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This study reveals general trends in ring puckering for diverse molecules, classifying conformations into clusters. It introduces models to predict ring shapes and efficiently generate low-energy conformations for various applications.

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Area of Science:

  • Computational Chemistry
  • Molecular Modeling
  • Structural Chemistry

Background:

  • Molecular geometry dictates physical and chemical properties.
  • Limited understanding of puckering in medium-sized rings and macrocycles.
  • Existing studies often focus on small rings or specific families.

Purpose of the Study:

  • To provide a general understanding of ring puckering preferences in diverse molecules.
  • To classify ring conformations and analyze puckering motions.
  • To develop models for predicting and generating ring conformations.

Main Methods:

  • Utilized Cremer-Pople puckering coordinates for conformational analysis.
  • Analyzed a dataset of 140,000 diverse small molecules, macrocycles, and cyclic peptides.
  • Developed models to map puckering preferences to torsion space and coupled substituent motion.

Main Results:

  • Identified a few canonical conformational clusters for ring structures.
  • Showed that the number of clusters increases slowly with ring size.
  • Demonstrated restricted ring puckering motions and distinct behaviors across clusters.
  • Proposed models explaining substituent orientation changes during puckering.

Conclusions:

  • Established a general framework for understanding ring puckering preferences.
  • Developed an efficient knowledge-based sampling method for conformation generation.
  • The findings will accelerate the identification of low-energy conformations for materials and drug discovery.