Artificial Intelligence for Bioinformatics: Applications in Protein Folding Prediction

AbstractAI recently shows great promise in the field of bioinformatics, such as protein structure prediction. The Critical Assessment of protein Structure Prediction (CASP) is a nationwide experiment that takes place biannually, which centered around analyzing the best current systems for predicting protein tertiary structures. In this paper, we research on available AI methods and features, and then explore novel methods based on reinforcement learning. Such method will have profound implications for R&D in bioinformatics and add an additional platform to the management of innovation in biotechnology.

Download Full-text

Faculty Opinions recommendation of Worth the effort. An account of the Seventh Meeting of the Worldwide Critical Assessment of Techniques for Protein Structure Prediction.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1083793.536717 ◽

2007 ◽

Author(s):

David Osguthorpe

Keyword(s):

Protein Structure ◽

Protein Structure Prediction ◽

Structure Prediction ◽

Critical Assessment

Download Full-text

Target Classification in the 14th Round of the Critical Assessment of Protein Structure Prediction ( CASP14 )

Proteins Structure Function and Bioinformatics ◽

10.1002/prot.26202 ◽

2021 ◽

Author(s):

Lisa N. Kinch ◽

Dustin R. Schaeffer ◽

Andriy Kryshtafovych ◽

Nick V. Grishin

Keyword(s):

Protein Structure ◽

Protein Structure Prediction ◽

Structure Prediction ◽

Critical Assessment ◽

Target Classification

Download Full-text

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

BMC Bioinformatics ◽

10.1186/s12859-021-04353-8 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Lupeng Kong ◽

Fusong Ju ◽

Haicang Zhang ◽

Shiwei Sun ◽

Dongbo Bu

Keyword(s):

Protein Structure ◽

Ab Initio ◽

Protein Structure Prediction ◽

Structure Prediction ◽

Web Server ◽

High Quality ◽

Tertiary Structures ◽

Target Proteins ◽

High Quality Protein ◽

Protein Functions

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.

Download Full-text