ACPYPE - AnteChamber PYthon Parser interfacE
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TLDR
ACPYPE is a tool that simplifies the automatic generation of topology and parameters in different formats for different molecular mechanics programmes, including calculation of partial charges, while being object oriented for integration with other applications.Abstract:
ACPYPE (or AnteChamber PYthon Parser interfacE) is a wrapper script around the ANTECHAMBER software that simplifies the generation of small molecule topologies and parameters for a variety of molecular dynamics programmes like GROMACS, CHARMM and CNS. It is written in the Python programming language and was developed as a tool for interfacing with other Python based applications such as the CCPN software suite (for NMR data analysis) and ARIA (for structure calculations from NMR data). ACPYPE is open source code, under GNU GPL v3, and is available as a stand-alone application at http://www.ccpn.ac.uk/acpype
and as a web portal application at http://webapps.ccpn.ac.uk/acpype
. We verified the topologies generated by ACPYPE in three ways: by comparing with default AMBER topologies for standard amino acids; by generating and verifying topologies for a large set of ligands from the PDB; and by recalculating the structures for 5 protein–ligand complexes from the PDB. ACPYPE is a tool that simplifies the automatic generation of topology and parameters in different formats for different molecular mechanics programmes, including calculation of partial charges, while being object oriented for integration with other applications.read more
Citations
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g_mmpbsa--a GROMACS tool for high-throughput MM-PBSA calculations.
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Crystal structures of agonist-bound human cannabinoid receptor CB1
Tian Hua,Kiran Vemuri,Spyros P. Nikas,Robert B. Laprairie,Yiran Wu,Lu Qu,Lu Qu,Mengchen Pu,Anisha Korde,Shan Jiang,Jo-Hao Ho,Gye Won Han,Kang Ding,Kang Ding,Xuanxuan Li,Haiguang Liu,Michael A. Hanson,Suwen Zhao,Laura M. Bohn,Alexandros Makriyannis,Raymond C. Stevens,Raymond C. Stevens,Zhi-Jie Liu,Zhi-Jie Liu +23 more
TL;DR: The structures reveal important insights into the activation mechanism of CB1 and provide a molecular basis for predicting the binding modes of Δ9-THC, and endogenous and synthetic cannabinoids and should inspire the design of chemically diverse ligands with distinct pharmacological properties.
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