Molecular ON-switches in which a chemical compound induces protein–protein interactions can allow cellular function to be controlled with small molecules. ON-switches based on clinically applicable compounds and human proteins would greatly facilitate their therapeutic use. Here, we developed an ON-switch system in which the human retinol binding protein 4 (hRBP4) of the lipocalin family interacts with engineered hRBP4 binders in a small molecule-dependent manner. Two different protein scaffolds were engineered to bind to hRBP4 when loaded with the orally available small molecule A1120. The crystal structure of an assembled ON-switch shows that the engineered binder specifically recognizes the conformational changes induced by A1120 in two loop regions of hRBP4. We demonstrate that this conformation-specific ON-switch is highly dependent on the presence of A1120, as demonstrated by an ∼500-fold increase in affinity upon addition of the small molecule drug. Furthermore, the ON-switch successfully regulated the activity of primary human CAR T cells in vitro. We anticipate that lipocalin-based ON-switches have the potential to be broadly applied for the safe pharmacological control of cellular therapeutics.

Sarcomeric proteins FATZ-1 and α-actinin-2 associate in a tight fuzzy complex, which forms phase-separated condensates.

The B-factor, also known as the atomic displacement parameter, is a fundamental metric in crystallography for quantifying the positional flexibility of atoms within crystal lattices. In structural biology, various developments have expanded the use of B-factors beyond conventional crystallographic analysis, allowing for a deeper understanding of protein flexibility, enzyme manipulation, and an improved understanding of molecular dynamics. However, the interpretation of B-factors is complicated by their sensitivity to various experimental and computational factors, necessitating rigorous rescaling methods to ensure meaningful comparisons across different structures. This article provides an in-depth description of rescaling approaches used for B-factors. It includes an examination of several methods for managing conformational disorder and selecting the atom types required for the analysis.

Pantothenate kinase-associated neurodegeneration (PKAN) is a progressive neurodegenerative disease caused by mutations in the pantothenate kinase 2 (PANK2) gene and associated with iron deposition in basal ganglia. Pantothenate kinase isoforms catalyze the first step in coenzyme A (CoA) biosynthesis. Since PANK2 is the only isoform in erythrocytes, these cells are an excellent ex vivo model to study the effect of PANK2 point mutations on expression/stability and activity of the protein as well as on the downstream molecular consequences. PKAN erythrocytes containing the T528M PANK2 mutant had residual enzyme activities but variable PANK2 abundances indicating an impaired regulation of the protein. Patients with G521R/G521R, G521R/G262R, and R264N/L275fs PANK2 mutants had no residual enzyme activity and strongly reduced PANK2 abundance. G521R inactivates the catalytic activity of the enzyme, whereas G262R and the R264N point mutations impair the switch from the inactive to the active conformation of the PANK2 dimer. Metabolites in cytosolic extracts were analyzed by gas chromatography–mass spectrometry and multivariate analytic methods revealing changes in the carboxylate metabolism of erythrocytes from PKAN patients as compared to that of the carrier and healthy control. Assuming low/absent CoA levels in PKAN erythrocytes, changes are consistent with a model of altered citrate channeling where citrate is preferentially converted to α-ketoglutarate and α-hydroxyglutarate instead of being used for de novo acetyl-CoA generation. This finding hints at the importance of carboxylate metabolism in PKAN pathology with potential links to reduced cytoplasmic acetyl-CoA levels in neurons and to aberrant brain iron regulation.

The analysis of protein-bound glycans has gained significant attention due to their pivotal roles in physiological and pathological processes like cell-cell recognition, immune response, and disease progression. Routine methods for glycan analysis are challenged by the very similar physicochemical properties of their carbohydrate components. As an alternative, lectins, which are proteins that specifically bind to glycans, have been integrated into biosensors for glycan detection. However, the effectiveness of protein-based biosensors depends heavily on the immobilization of proteins on the sensor surface. To enhance the sensitivity and/or selectivity of lectin biosensors, it is crucial to immobilize the lectin in an optimal orientation for ligand binding without compromising its function. Random immobilization methods often result in arbitrary orientation and reduced sensitivity. To address this, we explored a directed immobilization strategy relying on a reactive noncanonical amino acid (ncAA) and bioorthogonal chemistry. In this study, we site-specifically incorporated the reactive noncanonical lysine derivative, N epsilon-((2-azidoethoxy)carbonyl)-l-lysine, into a cysteine-less single-chain variant of human galectin-1 (scCSGal-1). The reactive bioorthogonal azide group allowed the directed immobilization of the lectin on a biosensor surface using strain-promoted azide-alkyne cycloaddition. Biolayer interferometry data demonstrated that the controlled, directed attachment of scCSGal-1 to the biosensor surface enhanced the binding sensitivity to glycosylated von Willebrand factor by about 12-fold compared to random immobilization. These findings emphasize the importance of controlled protein orientation in biosensor design. They also highlight the power of single site-specific genetic encoding of reactive ncAAs and bioorthogonal chemistry to improve the performance of lectin-based diagnostic tools.

Cardiomyopathies, diseases of the heart muscle, are a leading cause of heart failure. An increasing proportion of cardiomyopathies have been associated with specific genetic changes, such as mutations in FLNC , the gene that codes for filamin C. Altogether, more than 300 variants of FLNC have been identified in patients, including a number of single point mutations. However, the role of a significant number of these mutations remains unknown. Here, we conducted a comprehensive analysis, starting from clinical data that led to identification of new pathogenic and non-pathogenic FLNC variants. We selected some of these variants for further characterization that included studies of in vivo effects on the morphology of neonatal cardiomyocytes to establish links to phenotype, and the in vitro thermal stability and structure determination to understand biophysical factors impacting function. We used these findings to compile vast datasets of pathogenic and non-pathogenic variant structures and developed a machine-learning-based neural network (AMIVA-F) to predict the impact of single point mutations. AMIVA-F outperformed most commonly used predictors both in disease related as well as neutral variants, approaching ∼80% accuracy. Taken together, our study documents additional FLNC variants, their biophysical and structural properties, and their link to the disease phenotype. Furthermore, we developed a state-of-the-art web-based server AMIVA-F that can be used for accurate predictions regarding the effect of single point mutations in human filamin C, with broad implications for basic and clinical research.