Indonesian
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Shengwu Gongcheng Xuebao/Chinese Journal of Biotechnology 2008-May

Computational and structural investigation of deleterious functional SNPs in breast cancer BRCA2 gene.

Hanya pengguna terdaftar yang dapat menerjemahkan artikel
Masuk daftar
Tautan disimpan ke clipboard
R Rajasekaran
George Priya Doss
C Sudandiradoss
K Ramanathan
Purohit Rituraj
Rao Sethumadhavan

Kata kunci

Abstrak

In this work, we have analyzed the genetic variation that can alter the expression and the function in BRCA2 gene using computational methods. Out of the total 534 SNPs, 101 were found to be non synonymous (nsSNPs). Among the 7 SNPs in the untranslated region, 3 SNPs were found in 5' and 4 SNPs were found in 3' un-translated regions (UTR). Of the nsSNPs 20.7% were found to be damaging by both SIFT and PolyPhen server among the 101 nsSNPs investigated. UTR resource tool suggested that 2 SNPs in the 5' UTR region and 4 SNPs in the 3' UTR regions might change the protein expression levels. The mutation from asparagine to isoleucine at the position 3124 of the native protein of BRCA2 gene was most deleterious by both SIFT and PolyPhen servers. A structural analysis of this mutated protein and the native protein was made which had an RMSD value of 0.301 nm. Based on this work, we proposed that this most deleterious nsSNP with an SNPid rs28897759 is an important candidate for the cause of breast cancer by BRCA2 gene.

Bergabunglah dengan
halaman facebook kami

Database tanaman obat terlengkap yang didukung oleh sains

  • Bekerja dalam 55 bahasa
  • Pengobatan herbal didukung oleh sains
  • Pengenalan herbal melalui gambar
  • Peta GPS interaktif - beri tag herba di lokasi (segera hadir)
  • Baca publikasi ilmiah yang terkait dengan pencarian Anda
  • Cari tanaman obat berdasarkan efeknya
  • Atur minat Anda dan ikuti perkembangan berita, uji klinis, dan paten

Ketikkan gejala atau penyakit dan baca tentang jamu yang mungkin membantu, ketik jamu dan lihat penyakit dan gejala yang digunakan untuk melawannya.
* Semua informasi didasarkan pada penelitian ilmiah yang dipublikasikan

Google Play badgeApp Store badge