-
1دورية أكاديمية
المؤلفون: McGuffin, Liam J., Alharbi, Shuaa M. A.
الوصف: Accurate models of protein tertiary structures are now available from numerous advanced prediction methods, although the accuracy of each method often varies depending on the specific protein target. Additionally, many models may still contain significant local errors. Therefore, reliable, independent model quality estimates are essential both for identifying errors and selecting the very best models for further biological investigations. ModFOLD9 is a leading independent server for detecting the local errors in models produced by any method, and it can accurately discriminate between high-quality models from multiple alternative approaches. ModFOLD9 incorporates several new scores from deep learning-based approaches, leading to greatly improved prediction accuracy compared with earlier versions of the server. ModFOLD9 is continuously independently benchmarked, and it is shown to be highly competitive with other public servers. ModFOLD9 is freely available at https://www.reading.ac.uk/bioinf/ModFOLDTest/.
وصف الملف: text
العلاقة: https://centaur.reading.ac.uk/115716/1/JMB-D-24-00070_R1.pdfTest; McGuffin, L. J. orcid:0000-0003-4501-4767 and Alharbi, S. M. A. (2024) ModFOLD9: a web server for independent estimates of 3D protein model quality. Journal of Molecular Biology. 168531. ISSN 1089-8638 doi: https://doi.org/10.1016Test/j.jmb.2024.168531
-
2دورية أكاديمية
المؤلفون: Gerencer, Marijan, McGuffin, Liam J.
الوصف: The previous studies on the RGD motif (aa403-405) within the SARS CoV-2 spike (S) protein receptor binding domain (RBD) suggest that the RGD motif binding integrin(s) may play an important role in infection of the host cells. We also discussed the possible role of two other integrin binding motifs that are present in S protein: LDI (aa585-587) and ECD (661-663), the motifs used by some other viruses in the course of infection. The MultiFOLD models for protein structure analysis have shown that the ECD motif is clearly accessible in the S protein, whereas the RGD and LDI motifs are partially accessible in S protein. Furthermore, the amino acids that are present in Epstein-Barr virus protein (EBV) gp42 playing very important role in binding to the HLA-DRB1 molecule and in the subsequent immune response evasion, are also present in the S protein heptad repeat-2. Our MultiFOLD model analyses have shown that these amino acids are clearly accessible on the surface in each S protein chain as monomers and in the homotrimer complex and bind to HLA-DRB1 β chain. Accordingly, they may have the identical role in SARS CoV-2 immune evasion as in EBV infection. The prediction analyses of the MHC class II binding peptides within the S protein have shown that the RGD motif is present in the core 9-mer peptide IRGDEVRQI within the two HLA-DRB1*03:01 and HLA-DRB3*01.01 strong binding 15-mer peptides suggesting that RGD motif may be the potential immune epitope. Accordingly, infected HLA-DRB1*03:01 or HLA-DRB3*01.01 positive individuals may develop high affinity anti-RGD motif antibodies that react with the RGD motif in the host proteins, like fibrinogen, thrombin or von Willebrand factor, affecting haemostasis or participating in autoimmune disorders.
وصف الملف: text
العلاقة: https://centaur.reading.ac.uk/112024/3/fimmu-14-1177691.pdfTest; https://centaur.reading.ac.uk/112024/1/XID%201177691%20FrontImmun%20revised2.docxTest; Gerencer, M. and McGuffin, L. J. orcid:0000-0003-4501-4767 (2023) Are the integrin binding motifs within SARS CoV-2 spike protein and MHC class II alleles playing the key role in COVID-19? Frontiers in Immunology, 14. ISSN 1664-3224 doi: https://doi.org/10.3389/fimmu.2023.1177691Test
-
3دورية أكاديمية
المؤلفون: McGuffin, Liam J., Edmunds, Nicholas S., Genc, Ahmet G., Alharbi, Shuaa M. A., Salehe, Bajuna R., Adiyaman, Recep
الوصف: The IntFOLD server based at the University of Reading has been a leading method over the past decade in providing free access to accurate prediction of protein structures and functions. In a post-AlphaFold2 world, accurate models of tertiary structures are widely available for even more protein targets, so there has been a refocus in the prediction community towards the accurate modelling of protein-ligand interactions as well as modelling quaternary structure assemblies. In this paper, we describe the latest improvements to IntFOLD, which maintains its competitive structure prediction performance by including the latest deep learning methods while also integrating accurate model quality estimates and 3D models of protein-ligand interactions. Furthermore, we also introduce our two new server methods: MultiFOLD for accurately modelling both tertiary and quaternary structures, with performance which has been independently verified to outperform the standard AlphaFold2 methods, and ModFOLDdock, which provides world-leading quality estimates for quaternary structure models. The IntFOLD7, MultiFOLD and ModFOLDdock servers are available at: https://www.reading.ac.uk/bioinfTest/.
