title: Identifying representative drug resistant mutants of HIV.
abstract: BACKGROUND
  Drug resistance is one of the most important causes for failure of anti-AIDS treatment. During therapy, multiple mutations accumulate in the HIV genome, eventually rendering the drugs ineffective in blocking replication of the mutant virus. The huge number of possible mutants precludes experimental analysis to explore the molecular mechanisms of resistance and develop improved antiviral drugs.
  
  
  RESULTS
  In order to solve this problem, we have developed a new algorithm to reveal the most representative mutants from the whole drug resistant mutant database based on our newly proposed unified protein sequence and 3D structure encoding method. Mean shift clustering and multiple regression analysis were applied on genotype-resistance data for mutants of HIV protease and reverse transcriptase. This approach successfully chooses less than 100 mutants with the highest resistance to each drug out of about 10K in the whole database. When considering high level resistance to multiple drugs, the numbers reduce to one or two representative mutants.
  
  
  CONCLUSIONS
  This approach for predicting the most representative mutants for each drug has major importance for experimental verification since the results provide a small number of representative sequences, which will be amenable for in vitro testing and characterization of the expressed mutant proteins.
authors.forename: Xiaxia
authors.initials: X
authors.lastname: Yu
authors.forename: Irene T
authors.initials: IT
authors.lastname: Weber
authors.forename: Robert W
authors.initials: RW
authors.lastname: Harrison
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D024921:Drug Resistance, Multiple, Viral / Q000187:drug effects / Q000235:genetics; D024882:Drug Resistance, Viral / Q000187:drug effects / Q000235:genetics*; D015658:HIV Infections / Q000821:virology; D016333:HIV Protease / Q000235:genetics; D017320:HIV Protease Inhibitors / Q000494:pharmacology*; D015497:HIV-1 / Q000235:genetics*; D006801:Humans; D009154:Mutation / Q000235:genetics*; D012044:Regression Analysis; D018894:Reverse Transcriptase Inhibitors / Q000494:pharmacology
chemical_list: D017320:HIV Protease Inhibitors; D018894:Reverse Transcriptase Inhibitors; D016333:HIV Protease