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        "author": "Dongsheng Cao",
        "author_email": "oriental-cds@163.com",
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        "description": "Copyright (c) 2012CBDD03, Computational Biology and Drug Design Group, \nCentral South University, China.\nAll rights reserved.\n\nINSTRUCTION\n\nThe rapidly increasing amount of publicly available data in biology and chemistry enables researchers \nto revisit interaction problems by systematic integration and analysis of heterogeneous data. Herein, \nwe developed a comprehensive python package to emphasize the integration of chemoinformatics and \nbioinformatics into a molecular informatics platform for drug discovery. PyDPI (Drug-Protein \nInteraction with Python) is a powerful python toolkit for computing commonly-used structural and \nphysicochemical features of proteins and peptides from amino acid sequences, molecular descriptors of \ndrug molecules from their topology, and protein-protein interaction and protein-ligand interaction \ndescriptors. It computes six protein feature groups composed of fourteen features that include \nfifty-two descriptors and 9890 descriptor values, nine drug feature groups composed of eleven \ndescriptors that include 530 descriptor values. In addition, it provides seven types of molecular \nfingerprint systems for drug molecules, including topological fingerprints, electro-topological state \n(E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints \nand Morgan/circular fingerprints. By combining different types of descriptors from drugs and proteins \nin different ways, interaction descriptors representing protein-protein or drug-protein interactions \ncould be conveniently generated. These computed descriptors can be widely used in various fields \nrelevant to chemoinformatics, bioinformatics and chemogenomics.\n\nIf you have any problem, Please contact Dongsheng Cao (oriental-cds@163.com)\n\n#############################################FEATURES################################################\nThe protein descriptors calculated by pydpi:\n(1) AAC: amino acid composition descriptors (20)\n(2) DPC: dipeptide composition descriptors (400)\n(3) TPC: tri-peptide composition descriptors (8000)\n(4) MBauto: Normalized Moreau-Broto autocorrelation \ndescriptors (depend on the given properties, the default is 240)\n(5) Moranauto: Moran autocorrelation descriptors\n(depend on the given properties, the default is 240)\n(6) Gearyauto: Geary autocorrelation descriptors\n(depend on the given properties, the default is 240)\n(6) CTD: Composition, Transition, Distribution descriptors \n(CTD) (21+21+105=147)\n(7) SOCN: sequence order coupling numbers \n(depend on the choice of maxlag, the default is 60)\n(8) QSO: quasi-sequence order descriptors \n(depend on the choice of maxlag, the default is 100)\n(9) PAAC: pseudo amino acid composition descriptors \n(depend on the choice of lamda, the default is 50)\n(10) APAAC: amphiphilic pseudo amino acid composition descriptors\n(depend on the choice of lamda, the default is 50) \n(11) CT: conjoint triad features (343)\n######################################################################################################\nThe drug descriptors calculated by pydpi:\n(1) Constitutional descriptors (30)\n(2) Topologcial descriptors (25)\n(3) Molecular connectivity descriptors (44)\n(4) Kappa descriptors(7)\n(5) E-state descriptors (237)\n(6) Autocorrelation descriptors (96) \nincluding Moreau-Broto, Moran and Geary autocorrelation descriptors\n(7) Charge descriptors (25)\n(8) Molecular property descriptors (6)\n(9) MOE-type descriptors (60)\n(10) Daylight fingerprint (2048)\n(11) MACCS keys (166)\n(12) FP4 fingerprints (307) \n(13) E-state fingerprints (79)\n(14) Atom Paris fingerprints and Morgan fingerprints\n######################################################################################################\nInstall the pydpi package\npydpi has been successfully tested on Linux and Windows systems. \nThe author could download the pydpi package via:\nhttp://code.google.com/p/pydpi/downloads/list (.zip and .tar.gz). \n\nThe install process of pydpi is very easy:\n*********************************************************************\n*You first need to install RDkit, Openbabel, and pybel successfully.*\n*********************************************************************\nOpenbabel and pybel can be downloaded via: http://openbabel.org/wiki/Main_Page\nRDkit can be downloaded via: http://code.google.com/p/rdkit/\n\n\nOn Windows:\n(1): download the pydpi package (.zip)\n(2): extract or uncompress the .zip file \n(3): cd pydpi-1.0\n(4): python setup.py install\n\nOn Linux:\n(1): download the pydpi package (.tar.gz) \n(2): tar -zxf pydpi-1.0.tar.gz \n(3): cd pydpi-1.0 \n(4): python setup.py install or sudo python setup.py install \n######################################################################################################\nExample:\nFor more examples, please see the user guide.\n######################################################################################################\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n    * Redistributions of source code must retain the above copyright\n      notice, this list of conditions and the following disclaimer.\n    * Redistributions in binary form must reproduce the above copyright\n      notice, this list of conditions and the following disclaimer in the\n      documentation and/or other materials provided with the distribution.\n    * Neither the name of the computational biology and drug design group nor the\n      names of the authors may be used to endorse or promote products\n      derived from this software without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED \"AS IS\" AND\nANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\nWARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL COPYRIGHT HOLDERS BE LIABLE FOR ANY\nDIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES\n(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\nLOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND\nON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\nSOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n######################################################################################################\n",
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