وصف الملف: text
العلاقة: https://centaur.reading.ac.uk/111787/1/gkad297_final.pdfTest; McGuffin, L. J. orcid:0000-0003-4501-4767 , Edmunds, N. S., Genc, A. G., Alharbi, S. M. A., Salehe, B. R. and Adiyaman, R. (2023) Prediction of protein structures, functions and interactions using the IntFOLD7, MultiFOLD and ModFOLDdock servers. Nucleic Acids Research, 51 (W1). W274-W280. ISSN 1362-4962 doi: https://doi.org/10.1093/nar/gkad297Test
-
4دورية أكاديمية
المؤلفون: Edmunds, Nicholas S., Alharbi, Shuaa M.A., Genc, Ahmet G., Adiyaman, Recep, McGuffin, Liam J.
الوصف: In CASP15, there was a greater emphasis on multimeric modeling than in previous experiments, with assembly structures nearly doubling in number (41 up from 22) since the previous round. CASP15 also included a new estimation of model accuracy (EMA) category in recognition of the importance of objective quality assessment (QA) for quaternary structure models. ModFOLDdock is a multimeric model QA server developed by the McGuffin group at the University of Reading, which brings together a range of single-model, clustering, and deep learning methods to form a consensus of approaches. For CASP15, three variants of ModFOLDdock were developed to optimize for the different facets of the quality estimation problem. The standard ModFOLDdock variant produced predicted scores optimized for positive linear correlations with the observed scores. The ModFOLDdockR variant produced predicted scores optimized for ranking, that is, the top-ranked models have the highest accuracy. In addition, the ModFOLDdockS variant used a quasi-single model approach to score each model on an individual basis. The scores from all three variants achieved strongly positive Pearson correlation coefficients with the CASP observed scores (oligo-lDDT) in excess of 0.70, which were maintained across both homomeric and heteromeric model populations. In addition, at least one of the ModFOLDdock variants was consistently ranked in the top two methods across all three EMA categories. Specifically, for overall global fold prediction accuracy, ModFOLDdock placed second and ModFOLDdockR placed third; for overall interface quality prediction accuracy, ModFOLDdockR, ModFOLDdock, and ModFOLDdockS were placed above all other predictor methods, and ModFOLDdockR and ModFOLDdockS were placed second and third respectively for individual residue confidence scores. The ModFOLDdock server is available at: https://www.reading.ac.uk/bioinf/ModFOLDdockTest/. ModFOLDdock is also available as part of the MultiFOLD docker package: https://hub.docker.com/rTest/mcguffin/multifold.
وصف الملف: text
العلاقة: https://centaur.reading.ac.uk/112265/8/Proteins%20-%202023%20-%20Edmunds%20-%20Estimation%20of%20model%20accuracy%20in%20CASP15%20using%20the%20ModFOLDdock%20server.pdfTest; https://centaur.reading.ac.uk/112265/1/ModFOLDdock_Proteins_Final_Revised.pdfTest; Edmunds, N. S., Alharbi, S. M.A., Genc, A. G., Adiyaman, R. and McGuffin, L. J. orcid:0000-0003-4501-4767 (2023) Estimation of model accuracy in CASP15 using the ModFOLDdock server. Proteins: Structure, Function, and Bioinformatics, 91 (12). pp. 1871-1878. ISSN 1097-0134 doi: https://doi.org/10.1002/prot.26532Test
الإتاحة: https://doi.org/10.1002/prot.26532Test
https://centaur.reading.ac.uk/112265Test/
https://centaur.reading.ac.uk/112265/8/Proteins%20-%202023%20-%20Edmunds%20-%20Estimation%20of%20model%20accuracy%20in%20CASP15%20using%20the%20ModFOLDdock%20server.pdfTest
https://centaur.reading.ac.uk/112265/1/ModFOLDdock_Proteins_Final_Revised.pdfTest -
5دورية أكاديمية
المؤلفون: del Conte, Alessio, Bouhraoua, Adel, Mehdiabadi, Mahta, Clementel, Damiano, Monzon, Alexander, Miguel, Holehouse, Alex, S, Griffith, Daniel, Emenecker, Ryan, J, Patil, Ashwini, Sharma, Ronesh, Tsunoda, Tatsuhiko, Sharma, Alok, Tang, Yi, Jun, Liu, Bin, Mirabello, Claudio, Wallner, Björn, Rost, Burkhard, Ilzhöfer, Dagmar, Littmann, Maria, Heinzinger, Michael, Krautheimer, Lea, I M, Bernhofer, Michael, Mcguffin, Liam, J, Callebaut, Isabelle, Feildel, Tristan, Bitard, Liu, Jian, Cheng, Jianlin, Guo, Zhiye, Xu, Jinbo, Wang, Sheng, Malhis, Nawar, Gsponer, Jörg, Kim, Chol-Song, Han, Kun-Sop, Ma, Myong-Chol, Kurgan, Lukasz, Ghadermarzi, Sina, Katuwawala, Akila, Zhao, Bi, Peng, Zhenling, Wu, Zhonghua, Hu, Gang, Wang, Kui, Hoque, Md, Tamjidul, Kabir, Md, Wasi Ul, Vendruscolo, Michele, Sormanni, Pietro, Li, Min, Zhang, Fuhao, Jia, Pengzhen, Wang, Yida, Lobanov, Michail, Yu, Galzitskaya, Oxana, V, Vranken, Wim, Díaz, Adrián, Litfin, Thomas, Zhou, Yaoqi, Hanson, Jack, Paliwal, Kuldip, Dosztányi, Zsuzsanna, Erdős, Gábor, Tosatto, Silvio, C E, Piovesan, Damiano
