Literature DB >> 9334903

Multiple automatic base selection: protein-ligand docking based on incremental construction without manual intervention.

M Rarey1, B Kramer, T Lengauer.   

Abstract

A possible way of tackling the molecular docking problem arising in computer-aided drug design is the use of the incremental construction method. This method consists of three steps: the selection of a part of a molecule, a so-called base fragment, the placement of the base fragment into the active site of a protein, and the subsequent reconstruction of the complete drug molecule. Assuming that a part of a drug molecule is known, which is specific enough to be a good base fragment, the method is proven to be successful for a large set of docking examples. In addition, it leads to the fastest algorithms for flexible docking published so far. In most real-world applications of docking, large sets of ligands have to be tested for affinity to a given protein. Thus, manual selection of a base fragment is not practical. On the other hand, the selection of a base fragment is critical in that only few selections lead to a low-energy structure. We overcome this limitation by selecting a representative set of base fragments instead of a single one. In this paper, we present a set of rules and algorithms to automate this selection. In addition, we extend the incremental construction method to deal with multiple fragmentations of the drug molecule. Our results show that with multiple automated base selection, the quality of the docking predictions is almost as good as with one manually preselected base fragment. In addition, the set of solutions is more diverse and alternative binding modes with low scores are found. Although the run time of the overall algorithm increases, the method remains fast enough to search through large ligand data sets.

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Year:  1997        PMID: 9334903     DOI: 10.1023/a:1007913026166

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  15 in total

Review 1.  Structure-based strategies for drug design and discovery.

Authors:  I D Kuntz
Journal:  Science       Date:  1992-08-21       Impact factor: 47.728

Review 2.  Ligand-protein docking and rational drug design.

Authors:  T P Lybrand
Journal:  Curr Opin Struct Biol       Date:  1995-04       Impact factor: 6.809

3.  Distributed automated docking of flexible ligands to proteins: parallel applications of AutoDock 2.4.

Authors:  G M Morris; D S Goodsell; R Huey; A J Olson
Journal:  J Comput Aided Mol Des       Date:  1996-08       Impact factor: 3.686

4.  Hammerhead: fast, fully automated docking of flexible ligands to protein binding sites.

Authors:  W Welch; J Ruppert; A N Jain
Journal:  Chem Biol       Date:  1996-06

Review 5.  Computational methods for biomolecular docking.

Authors:  T Lengauer; M Rarey
Journal:  Curr Opin Struct Biol       Date:  1996-06       Impact factor: 6.809

6.  Flexible ligand docking using a genetic algorithm.

Authors:  C M Oshiro; I D Kuntz; J S Dixon
Journal:  J Comput Aided Mol Des       Date:  1995-04       Impact factor: 3.686

7.  Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation.

Authors:  G Jones; P Willett; R C Glen
Journal:  J Mol Biol       Date:  1995-01-06       Impact factor: 5.469

8.  A fast and efficient method to generate biologically relevant conformations.

Authors:  G Klebe; T Mietzner
Journal:  J Comput Aided Mol Des       Date:  1994-10       Impact factor: 3.686

9.  The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure.

Authors:  H J Böhm
Journal:  J Comput Aided Mol Des       Date:  1994-06       Impact factor: 3.686

10.  A geometric approach to macromolecule-ligand interactions.

Authors:  I D Kuntz; J M Blaney; S J Oatley; R Langridge; T E Ferrin
Journal:  J Mol Biol       Date:  1982-10-25       Impact factor: 5.469

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  29 in total

1.  The sensitivity of the results of molecular docking to induced fit effects: application to thrombin, thermolysin and neuraminidase.

Authors:  C W Murray; C A Baxter; A D Frenkel
Journal:  J Comput Aided Mol Des       Date:  1999-11       Impact factor: 3.686

2.  Deciphering common failures in molecular docking of ligand-protein complexes.

Authors:  G M Verkhivker; D Bouzida; D K Gehlhaar; P A Rejto; S Arthurs; A B Colson; S T Freer; V Larson; B A Luty; T Marrone; P W Rose
Journal:  J Comput Aided Mol Des       Date:  2000-11       Impact factor: 3.686

3.  Comparison of two implementations of the incremental construction algorithm in flexible docking of thrombin inhibitors.

Authors:  R M Knegtel; D M Bayada; R A Engh; W von der Saal; V J van Geerestein; P D Grootenhuis
Journal:  J Comput Aided Mol Des       Date:  1999-03       Impact factor: 3.686

4.  Similarity searching in large combinatorial chemistry spaces.

Authors:  M Rarey; M Stahl
Journal:  J Comput Aided Mol Des       Date:  2001-06       Impact factor: 3.686

5.  DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases.

Authors:  T J Ewing; S Makino; A G Skillman; I D Kuntz
Journal:  J Comput Aided Mol Des       Date:  2001-05       Impact factor: 3.686

6.  Protein ligand docking based on empirical method for binding affinity estimation.

Authors:  P Tao; L Lai
Journal:  J Comput Aided Mol Des       Date:  2001-05       Impact factor: 3.686

7.  Flexible docking under pharmacophore type constraints.

Authors:  Sally A Hindle; Matthias Rarey; Christian Buning; Thomas Lengaue
Journal:  J Comput Aided Mol Des       Date:  2002-02       Impact factor: 3.686

8.  Binding site characteristics in structure-based virtual screening: evaluation of current docking tools.

Authors:  Tanja Schulz-Gasch; Martin Stahl
Journal:  J Mol Model       Date:  2003-01-14       Impact factor: 1.810

Review 9.  A review of protein-small molecule docking methods.

Authors:  R D Taylor; P J Jewsbury; J W Essex
Journal:  J Comput Aided Mol Des       Date:  2002-03       Impact factor: 3.686

Review 10.  Information-based methods in the development of antiparasitic drugs.

Authors:  Kristina Wolf; Matthias Dormeyer
Journal:  Parasitol Res       Date:  2002-12-04       Impact factor: 2.289

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