دورية أكاديمية

FALCON2: a web server for high-quality prediction of protein tertiary structures

التفاصيل البيبلوغرافية
العنوان: FALCON2: a web server for high-quality prediction of protein tertiary structures
المؤلفون: Lupeng Kong, Fusong Ju, Haicang Zhang, Shiwei Sun, Dongbo Bu
المصدر: BMC Bioinformatics, Vol 22, Iss 1, Pp 1-14 (2021)
بيانات النشر: BMC, 2021.
سنة النشر: 2021
المجموعة: LCC:Computer applications to medicine. Medical informatics
LCC:Biology (General)
مصطلحات موضوعية: Protein structure prediction, Template-based modeling, Ab initio prediction, Protein structure prediction web service, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
الوصف: Abstract Background Accurate prediction of protein tertiary structures is highly desired as the knowledge of protein structures provides invaluable insights into protein functions. We have designed two approaches to protein structure prediction, including a template-based modeling approach (called ProALIGN) and an ab initio prediction approach (called ProFOLD). Briefly speaking, ProALIGN aligns a target protein with templates through exploiting the patterns of context-specific alignment motifs and then builds the final structure with reference to the homologous templates. In contrast, ProFOLD uses an end-to-end neural network to estimate inter-residue distances of target proteins and builds structures that satisfy these distance constraints. These two approaches emphasize different characteristics of target proteins: ProALIGN exploits structure information of homologous templates of target proteins while ProFOLD exploits the co-evolutionary information carried by homologous protein sequences. Recent progress has shown that the combination of template-based modeling and ab initio approaches is promising. Results In the study, we present FALCON2, a web server that integrates ProALIGN and ProFOLD to provide high-quality protein structure prediction service. For a target protein, FALCON2 executes ProALIGN and ProFOLD simultaneously to predict possible structures and selects the most likely one as the final prediction result. We evaluated FALCON2 on widely-used benchmarks, including 104 CASP13 (the 13th Critical Assessment of protein Structure Prediction) targets and 91 CASP14 targets. In-depth examination suggests that when high-quality templates are available, ProALIGN is superior to ProFOLD and in other cases, ProFOLD shows better performance. By integrating these two approaches with different emphasis, FALCON2 server outperforms the two individual approaches and also achieves state-of-the-art performance compared with existing approaches. Conclusions By integrating template-based modeling and ab initio approaches, FALCON2 provides an easy-to-use and high-quality protein structure prediction service for the community and we expect it to enable insights into a deep understanding of protein functions.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1471-2105
Relation: https://doaj.org/toc/1471-2105
DOI: 10.1186/s12859-021-04353-8
URL الوصول: https://doaj.org/article/8ebd7756e88a456bbbc1c44d3d008136
رقم الأكسشن: edsdoj.8ebd7756e88a456bbbc1c44d3d008136
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:14712105
DOI:10.1186/s12859-021-04353-8