المساهمون: Università degli Studi di Padova = University of Padua (Unipd), Bioinformatique et BioPhysique IMPMC (IMPMC_BIBIP), Institut de minéralogie, de physique des matériaux et de cosmochimie (IMPMC), Muséum national d'Histoire naturelle (MNHN)-Institut de recherche pour le développement IRD : UR206-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de recherche pour le développement IRD : UR206-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), DGA Maîtrise de l'information (DGA.MI), Direction générale de l'Armement (DGA)
المصدر: ISSN: 0305-1048.
مصطلحات موضوعية: [SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]
الوصف: International audience ; Intrinsic disorder (ID) in proteins is well-established in structural biology, with increasing evidence for its involvement in essential biological processes. As measuring d ynamic ID beha vior e xperimentall y on a large scale remains difficult, scores of published ID predictor s ha ve tried to fill this gap. Unfortunatel y, their heterogeneity makes it difficult to compare perf ormance, conf ounding biologists wanting to make an informed choice. To address this issue, the Critical Assessment of protein Intrinsic Disorder (CAID) benchmarks predictors for ID and binding regions as a community blind-test in a standardized computing environment. Here we present the CAID Prediction Portal, a web server executing all CAID methods on user-defined sequences. The server generates standardized output and facilitates comparison between methods, producing a consensus prediction highlighting high-confidence ID regions. The website contains extensive documentation explaining the meaning of different CAID statistics and providing a brief description of all methods. Predictor output is visualized in an interactive feature viewer and made available for download in a single table, with the option to recover previous sessions via a priv ate dashboar d. The CAID Prediction Portal is a valuable resource for researchers interested in studying ID in proteins. The server is available at the URL: https://caid.idpcentral.orgTest .
العلاقة: hal-04240607; https://hal.science/hal-04240607Test; https://hal.science/hal-04240607/documentTest; https://hal.science/hal-04240607/file/gkad430.pdfTest
الإتاحة: https://doi.org/10.1093/nar/gkad430Test
https://hal.science/hal-04240607Test
https://hal.science/hal-04240607/documentTest
https://hal.science/hal-04240607/file/gkad430.pdfTest -
6دورية أكاديمية
المؤلفون: McGuffin, Liam J, Edmunds, Nicholas S, Genc, Ahmet G, Alharbi, Shuaa M A, Salehe, Bajuna R, Adiyaman, Recep
المساهمون: Biotechnology and Biological Sciences Research Council, Saudi Arabian Government, Ministry of National Education
المصدر: Nucleic Acids Research ; volume 51, issue W1, page W274-W280 ; ISSN 0305-1048 1362-4962
الوصف: The IntFOLD server based at the University of Reading has been a leading method over the past decade in providing free access to accurate prediction of protein structures and functions. In a post-AlphaFold2 world, accurate models of tertiary structures are widely available for even more protein targets, so there has been a refocus in the prediction community towards the accurate modelling of protein-ligand interactions as well as modelling quaternary structure assemblies. In this paper, we describe the latest improvements to IntFOLD, which maintains its competitive structure prediction performance by including the latest deep learning methods while also integrating accurate model quality estimates and 3D models of protein-ligand interactions. Furthermore, we also introduce our two new server methods: MultiFOLD for accurately modelling both tertiary and quaternary structures, with performance which has been independently verified to outperform the standard AlphaFold2 methods, and ModFOLDdock, which provides world-leading quality estimates for quaternary structure models. The IntFOLD7, MultiFOLD and ModFOLDdock servers are available at: https://www.reading.ac.uk/bioinfTest/.
