Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: An RNAi in silico approach to find an optimal shRNA cocktail against HIV-1 | Mendez-Ortega et al. Virology Journal 2010 7 369 http content 7 1 369 J VIROLOGY JOURNAL RESEARCH Open Access An RNAi in silico approach to find an optimal shRNA cocktail against HIV-1 2 2 3 4 María C Mendez-Ortega Silvia Restrepo Luis M Rodríguez-R Iván Pérez Juan C Mendoza Andrés P Martinez1 Roberto Sierra2 Gloria J Rey-Benito1 Abstract Background HIV-1 can be inhibited by RNA interference in vitro through the expression of short hairpin RNAs shRNAs that target conserved genome sequences. In silico shRNA design for HIV has lacked a detailed study of virus variability constituting a possible breaking point in a clinical setting. We designed shRNAs against HIV-1 considering the variability observed in naive and drug-resistant isolates available at public databases. Methods A Bioperl-based algorithm was developed to automatically scan multiple sequence alignments of HIV while evaluating the possibility of identifying dominant and subdominant viral variants that could be used as efficient silencing molecules. Student t-test and Bonferroni Dunn correction test were used to assess statistical significance of our findings. Results Our in silico approach identified the most common viral variants within highly conserved genome regions with a calculated free energy of kcal mol. This is crucial for strand loading to RISC complex and for a predicted silencing efficiency score which could be used in combination for achieving over 90 silencing. Resistant and naive isolate variability revealed that the most frequent shRNA per region targets a maximum of 85 of viral sequences. Adding more divergent sequences maintained this percentage. Specific sequence features that have been found to be related with higher silencing efficiency were hardly accomplished in conserved regions even when lower entropy values correlated with better scores. We identified a conserved region among most HIV-1 genomes which meets as many sequence features for efficient .
