Dihedral angle detection software tools | Protein structure data analysis
The prediction of the secondary structure of a protein is a critical step in the prediction of its tertiary structure and, potentially, its function. Moreover, the backbone dihedral angles, highly correlated with secondary structures, provide crucial information about the local three-dimensional structure.
Gives access to many free software tools for sequence analysis. EMBOSS aims to serve the molecular biology community. It permits the creation and the release of software in an open source spirit. This tool is useful for sequence analysis into a seamless whole. It is free of charge and is available in open source.
Predicts different sets of structural protein properties. SPIDER is an iterative deep-learning neural network. It obtains secondary structure, torsion angles, Cα−atom based angles and dihedral angles, and solvent accessible surface area. It utilises both local and nonlocal structural information in iterations. At each iteration, SPIDER employs a deep-learning neural network to predict a structural property based on structural properties predicted in the previous iteration.
Provides a software tool for secondary structure assignment from atomic resolution protein structures. STRIDE implements a knowledge-based algorithm that makes combined use of hydrogen bond energy and statistically derived backbone torsional angle information and is optimized to return resulting assignments in maximal agreement with crystallographers' designations. The STRIDE web server provides access to this tool and allows visualization of the secondary structure, as well as contact and Ramachandran maps for any file uploaded by the user with atomic coordinates in the Protein Data Bank (PDB) format. A searchable database of STRIDE assignments for the latest PDB release is also provided as well as a link to the source code to use STRIDE as a stand-alone program.
Performs task of backbone structure determination of a protein primarily based on residual dipolar couplings (RDCs) data. REDCRAFT is an open source analysis tool that accommodates the analysis of RDC data for simultaneous structure characterization and identification of dynamics of proteins and polypeptides. It also incorporates advanced programming concepts such as class based programming.
An integrated system of neural networks for real-value prediction and apply the method to predict residue-solvent accessibility and backbone psi dihedral angles of proteins based on information derived from sequences only. Real-SPINE is trained with a large data set of 2640 protein chains, sequence profiles generated from multiple sequence alignment, representative amino-acid properties, a slow learning rate, overfitting protection, and predicted secondary structures.
A web server for predicting protein torsion angle restraints. PREDITOR accepts sequence and/or chemical shift data as input and generates torsion angle predictions (with predicted errors) for phi, psi, omega and chi-1 angles. PREDITOR combines sequence alignment methods with advanced chemical shift analysis techniques to generate its torsion angle predictions. The method is fast (<40 s per protein) and accurate, with 88% of phi/psi predictions being within 30 degrees of the correct values, 84% of chi-1 predictions being correct and 99.97% of omega angles being correct. PREDITOR is 35 times faster and up to 20% more accurate than any existing method.
Allows prediction of secondary structure, accessible surface area and dihedral angles. SPINE-X is a secondary structure prediction method consisting of six steps of iterative prediction of secondary structure (SS), real-value residue solvent accessibility (RSA), and dihedral angles. The software can produce a distribution of three secondary structure states that is very close to the native distribution.
A multi-step support vector machine (SVM) procedure to predict the dihedral angle state of residues from sequence. Trained on 20,000 residues our approach leads to dihedral region predictions, that in regions without alpha helices or beta sheets is higher than those from secondary structure prediction programs.
Allows users to manage torsion libraries for small molecule drug discovery. TorsionAnalyzer is based on a collection of smiles arbitrary target specification (SMARTS) patterns coupled to rules such as assigned peaks and tolerances, through a graphical user interface. The application includes various features such as the ability to create high-quality conformation ensembles or to perform torsion distributions analysis and generation.
Calculates D2Check values. D2Check is a web application for observing correlation of the dihedral angles in both at protein and residue level. Users can determine &Phi - &Psi and &Psi - &Phi values as well as plots for user-defined or existing protein structure in the PDB. It aims to ease sites location in a studied protein.
Provides a conformer generator. CONFECT is an approach dedicated for computational modeling such as structural superimposition, docking or manual analysis of conformational space. It combines a torsion pattern hierarchy with an incremental construction-based sampling algorithm, suited for small conformational ensembles. The application is available as part of the TorsionAnalyzer software package or as a standalone software on demand.
A machine-learning based algorithm for ab initio prediction of protein backbone torsion angles. For a given amino acid sequence, the real-value backbone torsion angles (phi and psi) for each residue are predicted by the combination of the neural network training and the support vector machine.
Predicts the protein backbone torsion angles from amino acid sequences. TANGLE uses a two-level support vector regression approach to perform real-value torsion angle prediction using a variety of features derived from amino acid sequences, including the evolutionary profiles in the form of position-specific scoring matrices, predicted secondary structure, solvent accessibility and natively disordered region as well as other global sequence features.
An accurate predictor of backbone dihedral angles and secondary structure. Using predicted secondary structure and dihedral angles, our method improves the predictive accuracy of both secondary structure and dihedral angle prediction in an iterative process using SVMs. The achieved secondary structure Q3 accuracy of 80% on a set of 513 non-redundant proteins shows that our method is more accurate than other secondary structure prediction methods.
Constructs probabilistic models of biomolecular structure, due to its support for directional statistics. Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distributions, including distributions from directional statistics (the statistics of angles, directions and orientations). The tool is suitable for the Kent distribution on the sphere and the bivariate von Mises distribution on the torus.
Calculates protein torsion angle prediction. DNTor is a deep learning machine that considers four methods: Deep Neural Network, Deep Recurrent Neural Network, Deep Restricted Boltzmann Machines and Deep Recurrent Restricted Boltzmann Machines. The software allows to highlight two novel features: predicted contact number and error distribution of fragment-based torsion angles which are efficient in torsion angle prediction.
Provides processing and protonation of molecules analyses. Mollib is a command line program and a Python library developed to validate, improve quality analysis and manipulate molecular structures with a focus on biophysical analysis. This method is built on a plugin framework to add new tools for manipulating and analyzing structures and data, which can then be merged and cross-validated.
Predicts a large number of protein torsion angles (phi, psi, omega, chi1) using only 1H, 13C and 15N chemical shift assignments as input. SHIFTOR program is capable of predicting chi1 angles with 81% accuracy and omega angles with 100% accuracy. SHIFTOR exploits many developments and observations regarding chemical shift dependencies as well as using information in the Protein Databank (PDB) to improve the quality of its shift-derived torsion angle predictions. SHIFTOR is available as a freely accessible web server.
Assists users in determining real-valued dihedral angles. RaptorX-Angle is an approach that gathers clustering and deep learning with the aim of improving functional study as well as protein structure prediction. The method consists in predicting the label posterior probability of each cluster of angles created by the algorithm thanks to a deep residual neural network. These probabilities are then mixed with the clusters to finally establish real-values prediction.