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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-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...
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...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...
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,...
Prodrugs01:30

Prodrugs

Prodrugs are a class of pharmaceutical compounds that undergo a biotransformation process within the body to be converted into a pharmacologically active drug. Prodrugs are designed to improve the therapeutic properties of the parent drug, such as enhancing bioavailability, increasing stability, or reducing toxicity. The concept of prodrugs revolves around modifying the chemical structure of the original drug to make it more effective or convenient for administration.
Prodrugs help overcome...

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Related Experiment Video

Updated: Jun 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

Proteomics-Driven Strategies for Proximity-Inducing Drug Discovery.

Rufeng Fan1,2, Jiahui Ni2, Tiantian Zhou2

  • 1Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, and Cancer Center, School of Medicine, Tongji University, Shanghai, China.

Angewandte Chemie (International Ed. in English)
|June 15, 2026
PubMed
Summary
This summary is machine-generated.

Proximity-inducing drugs offer novel therapeutic strategies by modulating protein interactions beyond traditional inhibition. Proteomics and machine learning accelerate the discovery and optimization of these advanced therapeutics.

Keywords:
drug discoverynew therapeutic modalityproteomicsproximity‐inducing drugstarget space expansion

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Last Updated: Jun 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

Mapping Dysfunctional Protein-Protein Interactions in Disease
09:39

Mapping Dysfunctional Protein-Protein Interactions in Disease

Published on: October 24, 2025

Area of Science:

  • Biochemistry
  • Pharmacology
  • Drug Discovery

Background:

  • Proximity-inducing drugs represent a novel therapeutic class that stabilizes or induces protein-protein interactions.
  • Their mechanism extends beyond targeted protein degradation (TPD), influencing diverse biological processes like signal transduction and gene transcription.
  • Rational drug design necessitates understanding protein interaction modulation, drug selectivity, and ligand development.

Purpose of the Study:

  • To review recent advancements in proximity-inducing drugs.
  • To highlight the pivotal role of proteomics in expanding target spaces and optimizing drug efficacy.
  • To discuss the contributions of machine learning and ligandability mapping in accelerating drug discovery.

Main Methods:

  • Proteomics for global target identification and proteome-wide response characterization.
  • Machine learning applied to proteomic data for enhanced drug discovery.
  • Analysis of protein-protein interaction networks modulated by proximity-inducing agents.

Main Results:

  • Proteomics provides detailed insights into drug mechanisms and downstream effects.
  • Machine learning and expanded ligandability maps are crucial for optimizing proximity-inducing drugs.
  • These technologies facilitate the identification of novel therapeutic targets and drug candidates.

Conclusions:

  • Proteomics and machine learning are indispensable tools for the rational development of proximity-inducing drugs.
  • These technologies enable a deeper understanding of drug mechanisms and facilitate optimization of therapeutic efficacy.
  • The integration of these approaches supports the advancement of next-generation proximity-inducing therapeutics.