2021
DOI: 10.1016/j.heliyon.2021.e06013
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Understanding protein structural changes for oncogenic missense variants

Abstract: Understanding and predicting the changes of protein structure and function upon mutation and their relationship to human health is a critical element to translate the genomic revolution into actionable interventions. Therefore, it is pertinent to explore how mutations result in structural changes leading to pathogenic proteins, but due to the protein structural knowledge gap, experimental approaches are lacking. Protein structure prediction methods, such as I-TASSER, have made it possible to predict the struct… Show more

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Cited by 6 publications
(4 citation statements)
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“…Following our previous approaches to demonstrate the usefulness of protein prediction methods to elucidate pathogenicity [10,[20][21][22][23], the canonical/reference sequence for the ERF protein was retrieved from UniProt (Uniprot ID: P50548) [24]. The variant sequence was manually modified and the two resulting sequences were submitted to the Phyre2 server [25] on intensive mode for structure prediction.…”
Section: Protein Prediction Modelingmentioning
confidence: 99%
“…Following our previous approaches to demonstrate the usefulness of protein prediction methods to elucidate pathogenicity [10,[20][21][22][23], the canonical/reference sequence for the ERF protein was retrieved from UniProt (Uniprot ID: P50548) [24]. The variant sequence was manually modified and the two resulting sequences were submitted to the Phyre2 server [25] on intensive mode for structure prediction.…”
Section: Protein Prediction Modelingmentioning
confidence: 99%
“… 4 Because of the apparent similarities in mutation patterns with polyGln expansion diseases, polyAla, too, might promote misfolding and aggregation as observed in the study carried out by Hernandez and Facelli in 2020 by structural prediction analyses; indeed, this mechanism has been proposed suggesting the formation of amyloid fibrils. 5 Differently, other studies indicated that polyAla aggregates into α-helical structures of an amorphous nature. 6 …”
Section: Introductionmentioning
confidence: 96%
“…Confirmation of significant association with prostate cancer risk in an independent population and observation of segregation of variants with prostate cancer in multiple high-risk pedigrees provided additional validation for a subset of the candidates considered. We used 3D protein structure prediction methods to analyze structural changes in one outstanding candidate variant that may provide insights on mechanisms of pathogenicity [ 11 ].…”
Section: Introductionmentioning
confidence: 99%