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      • Record: found
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      PyMine: a PyMOL plugin to integrate and visualize data for drug discovery

      research-article
      Author(s): ,
      Publication date (Electronic):
      Journal: BMC Research Notes
      Publisher: BioMed Central
      Keywords: PyMOL, Data integration, Data visualization, Drug discovery

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          Abstract

          Background

          Tremendous amount of chemical and biological data are being generated by various high-throughput biotechnologies that could facilitate modern drug discovery. However, lack of integration makes it very challenging for individual scientists to access and understand all the data related to a specific protein of interest.

          Findings

          To overcome this challenge, we developed PyMine, a PyMOL plugin that retrieves chemical, structural, pathway and other related biological data of a receptor and small molecules from a variety of high-quality databases and presents them in a graphic and uniformed way.

          Conclusions

          Developed as an interactive and user-friendly tool, PyMine can be used as a central data-hub for users to access and visualize multiple types of data and to generate new ideas intuitively for structure-based molecule design.

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          Most cited references11

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          PDB-wide collection of binding data: current status of the PDBbind database.

          Yan Li, Renxiao Wang, Wei-Zhi Nie … (2015)
          Molecular recognition between biological macromolecules and organic small molecules plays an important role in various life processes. Both structural information and binding data of biomolecular complexes are indispensable for depicting the underlying mechanism in such an event. The PDBbind database was created to collect experimentally measured binding data for the biomolecular complexes throughout the Protein Data Bank (PDB). It thus provides the linkage between structural information and energetic properties of biomolecular complexes, which is especially desirable for computational studies or statistical analyses. Since its first public release in 2004, the PDBbind database has been updated on an annual basis. The latest release (version 2013) provides experimental binding affinity data for 10,776 biomolecular complexes in PDB, including 8302 protein-ligand complexes and 2474 other types of complexes. In this article, we will describe the current methods used for compiling PDBbind and the updated status of this database. We will also review some typical applications of PDBbind published in the scientific literature. All contents of this database are freely accessible at the PDBbind-CN Web server at http://www.pdbbind-cn.org/. wangrx@mail.sioc.ac.cn. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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            Computer-aided drug design platform using PyMOL.

            Markus A. Lill, L A Danielson (2010)
            The understanding and optimization of protein-ligand interactions are instrumental to medicinal chemists investigating potential drug candidates. Over the past couple of decades, many powerful standalone tools for computer-aided drug discovery have been developed in academia providing insight into protein-ligand interactions. As programs are developed by various research groups, a consistent user-friendly graphical working environment combining computational techniques such as docking, scoring, molecular dynamics simulations, and free energy calculations is needed. Utilizing PyMOL we have developed such a graphical user interface incorporating individual academic packages designed for protein preparation (AMBER package and Reduce), molecular mechanics applications (AMBER package), and docking and scoring (AutoDock Vina and SLIDE). In addition to amassing several computational tools under one interface, the computational platform also provides a user-friendly combination of different programs. For example, utilizing a molecular dynamics (MD) simulation performed with AMBER as input for ensemble docking with AutoDock Vina. The overarching goal of this work was to provide a computational platform that facilitates medicinal chemists, many who are not experts in computational methodologies, to utilize several common computational techniques germane to drug discovery. Furthermore, our software is open source and is aimed to initiate collaborative efforts among computational researchers to combine other open source computational methods under a single, easily understandable graphical user interface.
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              PyMod: sequence similarity searches, multiple sequence-structure alignments, and homology modeling within PyMOL

              Emanuele Bramucci, Alessandro Paiardini, Francesco Bossa … (2012)
              Background In recent years, an exponential growing number of tools for protein sequence analysis, editing and modeling tasks have been put at the disposal of the scientific community. Despite the vast majority of these tools have been released as open source software, their deep learning curves often discourages even the most experienced users. Results A simple and intuitive interface, PyMod, between the popular molecular graphics system PyMOL and several other tools (i.e., [PSI-]BLAST, ClustalW, MUSCLE, CEalign and MODELLER) has been developed, to show how the integration of the individual steps required for homology modeling and sequence/structure analysis within the PyMOL framework can hugely simplify these tasks. Sequence similarity searches, multiple sequence and structural alignments generation and editing, and even the possibility to merge sequence and structure alignments have been implemented in PyMod, with the aim of creating a simple, yet powerful tool for sequence and structure analysis and building of homology models. Conclusions PyMod represents a new tool for the analysis and the manipulation of protein sequences and structures. The ease of use, integration with many sequence retrieving and alignment tools and PyMOL, one of the most used molecular visualization system, are the key features of this tool. Source code, installation instructions, video tutorials and a user's guide are freely available at the URL http://schubert.bio.uniroma1.it/pymod/index.html
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                Author and article information

                Contributors
                Rajan Chaudhari: rchaudhari@mail.usciences.edu
                Zhijun Li: z.li@usciences.edu
                Journal
                Journal ID (nlm-ta): BMC Res Notes
                Journal ID (iso-abbrev): BMC Res Notes
                Title: BMC Research Notes
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1756-0500
                Publication date (Electronic): 1 October 2015
                Publication date PMC-release: 1 October 2015
                Publication date Collection: 2015
                Volume: 8
                Electronic Location Identifier: 517
                Affiliations
                Department of Chemistry & Biochemistry, University of the Sciences in Philadelphia, Philadelphia, PA 19104 USA
                Article
                Publisher ID: 1483
                DOI: 10.1186/s13104-015-1483-3
                PMC ID: 4590260
                SO-VID: 9ec653f3-db44-4c5e-84cd-79d17b7ec8e7
                Copyright © © Chaudhari and Li. 2015
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                Date received : 9 April 2015
                Date accepted : 21 September 2015
                Categories
                Subject: Technical Note
                Custom metadata
                issue-copyright-statement © The Author(s) 2015

                ScienceOpen disciplines: Medicine
                Keywords: pymol,data integration,data visualization,drug discovery
                Data availability:
                ScienceOpen disciplines: Medicine
                Keywords: pymol, data integration, data visualization, drug discovery

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