We played the iPSAE game too, but we made some really cool designs we think are great but might not have high iPSAE. Search for "(Wells Wood Lab)" and give us your community vote :)

TIMED is a family of Convolutional Neural Networks (CNNs) models for protein sequence design. For this competition we used TIMED (vanilla), TIMED-Charge (charge aware), and co-TIMED (side-chain aware).

We begin by creating several backbone designs using BindCraft and SolubleMPNN. We then used TIMED models to generate probability distributions and sampled ~500K sequences total. These sequences were then scored using the E1 Large Language Model (LLM). For each backbone we picked the best scoring sequences and folded them with Boltz-2 to obtain iPSAE scores.

We treated these Boltz-2 scores as ground truth to train an ensemble of surrogate models (Ridge Regression and Random Forest). These models guided a round of in silico directed evolution, where we generated mutant pools from the top candidates, predicted their efficacy, and selected the highest-confidence, novel sequences for the final library using DE-STRESS.