Computational Investigation Identified Potential Chemical Scaffolds for Heparanase as Anticancer Therapeutics

Heparanase (Hpse) is an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains. Its upregulated expression is implicated in tumor growth, metastasis and angiogenesis, thus making it an attractive target in cancer therapeutics. Currently, a few small molecule inhibitors have been reported to inhibit Hpse, with promising oral administration and pharmacokinetic (PK) properties. In the present study, a ligand-based pharmacophore model was generated from a dataset of well-known active small molecule Hpse inhibitors which were observed to display favorable PK properties. The compounds from the InterBioScreen database of natural (69,034) and synthetic (195,469) molecules were first filtered for their drug-likeness and the pharmacophore model was used to screen the drug-like database. The compounds acquired from screening were subjected to molecular docking with Heparanase, where two molecules used in pharmacophore generation were used as reference. From the docking analysis, 33 compounds displayed higher docking scores than the reference and favorable interactions with the catalytic residues. Complex interactions were further evaluated by molecular dynamics simulations to assess their stability over a period of 50 ns. Furthermore, the binding free energies of the 33 compounds revealed 2 natural and 2 synthetic compounds, with better binding affinities than reference molecules, and were, therefore, deemed as hits. The hit compounds presented from this in silico investigation could act as potent Heparanase inhibitors and further serve as lead scaffolds to develop compounds targeting Heparanase upregulation in cancer.

The life cycle and in silico elucidation of non-structural replicating proteins of HCV through a pharmacoinformatics approach

Background: Hepatitis C virus (HCV) is an enveloped and positive-stranded RNA virus that is a major causative agent of chronic liver diseases worldwide. HCV has become the main cause of liver transplantations and there is no effective drug for all hepatitis genotypes. Elucidation of life cycle and nonstructural proteins of HCV involved in viral replication are the attractive targets for the development of antiviral drugs. Methods: In this work, pharmacoinformatics approaches coupled with docking analyses were applied on HCV nonstructural proteins to identify the novel potential hits and HCV drugs. Molecular docking analyses were carried out on HCV approved drugs followed by the ligand-based pharmacophore generation to screen the antiviral libraries for novel potential hits. Results: Virtual screening technique has made known the top-ranked five novel compounds (ZINC00607900, ZINC03635748, ZINC03875543, ZINC04097464, and ZINC12503102) along with the least binding energy (-8.0 kcal/mol, -6.1 kcal/mol, -7.5 kcal/mol, -7.4 kcal/mol, and -7.3 kcal/mol respectively) and stability with non-structural proteins target. Conclusion: These promising hits exhibited better absorption and ADMET properties as compared to the selected drug molecules. These potential compounds extracted from in silico approach may be significant in drug design and development against Hepatitis and other liver diseases.

Pharmacoinformatics and Molecular Docking Studies Reveal Potential Novel Compounds Against Schizophrenia by Target SYN II

Background: Synapsin II regulates neurotransmitter release from mature nerve terminals and plays important role in the formation of new nerve terminals. The associations of SYN II are identified in various studies that are linked to the onset of Schizophrenia. Schizophrenia is characterized by abnormal behavior like obsession, dampening of emotions and auditory hallucination. Methods: The bioinformatics approaches were utilized for structural modeling and docking analyses of SYN II followed by pharmacophore generation to identify potent inhibitors. Results: The comparative modeling approach was employed to generate the 3D model having 82.404% quality factor calculated by Errat. Pharmacophore was constructed by utilizing merge molecular and chemical features of selected five FDA approved Schizophrenia drugs by LigandScout 4.1.5. Comparative docking analyses were performed by utilizing the selected drugs and top screened hits by GOLD and AutoDock Vina. Conclusion: It was proposed that Aripiprazole drug and scrutinized compounds have strong binding affinities among the other selected drugs. The reported compounds may be used for further analyses in the drug discovery processes, as they have shown good human intestinal absorption and are noncarcinogenic. The present study provides the structural insights which may be used for further understating of the Schizophrenia therapeutic purposes by targeting SYN II and other inhibitors haunting.