title: VIRsiRNApred: a web server for predicting inhibition efficacy of siRNAs targeting human viruses.
abstract: BACKGROUND
  Selection of effective viral siRNA is an indispensable step in the development of siRNA based antiviral therapeutics. Despite immense potential, a viral siRNA efficacy prediction algorithm is still not available. Moreover, performances of the existing general mammalian siRNA efficacy predictors are not satisfactory for viral siRNAs. Therefore, we have developed "VIRsiRNApred" a support vector machine (SVM) based method for predicting the efficacy of viral siRNA.
  
  
  METHODS
  In the present study, we have employed a new dataset of 1725 viral siRNAs with experimentally verified quantitative efficacies tested under heterogeneous experimental conditions and targeting as many as 37 important human viruses including HIV, Influenza, HCV, HBV, SARS etc. These siRNAs were divided into training (T1380) and validation (V345) datasets. Important siRNA sequence features including mono to penta nucleotide frequencies, binary pattern, thermodynamic properties and secondary structure were employed for model development.
  
  
  RESULTS
  During 10-fold cross validation on T1380 using hybrid approach, we achieved a maximum Pearson Correlation Coefficient (PCC) of 0.55 between predicted and actual efficacy of viral siRNAs. On V345 independent dataset, our best model achieved a maximum correlation of 0.50 while existing general siRNA prediction methods showed PCC from 0.05 to 0.18. However, using leave one out cross validation PCC was improved to 0.58 and 0.55 on training and validation datasets respectively. SVM performed better than other machine learning techniques used like ANN, KNN and REP Tree.
  
  
  CONCLUSIONS
  VIRsiRNApred is the first algorithm for predicting inhibition efficacy of viral siRNAs which is developed using experimentally verified viral siRNAs. We hope this algorithm would be useful in predicting highly potent viral siRNA to aid siRNA based antiviral therapeutics development. The web server is freely available at http://crdd.osdd.net/servers/virsirnapred/.
authors: Abid
authors: A
authors: Qureshi
authors: Nishant
authors: N
authors: Thakur
authors: Bioinformatics Centre, Institute of Microbial Technology, Council of Scientific and Industrial Research, Sector 39-A, Chandigarh 160036, India. manojk@imtech.res.in.
authors: Manoj
authors: M
authors: Kumar
mesh_terms: D000465:Algorithms; D030541:Databases, Genetic; D006678:HIV / Q000235:genetics / Q000302:isolation & purification*; D006518:Hepatitis Viruses / Q000235:genetics / Q000302:isolation & purification*; D006801:Humans; D020407:Internet; D009690:Nucleic Acid Conformation; D009975:Orthomyxoviridae / Q000235:genetics / Q000302:isolation & purification*; D034741:RNA, Small Interfering / Q000737:chemistry / Q000235:genetics*; D045473:Severe acute respiratory syndrome-related coronavirus / Q000235:genetics / Q000302:isolation & purification*; D013816:Thermodynamics
chemical_list: D034741:RNA, Small Interfering