Protein Science最新文献

Engineering thermostable proteins is advantageous for industrial and biomedical applications, where improved thermal stability can enhance conformational integrity, prolong functional half-life, and increase catalytic efficiency at elevated temperatures. We explored modifying the length of buried hydrocarbon chains to improve protein thermal stability. By optimizing the hydrophobic core through targeted amino acid substitutions, we aimed to minimize internal voids and improve core packing. To achieve this, we developed an algorithm that replaces buried hydrophobic residues with longer or bulkier hydrophobic side chains. The algorithm calculates the free energy of unfolding (ΔG) for each substitution, selecting only significantly stabilizing configurations. Functionally important residues and contact networks were excluded from mutation to preserve protein function. We applied the method to several proteins from the beta-grasp fold family. For experimental validation, we chose NEDD8, a beta-grasp protein with poor solubility and low thermal stability. Two subtle substitutions predicted by our algorithm increased NEDD8's thermal stability by 1.7 kcal/mol and raised its melting point by 17°C. MD simulations and NMR spectroscopy revealed reduced conformational fluctuations and increased stabilizing interactions, such as hydrogen bonding and electrostatic contacts. Functional assays confirmed that the substitutions did not perturb NEDD8's global fold or interactions with cofactors and enzymes. These results highlight the effectiveness of tuning buried hydrophobic residues to enhance protein stability without compromising function. This strategy could serve as a general framework for designing robust therapeutic proteins and enzymes for industrial or biomedical applications.

Accurate prediction of protein interaction sites is crucial for understanding biological processes. Many existing methods capture structural, evolutionary, and sequence features; however, they overlook important physicochemical properties, limiting their performance. We propose Prediction of protein interaction sites based on solvent accessible surface area, hydrogen-bonding propensity, and electrostatic potential sites, an enhanced model that incorporates the three physicochemical features to improve site prediction for both obligate and non-obligate complexes. Feature ablation and other analyses identified key features to improve model performance. The model achieved up to 42.8% and 29.3% improvements in Area Under the Precision-Recall Curve for Test_315 and Test_71, respectively. The model also outperforms current state-of-the-art methods across other key metrics, such as Recall, Area Under the Curve, and Matthews Correlation Coefficient.

Trimethylamine-N-oxide (TMAO) is an organic osmolyte found in numerous species and is known to have a range of biological effects. TMAO has recently garnered attention in the medical field due to its association with cardiovascular diseases, underscoring the need for its reliable detection and quantification. Current methods for TMAO analysis often rely on hazardous reagents or costly analytical instrumentation. In this study, we focus on Methylocella silvestris BL2, which produces a TMAO-demethylase (Tdm), with the aim of developing a direct enzymatic assay for TMAO detection. We report on the bioinformatic analysis, expression, purification, and calorimetric characterization of Tdm. Structural predictions generated by AlphaFold suggest that the protein, previously described as hexameric, is organized as a trimer of dimers. The 3D model reveals that the binding sites for the metal cofactors Zn²⁺ and Fe²⁺ are located in close proximity. Differential scanning calorimetry (DSC) experiments show an irreversible unfolding behavior with two independent endothermic transitions, consistent with a two-state model. Isothermal titration calorimetry (ITC) was employed in a time-resolved manner to determine the enzyme's optimal reaction pH and substrate detection limit. The assay revealed an optimal pH of 7.0, a minimum effective enzyme concentration of 100 nM, and a TMAO detection limit of 10 μM. Kinetic parameters were also precisely measured using ITC, with the highest observed k_cat value being 15.47 s^-1 at 100 nM Tdm concentration. Overall, these findings support the potential application of Tdm as a sensitive and direct tool for the detection and quantification of the medically relevant biomarker TMAO.

