Cysteines in ß-lactoglobulin affects its interfacial adsorption and protein film stabilization.

HYPOTHESIS: Disulfide bonds in proteins are strong chemical bonds forming the secondary and tertiary structure like in the dairy protein ß-lactoglobulin. We hypothesize that the partial or complete removal of disulfide bonds affects the structural rearrangement of proteins caused by intra- and intermolecular interactions that in turn define the interfacial activity of proteins at oil/water interfaces. The experimental and numerical investigations contribute to the mechanistic understanding of the structure-function relationship, especially for the interfacial adsorption behavior of proteins. EXPERIMENTAL AND NUMERICAL: Systematically, the 5 cysteines of ß-lactoglobulin were recombinantly exchanged by alanine. First, the protein structure of the variants in bulk was analyzed with Fourier-transform-infrared-spectroscopy and molecular dynamic simulations. Second, the structural changes after adsorption to the interface have been also analyzed by molecular dynamic simulations. The adsorption behavior was investigated by pendant drop analysis and the interfacial film properties by dilatational rheology. FINDINGS: The structural flexibility of ß-lactoglobulin with no cysteines encourages its unfolding at the interface, and accelerates the interfacial protein film formation that results in more visco-elastic films in comparison to the reference.

Predicting protein interactions of the kinase Lck critical to T cell modulation.

Protein-protein interactions (PPIs) play pivotal roles in directing T cell fate. One key player is the non-receptor tyrosine protein kinase Lck that helps to transduce T cell activation signals. Lck is mediated by other proteins via interactions that are inadequately understood. Here, we use the deep learning method AF2Complex to predict PPIs involving Lck, by screening it against ∼1,000 proteins implicated in immune responses, followed by extensive structural modeling for selected interactions. Remarkably, we describe how Lck may be specifically targeted by a palmitoyltransferase using a phosphotyrosine motif. We uncover "hotspot" interactions between Lck and the tyrosine phosphatase CD45, leading to a significant conformational shift of Lck for activation. Lastly, we present intriguing interactions between the phosphotyrosine-binding domain of Lck and the cytoplasmic tail of the immune checkpoint LAG3 and propose a molecular mechanism for its inhibitory role. Together, this multifaceted study provides valuable insights into T cell regulation and signaling.

Evaluation of AlphaFold3 for the fatty acids docking to human fatty acid-binding proteins.

Human fatty acid-binding proteins (FABPs) are involved in many aspects of lipid metabolism, such as the uptake, transport, and storage of lipophilic molecules, as well as cellular functions. Understanding how FABPs recognize fatty acids (FAs) is crucial for identifying FABP function and applications, such as in inhibitor design or biomarker development. The recently developed AlphaFold3 (AF3) demonstrates significantly higher accuracy than other prediction tools, particularly in predicting protein-ligand interactions with state-of-the-art docking tools. Studies on whether AF3 can be used to identify the FAs of FABP are lacking. To assess the accuracy of FA docking to FABPs using AF3, models of FA docked into FABP generated using AF3 were compared with experimentally determined FA-bound FABP structures. FA ligands in AF3 structures docked reliably into the FA-binding pocket of FABPs; however, the detailed binding configuration of most FA ligands docked into FABPs and the interaction between FA and FABP determined using AF3 and experimentally differed. These results will aid in understanding FA docking to FABPs and other FA-binding proteins using AF3.

Macromolecular crowding effects on protein dynamics.

Macromolecular crowding experiments bridge the gap between in-vivo and in-vitro studies by mimicking some of the cellular complexities like high viscosity and limited space, while still manageable for experiments and analysis. Macromolecular crowding impacts all biological processes and is a focus of contemporary research. Recent reviews have highlighted the effect of crowding on various protein properties. One of the essential characteristics of protein is its dynamic nature; however, how protein dynamics get modulated in the crowded milieu has been largely ignored. This article discusses how protein translational, rotational, conformational, and solvation dynamics change under crowded conditions, summarizing key observations in the literature. We emphasize our research on microsecond conformational and water dynamics in crowded milieus and their impact on enzymatic activity and stability. Lastly, we provided our outlook on how this field might move forward in the future.

Domain swapping: a mathematical model for quantitative assessment of structural effects.

