What are the local scores in qmeanbrane?
The local scores are a linear combinations of the 4 statistical potential terms as well as the agreement terms evaluated on a per residue basis. They are as well in the range [0,1] with one being good. QMEANBrane is a version of QMEAN developed to assess the local quality of alpha-helical transmembrane protein models.
What is the range of the qmean4 scores?
They all provide scores in range [0,1] with one being good. QMEAN4 is a linear combination of four statistical potential terms. It is trained to predict global lDDT score in range [0,1]. The value displayed here is transformed into a Z-score to relate it with what one would expect from high resolution X-ray structures.
What is the difference between qmeandisco global score and error estimate?
The QMEANDisCo global score is the average per-residue score and the provided error estimate is based on global QMEANDisCo scores estimated for a large set of models and represents the root mean squared difference ( i.e. standard deviation) between QMEANDisCo global score and lDDT (the ground truth).
What is the difference between qmean4 and qmean6?
There are two global score values, QMEAN4 and QMEAN6. QMEAN4 is a linear combination of four statistical potential terms. QMEAN6 additionally uses two agreement terms evaluating the consistency of structural features with sequence based predictions.
What is Qmean score?
QMEAN, which stands for Qualitative Model Energy ANalysis, is a composite scoring function describing the major geometrical aspects of protein structures. Five different structural descriptors are used. The local geometry is analyzed by a new kind of torsion angle potential over three consecutive amino acids.
What is GMQE score?
GMQE (Global Model Quality Estimation) is is expressed as a number between 0 and 1, reflecting the expected accuracy of a model built with that alignment and template, normalized by the coverage of the target sequence. Higher numbers indicate higher reliability.
How do Swiss models work?
So what is the "Swiss model"? Rather than teams being drawn into eight groups of four, as is the case now, all clubs are placed into one giant table. It is based on the Swiss-system tournament used in chess, whereby each team does not play all of the others.
How do you reference a SWISS-MODEL?
If you are using models from the SWISS-MODEL Server or Repository, please cite the corresponding articles:SWISS-MODEL Workspace/ GMQE. ... SWISS-MODEL Repository. ... Swiss-PdbViewer/ DeepView project mode. ... ProMod3. ... QMEANDisCo. ... QMEANBrane. ... QMEAN. ... Quaternary Structure Prediction/ QSQE.More items...•
What is a good Qmean value?
QMEAN z-scores around zero indicate good agreement between the model structure and experimental structures of similar size. Models of low quality typically have scores of -4.0 or lower. The “thumbs-up” and “thumbs-down” symbols next to the score are used to indicate whether or not the model is of good quality (9).
What is a good Qmean z score?
Z-scores around 0.0 therefore reflect a "native-like" structure and, as a rule of thumb, a "QMEAN" Z-score below -4.0 indicates a model with low quality. This is illustrated by the "Comparison" plot ((5) in the figure above). The x-axis shows protein length (number of residues).
How accurate is SWISS-MODEL?
SWISS-MODEL is a structural bioinformatics web-server dedicated to homology modeling of 3D protein structures. Homology modeling is currently the most accurate method to generate reliable three-dimensional protein structure models and is routinely used in many practical applications.
What is the purpose of SWISS-MODEL?
is a fully automated protein structure homology-modelling server, accessible via the Expasy web server, or from the program DeepView (Swiss Pdb-Viewer). The purpose of this server is to make protein modelling accessible to all life science researchers worldwide.
What is Swiss PDB viewer?
Swiss-PdbViewer (aka DeepView) is an application that provides a user friendly interface allowing to analyze several proteins at the same time. The proteins can be superimposed in order to deduce structural alignments and compare their active sites or any other relevant parts.
How do Swiss models use homology Modelling?
How to build a homology model using superoxide dismutaseA checkbox to select and visualise the template in the 3D panel.The SMTL ID of the template and a link to the SWISS-MODEL Template Library page associated to that SMTL entry.The protein name of the template.More items...
Is SWISS-MODEL a database?
The SWISS-MODEL Repository is a database of annotated 3D protein structure models generated by the SWISS-MODEL homology-modelling pipeline.
How can you predict the structure of a protein?
Currently, the main techniques used to determine protein 3D structure are X-ray crystallography and nuclear magnetic resonance (NMR). In X-ray crystallography the protein is crystallized and then using X-ray diffraction the structure of protein is determined.
1. Introduction
Estimating the quality of protein structure models is a vital step in protein structure prediction. Often one ends up in having a set of alternative models ( e.g. from different modeling servers or based on alternative template structures and alignments) from which the best candidate shall be selected.
3. Input Format Requirements
Either a model in PDB format or tar.gz -archives with multiple models in PDB format sharing the same reference sequence (SEQRES) can be uploaded.
4. Input Data Processing
Local qualities are visible as color gradients in the model viewer. They additionally get mapped onto the structures available in the downloadable archives as bfactors. The server provides you with two alternative structures in the archives that undergo certain processing steps.
5. Programmatic Access
One can access QMEAN-SERVER programatically with provided API. In order to use QMEAN submission API you have to make a POST request to the https://swissmodel.expasy.org/qmean/submit/ with following parameters. (Parameters "structure" and "email" are required)
Abstract
Model quality estimation is an essential component of protein structure prediction, since ultimately the accuracy of a model determines its usefulness for specific applications. Usually, in the course of protein structure prediction a set of alternative models is produced, from which subsequently the most accurate model has to be selected.
INTRODUCTION
In the course of protein structure prediction usually a set of alternative models is produced from which subsequently the final model has to be selected. For this purpose, scoring functions have been developed which aim at estimating the expected accuracy of models.
THE QMEAN SERVER
The user has the possibility to either submit a single model (in PDB-format), or multiple models (as zip- or tar.gz -archive) and the full-length sequence of the target protein (which is needed for secondary structure and solvent accessibility prediction).
EXAMPLE
The start page of the QMEAN server provides a link to an example results page which allows the user to inspect a typical output of the server. A snapshot of the example results page is given in Figure 1 a.
CONCLUSIONS
Identifying the most accurate model among a set of alternatives is a crucial step in protein structure prediction. Here we present the QMEAN server which makes two methods for model quality estimation publicly available: QMEAN and QMEANclust. The QMEAN server addresses both users of protein structure models as well as method developers.