Wei Zheng

University of Michigan
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Articles (11)

The prediction of three-dimensional (3D) protein structure from amino acid sequences has stood as a significant challenge in computational and structural bioinformatics for decades. Recently, the widespread integration of artificial intelligence (AI) algorithms has substantially expedited advancements in protein structure prediction, yielding numerous significant milestones. In particular, the end-to-end deep learning method AlphaFold2 has facilitated the rise of structure prediction performance to new heights, regularly competitive with experimental structures in the 14th Critical Assessment of Protein Structure Prediction (CASP14). To provide a comprehensive understanding and guide future research in the field of protein structure prediction for researchers, this review describes various methodologies, assessments, and databases in protein structure prediction, including traditionally used protein structure prediction methods, such as template-based modeling (TBM) and template-free modeling (FM) approaches; recently developed deep learning-based methods, such as contact/distance-guided methods, end-to-end folding methods, and protein language model (PLM)-based methods; multi-domain protein structure prediction methods; the CASP experiments and related assessments; and the recently released AlphaFold Protein Structure Database (AlphaFold DB). We discuss their advantages, disadvantages, and application scopes, aiming to provide researchers with insights through which to understand the limitations, contexts, and effective selections of protein structure prediction methods in protein-related fields.

Year:

2024

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2023

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2023

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2023

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2023

The Treponema denticola gene encoding its major surface protein (Msp) is an ortholog of the T. pallidum tprA to - K gene family that includes tprK , whose remarkable in vivo hypervariability is proposed to contribute to T. pallidum immune evasion. Using a combined strategy of fine-scale mutagenesis and advanced predictive molecular modeling, we characterized the Msp protein and present a high-confidence model of its structure as an oligomer embedded in the outer membrane.

Year:

2022

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2022

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2022

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2022

Year:

2022

Year:

2022

Collaborators (5)

J. Christopher Fenno

University of Michigan

UNITED STATES
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Teresa A. Santantonio

University of Foggia

ITALY
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Torsten Schwede

Professor

University of Basel

SWITZERLAND
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Jingqi Zhou

University of Georgia

UNITED STATES
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Liang Liu

Professor

University of Georgia

UNITED STATES
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