AIMC Topic: Protein Folding

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PepPCBench is a Comprehensive Benchmarking Framework for Protein-Peptide Complex Structure Prediction.

Journal of chemical information and modeling
Accurate modeling of protein-peptide interactions is essential for understanding fundamental biological processes and designing peptide-based drugs. However, predicting the complex structures of these interactions remains challenging, primarily due t...

Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging.

Nature communications
The process of protein aggregation, central to neurodegenerative diseases like Huntington's, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in d...

Navigating protein landscapes with a machine-learned transferable coarse-grained model.

Nature chemistry
The most popular and universally predictive protein simulation models employ all-atom molecular dynamics, but they come at extreme computational cost. The development of a universal, computationally efficient coarse-grained (CG) model with similar pr...

Assisting and accelerating NMR assignment with restrained structure prediction.

Communications biology
Accurate dynamic protein structures are essential for drug design. NMR experiments can detect protein structures and potential dynamics, but the spectrum assignment and structure determination requires expertise and is time-consuming, while deep-lear...

AF3Score: A Score-Only Adaptation of AlphaFold3 for Biomolecular Structure Evaluation.

Journal of chemical information and modeling
Scoring biomolecular complexes remains central to structural modeling efforts. Recent studies suggest that AlphaFold (AF) - a revolutionary deep learning model for biomolecular structure prediction - has implicitly learned an approximate biophysical ...

End looms for protein contest?

Science (New York, N.Y.)
NIH has not committed to continuing support for contest that inspired AI tools for predicting how proteins would fold.

Mapping the Conformational Heterogeneity Intrinsic to the Protein Native Ensemble.

Biochemistry
In the AlphaFold era, there is a significant momentum in predicting protein structures, functionality, and mutational hotspots from deep learning approaches. In this review, we highlight how structural information is only a starting point in understa...

AbEpiTope-1.0: Improved antibody target prediction by use of AlphaFold and inverse folding.

Science advances
B cell epitope prediction tools are crucial for designing vaccines and disease diagnostics. However, predicting which antigens a specific antibody binds to and their exact binding sites (epitopes) remains challenging. Here, we present AbEpiTope-1.0, ...

Reliable protein-protein docking with AlphaFold, Rosetta, and replica exchange.

eLife
Despite the recent breakthrough of AlphaFold (AF) in the field of protein sequence-to-structure prediction, modeling protein interfaces and predicting protein complex structures remains challenging, especially when there is a significant conformation...

Structural Biology in the AlphaFold Era: How Far Is Artificial Intelligence from Deciphering the Protein Folding Code?

Biomolecules
Proteins are biomolecules characterized by uncommon chemical and physicochemical complexities coupled with extreme responsiveness to even minor chemical modifications or environmental variations. Since the shape that proteins assume is fundamental fo...