuberculosis (TB) is one of the leading causes of death in the post-COVID- 19 era. It has been observed that there is a devastating condition with a 25-30% increase in TB patients. DNA gyrase B isoform has proved its high potential to be a therapeutically effective target for developing newer and safer anti-TB agents.

Patent landscape for discovery of promising acyltransferase DGAT and MGAT inhibitors.

Introduction: DGAT and MGAT enzymes play an important role in triacylglycerol (TGA) biosynthesis. Overexpression of these enzymes may lead to accumulation of TGA in adipose tissues causing development of diseases such as obesity and diabetes. High triglyceride levels increase risk factors for atherosclerosis, and increase the risk of heart attack, stroke and other heart diseases.

3D-QSAR with R: A new 3D-QSAR methodology applied to a set of DGAT1 inhibitors [corrected].

The rapid advances in computational methods for the drug design have resulted in the accurate predictions of biological activities of ligands with or without the availability of enzyme structures. 3D-QSAR is one of the computational methods used for such purpose. Currently, freely available 3D-QSAR methods suffer the limitations like complex methodologies, difficulty in the analysis of results, applying the statistical methods and validations of models built.

Structural insights of dipeptidyl peptidase-IV inhibitors through molecular dynamics-guided receptor-dependent 4D-QSAR studies.

Dipeptidyl peptidase-IV (DPP-IV) inhibitors are promising antidiabetic agents. Currently, several DPP-IV inhibitors have been approved for therapeutic use in diabetes mellitus. Receptor-dependent 4D-QSAR is comparatively a new approach which uses molecular dynamics simulations to generate conformational ensemble profiles of compounds representing a dynamic state of compounds at a target's binding site.

Advances in studies on collagenase inhibitors.

Matrix metalloproteinases (MMPs) play an important role in many physiological and pathological processes. Development of MMP inhibitors, in particular collagenase inhibitors, for the treatment of arthritis has been more challenging, undoubtedly. Small-molecular-weight collagenase inhibitors may be classified into several different arbitrary structural classes, depending on the catalytic zinc-binding function as well as other structural elements of the inhibitors.

Development of highly predictive 3D-QSAR CoMSIA models for anthraquinone and acridone derivatives as telomerase inhibitors targeting G-quadruplex DNA telomere.

G-quadruplex structures of DNA represent a potentially useful target for anticancer drugs. Telomerase enzyme, involved in immortalization of cancer cells is inhibited by stabilization of G-quadruplex at the ends of chromosomes. Anthraquinone and acridone derivatives are promising G-quadruplex ligands as telomerase inhibitors.

Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors.

A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-alpha converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database.

Structural investigations of acridine derivatives by CoMFA and CoMSIA reveal novel insight into their structures toward DNA G-quadruplex mediated telomerase inhibition and offer a highly predictive 3D-model for substituted acridines.

Stabilization of G-quadruplex structures formed from telomeric DNA, by means of G-quadruplex selective ligands, is a means of inhibiting the telomerase enzyme. This makes G-quadruplex an emerging target for cancer therapy. The objective of the current 3D QSAR study is to uncover structural requirements for acridine derivatives, which would eventually assist and complement the rational drug-design attempts.

Development of predictive 3D-QSAR CoMFA and CoMSIA models for beta-aminohydroxamic acid-derived tumor necrosis factor-alpha converting enzyme inhibitors.

A three-dimensional quantitative structure-activity relationship study was performed on a series of beta-aminohydroxamic acid-derived tumor necrosis factor-alpha converting enzyme inhibitors employing comparative molecular field analysis and comparative molecular similarity indices analysis techniques to investigate the structural requirements for the inhibitors, and derive a predictive model that could be used for the design of novel tumor necrosis factor-alpha converting enzyme inhibitors. log P was used as an additional descriptor in the comparative molecular field analysis analysis to study the effects of lipophilic parameters on activity. Inclusion of log P did not improve the models significantly.