1 - 21 of 21 results

RCD+ / Random Coordinate Descent +

A quick online service for ab initio loop modeling combining a coarse-grained conformational search with a full-atom refinement. RCD+ is an upgrade of the original Random Coordinate Descent loop closure algorithm which has been greatly improved to enrich the sampling distribution towards near-native conformations. These improvements include a new workflow optimization, MPI-parallelization and fast backbone angle sampling based on neighbor-dependent Ramachandran probability distributions. The server starts by efficiently searching the vast conformational space from only the loop sequence information and the environment atomic coordinates. The generated closed loop models are subsequently ranked using a fast distance-orientation dependent energy filter. Top ranked loops are refined with the Rosetta energy function to obtain accurate all-atom predictions that can be interactively inspected in an user-friendly web interface.


Combines knowledge-based and ab initio approaches. Sphinx is a protein loop modelling algorithm that generate high-accuracy predictions and decoy sets enriched with near-native loop conformations. Given a protein structure, location of the loop to be modelled and the sequence of that loop, it searches a database of fragments for sections of other proteins that are shorter than the target loop, but that may have some structural similarity. By using ab initio techniques, the loop conformations can be made to be the correct length. Once a set of conformations has been produced, a fast statistical potential is used to cull the set to only 500 structures, which are then scored using SOAP-Loop to produce a ranking.


A method based on the Random Forest automated learning technique, which, given a target loop, selects a structural template for it from a database of loop candidates. Compared to the most recently available methods, LoopIng is able to achieve similar accuracy for short loops (4-10 residues) and significant enhancements for long loops (11-20 residues). The quality of the predictions is robust to errors that unavoidably affect the stem regions when these are modeled. The method returns a confidence score for the predicted template loops and has the advantage of being very fast (on average: 1 minute/loop).


Implements a fragment-search based method for predicting loop conformations. The inputs to the server are the atomic coordinates of the query protein and the position of the loop. The algorithm selects candidate loop fragments from a regularly updated loop library (Search Space) by matching the length, the types of bracing secondary structures of the query and by satisfying the geometrical restraints imposed by the stem residues. Subsequently, candidate loops are inserted in the query protein framework where their side chains are rebuilt and their fit is assessed by the root mean square deviation (r.m.s.d.) of stem regions and by the number of rigid body clashes with the environment. In the final step remaining candidate loops are ranked by a Z-score that combines information on sequence similarity and fit of predicted and observed [/psi] main chain dihedral angle propensities. The final loop conformation is built in the protein structure and annealed in the environment using conjugate gradient minimization.


Provides an online interface for protein loop modeling by employing an ab initio loop modeling method called FALC (fragment assembly and analytical loop closure). The server may be used to construct loop regions in homology modeling, to refine unreliable loop regions in experimental structures or to model segments of designed sequences. The FALC method is computationally less expensive than typical ab initio methods because the conformational search space is effectively reduced by the use of fragments derived from a structure database. The analytical loop closure algorithm allows efficient search for loop conformations that fit into the protein framework starting from the fragment-assembled structures.

MVP-Fit / Macromolecular Visualization and Processing with EM Density Map

Provides a visualization tool for interactive fitting atomic protein domain structures with the cryo-Electron Microscopy (EM) density map. To achieve the best match, MVP-Fit can conveniently adjust the loop and tail outliers of individual domains to accommodate the local conformational changes from the rigid-body rotation and translation of protein domains. MVP-Fit is based on MVP, a visualization system which generates quickly and accurately triangulated isosurfaces for density maps. The software is freely available for download.


Takes an input antibody sequence and returns an energy optimized accurate structure in minutes. SmrtMolAntibody is part of a suite of modeling tools provided by Macromoltek. It creates a structure of an antibody from an individual sequence. The tool was improved with sequences for eleven Fvs and asked to produce structures of each of the antibody sequences. In 10 of 11 cases, the results using SmrtMolAntibody show good agreement between the submitted models and X-ray crystal structures.


Analyzing the motion of flexible protein loops is becoming increasingly important in understanding the various roles that proteins play in human body. LoopTK is a C++ based object-oriented toolkit which models the kinematics of a protein chain and provides methods to explore its motion space. In LoopTK, a protein chain is modeled as a robot manipulator with bonds acting as arms and the dihedral degree of freedoms acting as joints. LoopTK is designed specifically to model the kinematics of protein loops, but it can be used to analyze the motion of any part of the protein chain.