Computing cavities, channels, pores and pockets in proteins from non-spherical ligands models

Benkaidali, Lydia; André, François; Maouche, Boubekeur; Siregar, Pridi; Benyettou, M.; Maurel, François; Petitjean, Michel

doi:10.1093/bioinformatics/btt644

Cited by 36 publications

(43 citation statements)

References 72 publications

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“…The name of this software was built from the five first initials of the title of ref. [8] (Computing Cavities, Channels, Pores and Pocket…), in which the method implemented in CCCPP is described. For clarity we summarize this method as follows.…”

Section: Methodsmentioning

confidence: 99%

“…[24] Molecular size/weight is considered through the CCCPP methodology, which takes in account the size and shape of the ligand. [8] We considered that block 1 (opened in the apo form) is neither hydrophilic nor electrophilic enough to receive molecules with high Log(P) and Hü ckel energy. Receiving such molecules is feasible due to the malleability of the 3A4, via opening of block 2.…”

Section: Full Papermentioning

confidence: 99%

See 1 more Smart Citation

The Cytochrome P450 3A4 has three Major Conformations: New Clues to Drug Recognition by this Promiscuous Enzyme

Benkaidali

André

Moroy

et al. 2017

Molecular Informatics

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Dedication: This paper is dedicated to the memory of Professor Boubekeur Maouche. Abstract:We computed the channels of the 3A4 isoform of the cytochrome P450 3A4 (CYP) on the basis of 24 crystal structures extracted from the Protein Data Bank (PDB). We identified three major conformations (denoted C, O1 and O2) using an enhanced version of the CCCPP software that we developed for the present work, while only two conformations (C and O 2 ) are considered in the literature.We established the flowchart of definition of these three conformations in function of the structural and physicochemical parameters of the ligand. The channels are characterized with qualitative and quantitative parameters, and not only with their surrounding secondary structures as it is usually done in the literature

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Section: Methodsmentioning

confidence: 99%

Section: Full Papermentioning

confidence: 99%

The Cytochrome P450 3A4 has three Major Conformations: New Clues to Drug Recognition by this Promiscuous Enzyme

Benkaidali

André

Moroy

et al. 2017

Molecular Informatics

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“…Many other methods for the detection of cavities and pockets exist, such as the method of Liang et al based on (weighted) alpha shapes and discrete flow, implemented in the software tool CASTp, or the method of Kim et al based on the Voronoi diagram of atomic balls and beta shapes. In Kim's method, the concept of small and large probes is used differently than in Kawabata's.…”

Section: Introductionmentioning

confidence: 99%

Voronoi‐based detection of pockets in proteins defined by large and small probes

Maňák

2019

J Comput Chem

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The function of enzymatic proteins is given by their ability to bind specific small molecules into their active sites. These sites can often be found in pockets on a hypothetical boundary between the protein and its environment. Detection, analysis, and visualization of pockets find its use in protein engineering and drug discovery. Many definitions of pockets and algorithms for their computation have been proposed. Kawabata and Go defined them as the regions of empty space into which a small spherical probe can enter but a large probe cannot and developed programs that can compute their approximate shape. In this article, this definition was slightly modified in order to capture the existence of large internal holes, and a Voronoi‐based method for the computation of the exact shape of these modified regions is introduced. The method first puts a finite number of large probes on the protein exterior surface and then, considering both large probes and atomic balls as obstacles for the small probe, the method computes the exact shape of the regions for the small probe. This is all achieved with Voronoi diagrams, which help with the safe navigation of spherical probes among spherical obstacles. Detected regions are internally represented as graphs of vertices and edges describing possible movements of the center of the small probe on Voronoi edges. The surface bounding each region is obtained from this representation and used for visualization, volume estimation, and comparison with other approaches. © 2019 Wiley Periodicals, Inc.

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“…How to define this boundary is polemical. Among the numerous methods computing cavities, very few compute a cavity boundary. Most methods view the boundary of a cavity through a set of heavy atoms in the protein.…”

Section: Methodsmentioning

confidence: 99%

A Fast Algorithm to Compute Conical Pockets in Proteins. Application to the Structural Characterization of γ‐Carbonic Anhydrases

Petitjean

2017

Molecular Informatics

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Some major proteins families, such as carbonic anhydrases (CAs), have a conical cavity at the active site. No algorithm was available to compute conical cavities, so we needed to design one. The fast algorithm we designed let us show on a set of 717 CAs extracted from the PDB database that γ-CAs are characterized by active site cavity cone angles significantly larger than those of α-CAs and β-CAs: the generatrix-axis angles are greater than 60° for the γ-CAs while they are smaller than 50° for the other CAs. Free binaries of the CONICA software implementing the algorithm are available through a software repository at http://petitjeanmichel.free.fr/itoweb.petitjean.freeware.html.

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Computing cavities, channels, pores and pockets in proteins from non-spherical ligands models

Abstract: michel.petitjean@univ-paris-diderot.fr.

Cited by 36 publications

References 72 publications

The Cytochrome P450 3A4 has three Major Conformations: New Clues to Drug Recognition by this Promiscuous Enzyme

The Cytochrome P450 3A4 has three Major Conformations: New Clues to Drug Recognition by this Promiscuous Enzyme

Voronoi‐based detection of pockets in proteins defined by large and small probes

A Fast Algorithm to Compute Conical Pockets in Proteins. Application to the Structural Characterization of γ‐Carbonic Anhydrases

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