The similarity principle - New trends and applications in ligand-based drug discovery and ADMET profiling

Scientia Pharmaceutica

Volumn 76, Issue 1, 2008, Pages 5-18

  Schwaha, Rita ^a   Ecker, Gerhard F ^a  

^a UNIVERSITY OF VIENNA   (Austria)

Author keywords

In silico screening; Pharmacological activity profiling; Shape similarity; Similarity calculation

Indexed keywords

CHLORPROMAZINE;

CHEMICAL STRUCTURE; DRUG DESIGN; DRUG DEVELOPMENT; DRUG DISCOVERY; DRUG MECHANISM; DRUG PENETRATION; DRUG SCREENING; DRUG SOLUBILITY; REVIEW;

EID: 42249098892     PISSN: 00368709     EISSN: 22180532     Source Type: Journal    
DOI: 10.3797/scipharm.0802-05     Document Type: Review

References (26)

1. Kubinyi H, Hamprecht FA, Mietzner T. Three-Dimensional Quantitative Similarity-Activity Relationships (3D QSiAR) from SEAL Similarity Matrices. J Med Chem. 1998; 41: 2553-2564. [doi:10.1021/jm970732a]
2. Oprea TI, Gottfries J. Chemography: The Art of Navigating in Chemical Space. J Comb Chem. 2001; 3: 157-166. [doi:10.1021/cc0000388]
3. Oprea TI, Zamora I, Ungell AL. Pharmacokinetically Based Mapping Device for Chemical Space Navigation. J Comb Chem. 2002; 4: 258-266. [doi:10.1021/cc010093w]
4. Koehler RT, Dixon SL, Villar HO. LASSOO: A Generalized Directed Diversity Approach to the Design and Enrichment of Chemical Libraries. J Med Chem. 1999; 42: 4695-4704. [doi:10.1021/jm990312g]
5. st ed. Volume 32. Weinheim: Wiley-VCH; 2006.
6. Seri-Levy A, West S, Richards WG. Molecular Similarity, Quantitative Chirality, and QSAR for Chiral Drugs. J Med Chem. 1994; 37: 1727-1732. [doi:10.1021/jm00037a025]
7. Ghuloum AM, Sage CR, Jain AN. Molecular Hashkeys: A Novel Method for Molecular Characterization and Its Application for Predicting Important Pharmaceutical Properties of Molecules. J Med Chem. 1999; 42: 1739-1748. [doi:10.1021/jm980527a]
8. Klein C, Kaiser D, Kopp S, Chiba P, Ecker GF. Similarity based SAR (SIBAR) as tool for early ADME profiling. J Comput-Aided Mol Des. 2002; 16: 785-793. [doi:10.1023/A:1023828527638]
9. Zdrazil B, Kaiser D, Kopp S, Chiba P, Ecker GF. Similarity-Based Descriptors (SIBAR) as Tool for QSAR Studies on PGlycoprotein Inhibitors: Influence of the Reference Set. QSAR Comb Sci. 2007; 26: 669-678. [doi:10.1002/qsar.200610149]
10. st Spring National Meeting; Atlanta: ACS; 2006.
11. Mestres J, Rohrer DC, Maggiora GM. A molecular field-based similarity approach to pharmacophoric pattern recognition. J Mol Graphics Modell. 1997; 15: 114-121. [doi:10.1016/S1093-3263(97)00003-X]
12. De Càceres M, Villà J, Lozano JJ, Sanz F. MIPSIM: similarity analysis of molecular interaction potentials. Bioinformatics. 2000; 16: 568-569. [doi:10.1093/bioinformatics/16.6.568]
13. Barbany M, Gutiérrez-de-Terán H, Sanz F, Villà-Freixa J. Towards a MIP-based alignment and docking in computer-aided drug design. Proteins: Struct, Funct, Bioinf. 2004; 56: 585-594. [doi:10.1002/prot.20153]
14. Jain AN. Ligand-Based Structural Hypotheses for Virtual Screening. J Med Chem. 2004; 47: 947-961. [doi:10.1021/jm030520f]
15. Masek BB, Merchant A, Matthew JB. Molecular shape comparison of angiotensin II receptor antagonists. J Med Chem. 1993; 36: 1230-1238. [doi:10.1021/jm00061a014]
16. Rush TS, Grant JA, Mosyak L, Nicholls A. A Shape-Based 3-D Scaffold Hopping Method and Its Application to a Bacterial Protein-Protein Interaction. J Med Chem. 2005; 48: 1489-1495. [doi:10.1021/jm040163o]
17. Gregori-Puigjane E, Mestres J. SHED: Shannon Entropy Descriptors from Topological Feature Distributions. J Chem Inf Model. 2006; 46: 1615-1622. [doi:10.1021/ci0600509]
18. Mestres J, Martin-Couce L, Gregori-Puigjane E, Cases M, Boyer S. Ligand-Based Approach to In Silico Pharmacology: Nuclear Receptor Profiling. J Chem Inf Model. 2006; 46: 2725-2736. [doi:10.1021/ci600300k]
19. Cleves AE, Jain AN. Robust Ligand-Based Modeling of the Biological Targets of Known Drugs. J Med Chem. 2006; 49: 2921-2938. [doi:10.1021/jm051139t]
20. Keiser MJ, Roth BL, Armbruster BN, Ernsberger P, Irwin JJ, Shoichet BK. Relating protein pharmacology by ligand chemistry. Nat Biotechol. 2007; 25: 197-206. [doi:10.1038/nbt1284]
21. Vidal D, Thormann M, Pons M. LINGO, an Efficient Holographic Text Based Method To Calculate Biophysical Properties and Intermolecular Similarities. J Chem Inf Model. 2005; 45: 386-393. [doi:10.1021/ci0496797]
22. Thormann M, Vidal D, Almstetter M, Pons M. Nomen Est Omen: Quantitative Prediction of Molecular Properties Directly from IUPAC Names. Open Appl Inf J. 2007; 1: 28-32. [doi:10.2174/1874136300701010028]
23. McGaughey GB, Sheridan RP, Bayly CI, Culberson JC, Kreatsoulas C, Lindsley S, Maiorov V, Truchon JF, Cornell WD. Comparison of Topological, Shape, and Docking Methods in Virtual Screening. J Chem Inf Model. 2007; 47: 1504-1519. [doi:10.1021/ci700052x]
24. Nicholls A, MacCuish NE, MacCuish JD. Variable selection and model validation of 2D and 3D molecular descriptors. J Comput-Aided Mol Des. 2004; 18: 451-474. [doi: 10.1007/s10822-004-5202-8]
25. Watson P. Naive Bayes Classification Using 2D Pharmacophore Feature Triplet Vectors. J Chem Inf Model. 2008; 48: 166-178. [doi:10.1021/ci7003253]
26. Fontaine F, Bolton E, Borodina Y, Bryant S. Fast 3D shape screening of large chemical databases through alignmentrecycling. Chem Cent J; 2007; 1: 12. [doi:10.1186/1752-153X-1-12]