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Virtual Screening in the Cloud: How Big Is Big Enough?

Christoph Grebner1, Erik Malmerberg1, Andrew Shewmaker2

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High-throughput virtual screening using 3D similarity on cloud platforms enables searching billions of molecules. This scalable approach expands accessible chemical space for discovering novel drug candidates efficiently.

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Area of Science:

  • Computational Chemistry
  • Drug Discovery
  • Bioinformatics

Background:

  • Virtual screening is crucial in Computer-Assisted Drug Design (CADD).
  • Ligand-based similarity searches are common early-stage methods.
  • Computational resource limitations restrict screening scale and speed.

Purpose of the Study:

  • To describe a high-throughput virtual screening project utilizing 3D similarity.
  • To demonstrate the scalability and flexibility of cloud computing for virtual screening.
  • To explore the impact of large search spaces on hit discovery and computational costs.

Main Methods:

  • Employed 3D similarity searching (FastROCS) on a cloud platform (Orion).
  • Utilized automated evaluation workflows for efficient processing.
  • Generated and searched billions of virtual molecules.

Main Results:

  • Cloud resources enabled fully scalable and flexible virtual screening.
  • Provided access to an unprecedented explicit 3D virtual chemical space.
  • Investigated the relationship between search space size and novel hit identification.

Conclusions:

  • Cloud-based 3D virtual screening offers a powerful, scalable solution for drug discovery.
  • Expanding the search space significantly impacts hit discovery and list size.
  • Computational and economic factors are key considerations for resource scaling in virtual screening.