The domain-swapping mechanism involves the exchange of structural elements within a secondary or supersecondary structure between two (or more) proteins. The present paper proposes to interpret the domain-swapping mechanism using a model that assesses the structure of proteins (and complexes) based on building the structure of a common hydrophobic core in a micelle-like arrangement (a central hydrophobic core with a polar shell in contact with polar water), which has a considerable impact on the stabilisation of the domain structure built by domain swapping. Domains with a hydrophobicity system that is incompatible with the micelle-like structure have also been identified. This incompatibility is the form of structural codes related to biological function.

PDFll: Predictors of Disorder and Function of Proteins from the Language of Life.

The identification of intrinsically disordered proteins and their functional roles is largely dependent on the performance of computational predictors, necessitating a high standard of accuracy in these tools. In this context, we introduce a novel series of computational predictors, termed PDFll (Predictors of Disorder and Function of proteins from the Language of Life), which are designed to offer precise predictions of protein disorder and associated functional roles based on protein sequences. PDFll is developed through a two-step process. Initially, it leverages large-scale protein language models (pLMs), trained on an extensive dataset comprising billions of protein sequences. Subsequently, the embeddings derived from pLMs are integrated into streamlined, yet sophisticated, deep-learning models to generate predictions. These predictions notably surpass the performance of existing state-of-the-art predictors, particularly those that forecast disorder and function without utilizing evolutionary information.

AARS Online: A collaborative database on the structure, function, and evolution of the aminoacyl-tRNA synthetases.

The aminoacyl-tRNA synthetases (aaRS) are a large group of enzymes that implement the genetic code in all known biological systems. They attach amino acids to their cognate tRNAs, moonlight in various translational and non-translational activities beyond aminoacylation, and are linked to many genetic disorders. The aaRS have a subtle ontology characterized by structural and functional idiosyncrasies that vary from organism to organism, and protein to protein. Across the tree of life, the 22 coded amino acids are handled by 16 evolutionary families of Class I aaRS and 21 families of Class II aaRS. We introduce AARS Online, an interactive Wikipedia-like tool curated by an international consortium of field experts. This platform systematizes existing knowledge about the aaRS by showcasing a taxonomically diverse selection of aaRS sequences and structures. Through its graphical user interface, AARS Online facilitates a seamless exploration between protein sequence and structure, providing a friendly introduction to the material for non-experts and a useful resource for experts. Curated multiple sequence alignments can be extracted for downstream analyses. Accessible at www.aars.online, AARS Online is a free resource to delve into the world of the aaRS.

Teaching protein structure and function through molecular visualization.

The function of proteins is governed by their three-dimensional structure. This structure is determined by the chemical characteristics and atomic interactions of amino acids. Students of biochemistry, with a particular focus on protein chemistry, benefit from looking at protein structures and understanding how proteins are built and fold. Due to their three-dimensional nature, static two-dimensional representations in textbooks can be limiting to student learning. Here, we developed a series of tutorials that introduce students to molecular graphics software. The students are challenged to apply the software to look at proteins and to get a deeper understanding of how amino acid properties are linked to structure. We also familiarize students with some of the latest tools in computational structural biology. Students performed the tutorials with visual enthusiasm and reported general satisfaction in being able to visualize theoretical concepts learned during lectures. We further stimulated student engagement by allowing space for self-exploration. We share the tutorial instructions for other teachers to build on them, and we also offer suggestions for further improvement based on student feedback. In summary, we present a series of tutorials aimed at students of an advanced course in protein biochemistry to enable them to explore the universe of protein structures and how those relate to function.

Exploration of SOD3 from gene to therapeutic prospects: a brief review.

Superoxide dismutase 3 (SOD3) is a type of antioxidant enzyme, which plays an important role in converting superoxide anion into hydrogen peroxide through its extracellular activity. This enzyme has been widely studied and evaluated from various points of view, including maintaining cellular redox balance, protecting against oxidative damage, and enhancing overall cellular resilience. The current paper focuses on SOD3 expression from a functional perspective. In addition to a detailed examination of the gene and protein structure, we found ample evidence indicating that the expression level of SOD3 undergoes alterations in response to various transcription factors, signaling pathways, and diverse conditions. These fluctuations, by disrupting the homeostasis of SOD3, can serve as crucial indicators of the onset or exacerbation of specific diseases. In this regard, significant efforts have been dedicated in recent years to the treatment of diseases through the regulation of SOD3 expression. The ultimate goal of this review is to extensively highlight and demonstrate the immense potential of SOD3 as a therapeutic target, emphasizing its profound impact on health outcomes.

