Channel detection bioinformatics tools | Protein structure analysis - OMICtools

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Provides rapid, accurate and fully automated calculation of tunnels and channels in static structures. The molecules amendable to analysis of CAVER include proteins, nucleic acids or inorganic materials. CAVER can be used either as PyMol plugin or independent application CAVER Analyst. CAVER Analyst has been designed for easy set-up of calculation, visualization of results and efficient data analysis. It can be used for both static structures and molecular ensembles from molecular dynamic simulations or NMR.

A web-based interactive application for the analysis of access/egress paths to interior molecular voids. MOLEonline 2.0 enables platform-independent, easy-to-use and interactive analyses of (bio)macromolecular channels, tunnels and pores. Results are presented in a clear manner, making their interpretation easy. For each channel, MOLEonline displays a 3D graphical representation of the channel, its profile accompanied by a list of lining residues and also its basic physicochemical properties.

A tool for the identification of high clearance pathways or corridors which represent molecular channels in the complement space of proteins. MolAxis is extremely efficient because it samples the medial axis of the complement of the molecule, reducing the problem dimension to two, since the medial axis is composed of surface patches. It is designed to analyze proteins channels, calculate pore dimensions and analyze atom accessibility.

3V / Voss Volume Voxelator

Extracts and comprehensively analyzes all the internal volumes from input RNA and protein structures. 3V rapidly finds internal volumes by taking the difference between two rolling-probe solvent-excluded surfaces, one with as large as possible a probe radius and the other with a solvent radius (typically 1.5 A for water).

A web server that can generate contiguous conformations of a molecule along a curved tunnel inside a protein, and the binding free energy profile along the predicted channel pathway. SLITHER adopts an iterative docking scheme, which combines with a puddle-skimming procedure, i.e. repeatedly elevating the potential energies of the identified global minima, thereby determines the contiguous binding modes of substrates inside the protein.

Molecular cavities, which include voids and channels, are critical for molecular function. BetaCavityWeb computes these cavities for a given molecular structure and a given spherical probe, and reports their geometrical properties: volume, boundary area, buried area, etc. The server's algorithms are based on the Voronoi diagram of atoms and its derivative construct: the beta-complex.

The increasing number of available atomic 3D structures of transmembrane channel proteins represents a valuable resource for better understanding their structure-function relationships and to eventually predict their selectivity. PoreLogo is an automatic tool for analysing, visualizing and comparing the amino acid composition of transmembrane channels and its conservation across the corresponding protein family.

CCCPP / Computes Cavities, Channels, Pores and Pockets in proteins

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.

Finds protein cavities throughout Molecular Dynamics (MD) simulation trajectories. trj_cavity can analyse the solvent occupancy of the cavities identified. This tool is implemented within the GROMACS framework for the rapid identification and characterization of cavities detected within MD trajectories. It is also optimized for usability and computational efficiency and is applicable to the time-dependent analysis of any cavity topology, and optional specialized descriptors can be used to characterize, protein channels.

A fully automated method designed to detect and characterise transmembrane protein channels from their 3D structure. A stepwise procedure is followed in which the pore centre and pore axis are first identified and optimised using geometric criteria, and then the biggest and longest cavity through the channel is detected. Finally, pore features, including diameter profiles, pore-lining residues, size, shape and regularity of the pore are calculated, providing a quantitative and visual characterization of the channel.

An algorithm to automatically find, characterize, and display tunnels or pores in proteins. The correctness and accuracy of the algorithm is verified on a constructed set of proteins and used to analyze large sets of real proteins.

Allows one to generate a Brownian dynamics trajectory of ions in a channel system. GCMC/BD is a web-based graphical user interface presented for grand canonical Monte Carlo (GCMC) BD simulations of channel proteins. This is a method used to maintain the desired electrochemical conditions in the boundaries (buffer regions) of the simulation system which are in (equilibrium) contact with the bulk. The webserver is designed to help users avoid most of the technical difficulties and issues encountered in setting up and simulating complex pore systems.

A sequence-based predictor for identifying the subfamilies of voltage-gated potassium channels. iVKC-OTC has been developed by incorporating the optimized tripeptide composition (OTC) generated by feature selection technique into the general form of pseudo-amino acid composition to identify six subfamilies of voltage-gated K+ channels (VKCs). One of the remarkable advantages of introducing the optimized tripeptide composition is being able to avoid the notorious dimension disaster or over fitting problems in statistical predictions.

A toolkit for identifying pockets, cavities and channels of protein structures. The toolkit was developed in PERL programming language and includes “PoreID” for pore identification, “PoreTrace” for pore axes determination and “GateOpen” for opening the gate between neighboring pores. “PoreID” is a grid-based method that avoids orientation dependency of the results. It targets all kinds of pores (pockets, cavities and channels) and is automatic so that only the PDB file of the target protein has to be specified by the user.

