Properties and Architecture of Drugs and Natural Products Revisited

Computer-based analysis revealed that natural products exhibit a remarkable structural diversity of molecular frameworks and scaffolds that could be systematically exploited for combinatorial synthesis. Natural products offer a rich pool of unique molecular frameworks that complement "drug space". They possess desirable druglike properties rendering them ideal starting points for molecular design considerations. This review provides an overview of chemotype diversity and molecular properties of collections of drugs and druglike molecules, pure natural products, and natural product- derived compounds. Compared to druglike molecules, pure natural products contain more oxygen atoms and chiral cen- ters, and have less aromatic atoms on average. Among the natural product library we identified more than one thousand scaffolds that were not contained in any other compound set analyzed. This outcome provides a basis for the design of new natural product-derived compound libraries. Our study demonstrates that computational chemical biology can assist in finding suitable molecular entities in collections of natural products for drug discovery.

[1]  Z. Khalil,et al.  Drugs from the sea: conotoxins as drug leads for neuropathic pain and other neurological conditions. , 2003, Mini reviews in medicinal chemistry.

[2]  A Ganesan,et al.  Natural products and combinatorial chemistry: back to the future. , 2004, Current opinion in chemical biology.

[3]  Y. Martin,et al.  A bioavailability score. , 2005, Journal of medicinal chemistry.

[4]  Herbert Waldmann,et al.  Discovery of protein phosphatase inhibitor classes by biology-oriented synthesis. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Gisbert Schneider,et al.  Collection of bioactive reference compounds for focused library design , 2003 .

[6]  Tudor I. Oprea,et al.  Property distribution of drug-related chemical databases* , 2000, J. Comput. Aided Mol. Des..

[7]  Herbert Waldmann,et al.  Natural product guided compound library development. , 2002, Current medicinal chemistry.

[8]  Leach,et al.  The in silico world of virtual libraries. , 2000, Drug discovery today.

[9]  F. Koehn,et al.  The evolving role of natural products in drug discovery , 2005, Nature Reviews Drug Discovery.

[10]  Gang Chen,et al.  A New Rapid and Effective Chemistry Space Filter in Recognizing a Druglike Database , 2005, J. Chem. Inf. Model..

[11]  J. Proudfoot Drugs, leads, and drug-likeness: an analysis of some recently launched drugs. , 2002, Bioorganic & medicinal chemistry letters.

[12]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. , 2001, Advanced drug delivery reviews.

[13]  Petra Schneider,et al.  De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks , 2000, J. Comput. Aided Mol. Des..

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

[15]  Reza Fathi,et al.  Diversity oriented synthesis and branching reaction pathway to generate natural product-like compounds. , 2003, Current medicinal chemistry.

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

[17]  E. Fattorusso,et al.  Chemical diversity of bioactive marine natural products: an illustrative case study. , 2004, Current medicinal chemistry.

[18]  Jonathan J. Lewis,et al.  T-cell responses against tyrosinase 368-376(370D) peptide in HLA*A0201+ melanoma patients: randomized trial comparing incomplete Freund's adjuvant, granulocyte macrophage colony-stimulating factor, and QS-21 as immunological adjuvants. , 2002, Clinical cancer research : an official journal of the American Association for Cancer Research.

[19]  Gordon M. Crippen,et al.  Prediction of Physicochemical Parameters by Atomic Contributions , 1999, J. Chem. Inf. Comput. Sci..

[20]  J. Bajorath,et al.  Distribution of Molecular Scaffolds and R-Groups Isolated from Large Compound Databases , 1999 .

[21]  Herbert Waldmann,et al.  Protein structure similarity clustering and natural product structure as guiding principles in drug discovery. , 2005, Drug discovery today.

[22]  Hong Liang,et al.  Three Antitumor Saponins from Albizia julibrissin. , 2006 .

[23]  P. Wright,et al.  The current status of natural products from marine fungi and their potential as anti-infective agents , 2006, Journal of Industrial Microbiology and Biotechnology.

[24]  Hong Liang,et al.  Three anti-tumor saponins from Albizia julibrissin. , 2006, Bioorganic & medicinal chemistry letters.

[25]  D. Faulkner Marine natural products. , 2000, Natural product reports.

[26]  C. Kensil,et al.  Separation and characterization of saponins with adjuvant activity from Quillaja saponaria Molina cortex. , 1991, Journal of immunology.

[27]  H. van de Waterbeemd,et al.  ADMET in silico modelling: towards prediction paradise? , 2003, Nature reviews. Drug discovery.

[28]  S. Kehraus,et al.  Natural Products from Marine Organisms and Their Associated Microbes , 2006, Chembiochem : a European journal of chemical biology.

[29]  Derek S. Tan,et al.  Current progress in natural product-like libraries for discovery screening. , 2004, Combinatorial chemistry & high throughput screening.

[30]  Stephen R. Johnson,et al.  Molecular properties that influence the oral bioavailability of drug candidates. , 2002, Journal of medicinal chemistry.

[31]  J. Huisman The Netherlands , 1996, The Lancet.

[32]  P. Selzer,et al.  Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties. , 2000, Journal of medicinal chemistry.

[33]  S. Fox,et al.  High-Throughput Screening: Searching for Higher Productivity , 2004, Journal of biomolecular screening.

[34]  Didier Rognan,et al.  Assessing the Scaffold Diversity of Screening Libraries , 2006, J. Chem. Inf. Model..

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

[36]  BING LIU,et al.  SARS‐CoV protease inhibitors design using virtual screening method from natural products libraries , 2005, J. Comput. Chem..

[37]  Oliver Schwarz,et al.  Natural products in combinatorial chemistry: an andrographolide-based library. , 2006, Journal of combinatorial chemistry.

[38]  C. Lipinski Drug-like properties and the causes of poor solubility and poor permeability. , 2000, Journal of pharmacological and toxicological methods.

[39]  Jens Sadowski,et al.  Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification , 2003, J. Chem. Inf. Comput. Sci..

[40]  A. Maureen Rouhi,et al.  Rediscovering natural products , 2003 .

[41]  D J Newman,et al.  Natural products in drug discovery and development. , 1997, Journal of natural products.

[42]  Daniela Barlocco,et al.  Privileged structures as leads in medicinal chemistry. , 2006, Current medicinal chemistry.

[43]  Brian Hudson,et al.  Strategic Pooling of Compounds for High-Throughput Screening , 1999, J. Chem. Inf. Comput. Sci..

[44]  G. Schneider,et al.  Virtual Screening for Bioactive Molecules , 2000 .

[45]  D. Faulkner Highlights of Marine Natural Products Chemistry (1972‐1999) , 2000 .

[46]  Jing Lei,et al.  A Marine Natural Product Database , 2002, J. Chem. Inf. Comput. Sci..

[47]  David J Newman,et al.  Natural products as sources of new drugs over the period 1981-2002. , 2003, Journal of natural products.

[48]  David J Newman,et al.  Natural product extracts of plant and marine origin having antileukemia potential. The NCI experience. , 2006, Journal of natural products.

[49]  G. Roth,et al.  Combinatorial synthesis of natural product-like molecules using a first-generation spiroketal scaffold. , 2002, Journal of combinatorial chemistry.