| Abstract
| - Research applications in chemoinformatics and toxicoinformatics increasingly use representations of molecules in the form of numerical descriptors that capture the structural characteristics and properties of molecules. These representations are useful for ADME/toxicity prediction, diversity analysis, library design, QSAR/QSPR, virtual screening, and other purposes. Molecular descriptors have ranged from relatively simple forms calculated from simple two-dimensional (2D) chemical structures to more complex forms representing three-dimensional (3D) chemical structures or complex molecular fingerprints consisting of numerous bit positions to represent specific chemical information. The Mold2 software was developed to enable the rapid calculation of a large and diverse set of descriptors encoding two-dimensional chemical structure information. Comparative analysis of Mold2 descriptors with those calculated by Cerius2, Dragon, and Molconn-Z on several data sets using Shannon entropy analysis demonstrated that Mold2 descriptors convey a similar amount of information. In addition, using the same classification method, slightly better models were generated using Mold2 descriptors compared to those generated using descriptors from the compared commercial software packages. The low computing cost for Mold2 makes it suitable not only for small data sets, such as in QSAR, but also for large databases in virtual screening. High reproducibility and reliability are expected because Mold2 does not require 3D structures. Mold2 is freely available to the public (http://www.fda.gov/nctr/science/centers/toxicoinformatics/index.htm).
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