Protein Science最新文献

Oculocutaneous albinism is an autosomal recessive inherited disorder associated with mutations in the TYR gene. A single missense change in the tyrosinase (Tyr) could result in partial or complete loss of catalytic activity. The effect of two genetic mutations in the same Tyr as the molecule is less studied. Here, we study single mutation variants, R217Q, R402Q, and a double mutant variant, R217Q/R402Q, to establish a link between alterations at the level of the atomic model of the protein and the disease phenotype. Human recombinant intra-melanosomal Tyr domains of Tyr and three mutant variants were expressed in T. ni. Larvae were purified using the combination of IMAC and SEC, and diphenolase activities were measured. The Tyr homology model was equilibrated using 100 ns molecular dynamics and analyzed using computational methods. The purified R217Q and R217Q/R402Q variants show decreased catalytic activities compared to those of the Tyr and R402Q variants. The R217Q/R402Q variant has the lowest protein activity and is significantly reduced.

N-Methylation of the peptide backbone confers pharmacologically beneficial characteristics to peptides that include greater membrane permeability and resistance to proteolytic degradation. The borosin family of ribosomally synthesized and post-translationally modified peptides offer a post-translational route to install amide backbone α-N-methylations. Previous work has elucidated the substrate scope and engineering potential of two examples of type I borosins, which feature autocatalytic precursors that encode N-methyltransferases that methylate their own C-termini in trans. We recently reported the first discrete N-methyltransferase and precursor peptide from Shewanella oneidensis MR-1, a minimally iterative, type IV borosin that allowed the first detailed kinetic analyses of borosin N-methyltransferases. Herein, we characterize the substrate scope and resilient regiospecificity of this discrete N-methyltransferase by comparison of relative rates and methylation patterns of over 40 precursor peptide variants along with structure analyses of nine enzyme-substrate complexes. Sequences critical to methylation are identified and demonstrated in assaying minimal peptide substrates and non-native peptide sequences for assessment of secondary structure requirements and engineering potential. This work grants understanding towards the mechanism of substrate recognition and iterative activity by discrete borosin N-methyltransferases.

Super-resolution microscopy has revolutionized biological imaging, enabling the visualization of structures at the nanometer length scale. Its application in live cells, however, has remained challenging. To address this, we adapted LIVE-PAINT, an approach we established in yeast, for application in live mammalian cells. Using the 101A/101B coiled-coil peptide pair as a peptide-based targeting system, we successfully demonstrate the super-resolution imaging of two distinct proteins in mammalian cells, one localized in the nucleus, and the second in the cytoplasm. This study highlights the versatility of LIVE-PAINT, suggesting its potential for live-cell super-resolution imaging across a range of protein targets in mammalian cells. We name the mammalian cell version of our original method mLIVE-PAINT.

Organisms from all kingdoms of life depend on Late Embryogenesis Abundant (LEA) proteins to survive desiccation. LEA proteins are divided into broad families distinguished by the presence of family-specific motif sequences. The LEA_4 family, characterized by 11-residue motifs, plays a crucial role in the desiccation tolerance of numerous species. However, the role of these motifs in the function of LEA_4 proteins is unclear, with some studies finding that they recapitulate the function of full-length LEA_4 proteins in vivo, and other studies finding the opposite result. In this study, we characterize the ability of LEA_4 motifs to protect a desiccation-sensitive enzyme, citrate synthase (CS), from loss of function during desiccation. We show here that LEA_4 motifs not only prevent the loss of function of CS during desiccation but also that they can do so more robustly via synergistically interactions with cosolutes. Our analysis further suggests that cosolutes induce synergy with LEA_4 motifs in a manner that correlates with transfer free energy. This research advances our understanding of LEA_4 proteins by demonstrating that during desiccation their motifs can protect specific clients to varying degrees and that their protective capacity is modulated by their chemical environment. Our findings extend beyond the realm of desiccation tolerance, offering insights into the interplay between IDPs and cosolutes. By investigating the function of LEA_4 motifs, we highlight broader strategies for understanding protein stability and function.

Biochemistry textbooks describe eukaryotic mRNAs as monocistronic. However, increasing evidence reveals the widespread presence and translation of upstream open reading frames preceding the "main" ORF. DNA and RNA viruses infecting eukaryotes often produce polycistronic mRNAs and viruses have evolved multiple ways of manipulating the host's translation machinery. Here, we introduce an experimental model to study gene expression regulation from virus-like bicistronic mRNAs in human cells. The model consists of a short upstream ORF and a reporter downstream ORF encoding a fluorescent protein. We have engineered synonymous variants of the upstream ORF to explore large parameter space, including codon usage preferences, mRNA folding features, and splicing propensity. We show that human translation machinery can translate the downstream ORF from bicistronic mRNAs, albeit reporter protein levels are thousand times lower than those from the upstream ORF. Furthermore, synonymous recoding of the upstream ORF exclusively during elongation significantly influences its own translation efficiency, reveals cryptic splice signals, and modulates the probability of downstream ORF translation. Our results are consistent with a leaky scanning mechanism facilitating downstream ORF translation from bicistronic mRNAs in human cells, offering new insights into the role of upstream ORFs in translation regulation.

