Identifification of Substrate Channels and Protein Cavities (original) (raw)
Related papers
An algorithm to find channels and cavities within protein crystals
Journal of Molecular Graphics, 1994
We have written a package called CHANNEL for determining and analyzing the channels and cavities within protein crystals. By using CHANNEL, the intermolecular space within a crystal lattice can be divided into closed cavities and channels. This package is certainly useful in determining the channel topological structure and quantitative characteristics. The package allows also the volume, and maximal and minimal areas of channels along a required direction to be calculated.
A novel and efficient tool for locating and characterizing protein cavities and binding sites
Proteins: Structure, Function, and Bioinformatics, 2009
Systematic investigation of a protein and its binding site characteristics are crucial for designing small molecules that modulate protein functions. However, fundamental uncertainties in binding site interactions and insufficient knowledge of the properties of even well-defined binding pockets can make it difficult to design optimal drugs. Herein, we report the development and implementation of a cavity detection algorithm built with HINT toolkit functions that we are naming VICE (Vectorial Identification of Cavity Extents). This very efficient algorithm is based on geometric criteria applied to simple integer grid maps. In testing, we carried out a systematic investigation on a very diverse data set of proteins and protein-protein/protein-polynucleotide complexes for locating and characterizing the indentations, cavities, pockets, grooves, channels and surface regions. Additionally, we evaluated a curated data set of unbound proteins for which a ligand-bound protein structures are also known; here the VICE algorithm located the actual ligand in the largest cavity in 83% of the cases and in one of the three largest in 90% of the cases. An interactive front-end provides a quick and simple procedure for locating, displaying and manipulating cavities in these structures. Information describing the cavity, including its volume and surface area metrics, and lists of atoms, residues and/or chains lining the binding pocket, can be easily obtained and analyzed. For example, the relative cross-sectional surface area (to total surface area) of cavity openings in well-enclosed cavities is 0.06 ± 0.04 and in surface clefts or crevices is 0.25 ± 0.09.
MolAxis: Efficient and accurate identification of channels in macromolecules
Proteins: Structure, Function, and Bioinformatics, 2008
Channels and cavities play important roles in macromolecular functions, serving as access/exit routes for substrates/products, cofactor and drug binding, catalytic sites, and ligand/protein. In addition, channels formed by transmembrane proteins serve as transporters and ion channels. MolAxis is a new sensitive and fast tool for the identification and classification of channels and cavities of various sizes and shapes in macromolecules. MolAxis constructs corridors, which are pathways that represent probable routes taken by small molecules passing through channels. The outer medial axis of the molecule is the collection of points that have more than one closest atom. It is composed of two-dimensional surface patches and can be seen as a skeleton of the complement of the molecule. We have implemented in MolAxis a novel algorithm that uses state-of-the-art computational geometry techniques to approximate and scan a useful subset of the outer medial axis, thereby reducing the dimension of the problem and consequently rendering the algorithm extremely efficient. MolAxis is designed to identify channels that connect buried cavities to the outside of macromolecules and to identify transmembrane channels in proteins. We apply MolAxis to enzyme cavities and transmembrane proteins. We further utilize MolAxis to monitor channel dimensions along Molecular Dynamics trajectories of a human Cytochrome P450. MolAxis constructs high quality corridors for snapshots at picosecond timescale intervals substantiating the gating mechanism in the 2e substrate access channel. We compare our results with previous tools in terms of accuracy, performance and underlying theoretical guarantees of finding the desired pathways. MolAxis is available on line as a web-server and as a standalone easy-to-use program (http://bioinfo3d.cs.tau.ac.il/MolAxis/).
MolAxis: a server for identification of channels in macromolecules
Nucleic Acids Research, 2008
MolAxis is a freely available, easy-to-use web server for identification of channels that connect buried cavities to the outside of macromolecules and for transmembrane (TM) channels in proteins. Biological channels are essential for physiological processes such as electrolyte and metabolite transport across membranes and enzyme catalysis, and can play a role in substrate specificity. Motivated by the importance of channel identification in macromolecules, we developed the MolAxis server. MolAxis implements state-of-the-art, accurate computational-geometry techniques that reduce the dimensions of the channel finding problem, rendering the algorithm extremely efficient. Given a protein or nucleic acid structure in the PDB format, the server outputs all possible channels that connect buried cavities to the outside of the protein or points to the main channel in TM proteins. For each channel, the gating residues and the narrowest radius termed 'bottleneck' are also given along with a full list of the lining residues and the channel surface in a 3D graphical representation. The users can manipulate advanced parameters and direct the channel search according to their needs. MolAxis is available as a web server or as a stand-alone program at http://bioinfo3d.cs.tau.ac.il/MolAxis.