الإتاحة: https://doi.org/10.1093/nar/gkad297Test
https://academic.oup.com/nar/article-pdf/51/W1/W274/50736942/gkad297.pdfTest -
7دورية أكاديمية
المساهمون: Lengauer, Thomas, Biotechnology and Biological Sciences Research Council
المصدر: Bioinformatics Advances ; volume 3, issue 1 ; ISSN 2635-0041
مصطلحات موضوعية: Computer Science Applications, Genetics, Molecular Biology, Structural Biology
الوصف: Motivation The accuracy gap between predicted and experimental structures has been significantly reduced following the development of AlphaFold2 (AF2). However, for many targets, AF2 models still have room for improvement. In previous CASP experiments, highly computationally intensive MD simulation-based methods have been widely used to improve the accuracy of single 3D models. Here, our ReFOLD pipeline was adapted to refine AF2 predictions while maintaining high model accuracy at a modest computational cost. Furthermore, the AF2 recycling process was utilized to improve 3D models by using them as custom template inputs for tertiary and quaternary structure predictions. Results According to the Molprobity score, 94% of the generated 3D models by ReFOLD were improved. AF2 recycling showed an improvement rate of 87.5% (using MSAs) and 81.25% (using single sequences) for monomeric AF2 models and 100% (MSA) and 97.8% (single sequence) for monomeric non-AF2 models, as measured by the average change in lDDT. By the same measure, the recycling of multimeric models showed an improvement rate of as much as 80% for AF2-Multimer (AF2M) models and 94% for non-AF2M models. Availability and implementation Refinement using AlphaFold2-Multimer recycling is available as part of the MultiFOLD docker package (https://hub.docker.com/rTest/mcguffin/multifold). The ReFOLD server is available at https://www.reading.ac.uk/bioinf/ReFOLDTest/ and the modified scripts can be downloaded from https://www.reading.ac.uk/bioinf/downloadsTest/. Supplementary information Supplementary data are available at Bioinformatics Advances online.
الإتاحة: https://doi.org/10.1093/bioadv/vbad078Test
https://academic.oup.com/bioinformaticsadvances/article-pdf/3/1/vbad078/50698054/vbad078.pdfTest -
8دورية أكاديمية
المؤلفون: Keasar, Chen, McGuffin, Liam J, Wallner, Björn, Chopra, Gaurav, Adhikari, Badri, Bhattacharya, Debswapna, Blake, Lauren, Bortot, Leandro Oliveira, Cao, Renzhi, Dhanasekaran, BK, Dimas, Itzhel, Faccioli, Rodrigo Antonio, Faraggi, Eshel, Ganzynkowicz, Robert, Ghosh, Sambit, Ghosh, Soma, Giełdoń, Artur, Golon, Lukasz, He, Yi, Heo, Lim, Hou, Jie, Khan, Main, Khatib, Firas, Khoury, George A, Kieslich, Chris, Kim, David E, Krupa, Pawel, Lee, Gyu Rie, Li, Hongbo, Li, Jilong, Lipska, Agnieszka, Liwo, Adam, Maghrabi, Ali Hassan A, Mirdita, Milot, Mirzaei, Shokoufeh, Mozolewska, Magdalena A, Onel, Melis, Ovchinnikov, Sergey, Shah, Anand, Shah, Utkarsh, Sidi, Tomer, Sieradzan, Adam K, Ślusarz, Magdalena, Ślusarz, Rafal, Smadbeck, James, Tamamis, Phanourios, Trieber, Nicholas, Wirecki, Tomasz, Yin, Yanping, Zhang, Yang, Bacardit, Jaume, Baranowski, Maciej, Chapman, Nicholas, Cooper, Seth, Defelicibus, Alexandre, Flatten, Jeff, Koepnick, Brian, Popović, Zoran, Zaborowski, Bartlomiej, Baker, David, Cheng, Jianlin, Czaplewski, Cezary, Delbem, Alexandre Cláudio Botazzo, Floudas, Christodoulos, Kloczkowski, Andrzej, Ołdziej, Stanislaw, Levitt, Michael, Scheraga, Harold, Seok, Chaok, Söding, Johannes, Vishveshwara, Saraswathi, Xu, Dong, Foldit Players consortium, Crivelli, Silvia N
المصدر: Scientific reports. 8(1)
مصطلحات موضوعية: Foldit Players consortium, Humans, Caspases, Computational Biology, Protein Conformation, Models, Molecular, Software, Caspase 12, Models, Molecular, Biochemistry and Cell Biology, Other Physical Sciences
الوصف: Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.
