Improved approach for proteochemometrics modeling: Application to organic compound - Amine G protein-coupled receptor interactions

Bioinformatics

Volumn 21, Issue 23, 2005, Pages 4289-4296

  Lapinsh, Maris ^a   Prusis, Peteris ^a   Uhlén, Staffan ^a   Wikberg, Jarl E S ^a  

^a UPPSALA UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ADRENERGIC RECEPTOR; AMINE; ANTIDEPRESSANT AGENT; ANTIHISTAMINIC AGENT; ANTIPARKINSON AGENT; ARIPIPRAZOLE; CHLORPROMAZINE; CHOLINERGIC RECEPTOR; CLOZAPINE; DOPAMINE RECEPTOR; FLUPHENAZINE; G PROTEIN COUPLED RECEPTOR; HALOPERIDOL; HISTAMINE RECEPTOR; LIGAND; MUSCARINIC RECEPTOR; NEUROLEPTIC AGENT; OLANZAPINE; ORGANIC COMPOUND; PSYCHOTROPIC AGENT; RISPERIDONE; SEROTONIN RECEPTOR;

ARTICLE; BINDING AFFINITY; BIOTECHNOLOGY; CHEMICAL MODEL; DRUG RECEPTOR BINDING; DRUG SELECTIVITY; MOLECULAR INTERACTION; PREDICTION; PRIORITY JOURNAL; PROTEIN FAMILY; PROTEIN INTERACTION; PROTEOMICS;

EID: 28444472402     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/bti703     Document Type: Article

References (21)

1. Baldwin,J.M. et al. (1997) An alpha-carbon template for the transmembrane helices in the rhodopsin family of G-protein-coupled receptors. J. Mol. Biol., 272, 144-164.
2. Baroni,M. et al. (1993) Generating optimal linear PLS estimations (GOLPE): An advanced chemometric tool for handling 3D-QSAR problems. Quant. Struct.-Act. Relat., 12, 9-20.
3. Bikker,J.A. et al. (1998) G-Protein coupled receptors: Models, mutagenesis, and drug design. J. Med. Chem., 41, 2911-2927.
4. Eriksson,L. and Johansson,E. (1996) Multivariate design and modeling in QSAR. Chemom. Intell. Lab., 34, 1-19.
5. Fontaine,F. et al. (2004) Incorporating molecular shape into the alignment-free GRid-INdependent descriptors. J. Med. Chem., 47, 2805-2825.
6. Geladi,P. and Kowalski,B.R. (1986) Partial least-squares regression: A tutorial. Anal. Chim. Acta, 185, 1-17.
7. Jacoby,E. et al. (1999) A three binding site hypothesis for the interaction of ligands with monoamine G protein-coupled receptors: implications for combinatorial ligand design. Quant. Struct.-Act. Relat., 18, 561-572.
8. Kastenholz,M.A. et al. (2000) GRID/CPCA: A new computational tool to design selective ligands. J. Med. Chem., 43, 3033-3044.
9. Lapinsh,M. et al. (2001) Development of proteo-chemometrics: A novel technology for the analysis of drug-receptor interactions. Biochim. Biophys. Acta, 1525, 180-190.
10. Lapinsh,M. et al. (2002a) Classification of G-protein coupled receptors by alignment-independent extraction of principal chemical properties of primary amino acid sequences. Protein Sci., 11, 795-805.
11. Lapinsh,M. et al. (2002b) Proteo-chemometrics modeling of the interaction of amine G-protein coupled receptors with a diverse set of ligands. Mol. Pharm., 61, 1465-1475.
12. Lapinsh,M. et al. (2005) Proteochemometric mapping of the interaction of organic compounds with melanocortin receptor subtypes. Mol. Pharm., 67, 50-59.
13. Pastor,M. et al. (2000) GRid-INdependent descriptors (GRIND): A novel class of alignment-independent three-dimensional molecular descriptors. J. Med. Chem., 43, 3233-3243.
14. Prusis,P. et al. (2001) PLS modeling of chimeric MS04/MSH-peptide and MC1/MC3-receptor interactions reveals a novel method for the analysis of ligand-receptor interactions. Biochim. Biophys. Acta., 1544, 350-357.
15. Prusis,P. et al. (2002) Proteo-chemometrics analysis of MSH peptide binding to melanocortin receptors. Protein Eng., 15, 305-311.
16. Sadowski,J. and Gasteiger,J. (1994) Comparison of automatic three-dimensional model builders using 639 X-ray structures. J. Chem. Inf. Comput. Sci., 34, 1000-1008.
17. Sandberg,M. et al. (1998) New chemical descriptors relevant for the design of biologically active peptides. A multivariate characterization of 87 amino acids. J. Med. Chem., 41, 2481-2491.
18. Wikberg,J.E.S. et al. (2003) Melanocortin receptors: Ligands and proteochemometrics modeling. Ann. N. Y. Acad. Sci., 994, 21-26.
19. Wikberg,J.E.S., Lapinsh,M. and Prusis,P. (2004) Proteochemometrics: A tool for modeling the molecular interaction space. In Kubinyi,H. and Müller,G. (eds), Chemogenomics in Drug Discovery - A Medicinal Chemistry Perspective. Wiley-VCH, Weinheim, pp. 289-309.
20. Wold,S. et al. (1987) Principal component analysis. Chemom. Intell. Lab., 2, 37-52.
21. Wold,S. (1995) PLS for multivariate linear modeling. In van de Waterbeemd,H. (ed.), Chemometric Methods in Molecular Design. VCH, Weinheim, Germany, pp. 195-218.