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Molecular Models02:00

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Updated: Jun 7, 2026

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
08:35

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Published on: May 29, 2021

Chemical space sampling in virtual screening by different crystal structures.

Natasja Brooijmans1, Christine Humblet

  • 1Chemical Sciences, Wyeth Research, 401 N. Middletown Road, Pearl River, NY 10965, USA. reprints@prodigy.net

Chemical Biology & Drug Design
|October 21, 2010
PubMed
Summary
This summary is machine-generated.

Consensus scoring using multiple PI3K-γ crystal structures enhances hit diversity in virtual screening. This approach, combining data from different structures, improves hit identification compared to single-structure screening.

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Last Updated: Jun 7, 2026

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06:29

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Published on: March 3, 2021

Area of Science:

  • Computational chemistry
  • Drug discovery
  • Structural biology

Background:

  • Virtual screening is crucial for identifying drug candidates.
  • Phosphoinositide 3-kinase gamma (PI3K-γ) is a key target in various diseases.
  • Utilizing multiple crystal structures of a target can improve screening accuracy.

Purpose of the Study:

  • To evaluate the effectiveness of consensus scoring by combining hit lists from different PI3K-γ crystal structures.
  • To assess if consensus scoring improves hit diversity and enrichment factors in virtual screening.
  • To determine the optimal number of crystal structures for consensus scoring.

Main Methods:

  • Retrospective virtual screening experiments were performed.
  • An in-house High Throughput Screening (HTS) dataset of PI3K-γ inhibitors was used.
  • Compounds were docked against five diverse PI3K-γ crystal structures.
  • Consensus scoring was applied by combining results from individual structures.

Main Results:

  • Consensus scoring prioritizes compounds with moderate scores across individual crystal structures, increasing hit diversity.
  • Enrichment factors (EFs) for consensus scores using two or three structures often matched or exceeded individual structure EFs.
  • Using four or five structures in consensus scoring generally resulted in lower enrichments.
  • Top-ranked consensus compounds also present in individual top-ranked lists yielded the most hits with minimal false positives.

Conclusions:

  • Consensus scoring is a valuable complementary strategy to single-structure virtual screening for PI3K-γ.
  • Combining data from multiple crystal structures enhances the identification of diverse and relevant hit compounds.
  • Careful selection of structures and scoring thresholds is important for maximizing the benefits of consensus scoring.