The chemokine XC motif chemokine ligand 1 (XCL1) is an unusually specialized member of a conserved family of around 50 small, secreted proteins that are best known for their ability to stimulate the directional migration of cells. All chemokines adopt a very similar folded structure that binds a specific G protein-coupled receptor (GPCR), and most chemokines bind extracellular matrix glycosaminoglycans, often in a dimeric or oligomeric form. Owing in part to the lack of a disulfide bond that is conserved in all other chemokines, XCL1 interconverts between two distinct structures with distinct functions. One XCL1 fold resembles the structure of all other chemokines (chemokine fold), while the other does not (alternate fold). The chemokine fold of XCL1 displays high affinity for the GPCR XCR1, while the alternative fold binds GAGs and exhibits antimicrobial activity. Although the canonical role of XCL1 as a CD8+ dendritic cell chemoattractant was defined more than a decade ago, the misconception that XCL1 is a lymphocyte-specific chemoattractant still prevails in the recent literature. This review aims to highlight the structure-guided functions of XCL1 and reclarify its immunological role. In addition, the implications of this metamorphic chemokine in vaccine development and emerging functions in the nervous system will be explored.

An important step of mainstream protein structure prediction is to model the 3D protein structure based on the predicted 2D inter-residue geometric information. This folding step has been integrated into a unified neural network to allow end-to-end training in state-of-the-art methods like AlphaFold2, but is separately implemented using the Rosetta folding environment in some traditional methods like trRosetta. Despite the inferiority in prediction accuracy, the conventional approach allows for the sampling of various protein conformations compatible with the predicted geometric constraints, partially capturing the dynamic information. Here, we propose GDFold2, a novel protein folding environment, to address the limitations of Rosetta. On the one hand, GDFold2 is highly computationally efficient, capable of accomplishing multiple folding processes in parallel within the time scale of minutes for generic proteins. On the other hand, GDFold2 supports freely defined objective functions to fulfill diversified optimization requirements. Moreover, we propose a quality assessment (QA) model to provide reliable prediction on the quality of protein structures folded by GDFold2, thus substantially simplifying the selection of structural models. GDFold2 and the QA model could be combined to investigate the transition path between protein conformational states, and the online server is available at https://structpred.life.tsinghua.edu.cn/server_gdfold2.html.

We have recently demonstrated a novel anaerobic NADH-dependent haem breakdown reaction, which is carried out by a range of haemoproteins. The Yersinia enterocolitica protein, HemS, is the focus of further research presented in the current paper. Using conventional experimental methods, bioinformatics, and energy landscape theory (ELT), we provide new insight into the mechanism of the novel breakdown process. Of particular interest is the behavior of a double phenylalanine gate, which opens and closes according to the relative situations of haem and NADH within the protein pocket. This behavior suggests that the double phe-gate fulfills a regulatory role within the pocket, controlling the access of NADH to haem. Additionally, stopped-flow spectroscopy results provide kinetic comparisons between the wild-type and the selected mutants. We also present a fully resolved crystal structure for the F104AF199A HemS monomer, including its extensive loop, the first such structure to be completely resolved for HemS or any of its close homologues. The energy landscapes approach provided key information regarding the gating strategy employed by HemS, compensating for current limitations with conventional biophysical and molecular dynamics approaches. We propose that ELT become more widely used in the field, particularly in the investigation of the dynamics and interactions of weak-binding ligands, and for gating features, within protein cavities.

Protein structure holds immense potential for pathogenicity prediction, albeit structure-based predictors are limited compared to the sequence-based counterparts due to the "structure knowledge gap" between large number of available protein sequences and relatively limited number of structures. Leveraging the highly accurate protein structures predicted by AlphaFold2 (AF2), we introduce AFFIPred, an ensemble machine learning classifier that combines sequence and AF2-based structural characteristics to predict missense variant pathogenicity. Based on the assessments on unseen datasets, AFFIPred reached a comparable level of performance with the state-of-the-art predictors such as AlphaMissense. We also showed that the recruitment of AF2 structures that are full-length and represent the unbound states ensures more precise SASA calculations compared to the recruitment of experimental structures. In line with the completeness of the AF2 structures, their use provide a more comprehensive view of the structural characteristics of the missense variation datasets by capturing all variants. AFFIPred maintains high-level accuracy without the limitations of PDB-based classifiers. AFFIPred has predicted over 210 million variations of the human proteome, which are accessible at https://affipred.timucinlab.com/.

Hydrogen exchange mass spectrometry (HXMS) is a powerful tool to understand protein folding pathways and energetics. However, HXMS experiments to date have used exchange conditions termed EX1 or EX2 which limit the information that can be gained compared to the more general EXX exchange regime. If EXX behavior could be understood and analyzed, a single HXMS timecourse on an intact protein could fully map its folding landscape without requiring denaturation. To address this challenge, we developed a numerical simulation method called NumSimEX that models EXX exchange for arbitrarily complex folding pathways. NumSimEx fits protein folding dynamics to experimental HXMS data by iteratively comparing the simulated and experimental timecourses, allowing for determination of both kinetic and thermodynamic protein folding parameters. After analytically verifying NumSimEX's accuracy, we demonstrated its power on HXMS data from beta-2 microglobulin (β2M), a protein involved in dialysis-related amyloidosis. In particular, using NumSimEX, we identified three-state kinetics that near-perfectly matched experimental observation. This proof-of-principle application of NumSimEX sets the stage for harnessing HXMS to expand our understanding of proteins currently excluded from traditional protein folding methods. NumSimEX is freely available at https://github.com/JaswalLab/NumSimEX_Public.