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Related Concept Videos

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...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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...
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...
Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...

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Related Experiment Video

Updated: May 16, 2026

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

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

Published on: December 1, 2020

Biological network inference for drug discovery.

Paola Lecca1, Corrado Priami

  • 1The Microsoft Research, University of Trento, Centre for Computational and Systems Biology, Piazza Manifattura 1 - 38068 Rovereto, Italy. paola.lecca@unitn.it

Drug Discovery Today
|November 14, 2012
PubMed
Summary

Biological network inference uses computational methods to map drug-target interactions from experimental data. This approach aids in identifying disease networks and drug mechanisms, accelerating drug discovery.

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Area of Science:

  • Computational biology
  • Pharmacology
  • Systems biology

Background:

  • Understanding disease pathophysiology is crucial for targeted drug development.
  • Biological network inference offers a computational approach to decipher complex biological interactions.

Purpose of the Study:

  • To review and compare recent computational technologies for biological network inference.
  • To highlight the application of these technologies in drug discovery.

Main Methods:

  • Utilizing high-throughput experimental data.
  • Applying computational methods for network inference to deduce interaction topology and causal structure.
  • Analyzing networks of drug-target interactions, gene/protein networks, and biochemical pathways.

Main Results:

  • Biological network inference aids in identifying disease-causing gene and protein networks.
  • It also elucidates biochemical networks related to drug metabolism and mechanisms of action.
  • High-level networks generated serve as a basis for detailed mechanistic models.

Conclusions:

  • Biological network inference is a valuable tool in modern drug discovery.
  • Computational technologies in this field are increasingly adopted by pharmaceutical and biotechnology companies.
  • This approach supports the identification of drug targets and understanding of drug action.