Biochemical and Computational Characterization of Haloalkane Dehalogenase Variants Designed by Generative AI: Accelerating the S2 Step.

Generative artificial intelligence (AI) models trained on natural protein sequences have been used to design functional enzymes. However, their ability to predict individual reaction steps in enzyme catalysis remains unclear, limiting the potential use of sequence information for enzyme engineering. In this study, we demonstrated that sequence information can predict the rate of the S2 step of a haloalkane dehalogenase using a generative maximum-entropy (MaxEnt) model.

Functional characterization of luciferase in a brittle star indicates parallel evolution influenced by genomic availability of haloalkane dehalogenase.

Determining why convergent traits use distinct versus shared genetic components is crucial for understanding how evolutionary processes generate and sustain biodiversity. However, the factors dictating the genetic underpinnings of convergent traits remain incompletely understood. Here, we use heterologous protein expression, biochemical assays, and phylogenetic analyses to confirm the origin of a luciferase gene from haloalkane dehalogenases in the brittle star .

Mechanism of BCDX2-mediated RAD51 nucleation on short ssDNA stretches and fork DNA.

Homologous recombination (HR) factors are crucial for DSB repair and processing stalled replication forks. RAD51 paralogs, including RAD51B, RAD51C, RAD51D, XRCC2 and XRCC3, have emerged as essential tumour suppressors, forming two subcomplexes, BCDX2 and CX3. Mutations in these genes are associated with cancer susceptibility and Fanconi anaemia, yet their biochemical activities remain unclear.

A closed 3D printed microfluidic device for automated growth and differentiation of cerebral organoids from single-cell suspension.

The development of 3D organoids has provided a valuable tool for studying human tissue and organ development in vitro. Cerebral organoids, in particular, offer a unique platform for investigating neural diseases. However, current methods for generating cerebral organoids suffer from limitations such as labor-intensive protocols and high heterogeneity among organoids.

Azobenzene-Based Photoswitchable Substrates for Advanced Mechanistic Studies of Model Haloalkane Dehalogenase Enzyme Family.

The engineering of efficient enzymes for large-scale production of industrially relevant compounds is a challenging task. Utilizing rational protein design, which relies on a comprehensive understanding of mechanistic information, holds significant promise for achieving success in this endeavor. Pre-steady-state kinetic measurements, obtained either through fast-mixing techniques or photoswitchable substrates, provide crucial mechanistic insights.