Structural Features Of Proteins Research Articles

G-K BertDTA: A graph representation learning and semantic embedding-based framework for drug-target affinity prediction

Developing new drugs is costly, time-consuming, and risky. Drug-target affinity (DTA), indicating the binding capability between drugs and target proteins, is a crucial indicator for drug development. Accurately predicting interaction strength between new drug-target pairs by analyzing previous experiments aids in screening potential drug molecules, repurposing them, and developing safe and effective medicines. Existing computational models for DTA prediction rely on strings or single-graph neural networks, lacking consideration of protein structure and molecular semantic information, leading to limited accuracy. Our experiments demonstrate that string-based methods may overlook protein conformations, causing a high root mean square error (RMSE) of 3.584 in affinity due to a lack of spatial context. Single graph networks also underperform on topology features, with a 6% lower confidence interval (CI) for activity classification. Absent semantic information also limits generalization across diverse compounds, resulting in 18% increment in RMSE and 5% in misclassifications within quantifications study, restricting potential drug discovery. To address these limitations, we propose G-K BertDTA, a novel framework for accurate DTA prediction incorporating protein features, molecular semantic features, and molecular structural information. In this proposed model, we represent drugs as graphs, with a GIN employed to learn the molecular topological information. For the extraction of protein structural features, we utilize a DenseNet architecture. A knowledge-based BERT semantic model is incorporated to obtain rich pre-trained semantic embeddings, thereby enhancing the feature information. We extensively evaluated our proposed approach on the publicly available benchmark datasets (i.e., KIBA and Davis), and experimental results demonstrate the promising performance of our method, which consistently outperforms previous state-of-the-art approaches. Code is available at https://github.com/AmbitYuki/G-K-BertDTA.

Study on stabilized mechanism of high internal phase Pickering emulsions based on commercial yeast proteins: Modulating the characteristics of Pickering particle via sonication

The primary significance of this work is that the commercial yeast proteins particles were successfully used to characterize the high internal phase Pickering emulsions (HIPPEs). The different sonication time (0,3,7,11,15 min) was used to modulate the structure and interface characteristics of yeast proteins (YPs) that as Pickering particles. Immediately afterward, the influence of YPs particles prepared at different sonication time on the rheological behavior and coalescence mechanism of HIPPEs was investigated. The results indicate that the YPs sonicated for 7 min exhibited a more relaxed molecular structures and conformation, the smallest particle size, the highest H0 and optimal amphiphilicity (the three-phase contact (θ) was 88.91°). The transition from extended to compact conformations of YPs occurred when the sonication time exceeded 7 min, resulting in an augmentation of size of YPs particles, a reduction in surface hydrophobicity (H0), and an elevation in hydrophilicity. The HIPPEs stabilized by YPs particles sonicated for 7 min exhibited the highest adsorption interface protein percentage and a more homogeneous three-dimensional (3D) protein network, resulting in the smallest droplet size and the highest storage (G′). The HIPPEs sample that stabilized by YPs particles sonicated for 15 min showed the lowest adsorption protein percentage. This caused a reduction in the thickness of its interface protein layer and an enlargement in the droplet diameter (D [3,2]). It was prone to droplet coalescence according to the equation used to evaluate the coalescence probability of droplets (Eq (2)). And the non-adsorbed YPs particles form larger aggregation structures in the continuous phase and act as “structural agents” in 3D protein network. Therefore, mechanistically, the interface protein layer formed by YPs particles sonicated 7 min contributed more to HIPPEs stability. Whereas the “structural agents” contributed more to HIPPEs stability when the sonication time exceeded 7 min. The present results shed important new light on the application of commercial YPs in the functional food fields, acting as an available and effective alternative protein.

