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Disconnected Maximum Common Substructures under Constraints.

Robert Schmidt1, Florian Krull1, Anna Lina Heinzke1

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|December 16, 2020
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Summary
This summary is machine-generated.

We introduce RIMACS, a new algorithm for calculating the disconnected maximum common substructure (dMCS). This method enables controlled identification of meaningful molecular fragments for improved chemical similarity analysis.

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Area of Science:

  • Cheminformatics
  • Computational Chemistry
  • Drug Discovery

Background:

  • The Maximum Common Substructure (MCS) problem is crucial in cheminformatics, with applications in molecular superimposition, scaffold detection, and similarity assessment for virtual screening and clustering.
  • While connected MCS is often preferred for computational efficiency, disconnected MCS (dMCS) can offer valuable insights by revealing conserved molecular parts linked by variable groups.

Purpose of the Study:

  • To present RIMACS, a novel algorithm designed to compute the disconnected maximum common substructure (dMCS) with user-defined constraints.
  • To enable control over the number of connected components and their minimum size in dMCS calculations.

Main Methods:

  • Development of a new algorithm, RIMACS, utilizing a modified local substructure mapping approach.
  • Implementation of constraints to manage the number and size of connected components within the dMCS.

Main Results:

  • RIMACS successfully calculates dMCS under specified constraints.
  • Formal proof of correctness and extensive runtime evaluations on chemical datasets are provided.
  • Evaluation demonstrates that limiting connected components in dMCS improves similarity meaningfully while maintaining reasonable computational time.

Conclusions:

  • The RIMACS algorithm provides an effective method for calculating constrained dMCS.
  • Controlling the number of connected components in dMCS enhances its utility in cheminformatics applications, offering a balance between chemical interpretability and computational feasibility.