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      Ligand docking and binding site analysis with PyMOL and Autodock/Vina

      research-article
      ,
      Journal of Computer-Aided Molecular Design
      Springer Netherlands
      Docking, Virtual screening, Autodock, Vina, PyMOL

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          Abstract

          Docking of small molecule compounds into the binding site of a receptor and estimating the binding affinity of the complex is an important part of the structure-based drug design process. For a thorough understanding of the structural principles that determine the strength of a protein/ligand complex both, an accurate and fast docking protocol and the ability to visualize binding geometries and interactions are mandatory. Here we present an interface between the popular molecular graphics system PyMOL and the molecular docking suites Autodock and Vina and demonstrate how the combination of docking and visualization can aid structure-based drug design efforts.

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          Most cited references7

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          A semiempirical free energy force field with charge-based desolvation.

          The authors describe the development and testing of a semiempirical free energy force field for use in AutoDock4 and similar grid-based docking methods. The force field is based on a comprehensive thermodynamic model that allows incorporation of intramolecular energies into the predicted free energy of binding. It also incorporates a charge-based method for evaluation of desolvation designed to use a typical set of atom types. The method has been calibrated on a set of 188 diverse protein-ligand complexes of known structure and binding energy, and tested on a set of 100 complexes of ligands with retroviral proteases. The force field shows improvement in redocking simulations over the previous AutoDock3 force field.
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            Is Open Access

            CAVER: a new tool to explore routes from protein clefts, pockets and cavities

            Background The main aim of this study was to develop and implement an algorithm for the rapid, accurate and automated identification of paths leading from buried protein clefts, pockets and cavities in dynamic and static protein structures to the outside solvent. Results The algorithm to perform a skeleton search was based on a reciprocal distance function grid that was developed and implemented for the CAVER program. The program identifies and visualizes routes from the interior of the protein to the bulk solvent. CAVER was primarily developed for proteins, but the algorithm is sufficiently robust to allow the analysis of any molecular system, including nucleic acids or inorganic material. Calculations can be performed using discrete structures from crystallographic analysis and NMR experiments as well as with trajectories from molecular dynamics simulations. The fully functional program is available as a stand-alone version and as plug-in for the molecular modeling program PyMol. Additionally, selected functions are accessible in an online version. Conclusion The algorithm developed automatically finds the path from a starting point located within the interior of a protein. The algorithm is sufficiently rapid and robust to enable routine analysis of molecular dynamics trajectories containing thousands of snapshots. The algorithm is based on reciprocal metrics and provides an easy method to find a centerline, i.e. the spine, of complicated objects such as a protein tunnel. It can also be applied to many other molecules. CAVER is freely available from the web site .
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              Analytical shape computation of macromolecules: I. Molecular area and volume through alpha shape.

              The size and shape of macromolecules such as proteins and nucleic acids play an important role in their functions. Prior efforts to quantify these properties have been based on various discretization or tessellation procedures involving analytical or numerical computations. In this article, we present an analytically exact method for computing the metric properties of macromolecules based on the alpha shape theory. This method uses the duality between alpha complex and the weighted Voronoi decomposition of a molecule. We describe the intuitive ideas and concepts behind the alpha shape theory and the algorithm for computing areas and volumes of macromolecules. We apply our method to compute areas and volumes of a number of protein systems. We also discuss several difficulties commonly encountered in molecular shape computations and outline methods to overcome these problems.
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                Author and article information

                Contributors
                +49-551-2012310 , +49-551-2012302 , dseelig@gwdg.de
                +49-551-2012308 , +49-551-2012302 , bgroot@gwdg.de
                Journal
                J Comput Aided Mol Des
                Journal of Computer-Aided Molecular Design
                Springer Netherlands (Dordrecht )
                0920-654X
                1573-4951
                17 April 2010
                17 April 2010
                May 2010
                : 24
                : 5
                : 417-422
                Affiliations
                Computational Biomolecular Dynamics Group, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Gottingen, Germany
                Article
                9352
                10.1007/s10822-010-9352-6
                2881210
                20401516
                c2da4cbd-3ff5-461f-a709-68985b2b0e73
                © The Author(s) 2010
                History
                : 22 January 2010
                : 26 March 2010
                Categories
                Article
                Custom metadata
                © Springer Science+Business Media B.V. 2010

                Biomedical engineering
                virtual screening,vina,autodock,docking,pymol
                Biomedical engineering
                virtual screening, vina, autodock, docking, pymol

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