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

Analysis of selection methodologies for combinatorial library design.

Rosalia Pascual1, José I Borrell, Jordi Teixidó

  • 1Grup d'Enginyeria Molecular, Institut Químic de Sarriá (IQS), Universitat Ramon Llull, Via Augusta 390, E-08017 Barcelona, Spain.

Molecular Diversity
|February 6, 2004
PubMed
Summary

This study introduces Pralins, a program for in silico library selection. Hierarchical clustering and Optimum Binning are best for space division, with hierarchical clustering excelling in selection for sparse and full array problems.

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

Rational Method for Structural Simplification as Key Step in Hit Discovery: The Case of FGFR2 and IGF1R Dual Inhibitors.

International journal of molecular sciences·2025
Same author

The Use of a Penta-Deuterophenyl Substituent to Improve the Metabolic Stability of a Tyrosine Kinase Inhibitor.

Molecules (Basel, Switzerland)·2025
Same author

Applying Molecular Modeling to the Design of Innovative, Non-Symmetrical CXCR4 Inhibitors with Potent Anticancer Activity.

International journal of molecular sciences·2024
Same author

Exploring the unexplored chemical space: Rational identification of new Tafenoquine analogs with antimalarial properties.

Bioorganic chemistry·2024
Same author

WLB-87848, a Selective σ<sub>1</sub> Receptor Agonist, with an Unusually Positioned NH Group as Positive Ionizable Moiety and Showing Neuroprotective Activity.

Journal of medicinal chemistry·2024
Same author

When Unsuspected Crystallinity Ruins Biological Testing in Early Discovery: A Case Study.

Pharmaceuticals (Basel, Switzerland)·2024

Area of Science:

  • Computational chemistry
  • Cheminformatics
  • Drug discovery

Background:

  • In silico screening of chemical libraries is crucial for drug discovery.
  • Selecting representative subsets of large chemical libraries is computationally challenging.
  • Existing algorithms for library selection vary in effectiveness.

Purpose of the Study:

  • To implement and adapt various popular sparse and full array selection algorithms within a single program, Pralins (Program for Rational Analysis of Libraries in silico).
  • To validate Pralins using a case study of a synthesized combinatorial library of FXR partial agonists.
  • To analyze the performance of different partitioning techniques and selection methodologies for population and space coverage.

Main Methods:

  • Implementation and adaptation of partitioning techniques (hierarchical clustering, k-means clustering, Optimum Binning, Jarvis Patrick, Pral-SE) and distance-based methods (MaxSum, MaxMin, MaxMin averaged, DN2, CTD).

Related Experiment Videos

  • Validation using a three-component combinatorial library of FXR partial agonists with standard computational chemistry descriptors.
  • Analysis of representativity, population coverage, and space coverage for various selection sizes.

    • Main Results:

    • Hierarchical clustering and Optimum Binning were identified as the most advantageous division strategies for chemical space.
    • Complete hierarchical clustering proved to be the preferred selection methodology for both sparse and full array library selection.
    • Optimization algorithms can effectively address full array restrictions, maintaining over 90% population coverage.

    Conclusions:

    • Pralins provides a robust platform for in silico library selection, integrating diverse algorithms.
    • Hierarchical clustering and Optimum Binning offer superior space division for library analysis.
    • The developed methods enable efficient and representative selection of chemical libraries for drug discovery efforts.