Effects of Heat Treatment on Structure and Processing Characteristics of Donkey Milk Whey Protein

Donkey milk is nutritionally rich and has low allergenicity; thus, whey protein derived from donkey milk is a suitable hypoallergenic alternative. However, the temperature during pasteurisation considerably influences the structure and processing characteristics of whey proteins. We found that donkey milk has poor thermal stability; the secondary structure of the whey proteins loosened and became disordered as the temperature increased. In addition, exposing tryptophan and tyrosine to an external polar environment changed the tertiary structure. High-temperature and long-duration heat treatments significantly affected the processing properties, such as emulsification, foaming, and rheological properties. However, a short treatment at approximately 85°C improved the processing properties. Therefore, we recommend that donkey milk be processed at temperatures no higher than this temperature to maintain the beneficial qualities of the whey proteins and provide a reference for processing donkey milk products.

Genome-Wide Characterization and Expression Analyses of Major Latex Protein Gene Family in Populus simonii × P. nigra.

Major latex proteins, or MLPs, are crucial to plants' capacity to grow, develop, and endure biotic and abiotic stresses. The MLP gene family has been found in numerous plants, but little is known about its role in Populus simonii × P. nigra. This study discovered and assessed 43 PtMLP genes that were unevenly dispersed throughout 12 chromosomes in terms of their physicochemical characteristics, gene structure, conserved motifs, and protein localization. Based on their phylogeny and protein structural characteristics, three separate subclasses of PtMLP family were identified. Segmental and tandem duplication were found to be essential variables in the expansion of the PtMLP genes. The involvement of the PtMLP genes in growth and development, as well as in the responses to different hormones and stresses, was demonstrated by cis-regulatory element prediction. The PtMLP genes showed varying expression patterns in various tissues and under different conditions (cold, salt, and drought stress), as demonstrated in RNA-Seq databases, suggesting that PsnMLP may have different functions. Following the further investigation of the genes demonstrating notable variations in expression before and after the application of three stresses, PsnMLP5 was identified as a candidate gene. Subsequent studies revealed that PsnMLP5 could be induced by ABA treatment. This study paves the way for further investigations into the MLP genes' functional mechanisms in response to abiotic stressors, as well as the ways in which they can be utilized in poplar breeding for improved stress tolerance.

Comprehensive analysis of the aldehyde dehydrogenase gene family in Phaseolus vulgaris L. and their response to saline-alkali stress.

Aldehyde dehydrogenase (ALDH) scavenges toxic aldehyde molecules by catalyzing the oxidation of aldehydes to carboxylic acids. Although ALDH gene family members in various plants have been extensively studied and were found to regulate plant response to abiotic stress, reports on ALDH genes in the common bean (Phaseolus vulgaris L.) are limited. In this study, we aimed to investigate the effects of neutral (NS) and basic alkaline (AS) stresses on growth, physiological and biochemical indices, and ALDH activity, ALDH gene expression of common bean. In addition, We used bioinformatics techniques to analyze the physical and chemical properties, phylogenetic relationships, gene replication, collinearity, cis-acting elements, gene structure, motifs, and protein structural characteristics of PvALDH family members. We found that both NS and AS stresses weakened the photosynthetic performance of the leaves, induced oxidative stress, inhibited common bean growth, and enhanced the antioxidative system to scavenge reactive oxygen species. Furthermore, we our findings revealed that ALDH in the common bean actively responds to NS or AS stress by inducing the expression of PvALDH genes. In addition, using the established classification criteria and phylogenetic analysis, 27 PvALDHs were identified in the common bean genome, belonging to 10 ALDH families. The primary expansion mode of PvALDH genes was segmental duplication. Cis-acting elemental analysis showed that PvALDHs were associated with abiotic stress and phytohormonal responses. Gene expression analysis revealed that the PvALDH gene expression was tissue-specific. For instance, PvALDH3F1 and PvALDH3H1 were highly expressed in flower buds and flowers, respectively, whereas PvALDH3H2 and PvALDH2B4 were highly expressed in green mature pods and young pods, respectively. PvALDH22A1 and PvALDH11A2 were highly expressed in leaves and young trifoliates, respectively; PvALDH18B2 and PvALDH18B3 were highly expressed in stems and nodules, respectively; and PvALDH2C2 and PvALDH2C3 were highly expressed in the roots. PvALDHs expression in the roots responded positively to NS-AS stress, and PvALDH2C3, PvALDH5F1, and PvALDH10A1 were significantly (P < 0.05) upregulated in the roots. These results indicate that AS stress causes higher levels of oxidative damage than NS stress, resulting in weaker photosynthetic performance and more significant inhibition of common bean growth. The influence of PvALDHs potentially modulates abiotic stress response, particularly in the context of saline-alkali stress. These findings establish a basis for future research into the potential roles of ALDHs in the common bean.

