# Holistic enzyme activity determination with computation [closed]

I'm currently working on a program which will determine the activity difference between an original enzyme and a variant with just 1 or 2 variants. Of course, I'm not talking about the "kinetic activity", but some indications of a probable activity difference should be given. The system has to be sensitive enough to determine the probable activity difference between unthought-of variants.

From the information that I've got from my research, there is two option. I can use one of 3 quantitive enzyme reaction analysis tools (such as EVB, FEB and LRA) or their hybrids.

EVB => Empirical Valence Bond

FEB => Free Energy Perturbation

LRA => Linear Response Approximation

Now, my questions are: - Does these application be used for such purpose? - For an accurate prediction of enzyme activity difference, are these programs good enough or require developement? - Which one of them can give the best result? - And lastly, are QM/MM methods a must for an accurate answer?

I'm a high school student so sorry if my questions sound dumb. If you can answer my inquiry's I would appreciate it:)

Thanks

Your title says holistic. This is a tad problematic as there's layers upon layers. Say, post-translation regulation, inhibiting metabolites, interacting protein etc. That is why when talking of an enzyme inhibitor, at the biochemical level one speaks in terms of k_i (inhibition constant), while at the cellular level ("holistic") one talks of IC50.

This could be a biocatalysis/synthetic biology problem (make an enzyme better) or translational medicine problem (why is this mutation pathogenic).

In terms of in silico enzyme design, one can have all sorts of issues that need to be addressed:

• catalysis
• side reactions
• stability
• aggregation
• solubility

Also there's the expression problems, which may be due to subpar promoter, insufficient cofactors and poor codon usage.

For clinical variant assessment, a variant may:

• remove a post-translational modification
• disrupt the active site, affecting catalysis
• lose a binding partner
• result in incorrect localisation
• result in solubility issues

So force-field scores are not the sole solution. Furthermore, a forcefield method gives one a ∆∆G (difference in relative Gibbs free energy), not a K_M (Michaelis constant) and a k_cat (catalytic rate), although it is somewhat possible to calculate these, or a relative variant of these.

a variant with just 1 or 2 variants

A variant protein can have one or two mutations (e.g. G10R) in its sequence. A mutant and a variant are near synonyms, but variant is generally intended to be a mutant in a population.

Does these application be used for such purpose?

For enzyme design MD simulations are not generally the first step. Rosetta pmut_scan for example is a nice starting step as the mutational landscape of a protein is N^19, while a MD simulation takes weeks and 6+ core per single variant. This calculates only an increase in stability (relative difference in Gibbs folding energy), not reactivity. For that you can use a transition state, whose results are inaccurate, but majorly affected by the set-up, i.e. junk-in junk-out plays a big part. There's a saying 'a week in the lab saves you an hour at the library': this is backwards for sarcasm as it happens too often, namely that is background research is always a lifesaver. An QM-MD simulation on the wild type reaction definitely can help in elucidating things if it is not clear.

## Online tools

Generally, however, there are resources out there to do many stability calculations already.

SynBio If you are interested in picking a residue or two to make an enzyme more stable, without resorting to a thermophilic enzyme, PROSS is a very nice tool.

Clinical (Caveat: If your variant is a variant that affects you, a friend or a relative, you/they should speak to a genetic councillor and not do research on it yourself) There are several tools that can describe a variant at the protein level. Do remember that ∆∆G is a potential so more negative is more stable —except in SDM where the score is inverted.