Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Drug Discovery: Overview

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...

Genetic Screens

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...

You might also read

Related Articles

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

Sort by

Same author

Identification of small molecule inhibitors of PPM1D using an integrated drug discovery platform.

iScience·2025

Same author

A potent and selective reaction hijacking inhibitor of Plasmodium falciparum tyrosine tRNA synthetase exhibits single dose oral efficacy in vivo.

PLoS pathogens·2024

Same author

Identification of Small Molecule Inhibitors of PPM1D Using a Novel Drug Discovery Platform.

bioRxiv : the preprint server for biology·2024

Same author

Mitigating the risk of antimalarial resistance via covalent dual-subunit inhibition of the Plasmodium proteasome.

Cell chemical biology·2023

Same author

Discovery of mobocertinib, a potent, oral inhibitor of EGFR exon 20 insertion mutations in non-small cell lung cancer.

Bioorganic & medicinal chemistry letters·2022

Same author

Susceptibilities of Ugandan Plasmodium falciparum Isolates to Proteasome Inhibitors.

Antimicrobial agents and chemotherapy·2022

Search research articles

Related Experiment Video

Updated: Aug 4, 2025

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Published on: August 25, 2023

Target-driven machine learning-enabled virtual screening (TAME-VS) platform for early-stage hit identification.

Yuemin Bian¹, Jason J Kwon^2,3,4, Cong Liu¹

¹Center for the Development of Therapeutics, Broad Institute of MIT and Harvard, Cambridge, MA, United States.

Frontiers in Molecular Biosciences

|March 30, 2023

Summary

This summary is machine-generated.

We developed TArget-driven Machine learning-Enabled VS (TAME-VS), a novel platform for efficient drug discovery. TAME-VS uses machine learning to identify potential drug candidates, accelerating the search for new medicines.

Keywords:

AIDD drug discovery hit identification machine learning virtual screening

More Related Videos

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy

Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy

Published on: April 3, 2018

Related Experiment Videos

Last Updated: Aug 4, 2025

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Published on: August 25, 2023

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy

Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy

Published on: April 3, 2018

Area of Science:

Computational chemistry
Drug discovery
Machine learning

Background:

High-throughput screening (HTS) and virtual screening (VS) are crucial for drug discovery.
VS methods, while effective, require expensive experimental data, posing challenges for novel targets.
Efficient hit identification is critical in early-stage drug discovery.

Purpose of the Study:

To present the TArget-driven Machine learning-Enabled VS (TAME-VS) platform for modular hit identification.
To enable bespoke hit identification campaigns for user-defined protein targets.
To provide a flexible, efficient, and accessible tool for early-stage drug discovery.

Main Methods:

Leveraging existing chemical databases of bioactive molecules.
Performing homology-based target expansion from a user-defined target ID.
Retrieving compounds with experimentally validated activity, vectorizing them, and training machine learning models.
Deploying models for inferential virtual screening and nominating compounds based on predicted activity.

Main Results:

Retrospective validation across ten diverse protein targets demonstrated clear predictive power.
The TAME-VS platform successfully identified potential active compounds.
The methodology proved flexible and efficient in hit identification campaigns.

Conclusions:

The TAME-VS platform offers a powerful approach for early-stage hit identification.
It significantly enhances the efficiency and reduces the cost of drug discovery efforts.
The platform is publicly available to facilitate broader adoption in the scientific community.