A program that generates a "casting" of the interior volume of the protein as dummy atoms. The use of HOLLOW significantly simplifies the generation of channel surfaces, and other interior surfaces of protein structures.

PrinCCes / Protein internal Channel & Cavity estimation

A computer program supporting the visualization of voids. PrinCCes includes a novel algorithm for the decomposition of the entire void volume of the protein or protein complex to individual entities. The decomposition is based on continuity. An individual void is defined by uninterrupted extension in space: a spherical probe can freely move between any two internal locations of a continuous void. Continuous voids are detected irrespective of their topological complexity, they may contain any number of holes and bifurcations. The voids of a protein can be visualized one by one or in combinations as triangulated surfaces.

A program that allows the analysis and visualisation of the pore dimensions of the holes through molecular structures of ion channels. The algorithm uses a Monte Carlo simulated annealing procedure to find the best route for a sphere with variable radius to squeeze through the channel.

Simulates electrophysiology of 11 different types of ion channels via Hodgkin-Huxley style differential equations. Panama assists users to create the response of whole-cell or single-channel parameters to electrical of pharmacological stimuli. It can simulate ion channels (such as among others, voltage-gated sodium, potassium, or chloride channels) under both current clamp and voltage clamp conditions.

A method for molecular channel extraction based on the alpha complex representation. The method computes geometrically feasible channels, stores both the volume occupied by the channel and its centerline in a unified representation, and reports significant channels. The representation also supports efficient computation of channel profiles that help understand channel properties.

Allows identification of ion channels and their types. IonchanPred consists in a support vector machine-based model employing a feature extraction method called pseudo-dipeptide. The software can discriminate between ion channels and non-ion channels, distinguish between voltage-gated ion channels and ligand-gated ion channels and predict sodium, potassium, calcium and anion voltage-gated channels.

A support vector machine based method was proposed to predict VKC subfamilies using amino acid and dipeptide compositions. In order to remove redundant information, a novel feature selection technique was employed to single out optimized features. In the jackknife cross-validation, the proposed method (VKCPred) achieved an overall accuracy of 93.09% with 93.22% average sensitivity and 98.34% average specificity, which are superior to that of other two state-of-the-art classifiers.

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Laurence Menu-Bouaouiche

Assistant professor Rouen University

Yashwanth Subbannayya

Metabolomics YU-IOB Center for Systems Biology and Molecular Medicine, Mangalore, India

Dr. Yashwanth Subbannayya obtained his M.Sc. degree in Medical Biochemistry from Manipal University. He qualified the competitive CSIR-UGC National Eligibility Test and joined the Institute of Bioinformatics, Bangalore as a UGC Junior Research Fellow. As part of his Ph.D. work, he studied the molecular mechanisms of gastric cancer in clinical specimens using quantitative proteomic technologies. This study, the results of which were published in Cancer Biology and Therapy, yielded a novel therapeutic target for gastric cancer- CAMKK2. Further, he also studied the serum proteome of gastric cancer patients and developed assays for potential markers using the revolutionary multiple reaction monitoring approach. The results of this study were published in Journal of Proteomics. In addition to his research work, he also trained extensively in sample preparation for mass spectrometry, fractionation techniques and gained expertise in quantitative proteomic techniques and data analysis. In addition, he also trained extensively in various validation platforms including immunohistochemsitry, multiple reaction monitoring and Western blot. He has also worked as a curator for several biological databases including NetPath, Human Protein Reference Database (HPRD) and Breast cancer database. His work in various research projects have yielded him 23 publications either as lead author or co-author in peer reviewed journals. He is a reviewer for the journal Proteomics. Dr. Yashwanth Subbannayya joined the YU-IOB Center for Systems Biology and Molecular Medicine in June, 2015. During the initial period, his job consisted of assisting other personnel of the university in the establishment of YU-IOB Center for Systems Biology and Molecular Medicine. He was also involved in training of Ph.D. students in biological aspects. After the establishment of the center, he trained in cell culture techniques and metabolomics analysis. At YU-IOB CSBMM, he is studying the molecular mechanisms in various cancers including oral cancer. In addition, he is studying the molecular mechanisms as well as the metabolic constituents of traditional medicine formulations using mass spectrometry technologies. In June 2016, he convened the national symposium “Genomics in clinical practice: Future of precision medicine” held at Yenepoya University on June 1 and 2, 2016. The resource persons included 16 individuals from various academic organizations as well as industry. The symposium was attended by 218 participants from 24 institutions around India. He is a member of the Scientific Review Board of Yenepoya Research Centre where he facilitates timely scientific review of research projects.

Research Associate UCL

MAFFT MOLE PSAIA

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