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The IntFOLD server
Developer(s)Prof Liam McGuffin

Dr Recep Adiyaman

Dr Bajuna Salehe
Stable release
IntFOLD version 5.0
Preview release
IntFOLD version 6.0
Written inJava,

Python,

R
Websitehttps://www.reading.ac.uk/bioinf/IntFOLD/

IntFOLD (Integrated Fold Recognition) is fully automated, integrated pipeline for prediction of 3D structure and function from amino acid sequences.[1]. The pipeline is wrapped up and deployed as a Web Server. The core of the server method is quality assessment using built-in accuracy self-estimates (ASE) which improves performance prediction of 3D model using ModFOLD [2].

Description

IntFOLD server provides the tertiary structure prediction at a competitive accuracy and combines the cutting edge methods including IntFOLD-TS for generation of 3D models [1], ModFOLD for 3D model quality estimation [2], ReFOLD for refinement of 3D models [3], DisoCLUST for disorder prediction [4], DomFOLD for structural domain prediction [5], and FunFOLD for protein ligand binding site prediction [6]. The integration of the tools enables users to reach all related information in a pipeline. IntFOLD Web Server has completed over ∼200 000 structure predictions since  January 2010 [1].

The only required input is a protein sequence for the prediction of the protein 3D structure and function [1]. The IntFOLD output is presented via a user-friendly interface for the use of life scientists. The raw data is also formatted in Critical Assessment of Methods for Protein Structure Prediction (CASP) standards with a detailed help page [1].

Performance in CASP and CAMEO experiments

The IntFOLD method was firstly benchmarked in Critical Assessment of Techniques for Protein Structure Prediction 9 (CASP9) and ranked among the top 5.[7]. The IntFOLD server has consolidated its performance in the following CASP experiments [1]

Its performance is being continually evaluated in Continuous Automated Model Evaluation (CAMEO) experiment.

Applications of IntFOLD server

Some of the several domains in which IntFOLD has been applied so far are listed below.

Public Health

IntFOLD was used to generate 3D models of the SARS-CoV-2 targets for the CASP Commons COVID-19 initiative[8] and elsewhere [9] accelerating the race of vaccines and other therapeutics development with regard to COVID-19 pandemic. In other aspect of chronic diseases, IntFOLD was used to model HEV PCP, an essential protein of Hepatitis E virus causing Hepatitis E disease [10]. Additionally, IntFOLD was used to model disordered region of the Bovine milk αS2-casein proteins which were implicated in the formation amyloidogenic fibrils some of which are known to be major causes of neurodegenerative diseases [11]

Food Security

IntFOLD has been used in different aspects of food security. For instance, it has been used to model effector proteins molecules that causes fungus in Barley [12]. Furthermore, it has been applied in modelling several proteins involved in the functioning of key systems in Atlantic salmon, and HaACBP1 protein, which is vital for development and growth of sunflower, a key crop plant used for production of widely used cooking oil [13] [14]. IntFOLD was used to model Chitin proteins in Podosphaera xanthii, a causal agent of fungal disease called cucurbit powdery mildew, which hamper crop productivity [15].

Contribution to Protein Structure Prediction Methods Development

IntFOLD has been used as one of the standard server-based methods in validating the performance of some of the newer methods used in prediction of the 3D-protein models. This is important in advancing the structural bioinformatics field [16].

