A method to estimate ease of synthesis (synthetic accessibility) of drug-like molecules is needed in many areas of the drug discovery process. The development and validation of such a method that is able to characterize molecule synthetic accessibility as a score between 1 (easy to make) and 10 (very difficult to make) is described in this article.

The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu.

The identification of small molecules that fall within the biologically relevant subfraction of vast chemical space is of utmost importance to chemical biology and medicinal chemistry research. The prerequirement of biological relevance to be met by such molecules is fulfilled by natural product-derived compound collections. We report a structural classification of natural products (SCONP) as organizing principle for charting the known chemical space explored by nature. SCONP arranges the scaffolds of the natural products in a tree-like fashion and provides a viable analysis- and hypothesis-generating tool for the design of natural product-derived compound collections. The validity of the approach is demonstrated in the development of a previously undescribed class of selective and potent inhibitors of 11β-hydroxysteroid dehydrogenase type 1 with activity in cells guided by SCONP and protein structure similarity clustering. 11β-hydroxysteroid dehydrogenase type 1 is a target in the development of new therapies for the treatment of diabetes, the metabolic syndrome, and obesity.