Identification and functional analysis of jasmonic acid signaling repressor McJAZ8 gene in Mentha canadensis

Mentha canadensis, as a plant with medicinal and culinary uses, holds significant economic value. Jasmonic acid signaling repressor JAZ protein has a crucial role in regulating plant response to adversity stresses. The M. canadensis McJAZ8 gene is cloned and analyzed for protein characterization, protein interactions, and expression patterns, so as to provide genetic resources for molecular breeding of M. canadensis for stress tolerance. This experiment will analyze the protein structural characteristics, subcellular localization, protein interactions, and gene expression of McJAZ8 using bioinformatics, yeast two-hybrid(Y2H), transient expression in tobacco leaves, qRT-PCR, and other technologies. The results show that:(1)The full length of the McJAZ8 gene is 543 bp, encoding 180 amino acids. The McJAZ8 protein contains conserved TIFY and Jas domains and exhibits high homology with Arabidopsis thaliana AtJAZ1 and AtJAZ2.(2)The McJAZ8 protein is localized in the nucleus and cytoplasm.(3)The Y2H results show that McJAZ8 interacts with itself or McJAZ1/3/4/5 proteins to form homologous or heterologous dimers.(4)McJAZ8 is expressed in different tissue, with the highest expression level in young leaves. In terms of leaf sequence, McJAZ8 shows the highest expression level in the fourth leaf and the lowest expression level in the second leaf.(5) In leaves and roots, the expression of McJAZ8 is upregulated to varying degrees under methyl jasmonate(MeJA), drought, and NaCl treatments. The expression of McJAZ8 shows an initial upregulation followed by a downregulation pattern under CdCl_2 treatment. In leaves, the expression of McJAZ8 tends to gradually decrease under CuCl_2 treatment, while in roots, it initially decreases and then increases before decreasing again. In both leaves and roots, the expression of McJAZ8 is downregulated to varying degrees under AlCl_(3 )treatment. This study has enriched the research on jasmonic acid signaling repressor JAZ genes in M. canadensis and provided genetic resources for the molecular breeding of M. canadensis.

Longitudinal Genotype-Phenotype (Vineland Questionnaire) Characterization of 15 ADNP Syndrome Cases Highlights Mutated Protein Length and Structural Characteristics Correlation with Communicative Abilities Accentuated in Males.

Activity-dependent neuroprotective protein (ADNP) is essential for neurodevelopment and de novo mutations in ADNP cause the ADNP syndrome. From brain pathologies point of view, tauopathy has been demonstrated at a young age, implying stunted development coupled with early/accelerated neurodegeneration. Given potential genotype-phenotype differences and age-dependency, we have assessed here a cohort of 15 individuals (1-27-year-old), using 1-3 longitudinal parent (caretaker) interview/s (Vineland 3 questionnaire) over several years. Our results indicated developmental delays, or even developmental arrests, coupled with potential spurts of development at early ages. Severe outcomes correlated with the truncating high impact mutation, in other words, the remaining mutated protein length as well as with the tested individual age, corroborating the hypothesis of developmental delays coupled with accelerated aging. A significant correlation was noted between mutated protein length and communication, implying a high impact of ADNP on communicative skills. Additionally, correlations were discovered between the two previously described epi-genetic signatures in ADNP emphasizing aberrant acquisition of motor behaviors, with truncating mutations around the nuclear localization signal being mostly affected. Finally, all individuals seem to acquire an age equivalent of 1-6years, requiring disease modification treatment, such as the ADNP-derived drug candidate, NAP (davunetide), which has recently shown efficacy in women suffering from the neurodegenerative disorder, progressive supranuclear palsy (PSP), a late-onset tauopathy.

