Understanding epistatic networks in the B1 β-lactamases through coevolutionary statistical modeling and deep mutational scanning.

Throughout evolution, protein families undergo substantial sequence divergence while preserving structure and function. Although most mutations are deleterious, evolution can explore sequence space via epistatic networks of intramolecular interactions that alleviate the harmful mutations. However, comprehensive analysis of such epistatic networks across protein families remains limited.

Emergent time scales of epistasis in protein evolution.

We introduce a data-driven epistatic model of protein evolution, capable of generating evolutionary trajectories spanning very different time scales reaching from individual mutations to diverged homologs. Our in silico evolution encompasses random nucleotide mutations, insertions and deletions, and models selection using a fitness landscape, which is inferred via a generative probabilistic model for protein families. We show that the proposed framework accurately reproduces the sequence statistics of both short-time (experimental) and long-time (natural) protein evolution, suggesting applicability also to relatively data-poor intermediate evolutionary time scales, which are currently inaccessible to evolution experiments.

Catalytic Asymmetric Synthesis of Diketopiperazines by Intramolecular Tsuji-Trost Allylation.

We report the intramolecular Tsuji-Trost reaction of Ugi adducts to give spiro-diketopiperazines in high yield and with high enantioselectivity. This approach allows the catalytic asymmetric construction of a broad range of these medicinally important heterocycles under mild conditions, in two steps from cheap, commercially available starting materials.