Biology subjects

Leonard, A. C.

Publications and source records attributed to Leonard, A. C..

4 recordsLinked to original sources

bioRxiv2025

Computational design of dynamic biosensors for emerging synthetic opioids

Nitazenes are an emergent class of synthetic opioids that rival or exceed fentanyl in their potency. These compounds have been detected internationally in illicit drugs and are the cause of increasing numbers of hospitalizations and overdoses. New analogs are consistently released, making detection challenging - new ways of testing a wide range of nitazenes and their metabolic products are urgently needed. Here, we developed a computational protocol to redesign the plant abscisic acid receptor PYR1 to bind diverse nitazenes and maintain its dynamic transduction mechanism. The best design has a low nanomolar limit of detection in vitro against nitazene and menitazene. Deep mutational scanning yielded sensors able to recognize a range of clinically relevant nitazenes and the common metabolic byproduct in complex biological matrices with limited cross-specificity against unrelated opioids. Application of protein design tools on privileged receptors like PYR1 may yield general sensors for a wide range of applications in vitro and in vivo.

biochemistry↗

bioRxiv2024

PYR1 biosensor-driven genome-wide CRISPR screens for improved monoterpenoid production in Kluyveromyces marxianus

Monoterpenoids are valued for their roles as flavors, fragrances, insecticides, and energy-dense fuels. Microbial biosynthesis offers sustainable biosynthesis routes for these important molecules, but production levels remain limited. Here, we introduce a biosensor-driven microbial engineering strategy to enhance monoterpenoid production, specifically targeting geraniol. Using mutagenized libraries of the PYR1 receptor--a versatile biosensor from plant ABA signaling pathways with a malleable binding pocket--we screened 24 monoterpenoids and identified PYR1 variants responsive to eight, including geraniol. A low background, highly selective geraniol-sensitive PYR1 variant was expressed in the thermotolerant yeast Kluyveromyces marxianus as a growth-based biosensor circuit, allowing for rapid strain engineering. By coupling the geraniol-sensitive PYR1 sensor with a genome-wide CRISPR-Cas9 mutagenesis approach, we identified six gene knockouts that enhance geraniol production, achieving up to a 2-fold increase in titer. This study demonstrates the power of the PYR1 biosensor platform to enable rapid strain engineering and the identification of mutants that improve titer of a desired metabolite.

synthetic biology↗

bioRxiv2024

Rationalizing diverse binding mechanisms to the same protein fold: in-sights for ligand recognition and biosensor design

The engineering of novel protein-ligand binding interactions, particularly for complex drug-like molecules, is an unsolved problem which could enable many practical applications of protein biosensors. In this work, we analyzed two engineer ed biosensors, derived from the plant hormone sensor PYR1, to recognize either the agrochemical mandipropamid or the synthetic cannabinoid WIN55,212-2. Using a combination of quantitative deep mutational scanning experiments and molecular dynamics simulations, we demonstrated that mutations at common positions can promote protein-ligand shape complementarity and revealed prominent differences in the electrostatic networks needed to complement diverse ligands. MD simulations indicate that both PYR1 protein-ligand complexes bind a single conformer of their target ligand that is close to the lowest free energy conformer. Computational design using a fixed conformer and rigid body orientation led to new WIN55,212-2 sensors with nanomolar limits of detection. This work reveals mechanisms by which the versatile PYR1 biosensor scaffold can bind diverse ligands. This work also provides computational methods to sample realistic ligand conformers and rigid body alignments that simplify the computational design of biosensors for novel ligands of interest.

bioengineering↗

bioRxiv2021

Stabilization of the SARS-CoV-2 Receptor Binding Domain by Protein Core Redesign and Deep Mutational Scanning

Stabilizing antigenic proteins as vaccine immunogens or diagnostic reagents is a stringent case of protein engineering and design as the exterior surface must maintain recognition by receptor(s) and antigen--specific antibodies at multiple distinct epitopes. This is a challenge, as stability-enhancing mutations must be focused on the protein core, whereas successful computational stabilization algorithms typically select mutations at solvent-facing positions. In this study we report the stabilization of SARS-CoV-2 Wuhan Hu-1 Spike receptor binding domain (S RBD) using a combination of deep mutational scanning and computational design, including the FuncLib algorithm. Our most successful design encodes I358F, Y365W, T430I, and I513L RBD mutations, maintains recognition by the receptor ACE2 and a panel of different anti-RBD monoclonal antibodies, is between 1-2{degrees}C more thermally stable than the original RBD using a thermal shift assay, and is less proteolytically sensitive to chymotrypsin and thermolysin than the original RBD. Our approach could be applied to the computational stabilization of a wide range of proteins without requiring detailed knowledge of active sites or binding epitopes, particularly powerful for cases when there are multiple or unknown binding sites.

biochemistry↗