Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Drug Discovery: Overview01:26

Drug Discovery: Overview

12.9K
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...
12.9K
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

2.0K
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...
2.0K
G Protein-coupled Receptors01:15

G Protein-coupled Receptors

19.4K
G Protein-Coupled Receptors or GPCRs are membrane-bound receptors that transiently associate with heterotrimeric G proteins and induce an appropriate response to sensory stimuli such as light, odors, hormones, cytokines, or neurotransmitters.
GPCRs are also called heptahelical, 7TM, or serpentine receptors, and consist of seven (H1-H7) transmembrane alpha-helices that span the bilayer to form a cylindrical core. The transmembrane helices are connected by three extracellular loops and three...
19.4K
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

5.6K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
5.6K
Synthetic Biology02:55

Synthetic Biology

5.8K
Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
5.8K
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

75
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...
75

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Precision fragment addition: domain-specific DeepFrag2 models for smarter lead optimization.

Digital discovery·2026
Same author

Teaching old docks new tricks with machine learning enhanced ensemble docking.

Scientific reports·2024
Same author

CENsible: Interpretable Insights into Small-Molecule Binding with Context Explanation Networks.

Journal of chemical information and modeling·2024
Same author

The chaperone PrsA2 regulates the secretion, stability, and folding of listeriolysin O during <i>Listeria monocytogenes</i> infection.

mBio·2024
Same author

MolModa: accessible and secure molecular docking in a web browser.

Nucleic acids research·2024
Same author

Functional convergence in gastric lysozymes of foregut-fermenting rodents, ruminants, and primates is not attributed to convergent molecular evolution.

Comparative biochemistry and physiology. Part B, Biochemistry & molecular biology·2024
Same journal

Experimental evidence for behavioural cooling as a response to virus infection in an ectothermic vertebrate.

BMC biology·2026
Same journal

DNA damage at an early developmental stage affects neurodevelopment in sterlet (Acipenser ruthenus).

BMC biology·2026
Same journal

The landscape of human genomic diversity.

BMC biology·2026
Same journal

AGCECDA: attention-guided heterogeneous graph collaborative embedding for circRNA-drug sensitivity association prediction.

BMC biology·2026
Same journal

A decoy receptor antagonizes interferon mediated antiviral responses in teleost fish.

BMC biology·2026
Same journal

Decoding the association between platinum resistance and HPV status in cervical cancer using organoid models.

BMC biology·2026
See all related articles

Related Experiment Video

Updated: Mar 23, 2026

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

3.1K

Generative AI in structure-based drug discovery.

Zhuoya Zhong1, Jacob D Durrant2

  • 1Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA.

BMC Biology
|March 22, 2026
PubMed
Summary
This summary is machine-generated.

Generative artificial intelligence (AI) designs novel drug compounds by learning protein structures, moving beyond traditional screening. This AI approach accelerates early drug discovery and lead optimization.

Keywords:
Computer-aided drug designDe novo molecular generationDeep learningGenerative artificial intelligenceLead optimizationStructure-based drug design

More Related Videos

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

1.5K
Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit
22:10

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

Published on: June 28, 2013

13.8K

Related Experiment Videos

Last Updated: Mar 23, 2026

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

3.1K
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

1.5K
Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit
22:10

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

Published on: June 28, 2013

13.8K

Area of Science:

  • Drug discovery and development
  • Computational chemistry
  • Artificial intelligence in medicine

Background:

  • Traditional drug discovery relies on screening existing molecules.
  • Structure-based generative AI offers a novel approach to designing compounds.
  • This method tailors molecules to specific protein binding pockets.

Purpose of the Study:

  • To review the application of structure-based generative AI in early drug discovery.
  • To categorize generative AI methods based on modeling paradigms and structural data utilization.
  • To survey lead optimization techniques, emphasizing generation-driven medicinal chemistry.

Main Methods:

  • Categorization of generative AI methods by modeling paradigms (e.g., de novo incremental builders, full structure generators).
  • Analysis of strategies for using structural data to guide molecular design.
  • Survey of lead optimization techniques in the context of generative AI.

Main Results:

  • Generative AI designs novel compounds tailored to protein binding pockets.
  • Distinction between incremental and full structure generation models.
  • Identification of a trend towards generation-driven medicinal chemistry in lead optimization.

Conclusions:

  • Structure-based generative AI is transforming early drug discovery.
  • AI enables the design of bespoke molecules for therapeutic targets.
  • The field is shifting towards AI-powered approaches for efficient drug development.