A normal mode-based geometric simulation approach for exploring biologically relevant conformational transitions in proteins. The approach has been shown to reproduce experimentally observed conformational variabilities in the case of domain and loop motions and is able to generate meaningful pathways of conformational transitions. The generated structures are of good stereochemical quality. Thus, they can serve as input to docking approaches or as starting points for more sophisticated sampling techniques.

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Provides an RNA conformational morphing procedure. KGS is an algorithm able to calculate motions of conformational change in the secondary structure constraint manifold between two conformers. It is implemented with secondary-structure-constraint-manifold-modulated conformational changes and clash-avoiding. This procedure first aligns the initial and the goal conformation and next deforms the molecule.

Combines the action minimization formalism and the Elastic Network Model (ENM) to generate trajectories between two known structural states of a given macromolecule. MinActionPath works if the harmonic approximation for the energy landscape around each state is valid. This method is exact if each state is experiencing a harmonic potential and, contrary to other similar methods, does not resort to numerical optimization methods such as Monte Carlo or simulated annealing.

Facilitates the exploration of such modes and generates feasible transition pathways between two homologous structures. iMODS supports advanced visualization capabilities for illustrating collective motions, including an improved affine-model-based arrow representation of domain dynamics. Several optimizations have been applied to iMod for supporting online service: (i) the method has been improved, including the implementation of a faster eigenproblem solver, (ii) an affine-modelbased approach has been implemented to facilitate normal mode visualization, and (iii) the simulation of conformational transition trajectories has been extended to address homologous structures.

A tool based on principal component geodesics for conformational analysis using circular data such as bond, torsion and pseudotorsion angles. The web interface of GeoPCA, which implements the principal component geodesics approach, requires as input, a file with angular data. It yields as output: (i) Cartesian coordinates of the data points projected on the first and second principal component geodesics of a sphere (orthogonal great circles on the sphere) and (ii) the values of two angles representing corresponding distances to first and second principal component geodesics for each data point. GeoPCA thus provides a useful way of visualizing, analyzing and predicting conformations of complex macromolecules with many degrees of freedom.

A web app to trace conformational transitions in proteins. GOdMD uses the fast CG dMD algorithm coupled to two biasing methods: (i) metadynamics adapted to follow proteins easiest deformation pattern, and (ii) a Metropolis-based Maxwell Demon algorithm. The method is fast and, contrary to many other approaches, always finds a smooth transition path when tested in a large dataset of transitions.

Allows modelling two or more interacting loops. m-DiSGro samples multiple loops by growing one residue at a randomly selected loop in each step. The calculation of the positions of newly added atoms is determined by the coordinates of previous placed atoms in all loops. This program can explore large conformational space of multi-loop.

A web app for determining pathways for conformational transitions in macromolecules based on the use of discrete molecular dynamics, and biasing techniques based on a combination of essential dynamics and Maxwell-Demon sampling techniques. MD-dMD can work with high efficiency at different levels of resolution, including the atomistic one, and can help to define initial pathways for further exploration by means of more accurate atomistic molecular dynamics simulations.

Pulls interresidue distances of a given conformation towards the distances in the target final conformation using a set of harmonic restraints. In this morphing method, the restraining energy depends linearly on the distance deviation between the current structure in a way that allows a great deal of flexibility to the motion of the protein. Climber moves towards the target by a sufficient amount as measured by the change in coordinate root-mean-square deviation each step to get there in Ncycle steps.

Elucidates the transition mechanisms in such supramolecular systems. Application to bacterial chaperonin GroEL and comparisons with experimental data, results from action minimization algorithm, and previous simulations support the utility of aANM as a tool for unraveling potential transition pathways sampled by large complexes. The application of aANM to GroEL therefore elucidates not only highly probable pathways or the hierarchic contribution of modes to achieve the transition, but it also provides insights into key interactions that initiate the transition, or those that form/break at the transition state(s).

