Calculates molecular descriptors and fingerprints. PaDEL-descriptor was developed using the Java language and consists of a library and an interface component. It currently calculates 797 descriptors (663 1D, 2D descriptors, and 134 3D descriptors) and 10 types of fingerprints. These descriptors and fingerprints are calculated mainly using The Chemistry Development Kit. Some additional descriptors and fingerprints were added, which include atom type electrotopological state descriptors, McGowan volume, molecular linear free energy relation descriptors, ring counts, count of chemical substructures identified by Laggner, and binary fingerprints and count of chemical substructures identified by Klekota and Roth. PaDEL-descriptor is free and open source, which has both graphical user interface (GUI) and command line interfaces, able to work on all major platforms (Windows, Linux, MacOS), supports more than 90 different molecular file formats, and is multithreaded.
Describes alignment-free molecules. xMap derives is based on MaP, a three-dimensional (3D) descriptor tool. This algorithm handles the fourth dimension (4D) and uses an ensemble of conformers generated by conformational searches. It functions through a five-step procedure and the most important descriptor variables are determined with chemometric regression tools. It can also display the derived quantitative structure-activity relationships.
Provides a customizable framework for molecular property calculation geared towards enabling database filtering. MolProp TK was developed to remove all compounds that should not be suggested to a medicinal chemist as a potential hit. The criteria for passing or failing a given molecule fall into three categories: (i) its physical properties such as molecular weight or bioavailability, (ii) the atomic and functional group content, and (iii) the molecular graph topology.
Enables the rapid calculation of a large and diverse set of descriptors encoding 2D chemical structure information. Mold(2) easily and quickly calculates molecular descriptors with no missing values, a common problem with most existing commercial systems. The descriptors used by this tool were compared with descriptors from commercial software packages using information entropy analysis, analysis of correlations between descriptors, and Decision Forest classification on several reported data sets.
Performs molecular filtering and selection. FILTER employs a combination of physical property calculations and functional group knowledge for removing undesirable compounds before they enter experimental or virtual screening. The software is able to remove, for instance toxic functionalities, a high likelihood of binding covalently with the target protein, a low probability of oral bioavailability, or interfering with the experimental assay.
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