<!--#if expr="$title" --> <!--#echo var="title" --> <!--#else --> HIV Drug Resistance Database <!--#endif -->
Stanford University HIV Drug Resistance Database - A curated public database designed to represent, store, and analyze the divergent forms of data underlying HIV drug resistance.

MARVEL on RT mutations at position 66


HIVdb Algorithm: Comments & Scores
  • Amino acid deletions (d) between codons 66 to 71 are rare and usually occur in combination with multiple TAMs, the Q151M mutation complex, or K65R. Deletions at position 67 are more often associated with multiple TAMs. Deletions at position 69 are more often associated with either the Q151M complex or K65R.
  • Double amino acid insertions between codons 66 to 71 most often align to codon 69 and occur in less than 1% of heavily treated persons. Together with TAMs, they confer high-level resistance to AZT, d4T, ddI, ABC and TDF and intermediate/high-level resistance to 3TC and FTC.

Mutation3TCFTCABCAZTD4TDDITDF
K66del15153030303030
K66ins30304545454545
Footnote:Mutation scores on the left are derived from published literature linking mutations and ARVs (the complete details can be found in the HIVdb Release Notes).
Genotype-treatment correlation
Mutation frequency according to subtype and drug-class experience.
The frequency of each mutation at position 66 according to subtype and drug-class experience. Data are shown for the 8 most common subtypes. The number of persons in each subtype/treatment category is shown beneath the subtype. Mutations occurring at a frequency >0.5% are shown. Each mutation is also a hyper-link to a separate web page with information on each isolate, including literature references with PubMed abstracts, the GenBank accession number, and complete sequence and treatment records.

PosWTRTI Naive Persons NRTI (but no NNRTI) Treated Persons
A
3547
B
25466
C
8621
D
1320
F
723
G
1577
AE
5645
AG
2906
 
A
179
B
4133
C
461
D
127
F
82
G
146
AE
339
AG
78
66 K                 N 1.3
Footnote: The query page Mutation Prevalence According to Subtype and Treatment to examine the frequency of all mutations according to subtype and treatment; The program HIVSeq provides similar output for mutations in user-submitted sequences; A complete description of the program that generates these tables can be found at Rhee et al AIDS 2006.
 

Mutation frequency according to treatment with individual ARVs.
The first row shows the frequency of the mutation in persons who are RTI-naive (indicated in green). The second row shows the frequency of the mutation in persons who have received one or more NRTIs (+/- NNRTIs). The following rows show the frequency of the mutation in persons who have received only a single NRTI. Mutation rates that differ significantly between treated and untreated isolates are indicated in yellow.
MutationNRTINNRTINumSeqNumMut% Mutantp
K66E0048142100.00 
K66E>=1056420  
K66E>=0>=11749170.000.280
K66EAZT>=04520  
K66EDDI>=0530  
K66ED4T>=0550  
K66EABC>=0460  
K66E>=0NVP42450  
K66E>=0EFV343730.000.069
K66E>=0ETR00  
MutationNRTINNRTINumSeqNumMut% Mutantp
K66N004814280.00 
K66N>=10564210.000.629
K66N>=0>=11749170.000.144
K66NAZT>=04520  
K66NDDI>=0530  
K66ND4T>=0550  
K66NABC>=0460  
K66N>=0NVP424510.000.780
K66N>=0EFV34370  
K66N>=0ETR00  
MutationNRTINNRTINumSeqNumMut% Mutantp
K66R0048142440.00 
K66R>=10564260.100.906
K66R>=0>=117491380.200.000
K66RAZT>=04520  
K66RDDI>=0530  
K66RD4T>=0550  
K66RABC>=0460  
K66R>=0NVP424570.100.224
K66R>=0EFV343740.100.862
K66R>=0ETR00  
Footnote: About one-half of the untreated isolates belong to non-subtype B isolates; About 20% of the treated isolates belong to non-subtype B isolates; A page containing summaries for all of the mutations at this position can be found here.

Genotype-phenotype correlation
Phenotypes of top 10 common patterns of drug resistance mutations with mutations at position 66.
Mutation pattern data is not available for K66.

A complete summary of additional in vitro susceptibility data for viruses with K66 obtained using other assays including the Antivirogram can be found here.

 

Phenotypic coefficients using machine learning
Least Square Regression (LSR) was used to learn the relative contribution of each mutation to the fold decrease in susceptibility for an ARV. The figure on the left (click to enlarge the figure) shows the regression coefficients (which correlate with the contribution to resistance) for the 23 nonpolymorphic NRTI-resistance mutations shown to contribute decreased susceptibility to at least one NRTI. A complete description of the method that generates this figure can be found at Rhee et al PNAS 2006.