Benchmarking AlphaMissense pathogenicity predictions against cystic fibrosis variants.

Variants in the cystic fibrosis transmembrane conductance regulator gene (CFTR) result in cystic fibrosis-a lethal autosomal recessive disorder. Missense variants that alter a single amino acid in the CFTR protein are among the most common cystic fibrosis variants, yet tools for accurately predicting molecular consequences of missense variants have been limited to date. AlphaMissense (AM) is a new technology that predicts the pathogenicity of missense variants based on dual learned protein structure and evolutionary features. Here, we evaluated the ability of AM to predict the pathogenicity of CFTR missense variants. AM predicted a high pathogenicity for CFTR residues overall, resulting in a high false positive rate and fair classification performance on CF variants from the CFTR2.org database. AM pathogenicity score correlated modestly with pathogenicity metrics from persons with CF including sweat chloride level, pancreatic insufficiency rate, and Pseudomonas aeruginosa infection rate. Correlation was also modest with CFTR trafficking and folding competency in vitro. By contrast, the AM score correlated well with CFTR channel function in vitro-demonstrating the dual structure and evolutionary training approach learns important functional information despite lacking such data during training. Different performance across metrics indicated AM may determine if polymorphisms in CFTR are recessive CF variants yet cannot differentiate mechanistic effects or the nature of pathophysiology. Finally, AM predictions offered limited utility to inform on the pharmacological response of CF variants i.e., theratype. Development of new approaches to differentiate the biochemical and pharmacological properties of CFTR variants is therefore still needed to refine the targeting of emerging precision CF therapeutics.

Lactylation prediction models based on protein sequence and structural feature fusion.

Lysine lactylation (Kla) is a newly discovered posttranslational modification that is involved in important life activities, such as glycolysis-related cell function, macrophage polarization and nervous system regulation, and has received widespread attention due to the Warburg effect in tumor cells. In this work, we first design a natural language processing method to automatically extract the 3D structural features of Kla sites, avoiding potential biases caused by manually designed structural features. Then, we establish two Kla prediction frameworks, Attention-based feature fusion Kla model (ABFF-Kla) and EBFF-Kla, to integrate the sequence features and the structure features based on the attention layer and embedding layer, respectively. The results indicate that ABFF-Kla and Embedding-based feature fusion Kla model (EBFF-Kla), which fuse features from protein sequences and spatial structures, have better predictive performance than that of models that use only sequence features. Our work provides an approach for the automatic extraction of protein structural features, as well as a flexible framework for Kla prediction. The source code and the training data of the ABFF-Kla and the EBFF-Kla are publicly deposited at: https://github.com/ispotato/Lactylation_model.

Structure-guided discovery of anti-CRISPR and anti-phage defense proteins

Bacteria use a variety of defense systems to protect themselves from phage infection. In turn, phages have evolved diverse counter-defense measures to overcome host defenses. Here, we use protein structural similarity and gene co-occurrence analyses to screen >66 million viral protein sequences and >330,000 metagenome-assembled genomes for the identification of anti-phage and counter-defense systems. We predict structures for ~300,000 proteins and perform large-scale, pairwise comparison to known anti-CRISPR (Acr) and anti-phage proteins to identify structural homologs that otherwise may not be uncovered using primary sequence search. This way, we identify a Bacteroidota phage Acr protein that inhibits Cas12a, and an Akkermansia muciniphila anti-phage defense protein, termed BxaP. Gene bxaP is found in loci encoding Bacteriophage Exclusion (BREX) and restriction-modification defense systems, but confers immunity independently. Our work highlights the advantage of combining protein structural features and gene co-localization information in studying host-phage interactions.

Getting to Grips with the Oxysterol-Binding Protein Family - a Forty Year Perspective.

