Drug design using comparative molecular surface analysis

Chemists have eagerly extended a concept of shape into the molecular scale in an attempt to explain molecular effects. Although the molecular surface that shapes a molecule is a fuzzy category, which makes important theoretical problems with its precise interpretation, shape analysis appears to be an efficient method providing an explanation for a variety of effects. Comparative molecular surface analysis (CoMSA) is a three-dimensional quantitative structure–activity relationship (3D QSAR) method used for the comparison of molecular surfaces and shapes. In this review, the authors demonstrate that 3D QSAR basically works as a visualisation tool that investigates molecular similarity and indicates pharmacophoric sites. In this context, CoMSA that is based on the Kohonen self-organising maps that allow the projection of three-dimensional molecular data into two-dimensional maps without topological distortion has an important advantage over the traditional 3D QSAR methods. However, It should be remembered that the majority of the 3D QSAR limitations are still important for this technique and consequently a strategy to use the molecular data to produce drugs in this way still maps a ‘far and bumpy road’.

[1]  Jaroslaw Polanski,et al.  Mapping dye pharmacophores by the Comparative Molecular Surface Analysis (CoMSA): application to heterocyclic monoazo dyes , 2004 .

[2]  J. Gasteiger,et al.  The comparison of molecular surfaces by neural networks and its applications to quantitative structure activity studies , 1998 .

[3]  J. Andrew Grant,et al.  Small Molecule Shape-Fingerprints , 2005, J. Chem. Inf. Model..

[4]  Jaroslaw Polanski,et al.  Modeling Robust QSAR, 2. Iterative Variable Elimination Schemes for CoMSA: Application for Modeling Benzoic Acid pKa Values , 2007, J. Chem. Inf. Model..

[5]  Christian Hofbauer,et al.  SURFCOMP: A Novel Graph-Based Approach to Molecular Surface Comparison , 2004, J. Chem. Inf. Model..

[6]  W. M. Carson,et al.  Drugs by design. , 1993, Scientific American.

[7]  Jaroslaw Polanski,et al.  Self-organizing neural networks for modeling robust 3D and 4D QSAR: application to dihydrofolate reductase inhibitors. , 2004, Molecules.

[8]  Jure Zupan,et al.  Neural networks in chemistry , 1993 .

[9]  M Le Bret,et al.  Modeling of the inhibition of retroviral integrases by styrylquinoline derivatives. , 2000, Journal of medicinal chemistry.

[10]  Johann Gasteiger,et al.  The comparison of geometric and electronic properties of molecular surfaces by neural networks: Application to the analysis of corticosteroid-binding globulin activity of steroids , 1996, J. Comput. Aided Mol. Des..

[11]  Jaroslaw Polanski,et al.  The Comparative Molecular Surface Analysis (CoMSA) with Modified Uniformative Variable Elimination-PLS (UVE-PLS) Method: Application to the Steroids Binding the Aromatase Enzyme. , 2003 .

[12]  P. Dean,et al.  Statistical method for surface pattern-making between dissimilar molecules: electrostatic potentials and accessible surfaces , 1986 .

[13]  Jaroslaw Polanski,et al.  Modeling Robust QSAR , 2006, J. Chem. Inf. Model..

[14]  P. Dean,et al.  Molecular recognition: 3d surface structure comparison by gnomonic , 1987 .

[15]  Jarosław Polański,et al.  A comparative molecular surface analysis (COMSA). A new efficient technique for drug design. , 2002, Acta poloniae pharmaceutica.

[16]  Johann Gasteiger,et al.  Use of the Kohonen neural network for rapid screening of ex vivo anti-HIV activity of styrylquinolines. , 2002, Journal of medicinal chemistry.

[17]  Peter Gedeck,et al.  Reviews in Computational Chemistry, Volume 9 , 1997 .

[18]  Jaroslaw Polanski,et al.  5-Hydroxy-6-Quinaldic Acid as a Novel Molecular Scaffold for HIV-1 Integrase Inhibitors , 2006 .

[19]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[20]  Donald B. Boyd,et al.  Successes of Computer‐Assisted Molecular Design , 2007 .

[21]  A. Hopkins,et al.  Navigating chemical space for biology and medicine , 2004, Nature.

[22]  Thomas G. Dietterich,et al.  Solving the Multiple Instance Problem with Axis-Parallel Rectangles , 1997, Artif. Intell..

[23]  Yvonne C. Martin,et al.  DIRECT PREDICTION OF LINEAR FREE ENERGY SUBSTITUENT EFFECTS FROM 3D STRUCTURES USING COMPARATIVE MOLECULAR FIELD ANALYSIS. I, ELECTRONIC EFFECTS OF SU BSTITUTED BENZOIC ACIDS , 1991 .

