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...

Drug Biotransformation: Overview

Drug Biotransformation: Overview

Pharmaceutical substances known as xenobiotics are predominantly lipophilic and nonionized. This enables them to permeate lipid bilayers, such as cell membranes, and interact with intracellular target receptors. Lipophilic drugs have an advantage in crossing biological barriers and reaching their intended sites of action. However, lipophilic drugs often have a restricted capacity for renal expulsion or elimination from the body. When these drugs enter the kidneys and undergo glomerular...

Structure-Activity Relationships and Drug Design

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...

You might also read

Related Articles

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

Sort by

Same author

ModelistsGCN: a multimodal graph convolutional network framework for single-cell spatial transcriptomic cell typing.

Briefings in bioinformatics·2026

Same author

InSituPREP enables 3D single-cell mapping of interaction-associated gene programs in the breast cancer tumor microenvironment.

Nucleic acids research·2026

Same author

Distribution-preserved sampling (DPS) for smarter machine learning assisted ultra-large-scale virtual screening.

RSC advances·2026

Same author

Biosensor for Lyme Disease: Real-time, Specific, and Label-Free Complementary Metal-Oxide-Silicon Transistor Sensing of <i>Borrelia burgdorferi s.l</i>. Outer Surface Protein A in Unprocessed Blood.

ACS sensors·2026

Same author

Biological Transistors for Direct Biosensing of L-Dopa in Ultrasmall Samples of Unprocessed and Unwashed Whole Blood.

ACS sensors·2025

Same author

Indole-containing inhibitors with improved efficacy targeting the gyrase of <i>Mycobacterium tuberculosis</i>.

NAR molecular medicine·2025

Same journal

RETRACTED: Atta et al. Effect of Montmorillonite Nanogel Composite Fillers on the Protection Performance of Epoxy Coatings on Steel Pipelines. <i>Molecules</i> 2017, <i>22</i>, 905.

Molecules (Basel, Switzerland)·2026

Same journal

Correction: Chen et al. Chemical Composition of <i>Litsea pungens</i> Essential Oil and Its Potential Antioxidant and Antimicrobial Activities. <i>Molecules</i> 2023, <i>28</i>, 6835.

Molecules (Basel, Switzerland)·2026

Same journal

Correction: Ruan et al. Comparison of Extraction, Isolation, Purification, Structural Characterization and Immunomodulatory Activity of Polysaccharides from Two Species of <i>Cistanche</i>. <i>Molecules</i> 2025, <i>30</i>, 4754.

Molecules (Basel, Switzerland)·2026

Same journal

Correction: Li et al. Gastrodin Ameliorates Cognitive Dysfunction in Vascular Dementia Rats by Suppressing Ferroptosis via the Regulation of the Nrf2/Keap1-GPx4 Signaling Pathway. <i>Molecules</i> 2022, <i>27</i>, 6311.

Molecules (Basel, Switzerland)·2026

Same journal

Correction: Zueva et al. Steady-State Kinetics of Enzyme-Catalyzed Hydrolysis of Echothiophate, a P-S Bonded Organophosphorus as Monitored by Spectrofluorimetry. <i>Molecules</i> 2020, <i>25</i>, 1371.

Molecules (Basel, Switzerland)·2026

Same journal

1,4-Diazatriphenylene and Its Hetero-Fused Analogs: Synthesis and Applications.

Molecules (Basel, Switzerland)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 5, 2025

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

Published on: June 4, 2021

MolOptimizer: A Molecular Optimization Toolkit for Fragment-Based Drug Design.

Adam Soffer^1,2, Samuel Joshua Viswas^1,2, Shahar Alon³

¹Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

Molecules (Basel, Switzerland)

|January 11, 2024

Summary

This summary is machine-generated.

MolOptimizer is a computational toolkit that accelerates drug discovery by predicting small molecule binding values. It uses machine learning on user data to optimize drug candidates with improved properties.

Keywords:

cheminformatics fragment screening hit-to-lead optimization

More Related Videos

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Published on: March 3, 2021

Related Experiment Videos

Last Updated: Jul 5, 2025

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

Published on: June 4, 2021

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Published on: March 3, 2021

Area of Science:

Computational chemistry
Drug discovery
Machine learning in pharmacology

Background:

The hit-to-lead optimization phase is critical in drug discovery.
Accurate prediction of small molecule binding affinity is essential for identifying viable drug candidates.
Computational tools can significantly expedite the drug discovery process.

Purpose of the Study:

To introduce MolOptimizer, a user-friendly computational toolkit.
To streamline the hit-to-lead optimization process in drug discovery.
To enable accurate prediction of binding values for novel small molecules.

Main Methods:

MolOptimizer extracts features from user-provided, labeled small-molecule datasets.
Machine learning models are trained on these extracted features.
The toolkit utilizes a web-based server hosted on Azure for accessibility.

Main Results:

MolOptimizer accurately predicts binding values for new small molecules with similar scaffolds.
The toolkit facilitates the identification of drug candidates with enhanced binding properties.
The computational approach speeds up the discovery and development timeline.

Conclusions:

MolOptimizer is a valuable resource for accelerating hit-to-lead optimization.
The toolkit enhances the efficiency of identifying drug candidates with improved binding.
Its user-friendly interface and machine learning capabilities make it a vital tool in modern drug discovery.