Related Experiment Video

Updated: Jul 17, 2026

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro
05:50

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Published on: September 26, 2025

Pharmacophore mapping of diverse classes of farnesyltransferase inhibitors

Tabish Equbal1, Om Silakari, Gundla Rambabu

  • 1Department of Pharmaceutical Science and Drug Research, Punjabi University, Patiala 147-002, India.

Bioorganic & Medicinal Chemistry Letters
|January 24, 2007
PubMed

Insights

This study developed a predictive pharmacophore model for identifying novel protein farnesyltransferase inhibitors (FTIs). The validated model effectively identifies diverse compounds with potential anti-cancer activity by targeting cell signaling proteins like H-Ras.

Area of Science:

  • Medicinal Chemistry
  • Computational Drug Discovery
  • Enzymology

Background:

  • Protein farnesyltransferase (FTase) is a zinc-dependent enzyme crucial for cell signaling pathways.
  • FTase activity is implicated in the function of oncogenic proteins such as H-Ras.
  • Inhibiting FTase presents a therapeutic strategy for cancers.

Purpose of the Study:

  • To develop a robust pharmacophore model for identifying novel farnesyltransferase inhibitors (FTIs).
  • To utilize computational methods for discovering diverse and potent FTIs.
  • To provide a reliable tool for drug discovery targeting FTase.

Main Methods:

  • Development of pharmacophore models using the Catalyst HypoGen program.
  • Selection of a diverse training set of 22 farnesyltransferase inhibitors (FTIs).
  • Validation of the best pharmacophore hypothesis (Hypo 1) using test sets and known inhibitors.

Main Results:

  • The best pharmacophore hypothesis (Hypo 1) comprised four features: one hydrogen-bond acceptor (HBA), one hydrophobic point (HY), and two ring aromatics (RA).
  • Hypo 1 demonstrated high predictive power with a correlation coefficient of 0.961 and low RMSD of 0.885 on the training set.
  • External validation using 181 test compounds yielded a correlation coefficient of 0.713, and screening a spiked database identified all 25 known inhibitors (enrichment factor of 10.892).

Conclusions:

  • The derived pharmacophore model is a highly predictive and reliable tool for identifying structurally diverse FTIs.
  • This model can significantly aid in the discovery of new compounds with desired biological activity against FTase.
  • The findings support the use of pharmacophore modeling in accelerating drug discovery for FTase-related targets.

More Related Videos

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

Förster Resonance Energy Transfer Mapping: A New Methodology to Elucidate Global Structural Features07:09

Förster Resonance Energy Transfer Mapping: A New Methodology to Elucidate Global Structural Features

Published on: March 16, 2022

Related Concept Videos

Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase01:11

Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase

Genetic polymorphisms in drug targets have emerged as critical determinants of interindividual variability in drug response and toxicity. Pharmacogenomic investigations increasingly focus on identifying these variations to personalize and optimize therapeutic interventions. A drug target may be a receptor, enzyme, or signaling protein involved in pharmacologic responses or disease-related pathways. While early pharmacogenetic studies focused primarily on drug metabolism, current research...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Targets for Drug Action: Overview01:26

Targets for Drug Action: Overview

Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
Pharmacogenetics of Phase II Enzymes: N-acetyltransferase, Thiopurine S-methyltransferase, UDP-glucuronosyltransferase01:27

Pharmacogenetics of Phase II Enzymes: N-acetyltransferase, Thiopurine S-methyltransferase, UDP-glucuronosyltransferase

Phase II biotransformation reactions are essential for detoxifying and eliminating xenobiotics, including many pharmaceutical compounds. These reactions typically involve conjugation, the covalent attachment of polar endogenous groups such as glucuronic acid, sulfate, methyl, or acetyl moieties to functional groups introduced during Phase I metabolism. The resulting conjugates are more water-soluble, enabling efficient renal or biliary excretion.The major classes of Phase II enzymes include...
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...
Pharmacogenetics of Phase I Enzymes: Cytochrome P450 Isozymes01:28

Pharmacogenetics of Phase I Enzymes: Cytochrome P450 Isozymes

Cytochrome P450 (CYP450) enzymes are a superfamily of heme-containing monooxygenases that play a pivotal role in Phase I drug metabolism by catalyzing oxidation and reduction reactions.These enzymes transform lipophilic xenobiotics into more hydrophilic metabolites, facilitating subsequent Phase II conjugation and eventual excretion. The CYP450 family is classified into families (e.g., CYP1–CYP3) and subfamilies (e.g., CYP2A, CYP2C), based on amino acid sequence homology.CYP450 isoenzymes,...