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      Is Open Access

      Open Babel: An open chemical toolbox

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          Abstract

          Background

          A frequent problem in computational modeling is the interconversion of chemical structures between different formats. While standard interchange formats exist (for example, Chemical Markup Language) and de facto standards have arisen (for example, SMILES format), the need to interconvert formats is a continuing problem due to the multitude of different application areas for chemistry data, differences in the data stored by different formats (0D versus 3D, for example), and competition between software along with a lack of vendor-neutral formats.

          Results

          We discuss, for the first time, Open Babel, an open-source chemical toolbox that speaks the many languages of chemical data. Open Babel version 2.3 interconverts over 110 formats. The need to represent such a wide variety of chemical and molecular data requires a library that implements a wide range of cheminformatics algorithms, from partial charge assignment and aromaticity detection, to bond order perception and canonicalization. We detail the implementation of Open Babel, describe key advances in the 2.3 release, and outline a variety of uses both in terms of software products and scientific research, including applications far beyond simple format interconversion.

          Conclusions

          Open Babel presents a solution to the proliferation of multiple chemical file formats. In addition, it provides a variety of useful utilities from conformer searching and 2D depiction, to filtering, batch conversion, and substructure and similarity searching. For developers, it can be used as a programming library to handle chemical data in areas such as organic chemistry, drug design, materials science, and computational chemistry. It is freely available under an open-source license from http://openbabel.org.

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          Most cited references66

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          Very fast prediction and rationalization of pKa values for protein-ligand complexes.

          The PROPKA method for the prediction of the pK(a) values of ionizable residues in proteins is extended to include the effect of non-proteinaceous ligands on protein pK(a) values as well as predict the change in pK(a) values of ionizable groups on the ligand itself. This new version of PROPKA (PROPKA 2.0) is, as much as possible, developed by adapting the empirical rules underlying PROPKA 1.0 to ligand functional groups. Thus, the speed of PROPKA is retained, so that the pK(a) values of all ionizable groups are computed in a matter of seconds for most proteins. This adaptation is validated by comparing PROPKA 2.0 predictions to experimental data for 26 protein-ligand complexes including trypsin, thrombin, three pepsins, HIV-1 protease, chymotrypsin, xylanase, hydroxynitrile lyase, and dihydrofolate reductase. For trypsin and thrombin, large protonation state changes (|n| > 0.5) have been observed experimentally for 4 out of 14 ligand complexes. PROPKA 2.0 and Klebe's PEOE approach (Czodrowski P et al. J Mol Biol 2007;367:1347-1356) both identify three of the four large protonation state changes. The protonation state changes due to plasmepsin II, cathepsin D and endothiapepsin binding to pepstatin are predicted to within 0.4 proton units at pH 6.5 and 7.0, respectively. The PROPKA 2.0 results indicate that structural changes due to ligand binding contribute significantly to the proton uptake/release, as do residues far away from the binding site, primarily due to the change in the local environment of a particular residue and hence the change in the local hydrogen bonding network. Overall the results suggest that PROPKA 2.0 provides a good description of the protein-ligand interactions that have an important effect on the pK(a) values of titratable groups, thereby permitting fast and accurate determination of the protonation states of key residues and ligand functional groups within the binding or active site of a protein.
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                Author and article information

                Journal
                J Cheminform
                Journal of Cheminformatics
                BioMed Central
                1758-2946
                2011
                7 October 2011
                : 3
                : 33
                Affiliations
                [1 ]Analytical and Biological Chemistry Research Facility, Cavanagh Pharmacy Building, University College Cork, Co. Cork, Ireland
                [2 ]Department of Chemistry, Technische Universität München, Garching D-85747, Germany
                [3 ]eMolecules, Inc., 420 Stevens Ave #120, Solana Beach, CA 92075, USA
                [4 ]Open Babel development team
                [5 ]University of Pittsburgh, Department of Chemistry, 219 Parkman Avenue, Pittsburgh, PA 15217, USA
                Article
                1758-2946-3-33
                10.1186/1758-2946-3-33
                3198950
                21982300
                8f8d8aea-00ea-4e25-ab22-35e832539b0f
                Copyright ©2011 O'Boyle et al; licensee Chemistry Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 June 2011
                : 7 October 2011
                Categories
                Software

                Chemoinformatics
                Chemoinformatics

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