A comparative analysis of the molecular topologies for drugs, clinical candidates, natural products, human metabolites and general bioactive compounds

Natural Products (NPs) and their subset Human Metabolites (HMs) are synthesized in living organisms and, due to their biogenic nature, can be used as starting points for drug discovery projects as well as a source of inspiration for designing new chemical libraries. It is therefore of interest to characterize NPs and HMs in relation to other types of molecules relevant for drug discovery. In this study, a comparative analysis of the molecular topologies was carried out for NPs, HMs, drugs from different time periods, clinical candidates and general bioactive compounds. It is shown that the NP and HM sets have the highest percentage of compounds with only one ring system. NPs have also the highest Ring System Complexity (RSC) of the compared datasets, while general bioactive compounds have the largest number of ring systems. The difference in molecular topology between the datasets is independent of the molecular size and lipophilicity. Further analysis of topological descriptors shows that NPs and HMs have a larger proportion of side chain atoms in relation to their size and have a higher proportion of aliphatic carbons (indicating a more three-dimensional shape) than compounds from the other sets.

[1]  W. Sneader.  Drug prototypes and their exploitation , 1996 .

[2]  T. Ritchie,et al.  The impact of aromatic ring count on compound developability--are too many aromatic rings a liability in drug design? , 2009, Drug discovery today.

[3]  Brian K. Shoichet,et al.  ZINC - A Free Database of Commercially Available Compounds for Virtual Screening , 2005, J. Chem. Inf. Model..

[4]  R. Abagyan,et al.  METLIN: A Metabolite Mass Spectral Database , 2005, Therapeutic drug monitoring.

[5]  D. Kell,et al.  'Metabolite-likeness' as a criterion in the design and selection of pharmaceutical drug libraries. , 2009, Drug discovery today.

[6]  Nigel W. Hardy,et al.  MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics , 2006, BMC Bioinformatics.

[7]  P. Greenwood,et al.  A Guide to Chi-Squared Testing , 1996 .

[8]  Varun Khanna,et al.  Physiochemical property space distribution among human metabolites, drugs and toxins , 2009, BMC Bioinformatics.

[9]  Tudor I. Oprea,et al.  Is There a Difference between Leads and Drugs? A Historical Perspective , 2001, J. Chem. Inf. Comput. Sci..

[10]  Bernard H. Munos,et al.  How to Revive Breakthrough Innovation in the Pharmaceutical Industry , 2011, Science Translational Medicine.

[11]  Ola Engkvist,et al.  Molecular Topology Analysis of the Differences between Drugs, Clinical Candidate Compounds, and Bioactive Molecules , 2010, J. Chem. Inf. Model..

[12]  Tudor I. Oprea,et al.  Novel chemical space exploration via natural products. , 2009, Journal of medicinal chemistry.

[13]  G. Bemis,et al.  The properties of known drugs. 1. Molecular frameworks. , 1996, Journal of medicinal chemistry.

[14]  D. Newman,et al.  Natural products as sources of new drugs over the last 25 years. , 2007, Journal of natural products.

[15]  P. Leeson,et al.  The influence of drug-like concepts on decision-making in medicinal chemistry , 2007, Nature Reviews Drug Discovery.

[16]  David Rogers,et al.  Extended-Connectivity Fingerprints , 2010, J. Chem. Inf. Model..

[17]  Thierry Kogej,et al.  Physicochemical property profiles of marketed drugs, clinical candidates and bioactive compounds. , 2009, Bioorganic & medicinal chemistry letters.

[18]  Paul D. Leeson,et al.  Impact of ion class and time on oral drug molecular properties , 2011 .

[19]  A. Ganesan.  The impact of natural products upon modern drug discovery. , 2008, Current opinion in chemical biology.

[20]  Lynda B. M. Ellis,et al.  The University of Minnesota Biocatalysis/Biodegradation Database: the first decade , 2005, Nucleic Acids Res..

[21]  Thomas Henkel,et al.  Statistical Investigation into the Structural Complementarity of Natural Products and Synthetic Compounds. , 1999, Angewandte Chemie.

[22]  J. Gasteiger,et al.  Enabling the exploration of biochemical pathways. , 2004, Organic & biomolecular chemistry.

[23]  M. Butler.  Natural products to drugs: natural product-derived compounds in clinical trials. , 2005, Natural product reports.

[24]  Artem Cherkasov,et al.  Comparative QSAR- and Fragments Distribution Analysis of Drugs, Druglikes, Metabolic Substances, and Antimicrobial Compounds , 2006, J. Chem. Inf. Model..

[25]  W. Guida,et al.  The art and practice of structure‐based drug design: A molecular modeling perspective , 1996, Medicinal research reviews.

[26]  Miklos Feher,et al.  Property Distributions: Differences between Drugs, Natural Products, and Molecules from Combinatorial Chemistry , 2003, J. Chem. Inf. Comput. Sci..

[27]  Wei Lu,et al.  Do Biologically Relevant Compounds Have More Chance To Be Drugs? , 2009, J. Chem. Inf. Model..

[28]  C. Humblet,et al.  Escape from flatland: increasing saturation as an approach to improving clinical success. , 2009, Journal of medicinal chemistry.

[29]  Catherine Brooksbank,et al.  The European Bioinformatics Institute's data resources: towards systems biology , 2004, Nucleic Acids Res..

[30]  Sunil Gupta,et al.  Comparing the chemical spaces of metabolites and available chemicals: models of metabolite-likeness , 2007, Molecular Diversity.

[31]  P. Leeson,et al.  A comparison of physiochemical property profiles of development and marketed oral drugs. , 2003, Journal of medicinal chemistry.

[32]  Ying Zhang,et al.  HMDB: the Human Metabolome Database , 2007, Nucleic Acids Res..

[33]  Michal Vieth,et al.  Dependence of molecular properties on proteomic family for marketed oral drugs. , 2006, Journal of medicinal chemistry.

[34]  G. Schneider,et al.  Scaffold architecture and pharmacophoric properties of natural products and trade drugs: application in the design of natural product-based combinatorial libraries. , 2001, Journal of combinatorial chemistry.

[35]  Peter Murray-Rust,et al.  MACiE: a database of enzyme reaction mechanisms , 2005, Bioinform..

[36]  D. Swinney,et al.  How were new medicines discovered? , 2011, Nature Reviews Drug Discovery.

[37]  S. Muresan,et al.  Investigation of the relationship between topology and selectivity for druglike molecules. , 2010, Journal of medicinal chemistry.

[38]  Nigel W. Hardy,et al.  A proposed framework for the description of plant metabolomics experiments and their results , 2004, Nature Biotechnology.

[39]  Dietrich Rebholz-Schuhmann,et al.  Facilitating the development of controlled vocabularies for metabolomics technologies with text mining , 2008, BMC Bioinformatics.

[40]  W Patrick Walters,et al.  What do medicinal chemists actually make? A 50-year retrospective. , 2011, Journal of medicinal chemistry.

[41]  S A Kulkarni,et al.  In silico techniques for the study and prediction of xenobiotic metabolism: A review , 2005, Xenobiotica; the fate of foreign compounds in biological systems.

[42]  Peter Ertl,et al.  Natural Product-likeness Score and Its Application for Prioritization of Compound Libraries , 2008, J. Chem. Inf. Model..

[43]  Kiyoko F. Aoki-Kinoshita,et al.  From genomics to chemical genomics: new developments in KEGG , 2005, Nucleic Acids Res..