Constructs a physically reasonable pathway between two endpoints of a conformational transition. ANMPathway represents a direct application of the “string method” to a two-state coarse-grained system approximated by anisotropic network model (ANM) energy surfaces. It can produce a completely optimized pathway for a 1000 residue protein in about one hour on a single CPU of a standard desktop computer. ANMPathway has been designed to provide a unique solution for the most probable pathway, with a minimal number of parameters and no biased simulations using the ANMs for the two endpoints.

Studies large-scale conformational transitions of proteins between two known structures. PATH-ENM is based on a mathematically simple form of a mixed potential, whose saddle-point and conformation-dependent free energies are easy to compute analytically or numerically. The Mixed Elastic Network Model (MENM) formalism is computationally efficient, as it only requires the construction and inversion of Hessian matrices, and is essentially not limited by the size of proteins. PATH-ENM is useful to explore large-scale conformational transitions with limited computational effort by using a coarse-grained model with a simplified energy function.

Generates a transition pathway between the two protein conformations. The key idea of iENM is to solve the saddle points of a general double-well potential function constructed from two elastic network model potential functions based at the beginning and end conformations of a transition. This mathematical problem is converted to the search for the minima of a linear interpolation of the above two Elastic Network Model (ENM) potential functions.

Permits users to prepare and run calculations. MaxOcc hides complexity of the interaction with the grid. Its calculations are run on the WeNMR grid, allowing a few hundred conformations to be analyzed simultaneously. This tool accepts as input data both paramagnetic Nuclear Magnetic Resonance (NMR) data (pcs, rdc and/or pre data) and Small-Angle X-ray Scattering (SAXS) profiles. It streamlines preparation of input data and the retrieval and analysis of the calculation results.

Allows users to construct arbitrary ligands. Rappertk can deliver multiple conformations of a protein consistent. It provides a platform for discrete restraints-based sampling and reproduces RAPPER functionalities for proteins as a special case. Its design makes it possible to apply discrete restraint-based modeling to a variety of problem.

Classifies snapshots of molecular dynamics (MD) trajectory data. DeepTrajectories is a temporal deep-learning model that employs the time-dependent nature of MD based trajectory data. It can recognize correct fold state changes from incorrect fold state changes. This tool assists users for understanding protein structure refinement in many structural bioinformatics fields such as in rational drug design.

Predicts residue positions involved in conformational switches using a protein sequence alone or in combination with solvent accessibility. FlexPred is a web server that performs the prediction using: (1) sequence-derived information for a given protein sequence, or (2) sequence-derived information and solvent accessibility of residue positions for a given PDB file. The software can discover conformational switches in proteins directly trained on a large dataset of experimentally characterized examples.

Constructs the generalized local propensity (GLP) flexibility profile and utilizes this profile to identify segments with high conformational flexibility. CFP is a web server that (i) utilizes the GLP for computing a raw numeric propensity profile for an amino acid sequence, (ii) smoothes the raw profile using a sliding window, (iii) uses the smoothed profile for partitioning the sequence into seed segments with high conformational flexibility, and (iv) assesses the significance of each final segment.

Serves to infer Markovian transition networks from time-independent data sampled from stationary equilibrium distributions. This framework associates Gaussian mixture approximations and self-consistent dimensionality reduction with multi-dimensional transition-state theory and minimal-energy path estimation. It deduces Markovian state-transition networks via reconstructed energy landscapes from high-dimensional static data.

Serves for analyzing the energetically relevant conformational changes of a biomolecule upon binding to various ligands. It can compute collective canonical variables such as linear combinations of the original features. It contains features for recognizing the conformational changes, which are relevant to the macroscopic thermodynamic change.

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Mechanism of potassium ion uptake by the
Na+/K+-ATPase

Tools (3):
ANMPathway, CHARMM, PROPKA

Topics (5):
Protein structure analysis, Metals, Alkali, Metals, Light, Metals, Alkali, Metals, Light

Prediction of protein motions from amino acid sequence and its application to protein-protein interaction

Tools (3):
FlexPred, DynDom, PROFbval

Topics (2):
Protein structure analysis, Dipturus trachyderma