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

Welch, William H.; Ruppert, Jim; Jain, Ajay N.

doi:10.1016/s1074-5521(96)90093-9

Cited by 331 publications

(249 citation statements)

References 13 publications

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“…The idea is to define a function composed of terms that are related to known physical processes that underlie the physics of protein ligand binding, and estimate the parameters of the function based on protein-ligand complexes of known affinities and structures. The scoring function used in Surflex (and in Hammerhead, which was Surflex's antecedent) borrowed heavily from the approach of Bohm [2,3,9,30]. Bohm's approach had terms for hydrophobic contact, polar interactions, and entropic fixation costs for loss of torsional, translational, and rotational degrees of freedom.…”

Section: Scoring Functionmentioning

confidence: 99%

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Surflex-Dock 2.1: Robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search

Jain

2007

J Comput Aided Mol Des

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534

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The Surflex flexible molecular docking method has been generalized and extended in two primary areas related to the search component of docking. First, incorporation of a small-molecule force-field extends the search into Cartesian coordinates constrained by internal ligand energetics. Whereas previous versions searched only the alignment and acyclic torsional space of the ligand, the new approach supports dynamic ring flexibility and allatom optimization of docked ligand poses. Second, knowledge of well established molecular interactions between ligand fragments and a target protein can be directly exploited to guide the search process. This offers advantages in some cases over the search strategy where ligand alignment is guided solely by a ''protomol'' (a pre-computed molecular representation of an idealized ligand). Results are presented on both docking accuracy and screening utility using multiple publicly available benchmark data sets that place Surflex's performance in the context of other molecular docking methods. In terms of docking accuracy, Surflex-Dock 2.1 performs as well as the best available methods. In the area of screening utility, Surflex's performance is extremely robust, and it is clearly superior to other methods within the set of cases for which comparative data are available, with roughly double the screening enrichment performance.

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Section: Scoring Functionmentioning

confidence: 99%

“…Many docking methods have been described, and they vary in their approaches to two components: scoring functions and search methods [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. The searching and scoring problems are intimately tied together for two reasons.…”

Section: Introductionmentioning

confidence: 99%

Surflex-Dock 2.1: Robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search

Jain

2007

J Comput Aided Mol Des

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534

502

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“…The pockets of streptavidin, DHFR, and trypsin that were discussed earlier all yield rapid and accurate dockings of the respective ligands using the Hammerhead program of Welch et al (1996). The pocket-finder has also been used in successful computational screens for novel ligands of streptavidin and thymidilate synthase.…”

Section: Pocket-finder Specificity and Utilitymentioning

confidence: 99%

“…They are discussed in detail in Welch et al ( 1996) and Jain (19%); the features of those components that pertain to the pocket-finder are reviewed here. The scoring function estimates the binding affinity between two molecules in a given alignment.…”

Section: Brief Review Of Scoring Function and Hammerhead Molecular Domentioning

confidence: 99%

Automatic identification and representation of protein binding sites for molecular docking

1997

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Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially, the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.

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“…The second class, sometimes called ''fragment-based'' docking, starts with placing one or several base fragments of a ligand into a binding pocket, and then constructs the rest of the molecule in the site. DOCK4.0, 7 FlexX, 8 LUDI, 9 Hammerhead, 10 GROWMOL, 11 and HOOK 12 are programs in this class. The fragment-based approach is often an order of magnitude faster than the whole molecule-based docking method.…”

Section: Introductionmentioning

confidence: 99%

Flexible ligand docking: A multistep strategy approach

1999

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A flexible ligand docking protocol based on a divide-and-conquer strategy is investigated. This approach first separates total search space into conformation and orientation space. It uses a grid-based method to sample the conformation of an unbound ligand and to select the lowenergy conformers. Rigid docking is then carried out to locate the low-energy binding orientations for these conformers. These docking structures are subsequently subjected to structure refinement including molecular mechanics minimization, conformational scanning at the binding site and a short period of molecular dynamics-based simulated annealing. This approach has been applied to twelve ligand-protein complexes with three to sixteen rotatable bonds. The docked lowest-energy structures have root mean square deviations ranging from 0.64 Å to 2.01 Å with respect to the corresponding crystal structures. The effect of atomic charges and van der Waals parameters on the docking results, and the role of the dielectric constant in the conformation sampling are discussed in detail. A fragment-based docking approach that takes advantages of the divide-and-conquer strategy has also been explored and the results are compared with those produced by a whole molecule-based approach. Proteins 1999;36:1-19.1999 Wiley-Liss, Inc.

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

Cited by 331 publications

References 13 publications

Surflex-Dock 2.1: Robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search

Surflex-Dock 2.1: Robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search

Automatic identification and representation of protein binding sites for molecular docking

Flexible ligand docking: A multistep strategy approach

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