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Related Concept Videos

Pharmacokinetic–Pharmacodynamic Relationship: Problems01:24

Pharmacokinetic–Pharmacodynamic Relationship: Problems

The empirical approach to drug therapy optimization relies on correlating pharmacological response with administered dosage. Such an approach can be costly, time-consuming, and often yields poor correlation due to variables like formulation factors and drug elimination characteristics. A more precise approach correlates response with plasma drug concentration or the amount of drug in the body, rather than dosage. This is achieved through pharmacokinetic-pharmacodynamic (PK/PD) modeling, which...
Pharmacodynamic Models: Emax Drug–Concentration Effect Model01:18

Pharmacodynamic Models: Emax Drug–Concentration Effect Model

The Emax drug-concentration effect model is central to pharmacodynamics in drug discovery and development. This model is predicated on the receptor occupancy theory, which posits that the effect of a drug is directly related to the number of receptors occupied by the drug and the resultant complex formation.The model describes the reversible interaction between a drug (C) and a receptor (R) to form a drug-receptor complex (RC). The kinetics of this interaction are quantified by an equation that...
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...
Drug Discovery: Overview01:26

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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...
Pharmaceutical Equivalents01:26

Pharmaceutical Equivalents

As defined by regulatory standards, pharmaceutical equivalents require generic drug products to have identical dosage forms and chemically identical active pharmaceutical ingredients (APIs). They must adhere to compendial or applicable standards for potency, content uniformity, disintegration times, and dissolution rates. In the case of modified-release dosage forms, variations in drug content are permissible as long as the delivered amount remains consistent with the innovator drug product.

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Related Experiment Video

Updated: Jun 1, 2026

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

Published on: September 26, 2025

Pharmer: efficient and exact pharmacophore search.

David Ryan Koes1, Carlos J Camacho

  • 1Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States. dkoes@pitt.edu

Journal of Chemical Information and Modeling
|May 25, 2011
PubMed
Summary

Pharmer accelerates drug discovery by enabling rapid pharmacophore searches. This computational approach significantly outperforms existing technologies for screening large compound libraries.

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Published on: December 1, 2020

Area of Science:

  • Computational chemistry
  • Drug discovery
  • Bioinformatics

Background:

  • Pharmacophore searching is crucial for identifying potential drug candidates.
  • Existing methods often struggle to scale with large compound libraries, leading to lengthy search times.

Purpose of the Study:

  • To introduce Pharmer, a novel computational approach for efficient pharmacophore searching.
  • To demonstrate Pharmer's ability to scale with query complexity rather than library size.

Main Methods:

  • Development of the Pharmer KDB-tree for organizing pharmacophore data.
  • Implementation of Bloom fingerprints for enhanced data organization and retrieval.
  • Utilizing these methods to perform exact pharmacophore searches on large datasets.

Main Results:

  • Pharmer successfully screened nearly two million structures in under a minute.
  • The approach demonstrated an order of magnitude speed improvement over existing technologies.
  • Pharmer's performance scales with query breadth and complexity.

Conclusions:

  • Pharmer offers a significant advancement in computational drug discovery by enabling faster and more scalable pharmacophore searches.
  • The open-source availability of Pharmer promotes wider adoption and further development in the field.