Ultra-intense, ultra-fast X-ray free-electron lasers (XFELs) enable the imaging of single protein molecules under ambient temperature and pressure. A crucial aspect of structure reconstruction involves determining the relative orientations of each diffraction pattern and recovering the missing phase information. In this paper, we introduce a predicted model-aided algorithm for orientation determination and phase retrieval, which has been tested on various simulated datasets and has shown significant improvements in the success rate, accuracy and efficiency of XFEL data reconstruction.

Problems with minced pork include water release and low gel strength. This study aimed to investigate the effect of treatments with κ-carrageenan (κ-CAR), egg white powder (EWP), wheat gluten (WG), soy isolate protein (SPI), and a combination of these treatments on the gel properties and protein structures of minced pork. The cooking loss and trapped water within minced pork increased when additives were incorporated; in particular, the SPI group reached 1.31 ± 0.01% and 91.42 ± 0.20%. The hardness and chewiness of minced pork reached their maximum values (38.91 ± 0.80 N, 14.73 ± 0.41 N) when the WG was added. The κ-CAR/WG-minced pork gel network structure was the densest and most stable, characterized by increased hydrophobic interactions, disulfide bonds in the mince gel, and enthalpy value. The α-helix content with κ-CAR/WG treatment decreased from 27% to 7.8%, transforming into other secondary structures. This suggests that the addition of κ-CAR/WG can be a more effective combination for improving the quality of minced pork.

Little is known about the structures and catalytic mechanisms of sesterterpene synthases (StTSs), which greatly hinders the structure-based engineering of StTSs for structural diversity expansion of sesterterpenes. We here report on the crystal structures of the terpene cyclization (TC) domains of two fungal StTSs: sesterfisherol synthase (NfSS) and sesterbrasiliatriene synthase (PbSS). Both TC structures contain benzyltriethylammonium chloride (BTAC), pyrophosphate (PPi), and magnesium ions (Mg2+), clearly defining the catalytic active sites. A combination of theory and experiments including carbocationic intermediates modeling, site-directed mutagenesis, and isotope labeling provided detailed insights into the structural basis for their catalytic mechanisms. Structure-based engineering of NfSS and PbSS resulted in the formation of 20 sesterterpenes including 13 new compounds and four pairs of epimers with different configurations at C18. These results expand the structural diversity of sesterterpenes and provide important insights for future synthetic biology research.

Highly accurate protein structure prediction can generate accurate models of protein and protein-protein complexes in X-ray crystallography. However, the question of how to make more effective use of predicted models for completing structure analysis, and which strategies should be employed for the more challenging cases such as multi-helical structures, multimeric structures and extremely large structures, both in the model preparation and in the completion steps, remains open for discussion. In this paper, a new strategy is proposed based on the framework of direct methods and dual-space iteration, which can greatly simplify the pre-processing steps of predicted models both in normal and in challenging cases. Following this strategy, full-length models or the conservative structural domains could be used directly as the starting model, and the phase error and the model bias between the starting model and the real structure would be modified in the direct-methods-based dual-space iteration. Many challenging cases (from CASP14) have been tested for the general applicability of this constructive strategy, and almost complete models have been generated with reasonable statistics. The hybrid strategy therefore provides a meaningful scheme for X-ray structure determination using a predicted model as the starting point.

Regio- and chemoselective C-H activation at multi-positions of a single molecule is fascinating but chemically challenging. The homologous cytochrome P450 enzymes IkaD and CftA catalyze multiple C-H oxidations on the same polycyclic tetramate macrolactam (PoTeM) ikarugamycin, with distinct regio- and chemoselectivity. Herein we provide mechanistic understanding of their functional differences by solving crystal structures of IkaD and CftA in complex with ikarugamycin and unnatural substrates. Distinct conformations of the F/G region in IkaD and CftA are found to differentiate the orientation of PoTeM substrates, by causing different binding patterns with polar moieties to determine site selection, oxidation order, and chemoselectivity. Fine-tuning the polar subpocket altered the regioselectivity of IkaD, indicating that substrate re-orientation by mutating residues distal to the oxidation site could serve as an important method in future engineering of P450 enzymes.