This review discusses how research around the oxysterol-binding protein family has evolved. We briefly summarize how this protein family, designated OSBP-related (ORP) or OSBP-like (OSBPL) proteins, was discovered, how protein domains highly conserved among family members between taxa paved the way for understanding their mechanisms of action, and how insights into protein structural and functional features help to understand their versatility as lipid transporters. We also discuss questions and future avenues of research opened by these findings. The investigations on oxysterol-binding protein family serve as a real-life example of the notion that science often advances as a collective effort of multiple lines of enquiry, including serendipitous routes. While original articles invariably explain the motivation of the research undertaken in rational terms, the actual paths to findings may be less intentional. Fortunately, this does not reduce the impact of the discoveries made. Besides hopefully providing a useful account of ORP family proteins, we aim to convey this message.

Accessing the thermal and electric effects in β-lactoglobulin denaturation and interaction with phenolic compounds

Protein-phenolic interactions have been on the spotlight in food research since they can change the structural, functional and nutritional properties of both compounds. Electric field processing technologies, such as ohmic heating (OHM), can contribute to improving food safety, quality and to tailor functionality of foods and ingredients. In this study, the potential of OHM processing in modifying protein-phenolic interactions was accessed. β-lactoglobulin (β-Lg) solutions were processed at 70 °C and 90 °C by conventional heating and OHM (26 V cm−1 at 50 Hz and 20 kHz), followed by their association with different phenolic compounds – i.e., quercetin (Qu), malvidin-3-glucoside (M3G), trans-resveratrol (TR), p-coumaric acid (p-C) and tyrosol (Ty). The protein solutions and protein-phenolic complexes were characterized by UV-spectroscopy, fluorescence spectroscopy, circular dichroism, and antioxidant capacity. Protein-phenolic interactions were confirmed by changes in the UV-absorbance spectra, reduction of the surface hydrophobicity and changes in the secondary structure of the protein. The formation of stable complexes was established through fluorescence quenching analysis and the binding affinities were found to be in the order TR > Qu > p-C > M3G > Ty. Furthermore, the binding parameters and changes of the protein's structural features were impacted by the processing conditions, including those associated with OHM. This study demonstrates for the first time that OHM processing and the control of its variables can potentially be used to tune β-Lg-PhCs interactions.

Efficient Expression in the Prokaryotic Host System, Purification and Structural Analyses of the Recombinant Human ACE2 Catalytic Subunit as a Hybrid Protein with the B Subunit of Cholera Toxin (CTB-ACE2).

Angiotensin-converting enzyme 2 (ACE2) has a specific interaction with the coronavirus spike protein, enabling its entry into human cells. This membrane enzyme converts angiotensin II into angiotensin 1-7, which has an essential role in protecting the heart and improving lung function. Many therapeutic properties have been attributed to the human recombinant ACE2 (hrACE2), especially in combating complications related to diabetes mellitus and hypertension, as well as, preventing the coronavirus from entering the target tissues. In the current study, we designed an appropriate gene construct for the hybrid protein containing the ACE2 catalytic subunit and the B subunit of cholera toxin (CTB-ACE2). This structural feature will probably help the recombinant hybrid protein enter the mucosal tissues, including the lung tissue. Optimization of this hybrid protein expression was investigated in BL21 bacterial host cells. Also, the hybrid protein was identified with an appropriate antibody using the ELISA method. A large amount of the hybrid protein (molecular weight of ~ 100kDa) was expressed as the inclusion body when the induction was performed in the presence of 0.25mM IPTG and 1% sucrose for 10h. Finally, the protein structural features were assessed using several biophysical methods. The fluorescence emission intensity and oligomeric size distribution of the CTB-ACE2 suggested a temperature-dependent alteration. The β-sheet and α-helix were also dominant in the hybrid protein structure, and this protein also displays acceptable chemical stability. In overall, according to our results, the efficient expression and successful purification of the CTB-ACE2 protein may pave the path for its therapeutic applications against diseases such as covid-19, diabetes mellitus and hypertension.