Ultrasound as Green Technology for the Valorization of Pumpkin Leaves: Intensification of Protein Recovery.

The recovery of valuable nutritional compounds, like proteins, from waste streams and by-products is a key strategy for enhancing production sustainability and opening up new market potential. This research aimed to use high-intensity ultrasound as an innovative technique to extract the soluble proteins from the pumpkin leaves. The impact of various sonication amplitudes and duration periods on protein yield, functional properties, antioxidant qualities, and structural characteristics, were studied. Utilization of ultrasound technology significantly increased the yield of pumpkin leaf protein by up to 40%-six times higher than maceration. The ultrasound extraction provided a RuBisCO-rich protein fraction with high radical scavenging and chelating activities, especially at 40% amplitude. Cavitation modified the tertiary and secondary structures of leaf proteins: the amount of α-helix changed based on amplitude (12.3-37.7%), the amount of random coil increased to 20.4%, and the amount of ß-turn reduced from 31 to 18.6%. The alteration of the protein fluorescence spectrum (blue shift in spectrum) provides further evidence that ultrasound alters the proteins' molecular structure in comparation with maceration; the maximum tryptophan fluorescence intensity decreased from 22.000 to 17.096. The hydrophobicity values of 76.8-101.5 were substantially higher than the maceration value of 53.4, indicating that ultrasound improved the hydrophobicity of protein surfaces. Ultrasound resulted in a significant increase in solubility in an acidic environment with the increase in sonication amplitude. A 2.4-fold increase in solubility at pH 2 becomes apparent (20% amplitude; 43.1%) versus maceration (18.2%). The emulsifying ability decreases from 6.62 to 5.13 m2/g once the sonication amplitude increases by 20-70%. By combining the ultrasound periods and amplitudes, it is possible to create high-value protein leaf extracts with improved properties which can find real application as food additives and dietary supplements.

ModFOLD9: A Web Server for Independent Estimates of 3D Protein Model Quality.

Accurate models of protein tertiary structures are now available from numerous advanced prediction methods, although the accuracy of each method often varies depending on the specific protein target. Additionally, many models may still contain significant local errors. Therefore, reliable, independent model quality estimates are essential both for identifying errors and selecting the very best models for further biological investigations. ModFOLD9 is a leading independent server for detecting the local errors in models produced by any method, and it can accurately discriminate between high-quality models from multiple alternative approaches. ModFOLD9 incorporates several new scores from deep learning-based approaches, leading to greatly improved prediction accuracy compared with earlier versions of the server. ModFOLD9 is continuously independently benchmarked, and it is shown to be highly competitive with other public servers. ModFOLD9 is freely available at https://www.reading.ac.uk/bioinf/ModFOLD/.

Assessing the role of evolutionary information for enhancing protein language model embeddings.

Embeddings from protein Language Models (pLMs) are replacing evolutionary information from multiple sequence alignments (MSAs) as the most successful input for protein prediction. Is this because embeddings capture evolutionary information? We tested various approaches to explicitly incorporate evolutionary information into embeddings on various protein prediction tasks. While older pLMs (SeqVec, ProtBert) significantly improved through MSAs, the more recent pLM ProtT5 did not benefit. For most tasks, pLM-based outperformed MSA-based methods, and the combination of both even decreased performance for some (intrinsic disorder). We highlight the effectiveness of pLM-based methods and find limited benefits from integrating MSAs.

The polymorphism analysis and therapy vaccine target epitopes screening of HPV-35 E6 E7 among the threaten α-9 HPV in Sichuan area.

