Friday, 1 April 2016

LELP metric validated

So I was wrong all along about LELP.  

I now have to concede that the LELP metric actually represents a seminal contribution to the science of drug design. Readers of this blog will recall our uncouth criticism of LELP which, to my eternal shame, I must now admit is actually the elusive, universal metric that achieves simultaneous normalization (and renormalization) of generalized interaction potential with respect to the size-scaled octanol/water partition function.

What changed my view so radically? Previously we observed that LELP treats the ADME risk associated with logP of 1 and 75 heavy atoms as equivalent to that associated with logP of 3 and 25 heavy atoms. Well it turns out that I was using the rest mass of the hydrogen atom to make this comparison which unequivocally invalidates the criticism of what turns out to be the most fundamental (and beautiful) of all the ligand efficiency metrics.

It is not intuitively obvious why relativistic correction is necessary for the correct normalization of affinity with respect to both molecular size and lipophilicity. However, I was fortunate to receive to receive a rare copy of the seminal article in the Carpathian Journal of Thermodynamics by T. T. Macoute, O. B. Ya and B. Samedi. The math is quite formidable and is based on convergence characteristics of the non-linear response to salt concentration of the Soucouyant Tensor, following application of the Douen p-Transform. B. Samedi is actually better known for his even more seminal study (with A. Bouchard) of the implications for cognitive function of the slow off-rate of tetrodotoxin in its dissociation from Duvalier's Tyrosine Kinase (DTK).

So there you have it. Ignore all false metrics and use LELP with confidence in your Sacred Quest for the Grail.  


Lewis Vidler said...

I am glad you have finally come round Peter. I blindly apply these metrics and don't even look at the structure any more as I was wasting my time. Just enumerate a library, predict activity with my QSAR model and pick the compounds with best proposed metrics for synthesis.

Peter Kenny said...

Looking at structures, Lewis, is just so last century and property-based metrics represent the key to successful drug discovery in the 21st century. I know the range of options can be overwhelming but we should all give thanks that the Sages of Stevenage have seen fit to share their seminal property forecast index (PFI) with The Great Unwashed.