Chanalyzer: A Computational Geometry Approach for the Analysis of Protein Channel Shape and Dynamics
Frontiers in Molecular Biosciences
Morphological analysis of protein channels is a key step for a thorough understanding of their biological function and mechanism. In this respect, molecular dynamics (MD) is a very powerful tool, enabling the description of relevant biological events at the atomic level, which might elude experimental observations, and pointing to the molecular determinants thereof. In this work, we present a computational geometry-based approach for the characterization of the shape and dynamics of biological ion channels or pores to be used in combination with MD trajectories. This technique relies on the earliest works of Edelsbrunner and on the NanoShaper software, which makes use of the alpha shape theory to build the solvent-excluded surface of a molecular system in an aqueous solution. In this framework, a channel can be simply defined as a cavity with two entrances on the opposite sides of a molecule. Morphological characterization, which includes identification of the main axis, the corresp...
Computing cavities, channels, pores and pockets in proteins from non-spherical ligands models
Bioinformatics, 2014
Identifying protein cavities, channels and pockets accessible to ligands is a major step to predict potential protein-ligands complexes. It is also essential for preparation of protein-ligand docking experiments in the context of enzymatic activity mechanism and structure-based drug design. We introduce a new method, implemented in a program named CCCPP, which computes the void parts of the proteins, i.e. cavities, channels and pockets. The present approach is a variant of the alpha shapes method, with the advantage of taking into account the size and the shape of the ligand. We show that the widely used spherical model of ligands is most of the time inadequate and that cylindrical shapes are more realistic. The analysis of the void parts of the protein is done via a network of channels depending on the ligand. The performance of CCCPP is tested with known substrates of cytochromes P450 (CYP) 1A2 and 3A4 involved in xenobiotics metabolism. The test results indicate that CCCPP is able to find pathways to the buried heminic P450 active site even for high molecular weight CYP 3A4 substrates such as two ketoconazoles together, an experimentally observed situation. Free binaries are available through a software repository at http://petitjeanmichel.free.fr/itoweb.petitjean.freeware.html michel.petitjean@univ-paris-diderot.fr.
Journal of Molecular Graphics, 1992
A new interactive graphics program is described that provides a quick and simple procedure for identifying, displaying, and manipulating the indentations, cavities, or holes in a known protein structure. These regions are defined as, e.g., the x,,, yO, z, values at ~vhich a test sphere of radius r can be placed without touching the centers of any protein atoms, subject to the condition that there is some x < x0 and some x > x0 where the sphere does touch the protein atoms. The surfaces of these pockets are modeled using a modification of the marching cubes algorithm. This modification provides identification of each closed sur$ace so that by "clicking' ' on any line of the surface, the entire surface can be selected. The surface can be displayed either as a line grid or as a solid surface. After the desired "pocket' ' has been selected, the amino acid residues and atoms that surround this pocket can be selected and displayed. The protein database that is input can have more than one protein "segment,' ' allowing identification of the pockets at the interface between proteins. The use of the program is illustrated with several specifc examples. The program is written in C and requires Silicon Graphics graphics routines.
A Novel Geometric Algorithm for Protein Pocket Extraction , Quantification And Visualization
2008
Molecular surfaces of proteins and other bio-molecules, while modeled as smooth analytic interfaces separating the molecule from solvent, often contain a number of pockets, holes and interconnected tunnels, aka molecular features in contact with the solvent. Several of these molecular features are biochemically significant as pockets are often active sites for ligand binding or enzymatic reactions, and tunnels are often solvent ion conductance zones. Since pockets or holes or tunnels share similar surface feature visavis their openings (mouths), we shall sometimes refer to these molecular features collectively as generalized pockets or pockets. In this paper we focus on elucidating all these pocket features of a protein (from its atomistic description), via a simple and practical geometric algorithm. We use a two-step level set marching method to compute a volumetric pocket function P (x) as the result of an outward and backward propagation. The regions inside pockets can be represe...
Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey
Computer Graphics Forum
Detecting and analyzing protein cavities provides significant information about active sites for biological processes (e.g., protein-protein or protein-ligand binding) in molecular graphics and modeling. Using the three-dimensional structure of a given protein (i.e., atom types and their locations in 3D) as retrieved from a PDB (Protein Data Bank) file, it is now computationally viable to determine a description of these cavities. Such cavities correspond to pockets, clefts, invaginations, voids, tunnels, channels, and grooves on the surface of a given protein. In this work, we survey the literature on protein cavity computation and classify algorithmic approaches into three categories: evolution-based, energy-based, and geometry-based. Our survey focuses on geometric algorithms, whose taxonomy is extended to include not only sphere-, grid-, and tessellation-based methods, but also surface-based, hybrid geometric, consensus, and time-varying methods. Finally, we detail those techniques that have been customized for GPU (Graphics Processing Unit) computing.