Feature extraction using molecular planes for fuzzy relational clustering of a flexible dopamine reuptake inhibitor

Amit Banerjee, Milind Misra, Deepa Pai, Liang Yu Shih, Rohan Woodley, Xiang Jun Lu, A. R. Srinivasan, Wilma K. Olson, Rajesh N. Davé, Carol A. Venanzi

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Six rigid-body parameters (Shift, Slide, Rise, Tilt, Roll, Twist) are commonly used to describe the relative displacement and orientation of successive base pairs in a nucleic acid structure. The present work adapts this approach to describe the relative displacement and orientation of any two planes in an arbitrary molecule - specifically, planes which contain important pharmacophore elements. Relevant code from the 3DNA software package (Nucleic Acids Res. 2003, 37, 5108-5121) was generalized to treat molecular fragments other than DNA bases as input for the calculation of me corresponding rigid-body (or "planes") parameters. These parameters were used to construct feature vectors for a fuzzy relational clustering study of over 700 conformations of a flexible analogue of the dopamine reuptake inhibitor, GBR 12909. Several cluster validity measures were used to determine the optimal number of clusters. Translational (Shift, Slide, Rise) rather than rotational (Tilt, Roll, Twist) features dominate clustering based on planes that are relatively far apart, whereas both types of features are important to clustering when the pair of planes are close by. This approach was able to classify the data set of molecular conformations into groups and to identify representative conformers for use as template conformers in future Comparative Molecular Field Analysis studies of GBR 12909 analogues. The advantage of using the planes parameters, rather than the combination of atomic coordinates and angles between molecular planes used in our previous fuzzy relational clustering of the same data set (J. Chem. Inf. Model. 2005, 45, 610-623), is that the present clustering results are independent of molecular superposition and the technique is able to identify clusters in the molecule considered as a whole. This approach is easily generalizable to any two planes in any molecule.

Original languageEnglish (US)
Pages (from-to)2216-2227
Number of pages12
JournalJournal of Chemical Information and Modeling
Volume47
Issue number6
DOIs
StatePublished - Nov 1 2007

Fingerprint

Dopamine Uptake Inhibitors
Feature extraction
Nucleic acids
Nucleic Acids
Molecules
Conformations
Software packages
DNA
Dopamine
present
vanoxerine
Group

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)
  • Computer Science Applications
  • Library and Information Sciences

Cite this

Banerjee, Amit ; Misra, Milind ; Pai, Deepa ; Shih, Liang Yu ; Woodley, Rohan ; Lu, Xiang Jun ; Srinivasan, A. R. ; Olson, Wilma K. ; Davé, Rajesh N. ; Venanzi, Carol A. / Feature extraction using molecular planes for fuzzy relational clustering of a flexible dopamine reuptake inhibitor. In: Journal of Chemical Information and Modeling. 2007 ; Vol. 47, No. 6. pp. 2216-2227.
@article{fe5cacf84a0f40c8b698bcfc6dc667ca,
title = "Feature extraction using molecular planes for fuzzy relational clustering of a flexible dopamine reuptake inhibitor",
abstract = "Six rigid-body parameters (Shift, Slide, Rise, Tilt, Roll, Twist) are commonly used to describe the relative displacement and orientation of successive base pairs in a nucleic acid structure. The present work adapts this approach to describe the relative displacement and orientation of any two planes in an arbitrary molecule - specifically, planes which contain important pharmacophore elements. Relevant code from the 3DNA software package (Nucleic Acids Res. 2003, 37, 5108-5121) was generalized to treat molecular fragments other than DNA bases as input for the calculation of me corresponding rigid-body (or {"}planes{"}) parameters. These parameters were used to construct feature vectors for a fuzzy relational clustering study of over 700 conformations of a flexible analogue of the dopamine reuptake inhibitor, GBR 12909. Several cluster validity measures were used to determine the optimal number of clusters. Translational (Shift, Slide, Rise) rather than rotational (Tilt, Roll, Twist) features dominate clustering based on planes that are relatively far apart, whereas both types of features are important to clustering when the pair of planes are close by. This approach was able to classify the data set of molecular conformations into groups and to identify representative conformers for use as template conformers in future Comparative Molecular Field Analysis studies of GBR 12909 analogues. The advantage of using the planes parameters, rather than the combination of atomic coordinates and angles between molecular planes used in our previous fuzzy relational clustering of the same data set (J. Chem. Inf. Model. 2005, 45, 610-623), is that the present clustering results are independent of molecular superposition and the technique is able to identify clusters in the molecule considered as a whole. This approach is easily generalizable to any two planes in any molecule.",
author = "Amit Banerjee and Milind Misra and Deepa Pai and Shih, {Liang Yu} and Rohan Woodley and Lu, {Xiang Jun} and Srinivasan, {A. R.} and Olson, {Wilma K.} and Dav{\'e}, {Rajesh N.} and Venanzi, {Carol A.}",
year = "2007",
month = "11",
day = "1",
doi = "10.1021/ci7001632",
language = "English (US)",
volume = "47",
pages = "2216--2227",
journal = "Journal of Chemical Information and Modeling",
issn = "1549-9596",
publisher = "American Chemical Society",
number = "6",

