Gram-negative bacteria Yersinia secrete virulence factors that invade eukaryotic cells via type III secretion system. One particular virulence member, Yersinia outer protein E (YopE), targets Rho family of small GTPases by mimicking regulator GAP protein activity, and its secretion mainly induces cytoskeletal disruption and depolymerization of actin stress fibers within the host cell. In this w...

Protein ligand interaction fingerprints are a powerful approach for the analysis and assessment of docking poses to improve docking performance in virtual screening. In this study, a novel interaction fingerprint approach (PADIF, protein per atom score contributions derived interaction fingerprint) is presented which was specifically designed for utilising the GOLD scoring functions' atom contr...

Zinc-dependent histone deacetylase 8 removes the epsilon-acetyl groups present in the N-terminal lysine residues of histone proteins, thereby restricting various transcription factors from being expressed. Inhibition of this enzyme has been reported to be a novel strategy in cancer treatment. To identify novel and diverse leads for use in potent histone deacetylase 8 inhibitor design, a pharmac...

Identifying potential protein targets for a small-compound ligand query is crucial to the process of drug development. However, there are tens of thousands of proteins in human alone, and it is almost impossible to scan all the existing proteins for a query ligand using current experimental methods. Recently, a computational technology called docking-based inverse virtual screening (IVS) has at...

The use of predicted binding sites (binding sites calculated from the protein structure alone) is evaluated here as a tool to focus the docking of small molecule ligands into protein structures, simulating cases where the real binding sites are unknown. The resulting approach consists of a few independent docking runs carried out on small boxes, centered on the predicted binding sites, as oppos...

Virtual high-throughput screening of molecular databases and in particular high-throughput protein-ligand docking are both common methodologies that identify and enrich hits in the early stages of the drug design process. Current protein-ligand docking algorithms often implement a program-specific model for protein-ligand interaction geometries. However, in order to create a platform for arbitr...

The present study attempts to establish a relationship between ethnopharmacological claims and bioactive constituents present in Pinus roxburghii against all possible targets for diabetes through molecular docking and to develop a pharmacophore model for the active target. The process of molecular docking involves study of different bonding modes of one ligand with active cavities of target rec...

Metallo-β-lactamases can hydrolyze a broad range of β-lactam antibiotics and no effective inhibitors could be used in the clinic. Therefore, the discovery of metallo-β-lactamase inhibitors has attracted much attention in recent years. In this study, a support vector machine (SVM) that separates compounds into positives and negatives, combined with docking method was employed for virtual screeni...

The main key to success in structure-based drug discovery is the accurate prediction of binding affinities of hit compounds. Molecular docking and scoring functions are often used for this purpose. However, it is often found that the top-ranked docking poses do not represent the right binding mode, and frequently there is no correlation between docking score and biological data. Therefore, “pos...

BACKGROUND Protein-based pharmacophore models are enriched with the information of potential interactions between ligands and the protein target. We have shown in a previous study that protein-based pharmacophore models can be applied for ligand pose prediction and pose ranking. In this publication, we present a new pharmacophore-based docking program PharmDock that combines pose sampling and r...