Literature DB >> 27210447

Structure-Based Identification, Characterization, and Disruption of Human Securin-Binding SH3 Domains in Lung Cancer.

Keping Wang1, Tiefeng Qiu2, Xianwen Li3.   

Abstract

The human securin is an oncogenic transcription factor that has been found to promote migration and invasion of lung cancer and many other tumors. The protein contains a PxxP motif that can be recognized and bound by diverse cellular partners via Src homology (SH3) domain to regulate biological and pathological events. The motif is covered by a decapeptide segment (161)LGPPSPVKMP(170) (SecPeptide) as the potential binding site of SH3 domains. Here, we attempted to systemically identify the SH3 binding partners of human securin in lung cancer and to characterize the intermolecular interaction between SecPeptide and the identified SH3 domains. A bioinformatics protocol that integrated literature curation, complex structural modeling, and binding affinity analysis was described to perform systematic search against an array of SH3-containing proteins involved in lung cancer signaling pathway and, consequently, three putative domains, namely GRB2, CRK, and RasGAP, were identified that have high potential to recognize and bind SecPeptide. The molecular mechanism and biological implication underlying the intermolecular interaction between these domains and SecPetide were investigated at structural and energetic level. Surface plasmon resonance assay revealed a high or moderate affinity of SecPeptide and its two mutants binding to CRK-SH3 domain with dissociation constants Kd = 79.8, 24.2, and 64.6 µM, respectively.

Entities:  

Keywords:  Human securin; Lung cancer; Oncology; Peptide; SH3 domain

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Year:  2016        PMID: 27210447     DOI: 10.1080/07357907.2016.1183024

Source DB:  PubMed          Journal:  Cancer Invest        ISSN: 0735-7907            Impact factor:   2.176


  2 in total

1.  Overexpression of ubiquitin specific proteases 44 promotes the malignancy of glioma by stabilizing tumor-promoter securin.

Authors:  Yongxiang Zou; Guanzhong Qiu; Lei Jiang; Zheng Cai; Wei Sun; Hongkang Hu; Chengyin Lu; Weilin Jin; Guohan Hu
Journal:  Oncotarget       Date:  2017-03-22

2.  Integrating node embeddings and biological annotations for genes to predict disease-gene associations.

Authors:  Sezin Kircali Ata; Le Ou-Yang; Yuan Fang; Chee-Keong Kwoh; Min Wu; Xiao-Li Li
Journal:  BMC Syst Biol       Date:  2018-12-31
  2 in total

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