}

Banerjee, A, Misra, M, Pai, D, Shih, LY, Woodley, R, Lu, XJ, Srinivasan, AR, Olson, WK, Davé, RN & Venanzi, CA 2007, 'Feature extraction using molecular planes for fuzzy relational clustering of a flexible dopamine reuptake inhibitor', Journal of Chemical Information and Modeling, vol. 47, no. 6, pp. 2216-2227. https://doi.org/10.1021/ci7001632

Feature extraction using molecular planes for fuzzy relational clustering of a flexible dopamine reuptake inhibitor. / Banerjee, Amit; Misra, Milind; Pai, Deepa; Shih, Liang Yu; Woodley, Rohan; Lu, Xiang Jun; Srinivasan, A. R.; Olson, Wilma K.; Davé, Rajesh N.; Venanzi, Carol A.

In: Journal of Chemical Information and Modeling, Vol. 47, No. 6, 01.11.2007, p. 2216-2227.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Feature extraction using molecular planes for fuzzy relational clustering of a flexible dopamine reuptake inhibitor

AU - Banerjee, Amit

AU - Misra, Milind

AU - Pai, Deepa

AU - Shih, Liang Yu

AU - Woodley, Rohan

AU - Lu, Xiang Jun

AU - Srinivasan, A. R.

AU - Olson, Wilma K.

AU - Davé, Rajesh N.

AU - Venanzi, Carol A.

PY - 2007/11/1

Y1 - 2007/11/1

N2 - Six rigid-body parameters (Shift, Slide, Rise, Tilt, Roll, Twist) are commonly used to describe the relative displacement and orientation of successive base pairs in a nucleic acid structure. The present work adapts this approach to describe the relative displacement and orientation of any two planes in an arbitrary molecule - specifically, planes which contain important pharmacophore elements. Relevant code from the 3DNA software package (Nucleic Acids Res. 2003, 37, 5108-5121) was generalized to treat molecular fragments other than DNA bases as input for the calculation of me corresponding rigid-body (or "planes") parameters. These parameters were used to construct feature vectors for a fuzzy relational clustering study of over 700 conformations of a flexible analogue of the dopamine reuptake inhibitor, GBR 12909. Several cluster validity measures were used to determine the optimal number of clusters. Translational (Shift, Slide, Rise) rather than rotational (Tilt, Roll, Twist) features dominate clustering based on planes that are relatively far apart, whereas both types of features are important to clustering when the pair of planes are close by. This approach was able to classify the data set of molecular conformations into groups and to identify representative conformers for use as template conformers in future Comparative Molecular Field Analysis studies of GBR 12909 analogues. The advantage of using the planes parameters, rather than the combination of atomic coordinates and angles between molecular planes used in our previous fuzzy relational clustering of the same data set (J. Chem. Inf. Model. 2005, 45, 610-623), is that the present clustering results are independent of molecular superposition and the technique is able to identify clusters in the molecule considered as a whole. This approach is easily generalizable to any two planes in any molecule.

AB - Six rigid-body parameters (Shift, Slide, Rise, Tilt, Roll, Twist) are commonly used to describe the relative displacement and orientation of successive base pairs in a nucleic acid structure. The present work adapts this approach to describe the relative displacement and orientation of any two planes in an arbitrary molecule - specifically, planes which contain important pharmacophore elements. Relevant code from the 3DNA software package (Nucleic Acids Res. 2003, 37, 5108-5121) was generalized to treat molecular fragments other than DNA bases as input for the calculation of me corresponding rigid-body (or "planes") parameters. These parameters were used to construct feature vectors for a fuzzy relational clustering study of over 700 conformations of a flexible analogue of the dopamine reuptake inhibitor, GBR 12909. Several cluster validity measures were used to determine the optimal number of clusters. Translational (Shift, Slide, Rise) rather than rotational (Tilt, Roll, Twist) features dominate clustering based on planes that are relatively far apart, whereas both types of features are important to clustering when the pair of planes are close by. This approach was able to classify the data set of molecular conformations into groups and to identify representative conformers for use as template conformers in future Comparative Molecular Field Analysis studies of GBR 12909 analogues. The advantage of using the planes parameters, rather than the combination of atomic coordinates and angles between molecular planes used in our previous fuzzy relational clustering of the same data set (J. Chem. Inf. Model. 2005, 45, 610-623), is that the present clustering results are independent of molecular superposition and the technique is able to identify clusters in the molecule considered as a whole. This approach is easily generalizable to any two planes in any molecule.

UR - http://www.scopus.com/inward/record.url?scp=37249081116&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=37249081116&partnerID=8YFLogxK

U2 - 10.1021/ci7001632

DO - 10.1021/ci7001632

M3 - Article

C2 - 17967005

AN - SCOPUS:37249081116

VL - 47

SP - 2216

EP - 2227

JO - Journal of Chemical Information and Modeling

JF - Journal of Chemical Information and Modeling

SN - 1549-9596

IS - 6

ER -