Expanded ensemble was also able to well capture average residue-wise mutation effects, potentially allowing for prediction of beneficial position-wise mutation sites.

We found that, although Flex-ddG was more accurate, this accuracy came from a conservative prediction tendency (predicting most mutations to be neutral). Expanded ensemble however, was better able to predict significantly stabilizing or destabilizing mutations.

Additionally, we re-ran Rosetta-based SSM using the Flex-ddG protocol.

Using Bayesian inference of the convoluted high-throughput FACS data from the publication of these designs [Chevalier, A.; Silva, D. A.; Rocklin, G. J.; Nature 2017, 550, 74–79 doi.org/10.1038/natu... ] we estimated the experimental binding affinities of all site-saturated mutants in the 3 binders.

We used the massive amount of statistics from these calculations to quantify sources of uncertainty. Our uncertainties were distributed bimodally with a mean of ~2 kcal/mol. Sources of larger uncertainties include number of alchemical atoms, charge changes, and slow DOFs.

How it feels to not be at BPS this year 😂

New preprint out from @voelzlab.bsky.social ! pylambdaopt is a method for optimizing an alchemical path from a single short trial. The method is based on equalizing the thermodynamic length between λ's and using the predicted mixing time of the transition matrix to optimize the number of λ's...🧵

#ACSSpring2024 I'm giving a talk in the Drug Design session (Hall B, Room 3) at 4:50 pm. I will be talking about how we are using massively parallel free energy simulations to do in silico site saturation mutagenesis on de novo designed miniprotein binders!