High-risk human papilloma virus (HR-HPV) persistent infection is closely associated with the development of cervical cancer and squamous intraepithelial lesion (SIL).The α-9 HPVs, which is predominantly composed of HR-HPV types, account for 75% of HR-HPV infection in Sichuan. The oncoproteins E6 and E7 of HPV play a crucial role in tumor initiation and progression. Notably, HPV-35 is the only HR-HPV type within the α-9 genus that is not included in the nine-valent HPV prophylactic vaccine. Cervical cell samples obtained from Sichuan were collected for HPV detection and genotyping. Among the 406 HPV-positive samples, 31 HPV-35 were detected, 24 HPV-35 E6 and 26 E7 were successfully amplified and sequenced, five nucleotide mutations in E6 and three in E7 were detected, T232C, T434G of E6 (W78R, I145R) and C67T, G84T of E7 (H23Y, L28F) were non-synonymy mutation. PAML 4.8 server was used to detect positive selection sites of HPV-35 E6, E7, and E6 is W78R. Phyre2 were used to predict and analyze protein structures, W78R made influences on protein structure. IEDB were used to screen epitopes vaccine target for HPV-35 affection therapy, and 5 HPV-35 E6 and 3 HPV-35 E7 most potential epitopes were obtained, the most potential peptides for therapy vaccine design were 79-91YRYSVYGETLEKQ, 45-60FACYDLCIVREGQPY, 124-135RFHNIGGRWTGR of E6; 3-19GEITTLQDYVLDLEPEA, 38-47TIDGPAGQAK, 70-88VQSTHIDIRKLEDLLMGTF of E7 and W78R mainly decreased the epitopes affinity.Conclusions Amino acid substitution in the positive selection sites of HPV-35 E6 and E7 genes have been found to influence protein structure and to decrease the overall affinity of antigen epitopes. This observation aligns with the evolutionary significance of positive selection site, which may confer advantages to the virus by making infected cells more challenging for the immune system to detect, thereby enhancing HPV's adaptability to the host environment. The polymorphism analysis of HPV-35 E6, E7 contributes to the enrichment of α-9 HPV data in Sichuan China, which is instrumental in improving the effectiveness of clinical detection. Furthermore, these findings provide a relevant theoretical foundation for the prevention and treatment of HPV-related diseases.

StrIDR: a database of intrinsically disordered regions of proteins with experimentally resolved structures.

Motivation: Intrinsically disordered regions (IDRs) of proteins exist as an ensemble of conformations, and not as a single structure. Existing databases contain extensive, experimentally derived annotations of intrinsic disorder for millions of proteins at the sequence level. However, only a tiny fraction of these IDRs are associated with an experimentally determined protein structure. Moreover, even if a structure exists, parts of the disordered regions may still be unresolved. Results: Here we organize Structures of Intrinsically Disordered Regions (StrIDR), a database of IDRs confirmed via experimental or homology-based evidence, resolved in experimentally determined structures. The database can provide useful insights into the dynamics, folding, and interactions of IDRs. It can also facilitate computational studies on IDRs, such as those using molecular dynamics simulations and/or machine learning. Availability: StrIDR is available at https://isblab.ncbs.res.in/stridr. The web UI allows for downloading PDB structures and SIFTS mappings of individual entries. Additionally, the entire database can be downloaded in a JSON format. The source code for creating and updating the database is available at https://github.com/isblab/stridr.

Key Factors Influencing Gelation in Plant vs. Animal Proteins: A Comparative Mini-Review.

This review presents a comparative analysis of gelation properties in plant-based versus animal-based proteins, emphasizing key factors such as pH, ionic environment, temperature, and anti-nutritional factors. Gelation, a crucial process in food texture formation, is influenced by these factors in varying ways for plant and animal proteins. Animal proteins, like casein, whey, meat, and egg, generally show stable gelation properties, responding predictably to pH, temperature, and ionic changes. In contrast, plant proteins such as soy, pea, wheat, and oilseed show more variable gelation, often requiring specific conditions, like the presence of NaCl or optimal pH, to form effective gels. Animal proteins tend to gel more reliably, while plant proteins require precise environmental adjustments for similar results. Understanding these factors is crucial for selecting and processing proteins to achieve desired textures and functionalities in food products. This review highlights how changing these key factors can optimize gel properties in both plant- and animal-based proteins.

A glance at structural biology in advancing rice blast fungus research.

