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Predicting biological activity: computational approach using novel distance based molecular descriptors.

R Dutt1, A K Madan

  • 1Guru Gobind Singh College of Pharmacy, Yamunanagar-135001, India.

Computers in Biology and Medicine
|September 12, 2012
PubMed
Summary

Novel molecular descriptors, superpendentic eccentric distance sum indices (∫P-EDS) and their topochemical counterparts (∫cP-EDS), were developed to predict receptor binding affinity. These indices show potential for drug design due to their high discriminating power and sensitivity to branching.

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Area of Science:

  • Computational Chemistry
  • Cheminformatics
  • Drug Design

Background:

  • Accurate prediction of drug-target interactions is crucial for efficient drug discovery.
  • Molecular descriptors play a vital role in quantitative structure-activity relationship (QSAR) studies.
  • Existing descriptors may have limitations in capturing specific structural features relevant to binding affinity.

Purpose of the Study:

  • To conceptualize and develop novel distance-based molecular descriptors: superpendentic eccentric distance sum indices (∫P-1EDS to ∫P-4EDS) and their topochemical counterparts (∫cP-1EDS to ∫cP-4EDS).
  • To investigate the sensitivity towards branching, discriminating power, and degeneracy of these new indices.
  • To develop predictive models for human corticotropin releasing factor-1 receptor binding affinity using these novel descriptors.

Main Methods:

  • Development of four novel distance-based molecular descriptors and their topochemical variants.
  • Utilized a dataset of 46 2D and 3D molecular descriptors, including the newly proposed indices.
  • Employed decision tree analysis for classification and model development, followed by moving average analysis for refining predictions.

Main Results:

  • Decision tree models achieved 92% accuracy on the training set and 71% during cross-validation.
  • Models developed using three selected descriptors via moving average analysis predicted binding affinity with ≥85% accuracy.
  • The novel descriptors demonstrated high discriminating power, sensitivity to branching, and negligible degeneracy.

Conclusions:

  • The newly developed superpendentic eccentric distance sum indices (∫P-EDS) and their topochemical counterparts (∫cP-EDS) are effective for predicting receptor binding affinity.
  • These descriptors show significant potential for application in quantitative structure-activity/property/toxicity relationships (QSAR/QSPR/QSTR).
  • The proposed indices can facilitate and optimize the drug design process.