Bacterial one-component signaling proteins integrate sensory and gene regulation functions within the same polypeptide, creating powerful natural sensors of environmental conditions which can also be adapted into powerful tools for synthetic biology and biotechnology. A key sensor motif within many of these proteins is the Per-ARNT-Sim (PAS) domain, known for its conserved fold yet highly divergent sequences, allowing for a broad range of ligands to control PAS protein function by changes in small molecule binding occupancy or configuration. This diversity introduces a challenging step-identification of ligands for "orphan" PAS proteins which show signatures of ligand binding but no copurifying high-affinity bound small molecules-into characterization and engineering of such proteins. In this study, we characterized CU228, a putative PAS-HTH transcription factor from Candidatus Solibacter usitatus, as a novel model system for searching for novel ligands by small molecule stabilization. Bioinformatics and structural analyses predicted a PAS domain with a Trp-rich internal cavity, suggesting potential small molecule interactions. Using a ~760 compound fragment library, differential scanning fluorimetry identified three ligands (KG-96, KG-408, and KG-484) that substantially increased CU228 thermal stability with ΔT_m values up to +10°C. Microfluidic modulation spectroscopy revealed ligand-induced preservation of α-helical and β-sheet integrity under thermal stress. Saturation transfer difference NMR confirmed direct binding of all three ligands and enabled estimation of micromolar-range dissociation constants, consistent with expected fragment-level affinity. Our findings expand the analytical toolbox for probing protein-ligand interactions in flexible, signal-responsive systems, laying the groundwork for designing synthetic chemogenetic variants of one-component transcription factors.

The rapid advancement of sequencing technology has created an immense reservoir of protein sequence-function information that has yet to be fully utilized for fundamental or biocatalytic applications. For example, ene reductases from the "old yellow enzyme" (OYE) family catalyze the asymmetric hydrogenation of activated alkenes with enhanced stereoselectivity-key transformations for sustainable production of pharmaceutical and industrial synthons. Despite proven biocatalytic applications, the OYE family remains relatively underexplored: ~0.1% of identified members have been experimentally characterized. Here, integrated bioinformatics and synthetic biology techniques were employed to systematically organize and screen the natural diversity of the OYE family. Using protein similarity networks, the known and unknown regions of >115,000 members of the OYE family were broadly explored to identify phylogenetic and sequence-based trends. From this analysis, 118 diverse and novel enzymes were characterized across the family to greatly expand the biocatalytic diversity of known OYEs. In particular, widespread reverse, oxidative chemistry was discovered among OYE family members at ambient conditions. Individually, 14 potential biocatalysts were identified exhibiting enhanced catalytic activity or altered stereospecificity when compared to previously characterized OYEs. Two of these enzymes were crystallized to better understand their unique activity, revealing an unusual loop conformation within a novel OYE subclass. Overall, our study significantly expands the known functional and chemical diversity of OYEs while identifying superior biocatalysts for asymmetric hydrogenation and oxidation. This multidisciplinary strategy could be adapted to comprehensively characterize the biocatalytic potential of other enzyme families that have yet to be explored.

Uncoupling Protein 1 (UCP1) is a mitochondrial protein which drives thermogenesis in brown adipose tissue. UCP1 facilitates the dissipation of the proton gradient as heat and plays a critical role in energy expenditure and metabolic regulation. We employ advanced molecular simulations and mutagenesis to reveal the mechanism of UCP1-mediated proton and fatty acid (FA) transport. We demonstrate that FAs bind spontaneously to UCP1's central substrate-binding site. In the binding site, a proton transfer to the FA is facilitated by a key aspartate residue (D28) and a coordinating water molecule. The protonated FA exits UCP1 through a well-defined pathway, and releases its proton into the mitochondrial matrix. UCP1 then facilitates the return of deprotonated FAs to the intermembrane space. Nucleotide binding disrupts this mechanism by inducing conformational changes in the transmembrane helices and obstructing the FA return pathway. Our mechanism explains every step of the transport cycle, is supported by simulation and biochemical data, and explains a diverse set of biochemical data about the transport mechanisms in UCP1 and its analogues: ANT, UCP2, and UCP3.

