Assessing the quality of modelled 3D protein structures using the ModFOLD server.

Model quality assessment programs (MQAPs) aim to assess the quality of modelled 3D protein structures. The provision of quality scores, describing both global and local (per-residue) accuracy are extremely important, as without quality scores we are unable to determine the usefulness of a 3D model for further computational and experimental wet lab studies.Here, we briefly discuss protein tertiary structure prediction, along with the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) competition and their key role in driving the field of protein model quality assessment methods (MQAPs). We also briefly discuss the top MQAPs from the previous CASP competitions. Additionally, we describe our downloadable and webserver-based model quality assessment methods: ModFOLD3, ModFOLDclust, ModFOLDclustQ, ModFOLDclust2, and IntFOLD-QA. We provide a practical step-by-step guide on using our downloadable and webserver-based tools and include examples of their application for improving tertiary structure prediction, ligand binding site residue prediction, and oligomer predictions.

[1]  Liam J. McGuffin,et al.  FunFOLDQA: A Quality Assessment Tool for Protein-Ligand Binding Site Residue Predictions , 2012, PloS one.

[2]  David C. Richardson,et al.  MOLPROBITY: structure validation and all-atom contact analysis for nucleic acids and their complexes , 2004, Nucleic Acids Res..

[3]  Nir Ben-Tal,et al.  Quality assessment of protein model-structures using evolutionary conservation , 2010, Bioinform..

[4]  Sitao Wu,et al.  Ab Initio Protein Structure Prediction , 2009 .

[5]  Jaime Prilusky,et al.  Assessment of CASP8 structure predictions for template free targets , 2009, Proteins.

[6]  Francisco Melo,et al.  ANOLEA: A WWW Server to Assess Protein Structures , 1997, ISMB.

[7]  Liam J. McGuffin,et al.  Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments , 2010, Bioinform..

[8]  Daniel B. Roche,et al.  Automated tertiary structure prediction with accurate local model quality assessment using the intfold‐ts method , 2011, Proteins.

[9]  Liam J. McGuffin,et al.  FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins , 2011, BMC Bioinformatics.

[10]  Anna Tramontano,et al.  Assessment of predictions in the model quality assessment category , 2007, Proteins.

[11]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[12]  Liam J. McGuffin,et al.  The ModFOLD server for the quality assessment of protein structural models , 2008, Bioinform..

[13]  Hongyi Zhou,et al.  Distance‐scaled, finite ideal‐gas reference state improves structure‐derived potentials of mean force for structure selection and stability prediction , 2002, Protein science : a publication of the Protein Society.

[14]  Anna Tramontano,et al.  Evaluation of disorder predictions in CASP9 , 2011, Proteins.

[15]  Anna Tramontano,et al.  Evaluation of CASP8 model quality predictions , 2009, Proteins.

[16]  B. Matthews.  Comparison of the predicted and observed secondary structure of T4 phage lysozyme. , 1975, Biochimica et biophysica acta.

[17]  Liam J. McGuffin,et al.  Intrinsic disorder prediction from the analysis of multiple protein fold recognition models , 2008, Bioinform..

[18]  C. Sander,et al.  Errors in protein structures , 1996, Nature.

[19]  U. Singh,et al.  A NEW FORCE FIELD FOR MOLECULAR MECHANICAL SIMULATION OF NUCLEIC ACIDS AND PROTEINS , 1984 .

[20]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[21]  Liam J. McGuffin,et al.  Model Quality Prediction , 2010 .

[22]  F. Melo,et al.  Novel knowledge-based mean force potential at atomic level. , 1997, Journal of molecular biology.

[23]  D S Moss,et al.  Main-chain bond lengths and bond angles in protein structures. , 1993, Journal of molecular biology.

[24]  T. Schwede,et al.  QMEANclust: estimation of protein model quality by combining a composite scoring function with structural density information , 2009, BMC Structural Biology.

[25]  Liam J. McGuffin,et al.  The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction , 2011, Nucleic Acids Res..

[26]  Ben M. Webb,et al.  Comparative Protein Structure Modeling Using Modeller , 2006, Current protocols in bioinformatics.

[27]  Anna Tramontano,et al.  Critical assessment of methods of protein structure prediction—Round VII , 2007, Proteins.

[28]  Liam J McGuffin,et al.  Proteogenomics and in silico structural and functional annotation of the barley powdery mildew Blumeria graminis f. sp. hordei. , 2011, Methods.

[29]  Xin Deng,et al.  The MULTICOM toolbox for protein structure prediction , 2012, BMC Bioinformatics.

[30]  K. Watson,et al.  EfeO-cupredoxins: major new members of the cupredoxin superfamily with roles in bacterial iron transport , 2010, BioMetals.

[31]  Qingguo Wang,et al.  MUFOLD‐WQA: A new selective consensus method for quality assessment in protein structure prediction , 2011, Proteins.

[32]  Pascal Benkert,et al.  QMEAN server for protein model quality estimation , 2009, Nucleic Acids Res..

[33]  David T. Jones,et al.  Getting the most from PSI-BLAST. , 2002, Trends in biochemical sciences.

[34]  Marco Biasini,et al.  Toward the estimation of the absolute quality of individual protein structure models , 2010, Bioinform..

[35]  Ilya N. Shindyalov,et al.  PDP: protein domain parser , 2003, Bioinform..

[36]  Liam J. McGuffin,et al.  The binding site distance test score: a robust method for the assessment of predicted protein binding sites , 2010, Bioinform..

[37]  Johannes Söding,et al.  Protein homology detection by HMM?CHMM comparison , 2005, Bioinform..

[38]  Pascal Benkert,et al.  QMEAN: A comprehensive scoring function for model quality assessment , 2008, Proteins.

[39]  Shaila C. Rössle,et al.  Homology modeling of human Toll‐like receptors TLR7, 8, and 9 ligand‐binding domains , 2009, Protein science : a publication of the Protein Society.

[40]  Yang Zhang,et al.  Scoring function for automated assessment of protein structure template quality , 2004, Proteins.

[41]  Janusz M. Bujnicki,et al.  MetaMQAP: A meta-server for the quality assessment of protein models , 2008, BMC Bioinformatics.

[42]  Liam J. McGuffin,et al.  Improvement of 3D protein models using multiple templates guided by single-template model quality assessment , 2012, Bioinform..

[43]  Torsten Schwede,et al.  Assessment of ligand‐binding residue predictions in CASP9 , 2011, Proteins.

[44]  Laura Pérez-Cano,et al.  Mapping of interaction sites of the Schizosaccharomyces pombe protein Translin with nucleic acids and proteins: a combined molecular genetics and bioinformatics study , 2010, Nucleic acids research.

[45]  Thomas L. Madden,et al.  Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. , 1997, Nucleic acids research.

[46]  Shaila C. Rössle,et al.  Inhibition of Toll-like receptors TLR4 and 7 signaling pathways by SIGIRR: a computational approach. , 2010, Journal of structural biology.

[47]  Liam J. McGuffin,et al.  The PSIPRED protein structure prediction server , 2000, Bioinform..

[48]  Anna Tramontano,et al.  Evaluation of model quality predictions in CASP9 , 2011, Proteins.

[49]  Liam J. McGuffin,et al.  Benchmarking consensus model quality assessment for protein fold recognition , 2007, BMC Bioinformatics.

[50]  Liam J. McGuffin,et al.  A novel non-canonical mechanism of regulation of MST3 (mammalian Sterile20-related kinase 3) , 2012, The Biochemical journal.

[51]  A. Biegert,et al.  HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment , 2011, Nature Methods.