ArachnoServer (www.arachnoserver.org) is a manually curated database providing information on the sequence, structure and biological activity of protein toxins from spider venoms. These proteins are of interest to a wide range of biologists due to their diverse applications in medicine, neuroscience, pharmacology, drug discovery and agriculture. ArachnoServer currently manages 1078 protein sequences, 759 nucleic acid sequences and 56 protein structures. Key features of ArachnoServer include a molecular target ontology designed specifically for venom toxins, current and historic taxonomic information and a powerful advanced search interface. The following significant improvements have been implemented in version 2.0: (i) the average and monoisotopic molecular masses of both the reduced and oxidized form of each mature toxin are provided; (ii) the advanced search feature now enables searches on the basis of toxin mass, external database accession numbers and publication date in ArachnoServer; (iii) toxins can now be browsed on the basis of their phyletic specificity; (iv) rapid BLAST searches based on the mature toxin sequence can be performed directly from the toxin card; (v) private silos can be requested from research groups engaged in venoms-based research, enabling them to easily manage and securely store data during the process of toxin discovery; and (vi) a detailed user manual is now available.
This paper reports a comparison of calculated molecular properties and of 2D fragment bit-strings when used for the selection of structurally diverse subsets of a file of 44295 compounds. MaxMin dissimilarity-based selection and k-means clusterbased selection are used to select subsets containing between 1% and 20% of the file. Investigation of the numbers of bioactive molecules in the selected subsets suggest: that the MaxMin subsets are noticeably superior to the k-means subsets; that the property-based descriptors are marginally superior to the fragment-based descriptors; and that both approaches are noticeably superior to random selection.
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