Context-dependent design of induced-fit enzymes using deep learning generates well-expressed, thermally stable and active enzymes.

The potential of engineered enzymes in industrial applications is often limited by their expression levels, thermal stability, and catalytic diversity. De novo enzyme design faces challenges due to the complexity of enzymatic catalysis. An alternative approach involves expanding natural enzyme capabilities for new substrates and parameters. Here, we introduce CoSaNN (Conformation Sampling using Neural Network), an enzyme design strategy using deep learning for structure prediction and sequence optimization. CoSaNN controls enzyme conformations to expand chemical space beyond simple mutagenesis. It employs a context-dependent approach for generating enzyme designs, considering non-linear relationships in sequence and structure space. We also developed SolvIT, a graph NN predicting protein solubility in Escherichia coli, optimizing enzyme expression selection from larger design sets. Using this method, we engineered enzymes with superior expression levels, with 54% expressed in E. coli, and increased thermal stability, with over 30% having higher Tm than the template, with no high-throughput screening. Our research underscores AI's transformative role in protein design, capturing high-order interactions and preserving allosteric mechanisms in extensively modified enzymes, and notably enhancing expression success rates. This method's ease of use and efficiency streamlines enzyme design, opening broad avenues for biotechnological applications and broadening field accessibility.

Dietary restriction and gonadal signaling differentially regulate post-development quality control functions in Caenorhabditis elegans.

Protein homeostasis is remodeled early in Caenorhabditis elegans adulthood, resulting in a sharp decline in folding capacity and reduced ability to cope with chronic and acute stress. Endocrine signals from the reproductive system can ameliorate this proteostatic collapse and reshape the quality control network. Given that environmental conditions, such as food availability, impact reproductive success, we asked whether conditions of dietary restriction (DR) can also reverse the decline in quality control function at the transition to adulthood, and if so, whether gonadal signaling and dietary signaling remodel the quality control network in a similar or different manner. For this, we employed the eat-2 genetic model and bacterial deprivation protocol. We found that animals under DR maintained heat shock response activation and high protein folding capacity during adulthood. However, while gonadal signaling required DAF-16, DR-associated rescue of quality control functions required the antagonistic transcription factor, PQM-1. Bioinformatic analyses supported a role for DAF-16 in acute stress responses and a role for PQM-1 in cellular maintenance and chronic stress. Comparing the stress activation and folding capacities of dietary- and gonadal-signaling mutant animals confirmed this prediction and demonstrated that each differentially impacts cellular quality control capabilities. These data suggest that the functional mode of cellular quality control networks can be differentially remodeled, affecting an organism's ability to respond to acute and chronic stresses during adulthood.

Dietary-Induced Signals That Activate the Gonadal Longevity Pathway during Development Regulate a Proteostasis Switch in Caenorhabditis elegans Adulthood.

Cell-non-autonomous signals dictate the functional state of cellular quality control systems, remodeling the ability of cells to cope with stress and maintain protein homeostasis (proteostasis). One highly regulated cell-non-autonomous switch controls proteostatic capacity in Caenorhabditis elegans adulthood. Signals from the reproductive system down-regulate cyto-protective pathways, unless countered by signals reporting on germline proliferation disruption. Here, we utilized dihomo-γ-linolenic acid (DGLA) that depletes the C. elegans germline to ask when cell-non-autonomous signals from the reproductive system determine somatic proteostasis and whether such regulation is reversible. We found that diet supplementation of DGLA resulted in the maintenance of somatic proteostasis after the onset of reproduction. DGLA-dependent proteostasis remodeling was only effective if animals were exposed to DGLA during larval development. A short exposure of 16 h during the second to fourth larval stages was sufficient and required to maintain somatic proteostasis in adulthood but not to extend lifespan. The reproductive system was required for DGLA-dependent remodeling of proteostasis in adulthood, likely via DGLA-dependent disruption of germline stem cells. However, arachidonic acid (AA), a somatic regulator of this pathway that does not require the reproductive system, presented similar regulatory timing. Finally, we showed that DGLA- and AA-supplementation led to activation of the gonadal longevity pathway but presented differential regulatory timing. Proteostasis and stress response regulators, including hsf-1 and daf-16, were only activated if exposed to DGLA and AA during development, while other gonadal longevity factors did not show this regulatory timing. We propose that C. elegans determines its proteostatic fate during development and is committed to either reproduction, and thus present restricted proteostasis, or survival, and thus present robust proteostasis. Given the critical role of proteostatic networks in the onset and progression of many aging-related diseases, such a choice could impact susceptibility to protein misfolding diseases later in life.