Protein dynamics play a crucial role in their diverse functions. The intracellular environment significantly influences protein dynamics, particularly for intrinsically disordered proteins (IDPs). To comprehensively capture structural information from various proteins within cells and characterize protein dynamics, chemical cross-linking mass spectrometry was employed. In this study, we introduce a hierarchical decoding strategy that enables the investigation of protein dynamics in vivo. Computational analysis based on distance restraints derived from cross-links is used to infer protein dynamics in cells. To facilitate this analysis, we leverage the prior structure obtained from AlphaFold2. By employing this strategy, we can characterize the full-length structure of multi-domain proteins taking into account their distinct dynamic features. Furthermore, by combining restraint sampling with an unbiased sampling and evaluation approach, we can provide a comprehensive description of the intrinsic motion of IDPs. Consequently, the hierarchical strategy we propose holds significant potential in advancing our understanding of the molecular mechanisms that undelie protein functions in cells.

Metal-binding proteins are essential for the vital activities and engage in their roles by acting in concert with metal cations. MbPA (The Metal-binding Protein Atlas) is the most comprehensive resource up to now dedicated to curating metal-binding proteins. Currently, it contains 106,373 entries and 440,187 sites related to 54 metals and 8169 species. Users can view all metal-binding proteins and species-specific proteins in MbPA. There are also metal-proteomics data that quantitatively describes protein expression in different tissues and organs. By analyzing the data of the amino acid residues at the metal-binding site, it is found that about 80% of the metal ions tend to bind to cysteine, aspartic acid, glutamic acid, and histidine. Moreover, we use Diversity Measure to confirm that the diversity of metal-binding is specific in different area of periodic table, and further elucidate the binding modes of 19 transition metals on 20 amino acids. In addition, MbPA also embraces 6855 potential pathogenic mutations related to metalloprotein. The resource is freely available at http://bioinfor.imu.edu.cn/mbpa.

It is essential to understand the mechanism of action of ultrasound synergistic free radical oxidation to promote covalent reactions between proteins and polyphenols. (-)-epigallo-catechin 3-gallate (EGCG) with rich bioactivity could be used to increase the functional properties of cereal protein-gliadin (GL). This study systematically explored the role of ultrasound treatment (US) on the binding mechanisms of GL and EGCG. Electrophoresis and high-performance liquid chromatography (HPLC) confirmed the greater molecular mass of the covalent complexes in the ultrasound environment. Quantitative analysis by the phenol content revealed that the ultrasound environment increased the EGCG content in the covalent complex by 15.08 mg/g of protein. The changes in the spatial structure of the proteins were indicated by Fourier infrared and ultraviolet spectroscopy. Additionally, scanning electron microscopy (SEM) and atomic force microscopy (AFM) found that US disrupted the aggregation of GL and the clustered structure of the covalent complexes. The results demonstrated that the water solubility of ultrasonic conjugates was significantly increased by 8.8-64.19%, the digestion rate was more efficient, and the radical scavenging capacity was twice that of GL. This research contributes to the theoretical basis for broadening the application of polyphenols in modifying protein.

Chemical cross-linking mass spectrometry (CXMS) has emerged as a powerful technology to analyze protein complexes. However, the progress of in vivo CXMS studies has been limited by cross-linking biocompatibility and data analysis. Herein, a glycosidic bond-based MS-cleavable cross-linker of trehalose disuccinimidyl ester (TDS) was designed and synthesized, which was fragmented in MS under CID/HCD to simplify the cross-linked peptides into conventional single peptides via selective cleavage between glycosidic and peptide bonds under individual MS collision energy. Consequently, the cross-linking identification accuracy and throughput were significantly enhanced, and the popular MS mode of stepped HCD was allowed. In addition, TDS showed proper cell-penetrating properties while being highly water-soluble, making it non-DMSO dependent during solubilization. Collectively, TDS provides a promising toolkit for CXMS characterization of living systems with high biocompatibility and accuracy.

This paper presents a novel framework, called PSAC-PDB, for analyzing and classifying protein structures from the Protein Data Bank (PDB). PSAC-PDB first finds, analyze and identifies protein structures in PDB that are similar to a protein structure of interest using a protein structure comparison tool. Second, the amino acids (AA) sequences of identified protein structures (obtained from PDB), their aligned amino acids (AAA) and aligned secondary structure elements (ASSE) (obtained by structural alignment), and frequent AA (FAA) patterns (discovered by sequential pattern mining), are used for the reliable detection/classification of protein structures. Eleven classifiers are used and their performance is compared using six evaluation metrics. Results show that three classifiers perform well on overall, and that FAA patterns can be used to efficiently classify protein structures in place of providing the whole AA sequences, AAA or ASSE. Furthermore, better classification results are obtained using AAA of protein structures rather than AA sequences. PSAC-PDB also performed better than state-of-the-art approaches for SARS-CoV-2 genome sequences classification.