A Computational Approach From Gene to Structure Analysis of the Human ABCA4 Transporter Involved in Genetic Retinal Diseases

作者：Trezza Alfonso; Bernini Andrea; Langella Andrea; Ascher David B; Pires Douglas E V; Sodi Andrea; Passerini Ilaria; Pelo Elisabetta; Rizzo Stanislao; Niccolai Neri; Spiga Ottavia^*

来源：Investigative Ophthalmology & Visual Science, 2017, 58(12): 5320-5328.

DOI：10.1167/iovs.17-22158

• ABCA4 protein
• ABC transporter
• mutations database

PURPOSE. The aim of this article is to report the investigation of the structural features of ABCA4, a protein associated with a genetic retinal disease. A new database collecting knowledge of ABCA4 structure may facilitate predictions about the possible functional consequences of gene mutations observed in clinical practice.
METHODS. In order to correlate structural and functional effects of the observed mutations, the structure of mouse P-glycoprotein was used as a template for homology modeling. The obtained structural information and genetic data are the basis of our relational database (ABCA4Database).
RESULTS. Sequence variability among all ABCA4-deposited entries was calculated and reported as Shannon entropy score at the residue level. The three-dimensional model of ABCA4 structure was used to locate the spatial distribution of the observed variable regions. Our predictions from structural in silico tools were able to accurately link the functional effects of mutations to phenotype. The development of the ABCA4Database gathers all the available genetic and structural information, yielding a global view of the molecular basis of some retinal diseases.
CONCLUSIONS. ABCA4 modeled structure provides a molecular basis on which to analyze protein sequence mutations related to genetic retinal disease in order to predict the risk of retinal disease across all possible ABCA4 mutations. Additionally, our ABCA4 predicted structure is a good starting point for the creation of a new data analysis model, appropriate for precision medicine, in order to develop a deeper knowledge network of the disease and to improve the management of patients.

• 出版日期2017-10