Protein language models can capture protein quaternary state

BackgroundDetermining a protein’s quaternary state, i.e. the number of monomers in a functional unit, is a critical step in protein characterization. Many proteins form multimers for their activity, and over 50% are estimated to naturally form homomultimers. Experimental quaternary state determination can be challenging and require extensive work. To complement these efforts, a number of computational tools have been developed for quaternary state prediction, often utilizing experimentally validated structural information. Recently, dramatic advances have been made in the field of deep learning for predicting protein structure and other characteristics. Protein language models, such as ESM-2, that apply computational natural-language models to proteins successfully capture secondary structure, protein cell localization and other characteristics, from a single sequence. Here we hypothesize that information about the protein quaternary state may be contained within protein sequences as well, allowing us to benefit from these novel approaches in the context of quaternary state prediction.ResultsWe generated ESM-2 embeddings for a large dataset of proteins with quaternary state labels from the curated QSbio dataset. We trained a model for quaternary state classification and assessed it on a non-overlapping set of distinct folds (ECOD family level). Our model, named QUEEN (QUaternary state prediction using dEEp learNing), performs worse than approaches that include information from solved crystal structures. However, it successfully learned to distinguish multimers from monomers, and predicts the specific quaternary state with moderate success, better than simple sequence similarity-based annotation transfer. Our results demonstrate that complex, quaternary state related information is included in such embeddings.ConclusionsQUEEN is the first to investigate the power of embeddings for the prediction of the quaternary state of proteins. As such, it lays out strengths as well as limitations of a sequence-based protein language model approach, compared to structure-based approaches. Since it does not require any structural information and is fast, we anticipate that it will be of wide use both for in-depth investigation of specific systems, as well as for studies of large sets of protein sequences. A simple colab implementation is available at: https://colab.research.google.com/github/Furman-Lab/QUEEN/blob/main/QUEEN_prediction_notebook.ipynb.

Deglycosylated RBD produced in Pichia pastoris as a low-cost sera COVID-19 diagnosis tool and a vaccine candidate.

During the COVID-19 outbreak, numerous tools including protein-based vaccines have been developed. The methylotrophic yeast Pichia pastoris (synonymous to Komagataella phaffii) is an eukaryotic cost-effective and scalable system for recombinant protein production, with the advantages of an efficient secretion system and the protein folding assistance of the secretory pathway of eukaryotic cells. In a previous work, we compared the expression of SARS-CoV-2 Spike Receptor Binding Domain in P. pastoris with that in human cells. Although the size and glycosylation pattern was different between them, their protein structural and conformational features were indistinguishable. Nevertheless, since high mannose glycan extensions in proteins expressed by yeast may be the cause of a nonspecific immune recognition, we deglycosylated RBD in native conditions. This resulted in a highly pure, homogenous, properly folded and monomeric stable protein. This was confirmed by circular dichroism and tryptophan fluorescence spectra and by SEC-HPLC, which were similar to those of RBD proteins produced in yeast or human cells. Deglycosylated RBD was obtained at high yields in a single step, and it was efficient in distinguishing between SARS-CoV-2-negative and positive sera from patients. Moreover, when the deglycosylated variant was used as an immunogen, it elicited a humoral immune response ten times greater than the glycosylated form, producing antibodies with enhanced neutralizing power and eliciting a more robust cellular response. The proposed approach may be used to produce at a low cost, many antigens that require glycosylation to fold and express, but do not require glycans for recognition purposes.

Effect of heat treatment on the release of off-flavor compounds in soy protein isolate

The effects of different heat treatment conditions (65℃ for 30 min, 75℃ for 15 min, and 95℃ for 2, 15 and 30 min) on the evolution of off-flavor compounds in soy protein isolate (SPI) were investigated in terms of lipid oxidation, Maillard reaction and protein structural characteristics. Higher off-flavor concentrations were observed in control and 65℃ treated SPI due to lipoxygenase-mediated enzymatic lipid oxidation. Protein structure played an important role in the release of off-flavors above 65℃. When heated from 75℃ to 95℃ for 2 min, Maillard reaction occurred, glycinin was completely denatured, the particle size increased and the small molecular weight soluble aggregates were formed, resulting in an increase in the content of partial off-flavors. The off-flavor content decreased with time at 95℃, accompanied by the formation of larger molecular weight soluble aggregates. This finding provides practical implications for the beany removal through the SPI structural regulation.

