Protein PocketViewer: A Web-Service Based Interface for Protein Pocket Extraction and Visualization (original) (raw)
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Nucleic Acids Research, 2004
Protein Dossier ( J PD) is a new concept, database and visualization tool providing one of the largest collections of the physicochemical parameters describing proteins' structure, stability, function and interaction with other macromolecules. By collecting as many descriptors/parameters as possible within a single database, we can achieve a better use of the available data and information. Furthermore, data grouping allows us to generate different parameters with the potential to provide new insights into the sequence-structure-function relationship. In J PD, residue selection can be performed according to multiple criteria. J PD can simultaneously display and analyze all the physicochemical parameters of any pair of structures, using precalculated structural alignments, allowing direct parameter comparison at corresponding amino acid positions among homologous structures. In order to focus on the physicochemical (and consequently pharmacological) profile of proteins, visualization tools (showing the structure and structural parameters) also had to be optimized. Our response to this challenge was the use of Java technology with its exceptional level of interactivity. J PD is freely accessible (within the Gold Sting Suite) at
PDB explorer — A web based algorithm for protein annotation viewer and 3D visualization
Interdisciplinary Sciences: Computational Life Sciences December 2014, Volume 6, Issue 4, pp 279-284
The PDB file format, is a text format characterizing the three dimensional structures of macro molecules available in the Protein Data Bank (PDB). Determined protein structure are found in coalition with other molecules or ions such as nucleic acids, water, ions, Drug molecules and so on, which therefore can be described in the PDB format and have been deposited in PDB database. PDB is a machine generated file, it's not human readable format, to read this file we need any computational tool to understand it. The objective of our present study is to develop a free online software for retrieval, visualization and reading of annotation of a protein 3D structure which is available in PDB database. Main aim is to create PDB file in human readable format, i.e., the information in PDB file is converted in readable sentences. It displays all possible information from a PDB file including 3D structure of that file. Programming languages and scripting languages like Perl, CSS, Javascript, Ajax, and HTML have been used for the development of PDB Explorer. The PDB Explorer directly parses the PDB file, calling methods for parsed element secondary structure element, atoms, coordinates etc. PDB Explorer is freely available at http://www.pdbexplorer.eminentbio.com/home with no requirement of log-in.
EXTRACTION, QUANTIFICATION AND VISUALIZATION OF PROTEIN POCKETS
Computational Systems Bioinformatics - Proceedings of the Conference CSB 2007, 2007
Molecular surfaces of proteins and other biomolecules, while modeled as smooth analytic interfaces separating the molecule from solvent, often contain a number of pockets, holes and interconnected tunnels with many openings (mouths), 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 φ P (x) as the result of an outward and backward propagation. The regions inside pockets can be represented as φ P (x) > 0 and pocket boundaries are computed as the level set φ P (x) = , where > 0 is a small number. The pocket function φ P (x) can be computed efficiently by fast distance transforms. This volumetric representation allows pockets to be analyzed quantitatively and visualized with various techniques. Such feature analysis and quantitative visualization are also generalizable to many other classes of smooth and analytic free-form surfaces or interface boundaries.
3D-SURFER 2.0: Web Platform for Real-Time Search and Characterization of Protein Surfaces
Methods in Molecular Biology, 2014
The increasing number of uncharacterized protein structures necessitates the development of computational approaches for function annotation using the protein tertiary structures. Protein structure database search is the basis of any structure-based functional elucidation of proteins. 3D-SURFER is a web platform for real-time protein surface comparison of a given protein structure against the entire PDB using 3D Zernike descriptors. It can smoothly navigate the protein structure space in real-time from one query structure to another. A major new feature of Release 2.0 is the ability to compare the protein surface of a single chain, a single domain, or a single complex against databases of protein chains, domains, complexes, or a combination of all three in the latest PDB. Additionally, two types of protein structures can now be compared: all-atom-surface and backbone-atom-surface. The server can also accept a batch job for a large number of database searches. Pockets in protein surfaces can be identified by VisGrid and LIGSITE csc . The server is available at http://kiharalab.org/3d-surfer/.
