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      DOCLASP - Docking ligands to target proteins using spatial and electrostatic congruence extracted from a known holoenzyme and applying simple geometrical transformations

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      a , 1 , 2 , 3
      F1000Research
      F1000Research
      protein, docking ligand, congruence

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          Abstract

          The ability to accurately and effectively predict the interaction between proteins and small drug-like compounds has long intrigued researchers for pedagogic, humanitarian and economic reasons. Protein docking methods (AutoDock, GOLD, DOCK, FlexX and Glide to name a few) rank a large number of possible conformations of protein-ligand complexes using fast algorithms. Previously, it has been shown that structural congruence leading to the same enzymatic function necessitates the congruence of electrostatic properties (CLASP). The current work presents a methodology for docking a ligand into a target protein, provided that there is at least one known holoenzyme with ligand bound - DOCLASP (Docking using CLASP). The contact points of the ligand in the holoenzyme defines a motif, which is used to query the target enzyme using CLASP. If there are significant matches, the holoenzyme and the target protein are superimposed based on congruent atoms. The same linear and rotational transformations are also applied to the ligand, thus creating a unified coordinate framework having the holoenzyme, the ligand and the target enzyme. In the current work, the dipeptidyl peptidase-IV inhibitor vildagliptin was docked to the PI-PLC structure complexed with myo-inositol using DOCLASP. Also, corroboration of the docking of phenylthiourea to the modelled structure of polyphenol oxidase (JrPPO1) from walnut is provided based on the subsequently solved structure of JrPPO1 (PDBid:5CE9). Analysis of the binding of the antitrypanosomial drug suramin to nine non-homologous proteins in the PDB database shows a diverse set of binding motifs, and multiple binding sites in the phospholipase A2-likeproteins from the Bothrops genus of pitvipers. The conformational changes in the suramin molecule on binding highlights the challenges in docking flexible ligands into an already ’plastic’ binding site. Thus, DOCLASP presents a method for ’soft docking’ ligands to proteins with low computational requirements.

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          Most cited references50

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          Molecular dynamics simulations and drug discovery

          This review discusses the many roles atomistic computer simulations of macromolecular (for example, protein) receptors and their associated small-molecule ligands can play in drug discovery, including the identification of cryptic or allosteric binding sites, the enhancement of traditional virtual-screening methodologies, and the direct prediction of small-molecule binding energies. The limitations of current simulation methodologies, including the high computational costs and approximations of molecular forces required, are also discussed. With constant improvements in both computer power and algorithm design, the future of computer-aided drug design is promising; molecular dynamics simulations are likely to play an increasingly important role.
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            Virtual Screening with AutoDock: Theory and Practice.

            IMPORTANCE TO THE FIELD: Virtual screening is a computer-based technique for identifying promising compounds to bind to a target molecule of known structure. Given the rapidly increasing number of protein and nucleic acid structures, virtual screening continues to grow as an effective method for the discovery of new inhibitors and drug molecules. AREAS COVERED IN THIS REVIEW: We describe virtual screening methods that are available in the AutoDock suite of programs, and several of our successes in using AutoDock virtual screening in pharmaceutical lead discovery. WHAT THE READER WILL GAIN: A general overview of the challenges of virtual screening is presented, along with the tools available in the AutoDock suite of programs for addressing these challenges. TAKE HOME MESSAGE: Virtual screening is an effective tool for the discovery of compounds for use as leads in drug discovery, and the free, open source program AutoDock is an effective tool for virtual screening.
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              The walnut (Juglans regia) genome sequence reveals diversity in genes coding for the biosynthesis of non-structural polyphenols.

              The Persian walnut (Juglans regia L.), a diploid species native to the mountainous regions of Central Asia, is the major walnut species cultivated for nut production and is one of the most widespread tree nut species in the world. The high nutritional value of J. regia nuts is associated with a rich array of polyphenolic compounds, whose complete biosynthetic pathways are still unknown. A J. regia genome sequence was obtained from the cultivar 'Chandler' to discover target genes and additional unknown genes. The 667-Mbp genome was assembled using two different methods (SOAPdenovo2 and MaSuRCA), with an N50 scaffold size of 464 955 bp (based on a genome size of 606 Mbp), 221 640 contigs and a GC content of 37%. Annotation with MAKER-P and other genomic resources yielded 32 498 gene models. Previous studies in walnut relying on tissue-specific methods have only identified a single polyphenol oxidase (PPO) gene (JrPPO1). Enabled by the J. regia genome sequence, a second homolog of PPO (JrPPO2) was discovered. In addition, about 130 genes in the large gallate 1-β-glucosyltransferase (GGT) superfamily were detected. Specifically, two genes, JrGGT1 and JrGGT2, were significantly homologous to the GGT from Quercus robur (QrGGT), which is involved in the synthesis of 1-O-galloyl-β-d-glucose, a precursor for the synthesis of hydrolysable tannins. The reference genome for J. regia provides meaningful insight into the complex pathways required for the synthesis of polyphenols. The walnut genome sequence provides important tools and methods to accelerate breeding and to facilitate the genetic dissection of complex traits.
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                Author and article information

                Journal
                F1000Res
                F1000Res
                F1000Research
                F1000Research
                F1000Research (London, UK )
                2046-1402
                16 June 2016
                2014
                : 3
                : 262
                Affiliations
                [1 ]Plant Sciences Department, University of California, Davis, CA, 95616, USA
                [2 ]Department of Biological Sciences, Tata Institute of Fundamental Research, Mumbai, 400 005, India
                [3 ]Celia Engineers, Navi Mumbai, India
                [1 ]Crystallography and Molecular Biology Division, Saha Institute of Nuclear Physics, Kolkata, India
                Tata Institute of Fundamental Research, India
                [1 ]Department of Computer Science, George Mason University, Fairfax, VA, USA
                Tata Institute of Fundamental Research, India
                [1 ]Department of Computer Science, George Mason University, Fairfax, VA, USA
                Tata Institute of Fundamental Research, India
                George Mason University, USA
                [1 ]Crystallography and Molecular Biology Division, Saha Institute of Nuclear Physics, Kolkata, India
                Tata Institute of Fundamental Research, India
                Author notes

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Article
                10.12688/f1000research.5145.3
                4934513
                27429737
                592f28ca-e336-49b8-b9d3-92ded6c12478
                Copyright: © 2016 Chakraborty S

                This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 June 2016
                Funding
                The author(s) declared that no grants were involved in supporting this work.
                Categories
                Research Note
                Articles
                Bioinformatics
                Protein Chemistry & Proteomics

                protein, docking ligand, congruence
                protein, docking ligand, congruence

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