scholarly journals EL_PSSM-RT: DNA-binding residue prediction by integrating ensemble learning with PSSM Relation Transformation

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Jiyun Zhou ◽  
Qin Lu ◽  
Ruifeng Xu ◽  
Yulan He ◽  
Hongpeng Wang
2018 ◽  
Vol 19 (S19) ◽  
Author(s):  
Lei Deng ◽  
Juan Pan ◽  
Xiaojie Xu ◽  
Wenyi Yang ◽  
Chuyao Liu ◽  
...  

2020 ◽  
Vol 29 (9) ◽  
pp. 1417-1425 ◽  
Author(s):  
Claire E L Smith ◽  
Laura L E Whitehouse ◽  
James A Poulter ◽  
Laura Wilkinson Hewitt ◽  
Fatima Nadat ◽  
...  

Abstract Amelogenesis is the process of enamel formation. For amelogenesis to proceed, the cells of the inner enamel epithelium (IEE) must first proliferate and then differentiate into the enamel-producing ameloblasts. Amelogenesis imperfecta (AI) is a heterogeneous group of genetic conditions that result in defective or absent tooth enamel. We identified a 2 bp variant c.817_818GC>AA in SP6, the gene encoding the SP6 transcription factor, in a Caucasian family with autosomal dominant hypoplastic AI. The resulting missense protein change, p.(Ala273Lys), is predicted to alter a DNA-binding residue in the first of three zinc fingers. SP6 has been shown to be crucial to both proliferation of the IEE and to its differentiation into ameloblasts. SP6 has also been implicated as an AI candidate gene through its study in rodent models. We investigated the effect of the missense variant in SP6 (p.(Ala273Lys)) using surface plasmon resonance protein-DNA binding studies. We identified a potential SP6 binding motif in the AMBN proximal promoter sequence and showed that wild-type (WT) SP6 binds more strongly to it than the mutant protein. We hypothesize that SP6 variants may be a very rare cause of AI due to the critical roles of SP6 in development and that the relatively mild effect of the missense variant identified in this study is sufficient to affect amelogenesis causing AI, but not so severe as to be incompatible with life. We suggest that current AI cohorts, both with autosomal recessive and dominant disease, be screened for SP6 variants.


2016 ◽  
Vol 12 (12) ◽  
pp. 3643-3650 ◽  
Author(s):  
H. Chai ◽  
J. Zhang ◽  
G. Yang ◽  
Z. Ma

A dynamic query-driven learning scheme helps to make more use of proteins with known structure and functions.


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