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 Experiment Videos

Strategies for compound selection.

Marius M Olah1, Cristian G Bologa, Tudor I Oprea

  • 1Division of Biocomputing, University of New Mexico School of Medicine, BMSB61, MSC 08 4670, 1 University of New Mexico, Albuquerque, NM 87131-0001, USA.

Current Drug Discovery Technologies
|February 14, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

How many protein pairs can we chemically target?

Drug discovery today·2026
Same author

Novel drug targets in 2025.

Nature reviews. Drug discovery·2026
Same author

Detecting Uncoded Self-Harm in Veterans' Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Cohort Study.

Journal of medical Internet research·2026
Same author

Target identification and assessment in the era of AI.

Nature reviews. Drug discovery·2026
Same author

Detecting Uncoded Self-Harm in Veterans' Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Observational Study.

Journal of medical Internet research·2026
Same author

The Common Fund Data Ecosystem (CFDE).

bioRxiv : the preprint server for biology·2026
Same journal

Discovery of Phytochemicals as Inhibitors of Human Metapneumovirus: In-Silico Docking Studies.

Current drug discovery technologies·2026
Same journal

From Molecules to Manufacturing: Expanding Role of Artificial Intelligence in Pharmaceutical Sciences.

Current drug discovery technologies·2026
Same journal

Targeting Biofilm Formation in Acinetobacter baumannii: In Silico Discovery of Novel Candidate Inhibitors for Acyl-Homoserine Lactone Synthase.

Current drug discovery technologies·2026
Same journal

Effects of Ganoderma lucidum Polysaccharide Peptide on Inflammatory and Metabolic Biomarkers in Obese Patients with Cardiometabolic Syndrome: A Randomized Controlled Trial.

Current drug discovery technologies·2026
Same journal

Using Computational Intelligence to Connect Data and Drug Design in Medicinal Chemistry: A Review.

Current drug discovery technologies·2026
Same journal

Uncovering the Anti-Pleurisy Mechanism of Shizao Decoction via Network Pharmacology and Molecular Docking.

Current drug discovery technologies·2026
See all related articles

Pharmaceutical companies need efficient chemical compound selection strategies beyond in-house libraries. This involves database assembly, structural verification, property filtering, and advanced selection methods for drug discovery.

Area of Science:

  • Medicinal Chemistry
  • Computational Chemistry
  • Drug Discovery

Background:

  • In-house pharmaceutical compound collections are insufficient for exploring diverse chemical spaces.
  • Advances in virtual screening and high-throughput screening necessitate rapid evaluation of large chemical libraries.

Purpose of the Study:

  • To outline a comprehensive strategy for selecting diverse and relevant chemical compounds for drug discovery.
  • To address the need for efficient pre-acquisition or pre-experiment chemical evaluation.

Main Methods:

  • Database assembly and 'in silico' inventory creation.
  • Structural integrity verification and exploration of chemical representations (stereoisomers, tautomers, ionization states).
  • Property and structural filtering to remove undesirable compounds.

Related Experiment Videos

  • 3D-structure generation for virtual screening and similarity analysis.
  • Advanced selection techniques including clustering, statistical design, similarity-based, and receptor-based approaches.
  • Inclusion of a random subset in the final compound list.

    • Main Results:

    • A systematic workflow for chemical space sampling and compound selection was detailed.
    • The strategy integrates multiple computational approaches for optimizing library composition.

    Conclusions:

    • Effective compound selection requires a multi-step computational strategy.
    • This approach enhances the efficiency of identifying novel bioactive chemotypes.