The filamentous fungus Magnaporthe oryzae is widely recognized as a notorious plant pathogen responsible for causing rice blasts. With rapid advancements in molecular biology technologies, numerous regulatory mechanisms have been thoroughly investigated. However, most recent studies have predominantly focused on infection-related pathways or host defence mechanisms, which may be insufficient for developing novel structure-based prevention strategies. A substantial body of literature has utilized cryo-electron microscopy and X-ray diffraction to explore the relationships between functional components, shedding light on the identification of potential drug targets. Owing to the complexity of protein extraction and stochastic nature of crystallization, obtaining high-quality structures remains a significant challenge for the scientific community. Emerging computational tools such as AlphaFold for structural prediction, docking for interaction analysis, and molecular dynamics simulations to replicate in vivo conditions provide novel avenues for overcoming these challenges. In this review, we aim to consolidate the structural biological advancements in M. oryzae, drawing upon mature experimental experiences from other species such as Saccharomyces cerevisiae and mammals. We aim to explore the potential of protein construction to address the invasion and proliferation of M. oryzae, with the goal of identifying new drug targets and designing small-molecule compounds to manage this disease.

[Molecular characteristics of Japanese encephalitis virus carried by Culex tritaeniorhynchus in Dongchuan District, Kunming City, Yunnan Province].

OBJECTIVE: To isolate the Japanese encephalitis virus carried by Culex tritaeniorhynchus in Dongchuan District of Yunnan Province and analyze its molecular characteristics, so as to provide insights into the prevention and control of Japanese encephalitis in Yunnan Province. METHODS: Mosquito specimens were collected using mosquito-trapping lamps from pig farms in Batang Village and Xiaoxin Village, Dongchuan District, Kunming City, Yunnan Province in July 2016, and the mosquito species was identified according to the mosquito morphology. Then, 60 to 100 mosquitoes of each species served as a group and were ground. Baby hamster kidney-21 (BHK-21) cells and Aedes albopictus clone C6/36 cells were used for virus isolation, and positive isolates were identified using flavivirus primers. The positive isolates were amplified using reverse transcription polymerase chain reaction (RT-PCR) assay with 15 pairs of specific primers covering the full length of the genotype I Japanese encephalitis virus, and DNA sequence assembly was performed using the software SeqMan in the DNASTAR package. The obtained sequences were aligned with the complete sequences of 38 Japanese encephalitis virus downloaded from the GenBank with the software MegAlign, and the nucleotide and amino acid homology analyses of the obtained sequences were performed. The difference in amino acid sites was analyzed with the software GeneDoc, and phylogenetic trees were created based on the sequences of the coding region and E protein of the isolated Japanese encephalitis virus with the software Mega X. In addition, the secondary and tertiary structures of the E protein of the Japanese encephalitis virus were predicted using the online tool SOPMA and the software Swiss-Model. RESULTS: A total of 5 820 mosquitoes were collected and 3 843 Cx. tritaeniorhynchus (66.03%) were identified according to the mosquito morphology. A positive virus isolate, termed YNDC55-33, was isolated from Cx. tritaeniorhynchoides following batches of virus isolation from mosquito specimens, and cytopathic effect was observed following inoculation into BHK-21 and C6/36 cells. The YNDC55-33 virus isolate was successfully amplified with the flavivirus primes, and a long sequence containing 300 nucleotides was obtained. Following sequence alignment using the BLAST tool, the sequence of the YNDC55-33 virus isolate had high homology with that of the genotype I Japanese encephalitis virus. A long sequence with 10 845 nucleotides in length, which encoded 3 432 amino acids, was obtained by splicing the full sequence of the YNDC55-33 virus isolate. Phylogenetic analysis based on the whole-genome sequence and E gene sequence of the YNDC55-33 virus isolate showed that the new YNDC55-33 virus isolate was most closely related to the genotype I Guizhou isolate (GenBank accession number: HM366552), with nucleotide homology of 98.5% and amino acid homology of 99.4%, and the YNDC55-33 virus isolate shared 97.96% ± 0.33% nucleotide homology and 99.35% ± 0.08% amino acid homology with other genotype I Japanese encephalitis virus isolates, and < 90% nucleotide homology and < 98% amino acid homology with other genotypes of Japanese encephalitis virus. The YNDC55-33 virus isolate and the live attenuated virus vaccine candidate SA14-14-2 isolate differed at 16 amino acid sites on E gene, and 7 out of 8 key amino acid sites related to neurovirulence. The secondary and tertiary structures of the E protein of the YNDC55-33 virus isolate were predicted to be characterized by random coils. CONCLUSIONS: A genotype I Japanese encephalitis virus was isolated from Cx. tritaeniorhynchus in Dongchuan District, Kunming City. This virus isolate and the live attenuated virus vaccine candidate SA14-14-2 isolate does not differ at antigenic epitopes-related key amino acid sites, and the major protein structure of the virus isolate is random coils. This study adds new data for the epidemiological distribution of Japanese encephalitis virus in Yunnan Province, which may provide insights into the prevention and control of Japanese encephalitis in the province.

