Classification is supervised machine learning applicable to predict chemicals based on their properties. The chemical properties are derived from its structural and functional groups. Many molecular descriptors have been developed, one of which, was pharmacophore. Pharmacophore a quantitative measure molecules in application as pharmaceutical ingredient. training datasets were 59 categorized ad...

Farnesyltransferase enzyme (FTase) is considered an essential enzyme in the Ras signaling pathway associated with cancer. Thus, designing inhibitors for this enzyme might lead to the discovery of compounds with effective anticancer activity. In an attempt to obtain effective FTase inhibitors, pharmacophore hypotheses were generated using structure-based and ligand-based approaches built in Disc...

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...

The pregnane X receptor (PXR) is involved in transcriptional regulation of multiple cytochromes P450 and multidrug resistanceassociated protein (MDR1), which encodes for the drug transporter P-glycoprotein. Crystal structure analyses suggest that the ligand binding domain is highly hydrophobic and flexible, allowing molecules of differing sizes to bind in multiple orientations. Using literature...

Protein microarrays are playing an increasingly important role in the discovery and characterization of protein-ligand interactions. The uniform orientation conferred by site-specific immobilization is a demonstrable advantage in using such microarrays. Here, we report on a general strategy for fabricating gold surfaces displaying a protein in a uniform orientation. An azido group was installed...

This paper introduces a novel molecular description--topological (2D) fuzzy pharmacophore triplets, 2D-FPT--using the number of interposed bonds as the measure of separation between the atoms representing pharmacophore types (hydrophobic, aromatic, hydrogen-bond donor and acceptor, cation, and anion). 2D-FPT features three key improvements with respect to the state-of-the-art pharmacophore fing...

In silico drug target identification, which includes many distinct algorithms for finding disease genes and proteins, is the first step in the drug discovery pipeline. When the 3D structures of the targets are available, the problem of target identification is usually converted to finding the best interaction mode between the potential target candidates and small molecule probes. Pharmacophore,...

Three neurokinin (NK) antagonist pharmacophore models (Models 1-3) accounting for hydrogen bonding groups in the 'head' and 'tail' of NK receptor ligands have been developed by use of a new procedure for treatment of hydrogen bonds during superimposition. Instead of modelling the hydrogen bond acceptor vector in the strict direction of the lone pair, an angle is allowed between the hydrogen bon...

Dualor multi-target ligands have gained increased attention in the past years due to several advantages, including more simple pharmacokinetic and phamarcodynamic properties compared to a combined application of several drugs. Furthermore multi-target ligands often possess improved efficacy [1]. We present a new approach for the discovery of dual-target ligands using aligned pharmacophore model...