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Science Poetry

Mental Models

“Michaelis-Menten-ly,
Enzymes will catalyze.   
Key derivation from 
Briggs and Haldane:
[ES] defined with approach 
Quasi-steady-state.
Lineweaver-Burk yields a
Graphical gain.”

The 25 April 2022 poem was similar to the “aromaticity ode” from a few days prior, in that its primary aim was to compile a significant amount of information in a memorable way.  It was posted on “DNA Day,” so a biochemistry theme seemed particularly appropriate. 

The poem compiles several names and big-picture findings of several scientists who studied enzyme catalysis.    

“Michaelis-Menten-ly, /
Enzymes will catalyze.” 

Enzymes are biological catalysts, remarkable in their specificity and efficiency: they speed up reactions but are not consumed in these reactions.  Many enzyme-related reactions can be modeled via the Michaelis-Menten mechanism, a step-by-step depiction that biochemists use to understand the kinetics (rates) of enzyme-catalyzed reactions.  

In 1913, biomedical researchers Leonor Michaelis and Maud Menten proposed this important mechanism.  In these first few lines, their famous names are adapted into an adverb for use in this pseudo-double-dactyl poem.  

The mechanism can be seen at this link and rationalizes how an enzyme (abbreviated E) interacts with a substrate (abbreviated S) to ultimately yield a product (abbreviated P).        

“Key derivation from /
Briggs and Haldane:/
[ES] defined with approach / 
Quasi-steady-state…”

George Briggs and J.B.S. Haldane published their work on a subsequent investigation of Michaelis-Menten kinetics in 1925, involving an innovation regarding the enzyme-substrate complex (ES) formed as a reaction intermediate, noting that its concentration in solution (designated in the poem by the square brackets) stays relatively constant (“quasi-steady-state”).    

“Lineweaver-Burk yields a /
Graphical gain.” 

Hans Lineweaver and Dean Burk proposed a graphical analysis of the Michaelis-Menten mechanism in 1934.  This type of analysis allows efficient interpretation of some of the important rate-related data under investigation, which can be quickly ascertained via algebraic manipulation, yielding a “gain” of key kinetic parameters. 

The post title notes that all three pairs of names relate to models that are useful in understanding biochemical processes; it alludes to Maud Menten’s name, specifically, in doing so.