Protein Structure Inspired Discovery of a Novel Inducer of Anoikis in Human Melanoma.

Drug discovery historically starts with an established function, either that of compounds or proteins. This can hamper discovery of novel therapeutics. As structure determines function, we hypothesized that unique 3D protein structures constitute primary data that can inform novel discovery. Using a computationally intensive physics-based analytical platform operating at supercomputing speeds, we probed a high-resolution protein X-ray crystallographic library developed by us. For each of the eight identified novel 3D structures, we analyzed binding of sixty million compounds. Top-ranking compounds were acquired and screened for efficacy against breast, prostate, colon, or lung cancer, and for toxicity on normal human bone marrow stem cells, both using eight-day colony formation assays. Effective and non-toxic compounds segregated to two pockets. One compound, Dxr2-017, exhibited selective anti-melanoma activity in the NCI-60 cell line screen. In eight-day assays, Dxr2-017 had an IC50 of 12 nM against melanoma cells, while concentrations over 2100-fold higher had minimal stem cell toxicity. Dxr2-017 induced anoikis, a unique form of programmed cell death in need of targeted therapeutics. Our findings demonstrate proof-of-concept that protein structures represent high-value primary data to support the discovery of novel acting therapeutics. This approach is widely applicable.

Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking.

MOTIVATION: Antibody-antigen complex modelling is an important step in computational workflows for therapeutic antibody design. While experimentally determined structures of both antibody and the cognate antigen are often not available, recent advances in machine learning-driven protein modelling have enabled accurate prediction of both antibody and antigen structures. Here, we analyse the ability of protein-protein docking tools to use machine learning generated input structures for information-driven docking. RESULTS: In an information-driven scenario, we find that HADDOCK can generate accurate models of antibody-antigen complexes using an ensemble of antibody structures generated by machine learning tools and AlphaFold2 predicted antigen structures. Targeted docking using knowledge of the complementary determining regions on the antibody and some information about the targeted epitope allows the generation of high quality models of the complex with reduced sampling, resulting in a computationally cheap protocol that outperforms the ZDOCK baseline. AVAILABILITY: The source code of HADDOCK3 is freely available at github.com/haddocking/haddock3. The code to generate and analyse the data is available at github.com/haddocking/ai-antibodies. The full runs, including docking models from all modules of a workflow have been deposited in our lab collection (data.sbgrid.org/labs/32/1139) at the SBGRID data repository. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Effect of ultrasonic pretreatment on the emulsion rheological properties and interface protein structure of epigallocatechin-3-gallate and rice bran protein complex.

The effect of ultrasonic pretreatment on the emulsion rheological properties and the structural characteristics of interface-adsorbed protein (IAP) and interface-unabsorbed protein (IUP) of rice bran protein and epigallocatechin-3-gallate complex (RBP-EGCG) were studied. Compared to RBP-EGCG without ultrasonic pretreatment, appropriate ultrasonic pretreatment (ultrasonic power was 425 W) enhanced the IAP trypsin sensitivity (from 3.20 to 3.73), increased the IUP surface hydrophobicity (from 12.59 to 20.87), and decreased the ζ-potential (from -24.93 mV to -36.88 mV) and particle size (from 567.30 nm to 273.13 nm) of IUP, thereby increasing the viscosity and viscoelasticity of emulsion. Compared to appropriate ultrasonic pretreatment, high-power ultrasonic pretreatment (ultrasonic power was 500 W) attenuated the IAP trypsin sensitivity, and increased the ζ-potential and particle size of IUP, thereby decreasing the viscosity and viscoelasticity of emulsion. Overall, ultrasonic pretreatment changed the EGCG-RBP emulsion viscoelasticity by regulating spatial structural characteristics and flexibility of interface protein.