The process of islet amyloid formation by the polypeptide hormone human IAPP contributes to the loss of β-cell function in type-2 diabetes. The S20G mutation in human IAPP has been linked to an increased risk of diabetes in individuals of Japanese and Chinese ancestry and leads to more rapid amyloid formation in vitro. The molecular basis of the S20G enhancement of amyloid formation was explored via experiments with genetically coded and non-coded amino acids combined with energy decomposition analysis. Ser20 was replaced by L-Ala, Gly, D-Ser, and D-Ala. All variants form amyloid more rapidly than wild type IAPP, and the largest effect is observed with the S20G mutant. The rank order of the rates to form amyloid is S20G ≥ S20D-Ala > S20A > S20D-Ser > wild type. Energy decomposition calculations were used to examine the steric consequences of replacing Ser-20 with Gly and with D and L-amino acids in existing models of IAPP amyloid fibrils. The experimental data and computational analysis indicate that the accelerated rate of amyloid formation by S20G IAPP is due to a combination of factors and cannot be ascribed to just the removal of unfavorable sidechain steric interactions in the fibril state or solely due to the need to populate conformations with a positive value of backbone dihedral angle ϕ. Constraining the backbone conformation propensities to favor positive ϕ angles appears to have the dominant effect.

Metal ions are essential for a broad range of biochemical processes in living organisms, with zinc being the second most abundant transition metal ion. Zinc has catalytic, structural, and regulatory functions in proteins, impacting virtually all aspects of cell biology. Currently, there are notable challenges in performing a large-scale accurate systematic analysis of the as-yet unexplored occurrences of zinc ion in nature. To address this, we developed ZincSight for predicting zinc-binding sites. ZincSight performs on par with existing structure-based tools in terms of the precision-recall curve for zinc ion detection, and the accuracy of spatial positioning of the ion, yet it is significantly faster, and offers a straightforward reasoning for its predictions, which is missing even in the best alternatives. Tests using a panel of metals show that, while trained on zinc-binding sites, ZincSight in fact detects all transition metal binding sites alike - a reflection of the similarity in coordination among the transition metals. It also detects binding sites for calcium and other alkaline-earth metals with lower accuracy, but not alkali metal binding sites. Suitable for exploring the usage of zinc and other transition metals in large sets of protein structures, or models thereof, ZincSight is available as a free-to-download open-source software at: https://github.com/MECHTI1/ZincSight. A Google Colab notebook is available at: https://colab.research.google.com/github/MECHTI1/ZincSight/blob/master/ZincSight.ipynb.

The chaperonin GroEL and its mitochondrial and chloroplastic homologs mHsp60 and Cpn60 are large barrel-like oligomeric proteins. Chaperonins facilitate folding by isolating nascent chains in their hollow interior and undergoing ATP-powered conformational transitions. Due to their vital importance, the structures of GroEL and its homologs were extensively studied by x-ray crystallography and CryoEM, revealing rings containing seven subunits. Each subunit has three folded domains and a 24 residue C-terminal extension. Whereas this C-terminal tail has been reported to bind and stimulate the folding of client proteins, it appears to be blurry or invisible, which suggests disorder. The objective of this study is to characterize conformational preferences in the C-terminal tails of GroEL, mHsp60 and representative Cpn60s using circular dichroism and nuclear magnetic resonance spectroscopies and molecular dynamics simulations. The tails of GroEL and mHsp60 consist of two segments. The first is rich in residues typical of intrinsically disordered proteins (PKNDAADLGA and PKEEKDPGMG in GroEL and mHsp60, respectively) and the second segment consists exclusively (GroEL) or almost entirely (mHsp60) of Gly and Met residues. The spectroscopic results reveal that these C-terminal extensions are not wholly disordered but adopt polyproline II helices whose populations are higher in the second Gly/Met-rich segment. These results are corroborated by MD simulations of GroEL₇GroES₇ complexes with ADP or ATP, or ATP and a client protein. Whereas the C-terminal segments of chloroplastic chaperonins are Gly-poor, they are rich in proline and also adopt polyproline II helix conformations. These results provide insight into the function of chaperonin C-terminal tails.