Literature DB >> 15615529

Ph4Dock: pharmacophore-based protein-ligand docking.

Junichi Goto1, Ryoichi Kataoka, Noriaki Hirayama.   

Abstract

The development and validation of the program Ph4Dock is presented. Ph4Dock is a novel automated ligand docking program that makes best use of pharmacophoric features both in a ligand and at concave portions of a protein. By mapping of pharmacophores of the ligand to the pharmacophoric features that represent the concaves of the target protein, Ph4Dock realizes an efficient and accurate prediction of the binding modes between the ligand and the protein. To validate the potential of this unique docking algorithm, we have selected 43 reliable crystal structures of protein-ligand complexes. All of the ligands are druglike, and they are varied in nature. The diffraction-component precision index (DPI) originally used in crystallography was applied in this study in order to evaluate the docking results quantitatively. The root-mean-square deviation (rmsd) between non-hydrogen atoms of the ligand in the prediction and experimental results were analyzed using DPI. The rmsd values for 25 structures, consisting of almost 60% of the dataset, are less than three times of the corresponding DPI values. It means that the precision of docking results obtained by Ph4Dock is mostly equivalent to the experimental error in these cases. The present study has demonstrated that Ph4Dock can accurately reproduce the experimentally determined docking modes if the reliable crystal structures are used. Normally the success rate of the docking is judged using rmsd < or = 2.0 A as the criterion. The Ph4Dock marked an appreciably good success rate of 86% based on this criterion.

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Year:  2004        PMID: 15615529     DOI: 10.1021/jm0493818

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  20 in total

Review 1.  Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

Authors:  N Moitessier; P Englebienne; D Lee; J Lawandi; C R Corbeil
Journal:  Br J Pharmacol       Date:  2007-11-26       Impact factor: 8.739

Review 2.  Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes?

Authors:  Johannes Kirchmair; Patrick Markt; Simona Distinto; Gerhard Wolber; Thierry Langer
Journal:  J Comput Aided Mol Des       Date:  2008-01-15       Impact factor: 3.686

Review 3.  New era for drug discovery and development in renal disease.

Authors:  Toshio Miyata; Katsushi Kikuchi; Hideyasu Kiyomoto; Charles van Ypersele de Strihou
Journal:  Nat Rev Nephrol       Date:  2011-07-05       Impact factor: 28.314

4.  AZT acts as an anti-influenza nucleotide triphosphate targeting the catalytic site of A/PR/8/34/H1N1 RNA dependent RNA polymerase.

Authors:  Nataraj Sekhar Pagadala
Journal:  J Comput Aided Mol Des       Date:  2019-02-09       Impact factor: 3.686

5.  Molecular docking and structural analysis of cofactor-protein interaction between NAD⁺ and 11β-hydroxysteroid dehydrogenase type 2.

Authors:  Hideaki Yamaguchi; Tatsuo Akitaya; Tao Yu; Yumi Kidachi; Katsuyoshi Kamiie; Toshiro Noshita; Hironori Umetsu; Kazuo Ryoyama
Journal:  J Mol Model       Date:  2011-06-11       Impact factor: 1.810

6.  Conformer generation with OMEGA: algorithm and validation using high quality structures from the Protein Databank and Cambridge Structural Database.

Authors:  Paul C D Hawkins; A Geoffrey Skillman; Gregory L Warren; Benjamin A Ellingson; Matthew T Stahl
Journal:  J Chem Inf Model       Date:  2010-04-26       Impact factor: 4.956

Review 7.  How to do an evaluation: pitfalls and traps.

Authors:  Paul C D Hawkins; Gregory L Warren; A Geoffrey Skillman; Anthony Nicholls
Journal:  J Comput Aided Mol Des       Date:  2008-01-23       Impact factor: 3.686

8.  Megsin gene: its genomic analysis, pathobiological functions, and therapeutic perspectives.

Authors:  Toshio Miyata; Ming Li; Xueqing Yu; Noriaki Hirayama
Journal:  Curr Genomics       Date:  2007-05       Impact factor: 2.236

9.  Structural insight into the ligand-receptor interaction between glycyrrhetinic acid (GA) and the high-mobility group protein B1 (HMGB1)-DNA complex.

Authors:  Hideaki Yamaguchi; Yumi Kidachi; Katsuyoshi Kamiie; Toshiro Noshita; Hironori Umetsu
Journal:  Bioinformation       Date:  2012-11-23

10.  Molecular modeling of the reductase domain to elucidate the reaction mechanism of reduction of peptidyl thioester into its corresponding alcohol in non-ribosomal peptide synthetases.

Authors:  Balachandran Manavalan; Senthil K Murugapiran; Gwang Lee; Sangdun Choi
Journal:  BMC Struct Biol       Date:  2010-01-12
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