One-pot multicomponent synthesis of N-sulfonyl amidines using magnetic separable nanoparticles-decorated N-heterocyclic carbene complex with copper

Research on Chemical Intermediates - Magnetic separable nanoparticles-decorated N-heterocyclic carbene complex with copper (MNP[1-Methyl benzimidazole]NHC@Cu) has been prepared by covalent grafting...     

Analysis of atypical orbits in one-dimensional piecewise-linear discontinuous maps

In this paper, boundary regions of 1-D linear piecewise-smooth discontinuous maps are examined analytically. It is shown that, under certain parameter conditions, maps exhibit atypical orbits like a continuum of periodic orbits and quasi-periodic orbits. Further, we have derived the conditions under which such phenomenon occurs. The paper also illustrates that there exists a specific parameter region where as the parameter is varied, there is a transition from stable to unstable periodic orbits. Moreover, we have derived an expression for the value of parameter at which this transition from stable to unstable periodic orbits occurs. Additionally, the dynamics concerning this value of parameter is also given.

     

Novel RIPK3 inhibitors discovered through a structure-based approach exert post-ischemic neuroprotection

Necroptosis or programmed necrosis is evident in various neurological disorders such as ischemic stroke. Receptor interacting serine/threonine protein kinase 3 (RIPK3) is one of the crucial targets of necroptosis and inhibition of this protein exerts neuroprotection. However, knowledge regarding the three-dimensional structure and binding site information of this protein is lacking. In the present study, structure-based in silico methods were implemented to identify the key amino acids in the RIPK3 binding site that might be responsible for ligand interactions. Further, novel RIPK3 inhibitors were identified through a dual ensemble screening strategy. Three inhibitors exhibited binding to RIPK3 in micromolar concentrations and exerted post-ischemic neuroprotection in vitro.     

A rational approach to selective pharmacophore designing: an innovative strategy for specific recognition of Gsk3β

We propose a novel cheminformatics approach that combines structure and ligand-based design to identify target-specific pharmacophores with well-defined exclusion ability. Our strategy includes the prediction of selective interactions, developing structure, and knowledge-based selective pharmacophore models, followed by database screening and molecular docking. This unique strategy was employed in addressing the off-target toxicity of Gsk3β and CDKs. The connections of Gsk3β in eukaryotic cell apoptosis and the extensive potency of Gsk3β inhibitors to block cell death have made it a potential drug-discovery target for many grievous human disorders. Gsk3β is phylogenetically very closely related to the CDKs, such as CDK1 and CDK2, which are suggested to be the off-target proteins of Gsk3β inhibitors. Here, we have employed novel computational approaches in designing the ligand candidates that are potentially inhibitory against Gsk3β, with well-defined the exclusion ability to CDKs. A structure-ligand -based selective pharmacophore was modeled. This model was used to retrieve molecules from the zinc database. The hits retrieved were further screened by molecular docking and protein-ligand interaction fingerprints. Based on these results, four molecules were predicted as selective Gsk3β antagonists. It is anticipated that this unique approach can be extended to investigate any protein-ligand specificity.     

Ensemble pharmacophore meets ensemble docking: a novel screening strategy for the identification of RIPK1 inhibitors

Programmed cell death has been a fascinating area of research since it throws new challenges and questions in spite of the tremendous ongoing research in this field. Recently, necroptosis, a programmed form of necrotic cell death, has been implicated in many diseases including neurological disorders. Receptor interacting serine/threonine protein kinase 1 (RIPK1) is an important regulatory protein involved in the necroptosis and inhibition of this protein is essential to stop necroptotic process and eventually cell death. Current structure-based virtual screening methods involve a wide range of strategies and recently, considering the multiple protein structures for pharmacophore extraction has been emphasized as a way to improve the outcome. However, using the pharmacophoric information completely during docking is very important. Further, in such methods, using the appropriate protein structures for docking is desirable. If not, potential compound hits, obtained through pharmacophore-based screening, may not have correct ranks and scores after docking. Therefore, a comprehensive integration of different ensemble methods is essential, which may provide better virtual screening results. In this study, dual ensemble screening, a novel computational strategy was used to identify diverse and potent inhibitors against RIPK1. All the pharmacophore features present in the binding site were captured using both the apo and holo protein structures and an ensemble pharmacophore was built by combining these features. This ensemble pharmacophore was employed in pharmacophore-based screening of ZINC database. The compound hits, thus obtained, were subjected to ensemble docking. The leads acquired through docking were further validated through feature evaluation and molecular dynamics simulation.     

Identification of novel potential HIF-prolyl hydroxylase inhibitors by in silico screening

Suppression of HIF-prolyl hydroxylase (PHD) activity by small-molecule inhibitors leads to the stabilization of hypoxia inducible factor and has been recognized as promising drug target for the treatment of ischemic diseases. In this study, pharmacophore-based virtual screening and molecular docking approaches were concurrently used with suitable modifications to identify target-specific PHD inhibitors with better absorption, distribution, metabolism, and excretion properties and to readily minimize false positives and false negatives. A customized method based on the active site information of the enzyme was used to generate a pharmacophore hypothesis (AAANR). The hypothesis was validated and utilized for chemical database screening and the retrieved hit compounds were subjected to molecular docking for further refinement. AAANR hypothesis comprised three H-bond acceptor, one negative ionizable group and one aromatic ring feature. The hypothesis was validated using decoy set with a goodness of fit score of 2 and was used as a 3D query for database screening. After manual selection, molecular docking and further refinement based on the molecular interactions of inhibitors with the essential amino acid residues, 18 hits with good absorption, distribution, metabolism, and excretion (ADME) properties were selected as excellent PHD inhibitors. The best pharmacophore hypothesis, AAANR, contains chemical features required for the effective inhibition of PHD. Using AAANR, we have identified 18 potential and diverse virtual leads, which can be readily evaluated for their potency as novel inhibitors of PHD. It can be concluded that the combination of pharmacophore, molecular docking, and manual interpretation approaches can be more successful than the traditional approach alone for discovering more effective inhibitors.