[24]  Kimito Funatsu,et al.  New Molecular Surface-based 3D-QSAR Method using Kohonen Neural Network and 3-way PLS , 2002, Comput. Chem..

[25]  Paul G. Mezey,et al.  Shape in Chemistry: An Introduction to Molecular Shape and Topology , 1993 .

[26]  Y. Martin,et al.  PLS analysis of distance matrices to detect nonlinear relationships between biological potency and molecular properties. , 1995, Journal of medicinal chemistry.

[27]  Kimito Funatsu,et al.  Novel Computational Approaches in QSAR and Molecular Design Based on GA, Multi-Way PLS and NN , 2005 .

[28]  Roberto Todeschini,et al.  Handbook of Molecular Descriptors , 2002 .

[29]  P M Dean,et al.  The search for functional correspondences in molecular structure between two dissimilar molecules. , 1985, Journal of theoretical biology.

[30]  Eugene A. Coats,et al.  The CoMFA Steroids as a Benchmark Dataset for Development of 3D QSAR Methods , 1998 .

[31]  Jaroslaw Polanski,et al.  Self-organizing neural networks for pharmacophore mapping. , 2003, Advanced drug delivery reviews.

[32]  Walter M. F. Fabian,et al.  Comparative molecular field analysis (CoMFA) of dye-fibre affinities. Part 2. Symmetrical bisazo dyes , 1996 .

[33]  W RuiterdeG.C.,et al.  Shape in chemistry: An introduction to molecular shape and topology , 1995 .

[34]  B. Masek,et al.  Molecular surface comparisons , 1995 .

[35]  P Schelling,et al.  Endothelin antagonists: discovery of EMD 122946, a highly potent and orally active ETA selective antagonist. , 1998, Bioorganic & medicinal chemistry letters.

[36]  Jaroslaw Polanski,et al.  GRID Formalism for the Comparative Molecular Surface Analysis: Application to the CoMFA Benchmark Steroids, Azo Dyes, and HEPT Derivatives , 2004, J. Chem. Inf. Model..

[37]  J. Mouscadet,et al.  Styrylquinoline derivatives: a new class of potent HIV-1 integrase inhibitors that block HIV-1 replication in CEM cells. , 1998, Journal of medicinal chemistry.

[38]  Barry K. Lavine Electronic van der Waals Surface Property Descriptors and Genetic Algorithms for Developing Structure-Activity Correlations in Olfactory Databases , 2003, J. Chem. Inf. Model..

[39]  P. Dean,et al.  Molecular recognition: optimized searching through rotational 3-space for pattern matches on molecular surfaces , 1987 .

[40]  Ioan Motoc,et al.  Molecular Shape Descriptors , 1983, Steric Effects in Drug Design.

[41]  J Brickmann,et al.  Segmentation of protein surfaces using fuzzy logic. , 1994, Journal of molecular graphics.

[42]  H. Kubinyi Comparative Molecular Field Analysis (CoMFA) , 2002 .

[43]  D. Massart,et al.  Elimination of uninformative variables for multivariate calibration. , 1996, Analytical chemistry.

[44]  Mark J. Embrechts,et al.  New developments in PEST shape/property hybrid descriptors , 2003, J. Comput. Aided Mol. Des..

[45]  Jaroslaw Polanski,et al.  The Comparative Molecular Surface Analysis (COMSA): A Novel Tool for Molecular Design , 2000, Comput. Chem..

[46]  O. Ivanciuc,et al.  Comparative Receptor Surface Analysis (CoRSA) Model for Calcium Channel Antagonists , 2001, SAR and QSAR in environmental research.

[47]  J Polański,et al.  The Non-Grid Technique for Modeling 3D QSAR Using Self-Organizing Neural Network (SOM) and PLS Analysis: Application to Steroids and Colchicinoids , 2000, SAR and QSAR in environmental research.

[48]  Jaroslaw Polanski,et al.  The Comparative Molecular Surface Analysis (COMSA) - A Nongrid 3D QSAR Method by a Coupled Neural Network and PLS System: Predicting pKa Values of Benzoic and Alkanoic Acids , 2002, J. Chem. Inf. Comput. Sci..

[49]  J Polanski,et al.  Self-organizing neural networks for screening and development of novel artificial sweetener candidates. , 2000, Combinatorial chemistry & high throughput screening.

[50]  M Le Bret,et al.  Tautomers of styrylquinoline derivatives containing a methoxy substituent: computation of their population in aqueous solution and their interaction with RSV integrase catalytic core. , 2000, Acta biochimica Polonica.

[51]  Stu Borman IMPROVING EFFICIENCY: To eliminate R&D bottlenecks, drug companies are evaluating all phases of discovery and development and are using novel approaches to speed them up , 2006 .

