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TrixX: structure-based molecule indexing for large-scale virtual screening in sublinear time

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Abstract

Structure-based virtual screening today is basically organized as a sequential process where the molecules of a screening library are evaluated for instance with respect to their fit with a biological target. In this paper, we present a novel structure-based screening paradigm avoiding sequential searching and therefore enabling sublinear runtime behavior. We implemented the novel paradigm in the virtual screening tool TrixX and successfully applied it in screening experiments on four targets from relevant therapeutic areas. With the screening paradigm implemented in TrixX, we propose some important extensions and modifications to traditional virtual screening approaches: Instead of processing all compounds in the screening library sequentially, TrixX first analyzes the geometric and physicochemical binding site characteristics and then draws compounds with matching features from a compound catalog. The catalog organizes the compounds by their physicochemical and geometric features making use of relational database technology with indexed tables in order to support efficient queries for compounds with specific features. A key element of the compound catalog is a highly selective geometric descriptor that carries information on the type of functional groups of the compound, their Euclidian distance, the preferred interaction direction of each functional group, and the location of steric bulk around the triangle.

In a re-docking experiment with 200 protein–ligand complexes, we could show that TrixX is able to correctly predict the location of ligand functional groups in co-crystallized complexes. In a retrospective virtual screening experiment for four different targets, the enrichment factors of TrixX are comparable to the enrichment factors of FlexX and FlexX-Scan. With computing times clearly below one second per compound, TrixX counts among the fastest virtual screening tools currently available and is nearly two orders of magnitude faster than standard FlexX.

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Notes

  1. This runtime behavior is valid within the tested library sizes. Libraries with more than 130,000 compounds demand more main memory and may require even more selective molecule descriptors. Further, experiments need to prove or disprove whether the observed runtime behavior can be further extrapolated.

  2. Hardware environment A: 32-bit version of TrixX on a 2.4 GHz Dual Xeon workstation with 4 GB of main memory. Hardware environment B: 64-bit version of TrixX on a SUN Fire server using a one of four CPUs and 32 GB of main memory: We observed similar average runtimes of TrixX on both hardware environments.

  3. The gap of re-docking performance between TrixX and FlexX/FlexX-Scan (number of correct predictions) is rather large for very accurate solutions (≤1.0 Å) and tends to close for less accurate solutions (≤2.5 Å).

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Acknowledgment

The authors thank BioSolveIT GmbH (St. Augustin, Germany) and AstraZeneca (Mölndal, Sweden) for funding our work. We are grateful for constructive discussions on the molecule descriptor and on method validation with colleagues from AstraZeneca and BioSolveIT, especially Jens Sadowski and Christian Lemmen.

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Correspondence to Matthias Rarey.

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Schellhammer, I., Rarey, M. TrixX: structure-based molecule indexing for large-scale virtual screening in sublinear time. J Comput Aided Mol Des 21, 223–238 (2007). https://doi.org/10.1007/s10822-007-9103-5

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  • DOI: https://doi.org/10.1007/s10822-007-9103-5

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