In most cheminformatics workflows, chemical information is stored in files which provide the necessary data for subsequent calculations. The correct interpretation of the file formats is an important prerequisite to obtain meaningful results. Consistent reading of molecules from files, however, is not an easy task. Each file format implicitly represents an underlying chemical model, which has to be taken into consideration when the input data is processed. Additionally, many data sources contain invalid molecules. These have to be identified and either corrected or discarded. We present the chemical file format converter NAOMI, which provides efficient procedures for reliable handling of molecules from the common chemical file formats SDF, MOL2, and SMILES. These procedures are based on a consistent chemical model which has been designed for the appropriate representation of molecules relevant in the context of drug discovery. NAOMI's functionality is tested by round robin file IO exercises with public data sets, which we believe should become a standard test for every cheminformatics tool.

The analysis of small molecule crystal structures is a common way to gather valuable information for drug development. The necessary structural data is usually provided in specific file formats containing only element identities and three-dimensional atomic coordinates as reliable chemical information. Consequently, the automated perception of molecular structures from atomic coordinates has become a standard task in cheminformatics. The molecules generated by such methods must be both chemically valid and reasonable to provide a reliable basis for subsequent calculations. This can be a difficult task since the provided coordinates may deviate from ideal molecular geometries due to experimental uncertainties or low resolution. Additionally, the quality of the input data often differs significantly thus making it difficult to distinguish between actual structural features and mere geometric distortions. We present a method for the generation of molecular structures from atomic coordinates based on the recently published NAOMI model. By making use of this consistent chemical description, our method is able to generate reliable results even with input data of low quality. Molecules from 363 Protein Data Bank (PDB) entries could be perceived with a success rate of 98%, a result which could not be achieved with previously described methods. The robustness of our approach has been assessed by processing all small molecules from the PDB and comparing them to reference structures. The complete data set can be processed in less than 3 min, thus showing that our approach is suitable for large scale applications.

Working with small‐molecule datasets is a routine task for cheminformaticians and chemists. The analysis and comparison of vendor catalogues and the compilation of promising candidates as starting points for screening campaigns are but a few very common applications. The workflows applied for this purpose usually consist of multiple basic cheminformatics tasks such as checking for duplicates or filtering by physico‐chemical properties. Pipelining tools allow to create and change such workflows without much effort, but usually do not support interventions once the pipeline has been started. In many contexts, however, the best suited workflow is not known in advance, thus making it necessary to take the results of the previous steps into consideration before proceeding.To support intuition‐driven processing of compound collections, we developed MONA, an interactive tool that has been designed to prepare and visualize large small‐molecule datasets. Using an SQL database common cheminformatics tasks such as analysis and filtering can be performed interactively with various methods for visual support. Great care was taken in creating a simple, intuitive user interface which can be instantly used without any setup steps. MONA combines the interactivity of molecule database systems with the simplicity of pipelining tools, thus enabling the case‐to‐case application of chemistry expert knowledge. The current version is available free of charge for academic use and can be downloaded at http://www.zbh.uni‐hamburg.de/mona.

No abstract

The synthesis of the title compounds (1) was achieved in two steps starting from readily available 2,4-dibromothiazole (2). In a regioselective Pd(0)-catalyzed cross-coupling step, compound 2 was converted into a variety of 2-substituted 4-bromothiazoles 3 (10 examples, 65-85% yield). Alkyl and aryl zinc halides were employed as nucleophiles to introduce an alkyl or aryl substituent. The Sonogashira protocol was followed to achieve an alkynyl-debromination. Bromo-lithium exchange at carbon atom C-4 and subsequent transmetalation to zinc or tin converted the 4-bromothiazoles 3 into carbon nucleophiles which underwent a second regioselective cross-coupling with another equivalent of 2,4-dibromothiazole (2). The Negishi cross-coupling gave high yields of the 2'-alkyl-4-bromo-2,4'-bithiazoles 1a-g (88-97%). The synthesis of the 2'-phenyl- and 2'-alkynyl-4-bromo-2,4'-bithiazoles 1h-j required a Stille cross-coupling that did not proceed as smoothly as the Negishi cross-coupling (58-62% yield). The title compounds which were accessible in total yields of 38-82% are versatile building blocks for the synthesis of 2,4'-bithiazoles.