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Combines multiple sources of information and complementary methods at all five stages of the protein structure prediction process including template identification, template combination, model generation, model assessment, and model refinement. The MULTICOM protein structure prediction pipeline stands ready to meet the needs of the research community and is accessible via a web service. The method uses a multi-level combination technique to combine multiple protein structure templates and sources of structural information to generate models and then employs a number of model refinement and selection tools to return the best possible predicted structure. The MULTICOM system is capable of using both template-based and template-free modeling to handle the full spectrum of protein modeling and generate predictions for all protein structure prediction tasks from the relatively easy to difficult.
RosettaES / Rosetta Enumerative Sampling
Automates, improves upon, and expedites de novo model building. RosettaES uses fragment-based sampling to enumerate a ‘pool’ of possible protein conformations that both possess physically realistic geometry and are consistent with the experimental density data. It rebuilds multiple interacting segments by independently sampling and combining, iterating the process as necessary until a set of non-clashing solutions is found. RosettaES is a part of the Rosetta Suite.
An interactive web server for consistent and computationally efficient protein structure refinement with the capability to perform web-based statistical and visual analysis. The 3Drefine refinement protocol utilizes iterative optimization of hydrogen bonding network combined with atomic-level energy minimization on the optimized model using a composite physics and knowledge-based force fields for efficient protein structure refinement. The method has been extensively evaluated on blind CASP experiments as well as on large-scale and diverse benchmark datasets and exhibits consistent improvement over the initial structure in both global and local structural quality measures. The 3Drefine web server allows for convenient protein structure refinement through a text or file input submission, email notification, provided example submission and is freely available without any registration requirement.
A web server for protein model structure refinement that is particularly successful in improving local structure quality as demonstrated by the tests on CASP refinement category targets and CASP10 server models. On average, it shows moderate improvement in backbone structure quality. GalaxyRefine first rebuilds all side-chain conformations and repeatedly relaxes the structure by short molecular dynamics simulations after side-chain repacking perturbations. The server may be used to refine model structures obtained from available structure prediction methods, including the current best template-based modeling servers.
Identifies and fixes likely errors in user supplied 3D models of proteins via successive rounds of refinement. ReFOLD allows users to quickly visualize the key residue locations, which are likely to have been improved. It uses a unique hybrid approach consisting of rapid iterative refinement with i3Drefine and molecular dynamics simulations with NAMD, combined with the leading model quality estimation method ModFOLD. The tool returns an accurate estimate of the likely percentage improvement in the global quality score based on the top refined model.
Princeton TIGRESS / proTeIn Geometry REfinement using Simulations and Support vector machines
Provides an automated refinement method that intends to refine an input protein structure by addressing both sampling and selection. First, Princeton_TIGRESS generates many local minima near the starting structure using torsion-angle dynamics in Cyana. Each of these local minima are next relaxed using Rosetta Fast Relax in order to repack the side-chains and to make movements that will enhance the number of hydrogen bonds. This ensemble of structures is next filtered to remove structures deviating and passed through a support vector machines model which classifies which structures have moved in the more native-like direction. The models are then scored using the dDFIRE energy function and the lowest energy structure is selected. This structure is then refined in CHARMM using the FACTS implicit solvent model. The final refined structure is sent to the user which has substantially lower clashes and aims to improve GDT_TS based on benchmarking on all CASP7, 8, 9, and 10 refinement targets and typical use runs.
PREFMD / Protein structure REFinement via Molecular Dynamics
Offers a protein structure refinement web server. PREFMD implements an extensive molecular dynamics (MD)-based refinement protocol based on the best-performing refinement method. It relies on initial rounds of explicit solvent MD simulations with weak positional restraints to prevent large structural deviations. This tool performs well at reduced computational costs to operate under the resource constraints of a community web service.
A molecular dynamics (MD) based algorithm for atomic-level protein structure refinement. Given an initial protein structure, FG-MD first identifies analogous fragments from the PDB by the structural alignment program TM-align. Spatial restraints extracted from the fragments are then used to re-shape the funnel of the MD energy landscape and guide the MD conformational sampling. FG-MD aims to refine the initial models closer to the native structure. It can also improve the local geometry of the structures by removing the steric clashes and improving the torsion angle and the hydrogen-binding networks.
REFMAC5 / Refinement of Macromolecular Structures
Aids crystallographic refinement at medium and higher resolutions over the past few decades. With REFMAC5, structural information may be utilized in various forms, such as secondary-structure restraints, homologous reference structures and homology models. This tool utilizes different likelihood functions depending on the diffraction data employed (amplitudes or intensities), the presence of twinning and the availability of SAD/SIRAS experimental diffraction data. To ensure chemical and structural integrity of the refined model, REFMAC5 offers several classes of restraints and choices of model parameterization.
Adapts the effective sampling method of GalaxyRefine by performing repetitive repacking of interface side chains followed by short MD relaxations. GalaxyRefineComplex is a method for refining protein-protein complex structures generated by other docking programs. The method was able to improve model quality not only for unbound/bound structures but also for homology model structures. It may be applied to various applications in which low- to medium-accuracy models are available but high-quality models are not.
An algorithm for atomic-level, high-resolution protein structure refinement, which can start from either C-alpha trace, main-chain model or full-atomic model. Both side-chain and backbone atoms are completely flexible during structure refinement simulations, where conformational search is guided by a composite of physics- and knowledge-based force field. ModRefiner has an option to allow for the assignment of a second structure which will be used as a reference to which the refinement simulations are driven. One aim of ModRefiner is to draw the initial starting models closer to their native state, in terms of hydrogen bonds, backbone topology and side-chain positioning. It also generates significant improvement in physical quality of local structures.
SPRING / Single Particle Reconstruction from Images of kNown Geometry
Provides a single-particle based helical reconstruction package for electron cryo-micrographs. SPRING has been used to determine 3D structures of a variety of highly ordered and less ordered specimens. Spring provides the entire single-particle based work-flow required for helical reconstruction including: classification, helical symmetry determination and refinement tools, high-resolution structure refinement, and multi-symmetry structure refinement.
Provides an online interface to a simple, consistent and computationally efficient protein structure refinement protocol based on minimization of a knowledge-based potential of mean force. The server can be used to refine either a single protein structure or an ensemble of proteins starting from their unrefined coordinates in PDB format. The refinement method is particularly fast and accurate due to the underlying knowledge-based potential derived from structures deposited in the PDB; as such, the energy function implicitly includes the effects of solvent and the crystal environment. Our server allows for an optional but recommended step that optimizes stereochemistry using the MESHI software. The KoBaMIN server also allows comparison of the refined structures with a provided reference structure to assess the changes brought about by the refinement protocol.
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