FRODOCK: a new approach for fast rotational protein–protein docking

Garzón, José Ignacio; López‐Blanco, José Ramón; Pons, Carles; Kovacs, Julio A.; Abagyan, Ruben; Fernández‐Recio, Juan; Chacón, Pablo

doi:10.1093/bioinformatics/btp447

Cited by 132 publications

(126 citation statements)

References 36 publications

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“…This is a limitation of any FFT-based algorithm, and it was already shown that performing parallel docking runs using several initial rotations provided more consistent docking results than using just a single one. 14 These results suggest that the selected conformers according to specific criteria (i.e. optimal binding energy, number of clashes) were more beneficial for docking than just a random selection of conformers or initial rotations.…”

Section: Selected Conformers Can Yield Significantly Better Docking Rmentioning

confidence: 88%

Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein–Protein Encounters

Pallara

Rueda

Abagyan

et al. 2016

J. Chem. Theory Comput.

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Section: Selected Conformers Can Yield Significantly Better Docking Rmentioning

confidence: 88%

Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein–Protein Encounters

Pallara

Rueda

Abagyan

et al. 2016

J. Chem. Theory Comput.

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“…This representation allows rotational searches to be accelerated by angular FFTs, and it enables translations to be calculated analytically in the Fourier basis (15). A similar approach has been developed by Chacon's group (16,17), in which translations are calculated numerically. However, both approaches were found to have lower accuracy than traditional Cartesian FFT sampling (15).…”

Section: Significancementioning

confidence: 99%

Protein–protein docking by fast generalized Fourier transforms on 5D rotational manifolds

Padhorny

Kazennov

Zerbe

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Energy evaluation using fast Fourier transforms (FFTs) enables sampling billions of putative complex structures and hence revolutionized rigid protein-protein docking. However, in current methods, efficient acceleration is achieved only in either the translational or the rotational subspace. Developing an efficient and accurate docking method that expands FFT-based sampling to five rotational coordinates is an extensively studied but still unsolved problem. The algorithm presented here retains the accuracy of earlier methods but yields at least 10-fold speedup. The improvement is due to two innovations. First, the search space is treated as the product manifold SO(3) × (SO(3)∖S 1 ), where SO(3) is the rotation group representing the space of the rotating ligand, and (SO(3)∖S 1 ) is the space spanned by the two Euler angles that define the orientation of the vector from the center of the fixed receptor toward the center of the ligand. This representation enables the use of efficient FFT methods developed for SO(3). Second, we select the centers of highly populated clusters of docked structures, rather than the lowest energy conformations, as predictions of the complex, and hence there is no need for very high accuracy in energy evaluation. Therefore, it is sufficient to use a limited number of spherical basis functions in the Fourier space, which increases the efficiency of sampling while retaining the accuracy of docking results. A major advantage of the method is that, in contrast to classical approaches, increasing the number of correlation function terms is computationally inexpensive, which enables using complex energy functions for scoring.etermining putative protein-protein interactions using genome-wide proteomics studies is a major step toward elucidating the molecular basis of cellular functions. Understanding the atomic details of these interactions, however, requires further biochemical and structural information. Although the most complete structural characterization is provided by X-ray crystallography, solving the structures of protein-protein complexes is frequently very difficult. Thus, it is desirable to develop computational docking methods that, starting from the coordinates of two unbound component molecules defined as receptor and ligand, respectively, are capable of providing a model of acceptable accuracy for the bound receptor-ligand complex (1-4). In view of the large number of putative proteinprotein interactions, the computational efficiency of docking is also a concern.Most global docking methods start with rigid body search that assumes only moderate conformational change upon the association, accounted for by using a smooth scoring function that allows for some level of steric overlaps (3). Rigid docking was revolutionized by the fast Fourier transform (FFT) correlation approach, introduced in 1992 by Katchalski-Katzir et al. (5). The major requirement of the method is to express the interaction energy in each receptor-ligand orientation as a sum of P correlation functions, i.e., in...

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“…FTDock (Gabb et al, 1997), ZDock (Mintseris et al, 2007), PIPER (Kozakov et al, 2006)), and by some other very successful geometry-based methods (e.g. FRODOCK (Garzon et al, 2009), Hex (Ritchie and Kemp, 2000), MolFit (Katchalski-Katzir et al, 1992)). A docking procedure usually involves several steps (Vajda and Kozakov, 2009).…”

Section: Protein-protein Dockingmentioning

confidence: 99%

Structural Bioinformatics of Proteins: Predicting the Tertiary and Quaternary Structure of Proteins from Sequence

Oliva¹,

Planas-Iglesias²,

Bonet³

et al. 2012

Protein-Protein Interactions - Computational and Experimental Tools

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FRODOCK: a new approach for fast rotational protein–protein docking

Abstract: http://sbg.cib.csic.es/Software/FRODOCK/

Cited by 132 publications

References 36 publications

Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein–Protein Encounters

Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein–Protein Encounters

Protein–protein docking by fast generalized Fourier transforms on 5D rotational manifolds

Structural Bioinformatics of Proteins: Predicting the Tertiary and Quaternary Structure of Proteins from Sequence

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