IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences

By Liam J. McGuffin, Jennifer D. Atkins, Bajuna R. Salehe, Ahmad N. Shuid, Daniel B. Roche. 2015

116 citations recorded by the source corpus.

IntFOLD is an independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance. The only required input to the server is an amino acid sequence for the target protein. Here we describe major performance and user interface updates to the server, which comprises an integrated pipeline of methods for: tertiary structure prediction, global and local 3D model quality assessment, disorder prediction, structural domain prediction, function prediction and modelling of protein-ligand interactions. The server has been independently validated during numerous CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiments, as well as being continuously evaluated by the CAMEO (Continuous Automated Model Evaluation) project. The IntFOLD server is available at: http://www.reading.ac.uk/bioinf/IntFOLD/

Subfields: Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

In Molecular Biology

Citations in the corpus

Introducing “best single template” models as reference baseline for the Continuous Automated Model Evaluation (CAMEO) (2019, neutral): “Within the top performing regime of this performance domain “ QMEANDisCo3 ” , 27 “ QMEANDisCo2, ” 29 “ ModFOLD6, ” 30 and “ ModFOLD7-lDDT ” 22 are clearly in the lead (Figure 3C), followed by “ QMEAN3, ” “ ModFOLD4, ” 31 and “ VoroMQA.”
IntFOLD: an integrated web resource for high performance protein structure and function prediction (2019, methodology): “Since its inception, the high performance tertiary structure prediction algorithms with integrated model quality assessment have been at the core of IntFOLD server (10,11,18), and these factors have been key contributors to the historical success of the component methods (5,7,9,18,26–30).”
Methods for estimation of model accuracy in CASP12 (2017, methodology): “Additionally, 3 alternative quasi-single model methods were used to score models including: the newly developed Disorder B-factor Agreement, the ModFOLD5_single and the ModFOLDclustQ_single scores(16)—each of which made use of a set of 130 reference 3D models that were generated using the latest ver”
ModFOLD6: an accurate web server for the global and local quality estimation of 3D protein models (2017, unknown): “The method has since undergone a number of updates: ModFOLD4 (17), which makes use of IntFOLD2-TS (20) models, and ModFOLD5, which makes use of IntFOLD3-TS (21) models.”
Computational methods and tools for binding site recognition between proteins and small molecules: from classical geometrical approaches to modern machine learning strategies (2019, background): “FunFOLD3 [42] is a module of the web server IntFOLD [76].”
Disorder Prediction Methods, Their Applicability to Different Protein Targets and Their Usefulness for Guiding Experimental Studies (2015, methodology): “An example of this approach is used in DISOclust, which is now integrated with the IntFOLD server [51,52].”
Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions (2017, methodology): “DISOclust3 [75] was released by McGuffin et al.”