The Experts below are selected from a list of 39708 Experts worldwide ranked by ideXlab platform

Thomas Nordahl Petersen - One of the best experts on this subject based on the ideXlab platform.

  • cphmodels 3 0 remote Homology Modeling using structure guided sequence profiles
    Nucleic Acids Research, 2010
    Co-Authors: Morten Nielsen, Claus Lundegaard, Ole Lund, Thomas Nordahl Petersen
    Abstract:

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template Homology Modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote Homology-Modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close Homology Modeling. The new computational costly remote Homology-Modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is <20 min. The web server is available at http://www.cbs.dtu.dk/services/CPHmodels/.

  • CPHmodels-3.0-remote Homology Modeling using structure-guided sequence profiles
    Nucleic Acids Research, 2010
    Co-Authors: Morten Nielsen, Claus Lundegaard, Ole Lund, Thomas Nordahl Petersen
    Abstract:

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template Homology Modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote Homology-Modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close Homology Modeling. The new computational costly remote Homology-Modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is

Roland L Dunbrack - One of the best experts on this subject based on the ideXlab platform.

  • SCWRL and MolIDE: computer programs for side-chain conformation prediction and Homology Modeling
    Nature Protocols, 2008
    Co-Authors: Qiang Wang, Adrian A Canutescu, Roland L Dunbrack
    Abstract:

    SCWRL and MolIDE are software applications for prediction of protein structures. SCWRL is designed specifically for the task of prediction of side-chain conformations given a fixed backbone usually obtained from an experimental structure determined by X-ray crystallography or NMR. SCWRL is a command-line program that typically runs in a few seconds. MolIDE provides a graphical interface for basic comparative (Homology) Modeling using SCWRL and other programs. MolIDE takes an input target sequence and uses PSI-BLAST to identify and align templates for comparative Modeling of the target. The sequence alignment to any template can be manually modified within a graphical window of the target–template alignment and visualization of the alignment on the template structure. MolIDE builds the model of the target structure on the basis of the template backbone, predicted side-chain conformations with SCWRL and a loop-Modeling program for insertion–deletion regions with user-selected sequence segments. SCWRL and MolIDE can be obtained at http://dunbrack.fccc.edu/Software.php .

  • SCWRL and MolIDE: computer programs for side-chain conformation prediction and Homology Modeling
    Nature Protocols, 2008
    Co-Authors: Qiang Wang, Adrian A Canutescu, Roland L Dunbrack
    Abstract:

    SCWRL and MolIDE are software applications for prediction of protein structures. SCWRL is designed specifically for the task of prediction of side-chain conformations given a fixed backbone usually obtained from an experimental structure determined by X-ray crystallography or NMR. SCWRL is a command-line program that typically runs in a few seconds. MolIDE provides a graphical interface for basic comparative (Homology) Modeling using SCWRL and other programs. MolIDE takes an input target sequence and uses PSI-BLAST to identify and align templates for comparative Modeling of the target. The sequence alignment to any template can be manually modified within a graphical window of the target–template alignment and visualization of the alignment on the template structure. MolIDE builds the model of the target structure on the basis of the template backbone, predicted side-chain conformations with SCWRL and a loop-Modeling program for insertion–deletion regions with user-selected sequence segments. SCWRL and MolIDE can be obtained at http://dunbrack.fccc.edu/Software.php .

  • scwrl and molide computer programs for side chain conformation prediction and Homology Modeling
    Nature Protocols, 2008
    Co-Authors: Qiang Wang, Adrian A Canutescu, Roland L Dunbrack
    Abstract:

    SCWRL and MolIDE: computer programs for side-chain conformation prediction and Homology Modeling

  • prediction of protein side chain rotamers from a backbone dependent rotamer library a new Homology Modeling tool
    Journal of Molecular Biology, 1997
    Co-Authors: Michael J Bower, Fred E Cohen, Roland L Dunbrack
    Abstract:

