Literature DB >> 9089432

EVA: a new theoretically based molecular descriptor for use in QSAR/QSPR analysis.

A M Ferguson1, T Heritage, P Jonathon, S E Pack, L Phillips, J Rogan, P J Snaith.   

Abstract

A new descriptor of molecular structure, EVA, for use in the derivation of robustly predictive QSAR relationships is described. It is based on theoretically derived normal coordinate frequencies, and has been used extensively and successfully in proprietary chemical discovery programmes within Shell Research. As a result of informal dissemination of the methodology, it is now being used successfully in related areas such as pharmaceutical drug discovery. Much of the experimental data used in development remain proprietary, and are not available for publication. This paper describes the method and illustrates its application to the calculation of nonproprietary data, log P(ow), in both explanatory and predictive modes. It will be followed by other publications illustrating its application to a range of data derived from biological systems.

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Year:  1997        PMID: 9089432     DOI: 10.1023/a:1008026308790

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  3 in total

1.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.

Authors:  R D Cramer; D E Patterson; J D Bunce
Journal:  J Am Chem Soc       Date:  1988-08-01       Impact factor: 15.419

Review 2.  Multivariate data analysis and experimental design in biomedical research.

Authors:  L Ståhle; S Wold
Journal:  Prog Med Chem       Date:  1988

3.  Cross-validated R2-guided region selection for comparative molecular field analysis: a simple method to achieve consistent results.

Authors:  S J Cho; A Tropsha
Journal:  J Med Chem       Date:  1995-03-31       Impact factor: 7.446

  3 in total
  12 in total

1.  Evaluation of the EVA descriptor for QSAR studies: 3. The use of a genetic algorithm to search for models with enhanced predictive properties (EVA_GA).

Authors:  D B Turner; P Willett
Journal:  J Comput Aided Mol Des       Date:  2000-01       Impact factor: 3.686

2.  Evaluation of a novel molecular vibration-based descriptor (EVA) for QSAR studies: 2. Model validation using a benchmark steroid dataset.

Authors:  D B Turner; P Willett; A M Ferguson; T W Heritage
Journal:  J Comput Aided Mol Des       Date:  1999-05       Impact factor: 3.686

3.  3D-QSAR illusions.

Authors:  Arthur M Doweyko
Journal:  J Comput Aided Mol Des       Date:  2004 Jul-Sep       Impact factor: 3.686

4.  GALAHAD: 1. pharmacophore identification by hypermolecular alignment of ligands in 3D.

Authors:  Nicola J Richmond; Charlene A Abrams; Philippa R N Wolohan; Edmond Abrahamian; Peter Willett; Robert D Clark
Journal:  J Comput Aided Mol Des       Date:  2006-10-19       Impact factor: 3.686

Review 5.  Computer tools in the discovery of HIV-1 integrase inhibitors.

Authors:  Chenzhong Liao; Marc C Nicklaus
Journal:  Future Med Chem       Date:  2010-07       Impact factor: 3.808

6.  Evaluation of a novel infrared range vibration-based descriptor (EVA) for QSAR studies. 1. General application.

Authors:  D B Turner; P Willett; A M Ferguson; T Heritage
Journal:  J Comput Aided Mol Des       Date:  1997-07       Impact factor: 3.686

7.  Molecular fingerprint-based artificial neural networks QSAR for ligand biological activity predictions.

Authors:  Kyaw-Zeyar Myint; Lirong Wang; Qin Tong; Xiang-Qun Xie
Journal:  Mol Pharm       Date:  2012-08-31       Impact factor: 4.939

8.  Ligand biological activity predictions using fingerprint-based artificial neural networks (FANN-QSAR).

Authors:  Kyaw Z Myint; Xiang-Qun Xie
Journal:  Methods Mol Biol       Date:  2015

9.  Modeling MEK4 Kinase Inhibitors through Perturbed Electrostatic Potential Charges.

Authors:  Rama K Mishra; Kristine K Deibler; Matthew R Clutter; Purav P Vagadia; Matthew O'Connor; Gary E Schiltz; Raymond Bergan; Karl A Scheidt
Journal:  J Chem Inf Model       Date:  2019-10-14       Impact factor: 4.956

10.  Classification of drug molecules considering their IC50 values using mixed-integer linear programming based hyper-boxes method.

Authors:  Pelin Armutlu; Muhittin E Ozdemir; Fadime Uney-Yuksektepe; I Halil Kavakli; Metin Turkay
Journal:  BMC Bioinformatics       Date:  2008-10-03       Impact factor: 3.169

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