Transcript How Does Antiretroviral Therapy Affect HIV Mutation and

How Does Antiretroviral Therapy
Affect HIV Mutation and Vice
Versa?
Arlin Toro
Devin Iimoto
Purpose
To use a case or scenario to motivate
student learning about topics in
biology and biochemistry courses
Courses For Which This is an
Appropriate Module
Lower level biology courses such as
Introduction to Biology or a Basic
Cell Biology course
Upper level biology courses such as
Biochemistry, Molecular Biology,
Microbiology, or Virology
The Case
Undergraduate students are
shadowing a physician working with
HIV infected patients
Physician decides to determine the
amino acid and nucleotide sequences
in HIV-1 protease and reverse
transcriptase before prescribing
medication
Database for Exercise
The HIV Reverse Transcriptase and
Protease Sequence Database
Case study used from the database
Cabana, Clotet, and Martinez.
Emergence and genetic evolution of
HIV-1 variants with mutations
conferring resistance to multiple
reverse transcriptase and protease
inhibitors. J. Med. Virol. 59: 480490 (1999).
Topics for Student Learning
DNA and protein: structure and
function
Enzymes
Evolution
Bioinformatics
AIDS – HIV structure and replication
and treatments
Learning Process
Students will be asked the following
– What do you already know about
antiretroviral therapy and HIV mutation?
– What questions do you have?
– What do you need to know to
understand how antiretroviral therapy
and HIV are linked together?
Background Information – All
course levels
General AIDS
information
HIV structure
HIV replication
Immune system
function
Topics For Lower Division Courses
DNA replication
Types of mutations
Impacts of those mutations
Epidemiology
Amino acids nomenclature and
structure
Dendogram interpretation
Biology workbench
– Clustal W
Exercises for Lower Division
Courses
Questions
Are the sequences different?
What mutations occurred?
How many nucleotides or regions have changed?
In mutated regions of the protein/gene, which
sequences changed most?
Which patient had the greatest number of mutations in
the protein/nucleotide sequences over time? What did
you observe about the mutation rate in the patient?
From what you have learned from your evolution class,
how does this evolution rate compare to most
organisms?
How many amino acids are different in
each sequence?
Select a region where you can see a
change. Compare the structure of the
most frequently mutated amino acid
before and after mutation.
Based on the side chains of the amino
acids, could the substitution lead to a
different protein structure? Check on the
other amino acids substitutions to address
this question.
Do you think the mutations in the virus
infecting patient “a” are enough to enable
viral resistance to the drug that targets
the viral protease.
Topics for Upper Division Courses
Michaelis-Menten
kinetics
Michaelis-Menten
inhibitors
Enzyme
Mechanism
HIV-1 protease
structure and
function
Bioinformatics Exercise for Upper
Division Courses
Questions
- Is there greater amino acid sequence
variation in HIV-1 protease between
patients or between time visits for an
individual patient?
- What amino acids are more likely to
mutate, and what type of amino acids do
they mutate to? What does this tell you
about viral mutation and drug resistance?
- In which protein domains do these
mutations cluster? What does that
tell you about viral mutation and
drug resistance?
- What are some possible structural
impacts of these mutations?
- How much uncertainty is there in
predicting protein secondary
structure from primary structure?
 Cab-b_1990-05
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....:....x....:....x....:....x....:....x....:....x....:....x
PQITLWQRPLVTIRIGGQLKEALLDTGADDTVLEDMDLPGRWKPKMIGGIGRFIKVRQYD
CCCCCCCEEEEEEEEECCCCCCCCCCCCCCCHHHHCCCCCCCCCCCCCCCCCCCCEHHEC
CCEEEEHHCEEEEEECCCHHHHHHCCCCCCEEHHHHCCCCCCCCCHECCECEEEEEEHEC
CCCCCCCCCEEEEEECCCHHHHHHCCCCCHHHHHHCCCCCCCEEEEECCCCCCEEECCCC
CCCCCCCCCEEEEEECCHHHHHHHHCCCCCEEEECCCCCCCCCCCCEEECCEEEEECCCC
CHHEEHHCCEEEEEHCCCCHHHHHHHCCCCHHHHHHHCCCCCCCCCCCCCEEEEEECCCC
CCCEEECCCCCCEECCCCCHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHCCC
CCCCCCCCCCHHHHHHHHHHCCCCCCHHHHHHHHHCCCCCCHHHHHHHHHHHHHHHHCCC
CCCCCCCCCEEEEEECCCHHHHHHCCCCCCCHHHHCCCCCCCCCCCCCCCCCCEEECCCC
Cab-b_1990-05
BPS
D_R
DSC
GGR
GOR
H_K
K_S
JOI
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....:....x....:....x....:....x....:....x....:....x....:....x
QIPIEICGHKAIGTVLVGPTPINIIGRNLLTQIGCTLNF
CCCCCCCCCCCEEEEECEEEECCCEEEECCEEEEECCCC
CECEEEECCCHEEEEEECCCCEEEECECHEEEEEEEECC
CCEEEEECCCCCEEEEECCCCCEEECCCCCCCCCCCCCC
EECEEECCCCCCEEEECCCCCCEEECCEEEEEECCEEEC
CCCHEEECCCCCEEEEECCCCCEEEECEEEECEEEEECC
CCCCCCCCCCCCEEEECCCCCCCEECCCCCCCCCCCCCC
CHHHHHHHHHHHHHHHHHCCCCHHHHHHHHHHHHHCCCC
CCCCEECCCCCCEEEECCCCCCEEECCCCCECECCCCCC
Cab-b_1990-05
BPS
D_R
DSC
GGR
GOR
H_K
K_S
JOI
Future directions
EVOLVE
– Model the mutation rate
STELLA
– Enzyme kinetics
– HIV Prevalence rates
EPIDEMIOLOGY
– Predictions on spread of HIV
Biology Workbench Programs
– TACG
– Six Frame
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