Mutation analysis of SHP2, SOS1, and SOS2 related to dysregulation of Ras/MAPK pathway in Noonan syndrome
Abstract
Background: Noonan syndrome, characterized by short stature, congenital heart defects, and facial dysmorphology, results from dysregulation of the Ras/MAPK pathway. Mutations in Ras/MAPK pathway proteins such as SHP2, SOS1, and SOS2 are responsible for this condition.
Objective: This study aimed to model the mutations in SHP2, SOS1, and SOS2 using FoldX and predict the structural impact.
Methods: Mutations were sourced from the OMIM Database. Protein sequence was retrieved from UniProt, and evolutionary conservation profiles were estimated by ConSurf. The structures of SHP2 and SOS1 were obtained from Protein Data Bank, while the undefined structure of SOS2 was modeled using YASARA. FoldX was used to model the mutations in two steps: structure repair and residue mutation.
Results: The evolutionary conservation profile indicated that most mutations occur in the highly conserved residues. These mutations disrupt various important interactions at domain interfaces. The total energy changes were predominantly positive, indicating instability in the mutated proteins due to the loss of the domain interactions and some unfavorable local conformational changes.
Conclusion: FoldX is a valuable tool for modeling protein mutations and predicting altered function. The models demonstrate that the mutations contribute to the aberrant autoinhibitory control and catalytic activity of the proteins.
References
Allen MJ, Sharma S. Noonan Syndrome. StatPearls. Treasure Island (FL): StatPearls Publishing; 2023. Available: http://www.ncbi.nlm.nih.gov/books/NBK532269/
Koh A, Tan E, Brett MS, Lai AHM, Jamuar SS, Ng I, et al. The spectrum of genetic variants and phenotypic features of Southeast Asian patients with Noonan syndrome. Molec Gen & Gen Med. 2019;7: e00581. https://doi.org/10.1002/mgg3.581
Tartaglia M, Zampino G, Gelb BD. Noonan Syndrome: Clinical Aspects and Molecular Pathogenesis. Mol Syndromol. 2010;1: 2-26. https://doi.org/10.1159/000276766
Diop A, Santorelli D, Malagrinò F, Nardella C, Pennacchietti V, Pagano L, et al. SH2 Domains: Folding, Binding and Therapeutical Approaches. IJMS. 2022;23: 15944. https://doi.org/10.3390/ijms232415944
Buday L, Vas V. Novel regulation of Ras proteins by direct tyrosine phosphorylation and dephosphorylation. Cancer Metastasis Rev. 2020;39: 1067-1073. https://doi.org/10.1007/s10555-020-09918-2
Findlay GM, Pawson T. How is SOS activated? Let us count the ways. Nat Struct Mol Biol. 2008;15: 538-540. https://doi.org/10.1038/nsmb0608-538
Bandaru P, Kondo Y, Kuriyan J. The Interdependent Activation of Son-of-Sevenless and Ras. Cold Spring Harb Perspect Med. 2019;9: a031534. https://doi.org/10.1101/cshperspect.a031534
Van Durme J, Delgado J, Stricher F, Serrano L, Schymkowitz J, Rousseau F. A graphical interface for the FoldX forcefield. Bioinformatics. 2011;27: 1711-1712. https://doi.org/10.1093/bioinformatics/btr254
Buß O, Rudat J, Ochsenreither K. FoldX as Protein Engineering Tool: Better Than Random Based Approaches? Computational and Structural Biotechnology Journal. 2018;16: 25-33. https://doi.org/10.1016/j.csbj.2018.01.002
Amberger JS, Bocchini CA, Scott AF, Hamosh A. OMIM.org: leveraging knowledge across phenotype-gene relationships. Nucleic Acids Research. 2019;47: D1038-D1043. https://doi.org/10.1093/nar/gky1151
The UniProt Consortium, Bateman A, Martin M-J, Orchard S, Magrane M, Ahmad S, et al. UniProt: the Universal Protein Knowledgebase in 2023. Nucleic Acids Research. 2023;51: D523-D531. https://doi.org/10.1093/nar/gkac1052
Hekkelman ML, Vriend G. MRS: a fast and compact retrieval system for biological data. Nucleic Acids Research. 2005;33: W766-W769. https://doi.org/10.1093/nar/gki422
Burley SK, Bhikadiya C, Bi C, Bittrich S, Chao H, Chen L, et al. RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning. Nucleic Acids Research. 2023;51: D488-D508. https://doi.org/10.1093/nar/gkac1077
Ashkenazy H, Abadi S, Martz E, Chay O, Mayrose I, Pupko T, et al. ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules. Nucleic Acids Res. 2016;44: W344-W350. https://doi.org/10.1093/nar/gkw408
Sander C, Schneider R. Database of homology-derived protein structures and the structural meaning of sequence alignment. Proteins. 1991;9: 56-68. https://doi.org/10.1002/prot.340090107
Land H, Humble MS. YASARA: A Tool to Obtain Structural Guidance in Biocatalytic Investigations. In: Bornscheuer UT, Höhne M, editors. Protein Engineering. New York, NY: Springer New York; 2018. pp. 43-67. https://doi.org/10.1007/978-1-4939-7366-8_4
Delgado J, Radusky LG, Cianferoni D, Serrano L. FoldX 5.0: working with RNA, small molecules and a new graphical interface. Valencia A, editor. Bioinformatics. 2019;35: 4168-4169. https://doi.org/10.1093/bioinformatics/btz184
Zhu G, Xie J, Kong W, Xie J, Li Y, Du L, et al. Phase Separation of Disease-Associated SHP2 Mutants Underlies MAPK Hyperactivation. Cell. 2020;183: 490-502.e18. https://doi.org/10.1016/j.cell.2020.09.002
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