Abstract
Systematic identification of binding partners for SH2 domains is important for understanding the biological function of the corresponding SH2 domain-containing proteins. Here, we describe two different web-accessible computer programs, SMALI and DomPep, for predicting binding ligands for SH2 domains. The former was developed using a Scoring Matrix method and the latter based on the Support Vector Machine model.
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Acknowledgment
This work was supported, in part, by funds from Taishan Scholar Construction Project (to L.L.), the Canadian Cancer Society (to S.S.L.) and the Ontario Research Fund (to S.S.L.). S.S.L. holds a Canadian Research Chair in Functional Genomics and Cellular Proteomics. L.L. holds a Taishan Scholarship.
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Li, S.S.C., Li, L. (2017). SH2 Ligand Prediction–Guidance for In-Silico Screening. In: Machida, K., Liu, B. (eds) SH2 Domains. Methods in Molecular Biology, vol 1555. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6762-9_5
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DOI: https://doi.org/10.1007/978-1-4939-6762-9_5
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Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-6760-5
Online ISBN: 978-1-4939-6762-9
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