Marcio Pie wrote:
> This paper just came out in the Annual Review of Ecology and Systematics.
> This might answer Moorad's question a couple of weeks ago on practical
> applications of evolutionary theory.
>
I just recently read an article in Nature Structural
Biology (March 2001) related to this topic. In fact,
if you use a search engine like
http://www3.ncbi.nlm.nih.gov/entrez/query.fcgi
you will about 1380 hits related to the keywords
"drug resistance AND evolution"
By Grace we proceed,
Wayne
------------------------------------------------------
Nat Struct Biol 2001 Mar;8(3):238-42
Predicting the emergence of antibiotic resistance by
directed evolution and structural analysis.
Orencia MC, Yoon JS, Ness JE, Stemmer WP, Stevens RC.
Department of Molecular Biology, The Scripps Research
Institute, La Jolla, California 92037, USA.
Directed evolution can be a powerful tool to predict
antibiotic resistance. Resistance involves the accumulation
of mutations beneficial to the pathogen while maintaining
residue interactions and core packing that are critical for
preserving function. The constraint of maintaining stability,
while increasing activity, drastically reduces the number of
possible mutational combination pathways. To test this theory,
TEM-1 beta-lactamase was evolved using a hypermutator E.
coli-based directed evolution technique with cefotaxime selection.
The selected mutants were compared to two previous directed
evolution studies and a database of clinical isolates. In
all cases, evolution resulted in the generation of the
E104K/M182T/G238S combination of mutations ( approximately
500-fold increased resistance), which is equivalent to clinical
isolate TEM-52. The structure of TEM-52 was determined to 2.4 A.
G238S widens access to the active site by 2.8 A whereas E104K
stabilizes the reorganized topology. The M182T mutation is
located 17 A from the active site and appears to be a global
suppressor mutation that acts to stabilize the new enzyme
structure. Our results demonstrate that directed evolution
coupled with structural analysis can be used to predict future
mutations that lead to increased antibiotic resistance.
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