Small-angle X-ray scattering for the proteomics community: current overview and future potential

Kursula, Petri

doi:10.1080/14789450.2021.1951242

Cited by 5 publications

(2 citation statements)

References 99 publications

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“…For the fusion protein BCR‐ABL, the ABL1 kinase domain acts as a well‐established template, with its structure available in the Protein Data Bank (PDB) such as 2HYY, 1OPJ, 1OPL, 1OPK, 2F4J, 2GQG, 2HZF, 2I4I, 2OIQ and 2OIR. 15 , 16 Similarly, for the TF fusion protein EWSR1‐FLI1, the FLI1 component's structure is known and is available in the PDB with entries like 1FLI, 4JYZ, 4JZD, 4JZF, 4JZG, 5L9X and 4JZH. These known structures provide a foundational framework for modelling and predicting the architecture of the respective fusion proteins.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence in fusion protein three‐dimensional structure prediction: Review and perspective

Kumar,

Kim

2024

Clinical & Translational Med

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Recent advancements in artificial intelligence (AI) have accelerated the prediction of unknown protein structures. However, accurately predicting the three‐dimensional (3D) structures of fusion proteins remains a difficult task because the current AI‐based protein structure predictions are focused on the WT proteins rather than on the newly fused proteins in nature. Following the central dogma of biology, fusion proteins are translated from fusion transcripts, which are made by transcribing the fusion genes between two different loci through the chromosomal rearrangements in cancer. Accurately predicting the 3D structures of fusion proteins is important for understanding the functional roles and mechanisms of action of new chimeric proteins. However, predicting their 3D structure using a template‐based model is challenging because known template structures are often unavailable in databases. Deep learning (DL) models that utilize multi‐level protein information have revolutionized the prediction of protein 3D structures. In this review paper, we highlighted the latest advancements and ongoing challenges in predicting the 3D structure of fusion proteins using DL models. We aim to explore both the advantages and challenges of employing AlphaFold2, RoseTTAFold, tr‐Rosetta and D‐I‐TASSER for modelling the 3D structures.Highlights This review provides the overall pipeline and landscape of the prediction of the 3D structure of fusion protein. This review provides the factors that should be considered in predicting the 3D structures of fusion proteins using AI approaches in each step. This review highlights the latest advancements and ongoing challenges in predicting the 3D structure of fusion proteins using deep learning models. This review explores the advantages and challenges of employing AlphaFold2, RoseTTAFold, tr-Rosetta, and D-I-TASSER to model 3D structures.

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Section: Introductionmentioning

confidence: 99%

Artificial intelligence in fusion protein three‐dimensional structure prediction: Review and perspective

Kumar,

Kim

2024

Clinical & Translational Med

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“…Small-angle X-ray scattering (SAXS) provides shape and supramolecular structural features of aggregates and large molecules in solution. , SAXS can also act as an analytical method when data is reported on the absolute scale, e.g., providing a volume fraction estimation. For protein science, SAXS provides low-resolution information on protein shape, conformation, and the state of its assembly .…”

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confidence: 99%

Measuring the Radius of Gyration and Intrinsic Flexibility of Viral Proteins in Buffer Solution Using Small-Angle X-ray Scattering

2022

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Measuring structural features of proteins dispersed in buffer solution, in contrast to crystal form, is indispensable in understanding morphological characteristics of the biomolecule in a native environment. We report on the structure and apparent viscosity of unfolded α and β variants of SARS-CoV-2 spike proteins dispersed in buffer solutions. The radius of gyration of the β variant is found to be larger than that of the α variant, while the ab initio computation of one of the possible particle-like bodies is consistent with the small-angle X-ray scattering (SAXS) profiles resembling a conformation similar to the three-dimensional structure of the folded state of the corresponding α and β spike variant. However, a smaller radius of gyration with respect to the predicted folded state of 2.4 and 2.7 is observed for both α and β variants, respectively. Our work complements the structural characterization of spike proteins using cryo-electron microscopy techniques. The measurement/analysis discussed here might be useful for quick and cost-effective evaluation of several protein structures, let alone mutated viral proteins, which is useful for drug discovery/development applications.

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Biophysical Approaches for the Characterization of Protein-Metabolite Interactions

Thalhammer

Bröker

2022

Methods in Molecular Biology

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Small-angle X-ray scattering for the proteomics community: current overview and future potential

Cited by 5 publications

References 99 publications

Artificial intelligence in fusion protein three‐dimensional structure prediction: Review and perspective

Artificial intelligence in fusion protein three‐dimensional structure prediction: Review and perspective

Measuring the Radius of Gyration and Intrinsic Flexibility of Viral Proteins in Buffer Solution Using Small-Angle X-ray Scattering

Biophysical Approaches for the Characterization of Protein-Metabolite Interactions

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