CAVER: a new tool to explore routes from protein clefts, pockets and cavities
BMC bioinformatics, 2006
The main aim of this study was to develop and implement an algorithm for the rapid, accurate and automated identification of paths leading from buried protein clefts, pockets and cavities in dynamic and static protein structures to the outside solvent. The algorithm to perform a skeleton search was based on a reciprocal distance function grid that was developed and implemented for the CAVER program. The program identifies and visualizes routes from the interior of the protein to the bulk solvent. CAVER was primarily developed for proteins, but the algorithm is sufficiently robust to allow the analysis of any molecular system, including nucleic acids or inorganic material. Calculations can be performed using discrete structures from crystallographic analysis and NMR experiments as well as with trajectories from molecular dynamics simulations. The fully functional program is available as a stand-alone version and as plug-in for the molecular modeling program PyMol. Additionally, selec...
ProteinTools: a toolkit to analyze protein structures
Nucleic Acids Research, 2021
The experimental characterization and computational prediction of protein structures has become increasingly rapid and precise. However, the analysis of protein structures often requires researchers to use several software packages or web servers, which complicates matters. To provide long-established structural analyses in a modern, easy-to-use interface, we implemented ProteinTools, a web server toolkit for protein structure analysis. ProteinTools gathers four applications so far, namely the identification of hydrophobic clusters, hydrogen bond networks, salt bridges, and contact maps. In all cases, the input data is a PDB identifier or an uploaded structure, whereas the output is an interactive dynamic web interface. Thanks to the modular nature of ProteinTools, the addition of new applications will become an easy task. Given the current need to have these tools in a single, fast, and interpretable interface, we believe that ProteinTools will become an essential toolkit for the w...
Proteins Pockets Analysis and Description
Proceedings of the First International Conference on Bioinformatics, 2010
The development of computational techniques to guide the experimental processes is an important step for the determination of the protein functions. The purpose of the activity here described is the characterization of the active sites in protein surfaces and their quantitative representation. A few pocket parameters like volume, travel depth, mouth area and perimeter, amplitude parameters, interfacial area ratio, summit density and mean summit curvature are hierarchically accessible through a concavity tree that topologically represents the entire protein molecule. This structural representation is particularly useful for the evaluation of binding pockets, the comparison of the morphological similarity and the identification of potential ligand docking.
Nucleic Acids Research, 2013
Residue depth accurately measures burial and parameterizes local protein environment. Depth is the distance of any atom/residue to the closest bulk water. We consider the non-bulk waters to occupy cavities, whose volumes are determined using a Voronoi procedure. Our estimation of cavity sizes is statistically superior to estimates made by CASTp and VOIDOO, and on par with McVol over a data set of 40 cavities. Our calculated cavity volumes correlated best with the experimentally determined destabilization of 34 mutants from five proteins. Some of the cavities identified are capable of binding small molecule ligands. In this study, we have enhanced our depth-based predictions of binding sites by including evolutionary information. We have demonstrated that on a database (LigASite) of $200 proteins, we perform on par with ConCavity and better than MetaPocket 2.0. Our predictions, while less sensitive, are more specific and precise. Finally, we use depth (and other features) to predict pK a s of GLU, ASP, LYS and HIS residues. Our results produce an average error of just <1 pH unit over 60 predictions. Our simple empirical method is statistically on par with two and superior to three other methods while inferior to only one. The DEPTH server (http://mspc.bii.a-star.edu.sg/depth/) is an ideal tool for rapid yet accurate structural analyses of protein structures.
Journal of Molecular Graphics, 1992
A new interactive graphics program is described that provides a quick and simple procedure for identifying, displaying, and manipulating the indentations, cavities, or holes in a known protein structure. These regions are defined as, e.g., the x,,, yO, z, values at ~vhich a test sphere of radius r can be placed without touching the centers of any protein atoms, subject to the condition that there is some x < x0 and some x > x0 where the sphere does touch the protein atoms. The surfaces of these pockets are modeled using a modification of the marching cubes algorithm. This modification provides identification of each closed sur$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.