For toxicological-based structure-activity relationships to advance, will require a better understanding of molecular reactivity. A rapid and inexpensive spectrophotometric assay for determining the reactive to glutathione (GSH) was developed and used to determine GSH reactivity (reactGSH) data for 21 aliphatic derivatives of esters, ketones and aldehydes. From these data, a series of structure-activity relationships were evaluated. The structure feature associated with reactGSH was an acetylenic or olefinic moiety conjugated to a carbonyl group (i.e. polarized alpha,beta-unsaturation). This structure conveys the capacity to undergo a covalent interaction with the thiol group of cysteine (i.e. Michael- addition). Quantitatively reactGSH of the alpha,beta-unsaturated carbonyl compounds is reliant upon the specific molecular structure with several tendencies observed. Specifically, it was noted that for alpha,beta-unsaturated carbonyl compounds: (1) the acetylenic-substituted derivatives were more reactive than the corresponding olefinic-substituted ones; (2) terminal vinyl-substituted derivatives was more reactive than the internal vinylene-substituted ones; (3) methyl substitution on the vinyl carbon atoms diminishes reactivity and methyl-substitution on the carbon atom farthest from the carbonyl group causes a larger reduction; (4) derivatives with carbon-carbon double bond on the end of the molecule (i.e. vinyl ketone) were more reactive than one with the carbon-oxygen bond at the end of the molecule (i.e. aldehyde) and (5) the ester with an additional unsaturated vinyl groups were more reactive than the derivative having an unsaturated ethyl group.

We present a quantitative, population genetics based physico-chemical model which predicts the stationary probability of observing an amino acid residue based on the optimal residue for the site and the sensitivity of the protein functionality to deviation from the optimum. We contextualize our physico-chemical model by comparing it to the more general, but less biologically meaningful models of sequence entropy. To illustrate our model's use, we parameterize our model using over a 1000 different sequences of HIV subtype C's Gag poly-protein. Using data from the LANL HIV database, we evaluate our physico-chemical model's performance by first comparing its site sensitivity parameters G to the entropy based measures of site conservation and its ability to predict empirical in vitro and in vivo measures of HIV fitness. While our model's G is well correlated with conservation, G does a significantly better job predicting the empirical fitness data. More importantly, unlike the entropy model, our model can be further refined and used to test more complex biological hypotheses. For example, in our analysis we find evidence that different protein regions of the gag poly-protein have different sensitivities to deviation from the optimal amino acid residue's molecular . CC-BY-NC 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/204297 doi: bioRxiv preprint first posted online Oct. 16, 2017; volume. Finally, given its biological basis, it should be possible to extend our method to include epistasis in a more realistic manner than Ising models while requiring many fewer parameters than Potts models.