[52]  J. Zupan,et al.  REPRESENTATION OF MOLECULAR ELECTROSTATIC POTENTIALS BY TOPOLOGICAL FEATURE MAPS , 1994 .

[53]  R M Stroud,et al.  Crystal structure of the HIV-1 integrase catalytic core and C-terminal domains: a model for viral DNA binding. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[54]  Jens Sadowski,et al.  The Use of Self-organizing Neural Networks in Drug Design , 2002 .

[55]  Nobuo Shimma,et al.  3D-QSAR study of antifungal N-myristoyltransferase inhibitors by comparative molecular surface analysis , 2003 .

[56]  Stu Borman DRUGS BY DESIGN: With little fanfare, structure-based drug design is filling development pipelines , 2005 .

[57]  M. G. Finn,et al.  Click Chemistry: Diverse Chemical Function from a Few Good Reactions. , 2001, Angewandte Chemie.

[58]  Jaroslaw Polanski,et al.  Modeling Robust QSAR. 1. Coding Molecules in 3D-QSAR - from a Point to Surface Sectors and Molecular Volumes , 2005, J. Chem. Inf. Model..

[59]  Hicham Fenniri Combinatorial chemistry : a practical approach , 2000 .

[60]  P Finn,et al.  Molecular surface comparison: application to drug design. , 1993, Journal of molecular graphics.

[61]  Gustavo A. Arteca,et al.  Molecular Shape Descriptors , 2007 .

[62]  A. Hopfinger,et al.  Construction of 3D-QSAR Models Using the 4D-QSAR Analysis Formalism , 1997 .

[63]  M Le Bret,et al.  Structure-activity relationships and binding mode of styrylquinolines as potent inhibitors of HIV-1 integrase and replication of HIV-1 in cell culture. , 2000, Journal of medicinal chemistry.

[64]  Jaroslaw Polanski,et al.  Probability issues in molecular design: predictive and modeling ability in 3D-QSAR schemes. , 2004, Combinatorial chemistry & high throughput screening.

[65]  J. Gasteiger,et al.  Mapping the Electrostatic Potential of Muscarinic and Nicotinic Agonists with Artificial Neural Networks , 1994 .

[66]  F E Blaney,et al.  Molecular surface comparison. 2. Similarity of electrostatic vector fields in drug design. , 1995, Journal of molecular graphics.

[67]  S. Anzali,et al.  Endothelin antagonists: search for surrogates of methylendioxyphenyl by means of a Kohonen neural network. , 1998, Bioorganic & medicinal chemistry letters.

[68]  C. Jun,et al.  Performance of some variable selection methods when multicollinearity is present , 2005 .

[69]  Johann Gasteiger,et al.  Neural networks in chemistry and drug design , 1999 .

[70]  T. W. Barlow Self-organizing maps and molecular similarity. , 1995, Journal of molecular graphics.

[71]  Jaroslaw Polanski,et al.  Modeling Steric and Electronic Effects in 3D- and 4D-QSAR Schemes: Predicting Benzoic pKa Values and Steroid CBG Binding Affinities , 2003, J. Chem. Inf. Comput. Sci..

[72]  J. Gasteiger,et al.  Autocorrelation of Molecular Surface Properties for Modeling Corticosteroid Binding Globulin and Cytosolic Ah Receptor Activity by Neural Networks , 1995 .

[73]  J Polański,et al.  Self-organizing neural network for modeling 3D QSAR of colchicinoids. , 2000, Acta biochimica Polonica.

[74]  S. Wold,et al.  Partial Least Squares Projections to Latent Structures (PLS) in Chemistry , 2002 .

[75]  Tomasz Magdziarz,et al.  3D QSAR study of hypolipidemic asarones by comparative molecular surface analysis. , 2006, Bioorganic & medicinal chemistry.

[76]  R. Cramer,et al.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. , 1988, Journal of the American Chemical Society.

[77]  A. N. Jain,et al.  Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark. , 1994, Journal of medicinal chemistry.

[78]  Walter M. F. Fabian,et al.  Comparative Molecular Field Analysis of Heterocyclic Monoazo Dye-Fiber Affinities , 1998, J. Chem. Inf. Comput. Sci..

[79]  Walter M. F. Fabian,et al.  Comparative molecular field analysis (CoMFA), semiempirical (AM1) molecular orbital and multiconformational minimal steric difference (MTD) calculations of anthraquinone dye-fibre affinities , 1995 .

[80]  Jaroslaw Polanski,et al.  Comparative Molecular Surface Analysis (CoMSA) for Modeling Dye—Fiber Affinities of the Azo and Anthraquinone Dyes. , 2004 .