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Related Concept Videos

Molecular Models02:00

Molecular Models

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.
Molecular Shapes01:18

Molecular Shapes

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Structural Isomerism02:34

Structural Isomerism

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Isomers are different chemical species that have the same chemical formula. Structural isomerism of coordination compounds can be divided into two subcategories, the linkage isomers and coordination-sphere isomers.
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Resonance and Hybrid Structures02:16

Resonance and Hybrid Structures

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Structure and Bonding of Alkenes02:47

Structure and Bonding of Alkenes

Olefins, which are unsaturated hydrocarbons containing one or more carbon–carbon double bonds, are broadly divided into alkenes and cycloalkenes. The general chemical formula of an alkene is CnH2n.
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Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries

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Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
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Published on: April 13, 2022

Build-up algorithm for atomic correspondence between chemical structures.

Takeshi Kawabata1

  • 1Institute of Protein Science, Osaka University, Osaka 565-0871 Japan. kawabata@protein.osaka-u.ac.jp

Journal of Chemical Information and Modeling
|July 9, 2011
PubMed
Summary
This summary is machine-generated.

A new build-up algorithm, kcombu, efficiently finds maximum common substructures (MCS) for molecular similarity. It accurately identifies topologically constrained disconnected MCS (TD-MCS), outperforming existing methods in speed and agreement.

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Construction and Systematical Symmetric Studies of a Series of Supramolecular Clusters with Binary or Ternary Ammonium Triphenylacetates

Published on: February 15, 2016

Area of Science:

  • Computational chemistry
  • Cheminformatics
  • Bioinformatics

Background:

  • Determining atom correspondence is crucial for molecular similarity and predicting biological activity.
  • The maximum common substructure (MCS) problem, a formalized approach, is computationally challenging (NP-complete).
  • Existing MCS algorithms lack sufficient speed and accuracy.

Purpose of the Study:

  • To develop a novel, efficient algorithm for finding maximum common substructures (MCS).
  • To introduce and evaluate a new type of MCS: topologically constrained disconnected MCS (TD-MCS).
  • To assess the performance of the new algorithm against established methods.

Main Methods:

  • Development of "kcombu", a program utilizing a build-up greedy heuristic algorithm.
  • Implementation of searches for connected, disconnected, and topologically constrained disconnected MCS (TD-MCS).
  • Validation using exact correspondences from maximum clique algorithms and 3D correspondences from superimposed molecular structures.

Main Results:

  • The kcombu build-up algorithm demonstrates high agreement with exact correspondences for connected MCS.
  • kcombu significantly reduces computation time compared to exact MCS algorithms.
  • TD-MCS shows superior agreement compared to other MCS types when compared against 3D correspondences.
  • A strong correlation exists between molecular similarity and accurate atom matching.

Conclusions:

  • The kcombu program offers a fast and accurate solution for MCS problems, including the novel TD-MCS.
  • The build-up algorithm is a viable and efficient approach for molecular similarity assessments.
  • High molecular similarity (e.g., >40% Tanimoto similarity) facilitates accurate atom matching, particularly with 3D correspondences.