    Modeling by Homology is the most accurate computational method for translating an amino acid sequence into a protein structure. Homology Modeling can be divided into two sub-problems, placing the polypeptide backbone and adding side-chains. We present a method for rapidly predicting the conformations of protein side-chains, starting from main-chain coordinates alone. The method involves using fewer than ten rotamers per residue from a backbone-dependent rotamer library and a search to remove steric conflicts. The method is initially tested on 299 high resolution crystal structures by rebuilding side-chains onto the experimentally determined backbone structures. A total of 77% of χ1 and 66% of χ1+2 dihedral angles are predicted within 40° of their crystal structure values. We then tested the method on the entire database of known structures in the Protein Data Bank. The predictive accuracy of the algorithm was strongly correlated with the resolution of the structures. In an effort to simulate a realistic Homology Modeling problem, 9424 Homology models were created using three different Modeling strategies. For prediction purposes, pairs of structures were identified which shared between 30% and 90% sequence identity. One strategy results in 82% of χ1 and 72% χ1+2 dihedral angles predicted within 40 degrees of the target crystal structure values, suggesting that movements of the backbone associated with this degree of sequence identity are not large enough to disrupt the predictive ability of our method for non-native backbones. These results compared favorably with existing methods over a comprehensive data set.

Morten Nielsen - One of the best experts on this subject based on the ideXlab platform.

  • cphmodels 3 0 remote Homology Modeling using structure guided sequence profiles
    Nucleic Acids Research, 2010
    Co-Authors: Morten Nielsen, Claus Lundegaard, Ole Lund, Thomas Nordahl Petersen
    Abstract:

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template Homology Modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote Homology-Modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close Homology Modeling. The new computational costly remote Homology-Modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is <20 min. The web server is available at http://www.cbs.dtu.dk/services/CPHmodels/.

  • CPHmodels-3.0-remote Homology Modeling using structure-guided sequence profiles
    Nucleic Acids Research, 2010
    Co-Authors: Morten Nielsen, Claus Lundegaard, Ole Lund, Thomas Nordahl Petersen
    Abstract:

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template Homology Modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote Homology-Modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close Homology Modeling. The new computational costly remote Homology-Modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is

Ole Lund - One of the best experts on this subject based on the ideXlab platform.

  • cphmodels 3 0 remote Homology Modeling using structure guided sequence profiles
    Nucleic Acids Research, 2010
    Co-Authors: Morten Nielsen, Claus Lundegaard, Ole Lund, Thomas Nordahl Petersen
    Abstract:

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template Homology Modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote Homology-Modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close Homology Modeling. The new computational costly remote Homology-Modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is <20 min. The web server is available at http://www.cbs.dtu.dk/services/CPHmodels/.

  • CPHmodels-3.0-remote Homology Modeling using structure-guided sequence profiles
    Nucleic Acids Research, 2010
    Co-Authors: Morten Nielsen, Claus Lundegaard, Ole Lund, Thomas Nordahl Petersen
    Abstract:

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template Homology Modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote Homology-Modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close Homology Modeling. The new computational costly remote Homology-Modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is

Claus Lundegaard - One of the best experts on this subject based on the ideXlab platform.

  • cphmodels 3 0 remote Homology Modeling using structure guided sequence profiles
    Nucleic Acids Research, 2010
    Co-Authors: Morten Nielsen, Claus Lundegaard, Ole Lund, Thomas Nordahl Petersen
    Abstract:

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template Homology Modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote Homology-Modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close Homology Modeling. The new computational costly remote Homology-Modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is <20 min. The web server is available at http://www.cbs.dtu.dk/services/CPHmodels/.

  • CPHmodels-3.0-remote Homology Modeling using structure-guided sequence profiles
    Nucleic Acids Research, 2010
    Co-Authors: Morten Nielsen, Claus Lundegaard, Ole Lund, Thomas Nordahl Petersen
    Abstract:

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template Homology Modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote Homology-Modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close Homology Modeling. The new computational costly remote Homology-Modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is