References

  1. ^ a b c d e f McGuffin, Liam J; Adiyaman, Recep; Maghrabi, Ali H A; Shuid, Ahmad N; Brackenridge, Danielle A; Nealon, John O; Philomina, Limcy S (2019-05-02). "IntFOLD: an integrated web resource for high performance protein structure and function prediction". Nucleic Acids Research. 47 (W1): W408–W413. doi:10.1093/nar/gkz322. ISSN 0305-1048. PMC 6602432. PMID 31045208.
  2. ^ a b Maghrabi, Ali H. A.; McGuffin, Liam J. (2017-04-29). "ModFOLD6: an accurate web server for the global and local quality estimation of 3D protein models". Nucleic Acids Research. 45 (W1): W416–W421. doi:10.1093/nar/gkx332. ISSN 0305-1048. PMC 5570241. PMID 28460136.
  3. ^ Adiyaman, Recep; McGuffin, Liam J (2021-05-01). "ReFOLD3: refinement of 3D protein models with gradual restraints based on predicted local quality and residue contacts". Nucleic Acids Research. 49 (W1): W589–W596. doi:10.1093/nar/gkab300. ISSN 0305-1048. PMC 8218204. PMID 34009387.
  4. ^ Atkins, Jennifer; Boateng, Samuel; Sorensen, Thomas; McGuffin, Liam (2015-08-13). "Disorder Prediction Methods, Their Applicability to Different Protein Targets and Their Usefulness for Guiding Experimental Studies". International Journal of Molecular Sciences. 16 (8): 19040–19054. doi:10.3390/ijms160819040. ISSN 1422-0067. PMC 4581285. PMID 26287166.
  5. ^ McGuffin, Liam J.; Atkins, Jennifer D.; Salehe, Bajuna R.; Shuid, Ahmad N.; Roche, Daniel B. (2015-03-27). "IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences: Figure 1". Nucleic Acids Research. 43 (W1): W169–W173. doi:10.1093/nar/gkv236. ISSN 0305-1048. PMC 4489238. PMID 25820431.
  6. ^ Roche, Daniel B.; Buenavista, Maria T.; McGuffin, Liam J. (2013-06-11). "The FunFOLD2 server for the prediction of protein–ligand interactions". Nucleic Acids Research. 41 (W1): W303–W307. doi:10.1093/nar/gkt498. ISSN 1362-4962. PMC 3692132. PMID 23761453.
  7. ^ Roche, D. B.; Buenavista, M. T.; Tetchner, S. J.; McGuffin, L. J. (2011-03-31). "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". Nucleic Acids Research. 39 (suppl): W171–W176. doi:10.1093/nar/gkr184. ISSN 0305-1048. PMC 3125722. PMID 21459847.
  8. ^ Kryshtafovych, Andriy; Moult, John; Billings, Wendy M.; Corte, Dennis Della; Fidelis, Krzysztof; Kwon, Sohee; Olechnovič, Kliment; Seok, Chaok; Venclovas, Česlovas; Won, Jonghun (2021). "Modeling SARS-CoV2 proteins in the CASP-commons experiment". Proteins: Structure, Function, and Bioinformatics. 89 (12): 1987–1996. doi:10.1002/prot.26231. ISSN 1097-0134. PMC 8616790. PMID 34462960.
  9. ^ Sadat, Seyed Mehdi; Aghadadeghi, Mohammad Reza; Yousefi, Masoume; Khodaei, Arezoo; Sadat Larijani, Mona; Bahramali, Golnaz (2021-05-01). "Bioinformatics Analysis of SARS-CoV-2 to Approach an Effective Vaccine Candidate Against COVID-19". Molecular Biotechnology. 63 (5): 389–409. doi:10.1007/s12033-021-00303-0. ISSN 1559-0305. PMC 7902242. PMID 33625681.
  10. ^ Saraswat, Shweta; Chaudhary, Meenakshi; Sehgal, Deepak (2020). "Hepatitis E Virus Cysteine Protease Has Papain Like Properties Validated by in silico Modeling and Cell-Free Inhibition Assays". Frontiers in Cellular and Infection Microbiology. 9: 478. doi:10.3389/fcimb.2019.00478. ISSN 2235-2988. PMC 6989534. PMID 32039053.
  11. ^ Thorn, David C.; Bahraminejad, Elmira; Grosas, Aidan B.; Koudelka, Tomas; Hoffmann, Peter; Mata, Jitendra P.; Devlin, Glyn L.; Sunde, Margaret; Ecroyd, Heath; Holt, Carl; Carver, John A. (2021-03-01). "Native disulphide-linked dimers facilitate amyloid fibril formation by bovine milk αS2-casein". Biophysical Chemistry. 270: 106530. doi:10.1016/j.bpc.2020.106530. ISSN 0301-4622. PMID 33545456. S2CID 230603636.
  12. ^ Bauer, Saskia; Yu, Dongli; Lawson, Aaron W.; Saur, Isabel M. L.; Frantzeskakis, Lamprinos; Kracher, Barbara; Logemann, Elke; Chai, Jijie; Maekawa, Takaki; Schulze-Lefert, Paul (2021-02-03). "The leucine-rich repeats in allelic barley MLA immune receptors define specificity towards sequence-unrelated powdery mildew avirulence effectors with a predicted common RNase-like fold". PLOS Pathogens. 17 (2): e1009223. doi:10.1371/journal.ppat.1009223. ISSN 1553-7374. PMC 7857584. PMID 33534797.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  13. ^ Aznar-Moreno, Jose A.; Venegas-Calerón, Mónica; Du, Zhi-Yan; Garcés, Rafael; Tanner, Julian A.; Chye, Mee-Len; Martínez-Force, Enrique; Salas, Joaquín J. (2020-11-01). "Characterization and function of a sunflower (Helianthus annuus L.) Class II acyl-CoA-binding protein". Plant Science. 300: 110630. doi:10.1016/j.plantsci.2020.110630. hdl:10261/221145. ISSN 0168-9452. PMID 33180709. S2CID 225009983.
  14. ^ Kalananthan, Tharmini; Lai, Floriana; Gomes, Ana S.; Murashita, Koji; Handeland, Sigurd; Rønnestad, Ivar (2020). "The Melanocortin System in Atlantic Salmon (Salmo salar L.) and Its Role in Appetite Control". Frontiers in Neuroanatomy. 14: 48. doi:10.3389/fnana.2020.00048. ISSN 1662-5129. PMC 7471746. PMID 32973463.
  15. ^ Polonio, Álvaro; Fernández-Ortuño, Dolores; Vicente, Antonio de; Pérez-García, Alejandro (2021). "A haustorial-expressed lytic polysaccharide monooxygenase from the cucurbit powdery mildew pathogen Podosphaera xanthii contributes to the suppression of chitin-triggered immunity". Molecular Plant Pathology. 22 (5): 580–601. doi:10.1111/mpp.13045. ISSN 1364-3703. PMC 8035642. PMID 33742545.
  16. ^ Su, Hong; Wang, Wenkai; Du, Zongyang; Peng, Zhenling; Gao, Shang-Hua; Cheng, Ming-Ming; Yang, Jianyi (2021). "Improved Protein Structure Prediction Using a New Multi-Scale Network and Homologous Templates". Advanced Science. 8 (24): 2102592. doi:10.1002/advs.202102592. ISSN 2198-3844. PMC 8693034. PMID 34719864.
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