وصف الملف: application/pdf
الوصول الحر: https://escholarship.org/uc/item/5jp72387Test
-
9
المؤلفون: Elofsson, Arne, Joo, Keehyoung, Keasar, Chen, Lee, Jooyoung, Maghrabi, Ali H. A., Manavalan, Balachandran, McGuffin, Liam J., Hurtado, David Menendez, Mirabello, Claudio, Pilstål, Robert, Sidi, Tomer, Uziela, Karolis, Wallner, Björn
المصدر: Proteins. 86:361-373
مصطلحات موضوعية: CASP, consensus predictions, estimates of model accuracy, machine learning, protein structure prediction, quality assessment
الوصف: Methods to reliably estimate the quality of 3D models of proteins are essential drivers for the wide adoption and serious acceptance of protein structure predictions by life scientists. In this article, the most successful groups in CASP12 describe their latest methods for estimates of model accuracy (EMA). We show that pure single model accuracy estimation methods have shown clear progress since CASP11; the 3 top methods (MESHI, ProQ3, SVMQA) all perform better than the top method of CASP11 (ProQ2). Although the pure single model accuracy estimation methods outperform quasi-single (ModFOLD6 variations) and consensus methods (Pcons, ModFOLDclust2, Pcomb-domain, and Wallner) in model selection, they are still not as good as those methods in absolute model quality estimation and predictions of local quality. Finally, we show that when using contact-based model quality measures (CAD, lDDT) the single model quality methods perform relatively better.
وصف الملف: electronic
الوصول الحر: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-145749Test
https://liu.diva-portal.org/smash/get/diva2:1192521/FULLTEXT01.pdfTest -
10دورية أكاديمية
الوصف: Methods for estimating the quality of 3D models of proteins are vital tools for driving the acceptance and utility of predicted tertiary structures by the wider bioscience community. Here we describe the significant major updates to ModFOLD, which has maintained its position as a leading server for the prediction of global and local quality of 3D protein models, over the past decade (>20 000 unique external users). ModFOLD8 is the latest version of the server, which combines the strengths of multiple pure-single and quasi-single model methods. Improvements have been made to the web server interface and there has been successive increases in prediction accuracy, which were achieved through integration of newly developed scoring methods and advanced deep learning-based residue contact predictions. Each version of the ModFOLD server has been independently blind tested in the biennial CASP experiments, as well as being continuously evaluated via the CAMEO project. In CASP13 and CASP14, the ModFOLD7 and ModFOLD8 variants ranked among the top 10 quality estimation methods according to almost every official analysis. Prior to CASP14, ModFOLD8 was also applied for the evaluation of SARS-CoV-2 protein models as part of CASP Commons 2020 initiative. The ModFOLD8 server is freely available at: https://www.reading.ac.uk/bioinf/ModFOLDTest/.
وصف الملف: text
العلاقة: https://centaur.reading.ac.uk/97498/8/gkab321.pdfTest; https://centaur.reading.ac.uk/97498/1/New%20version.pdfTest; McGuffin, L. J. orcid:0000-0003-4501-4767 , Aldowsari, F. M. F., Alharbi, S. M. A. and Adiyaman, R. (2022) ModFOLD8: accurate global and local quality estimates for 3D protein models. Nucleic Acids Research, 49 (W1). W425-W430. ISSN 1362-4962 doi: https://doi.org/10.1093/nar/gkab321Test