VeloPro: A pipeline integrating Ribo-seq and AlphaFold deciphersassociation patterns between translation velocity and protein structure features.

VeloPro integrates Ribo-seq data and AlphaFold2-predicted 3D protein structure information for characterization of the association patterns between translation velocity and many protein structure features in prokaryotic and eukaryotic organisms across different taxonomical clades such as bacteria, fungi, protozoa, nematode, plants, insect, and mammals. We illustrated that association patterns between translation velocity and protein structure features differ across organisms, partially reflecting their taxonomical relationship.

Large-scale clustering of AlphaFold2 3D models shines light on the structure and function of proteins

Two recent studies exploited ultra-fast structural aligners and deep-learning approaches to cluster the protein structure space in the AlphaFold Database. Barrio-Hernandez etal.1 and Durairaj etal.2 uncovered fascinating new protein functions and structural features previously unknown.

Homology Modeling and Structure Based Drug Design for Human Gastric Cancer

Abstract: This research article delves into the multifaceted world of structural biology and bioinformatics, exploring a diverse array of tools and resources employed to decipher the intricacies of proteins and their implications in health and disease. The paper navigates through various computational tools and databases used for sequence analysis, structural analysis, mutation site detection, and molecular docking, shedding light on their individual contributions in unraveling the secrets of proteins. COBALT serves as the initial compass, guiding researchers in the alignment of protein sequences, identifying conserved domains, and elucidating structural features in proteins. The exploration continues, with a focus on tools such as RasMol, PyMol, and Pharmit. This research article explores a range of bioinformatics tools and databases crucial for elucidating the complex world of proteins and their involvement in diseases like gastric cancer. It begins by highlighting the pivotal role of the Catalogue of Somatic Mutations in Cancer (COSMIC) in mutation site detection, providing a comprehensive repository of somatic mutations in cancer. The Kyoto Encyclopedia of Genes and Genomes (KEGG) complements this with a wealth of biological data and pathways. Shifting the focus to protein stability and dynamics, the article introduces DynaMUT, a computational tool employing molecular dynamics simulations to predict mutation impacts on protein behavior. Lastly, SwissDock takes the stage for drug discovery, facilitating the prediction and analysis of interactions between small molecules and target proteins. Collectively, these tools and databases offer an interdisciplinary lens through which researchers unravel protein intricacies and their relevance in diseases, exemplifying the indispensable role of structural biology and bioinformatics in advancing biological understanding.

Transcriptional and protein structural characterization of homogentisate phytyltransferase genes in barley, wheat, and oat

BackgroundHomogentisate phytyltransferase (HPT) is the critical enzyme for the biosynthesis of tocopherols (vitamin E), which are the major lipid-soluble antioxidants and help plants adapt to various stress conditions. HPT is generally strictly conserved in various plant genomes; however, a divergent lineage HPT2 was identified recently in some Triticeae species. The molecular function and transcriptional profiles of HPT2 remain to be characterized.ResultsIn this study, we performed comprehensive transcriptome data mining of HPT1 and HPT2 in different tissues and stages of barley (Hordeum vulgare), wheat (Triticum aestivum), and oat (Avena sativa), followed by qRT-PCR experiments on HPT1 and HPT2 in different tissues of barley and wheat. We found that the common HPT1 genes (HvHPT1, TaHPT1s, and AsHPT1s) displayed a conserved transcriptional pattern in the three target species and were universally transcribed in various tissues, with a notable preference in leaf. In contrast, HPT2 genes (HvHPT2, TaHPT2, and AsHPT2) were specifically transcribed in spike (developmentally up-regulated) and shoot apex tissues, displaying a divergent tissue-specific pattern. Cis-regulatory elements prediction in the promoter region identified common factors related to light-, plant hormone-, low temperature-, drought- and defense- responses in both HPT1s and HPT2s. We observed the transcriptional up-regulation of HvHPT1 and HvHPT2 under various stress conditions, supporting their conserved function in environmental adaption. We detected a clear, relaxed selection pressure in the HPT2 lineage, consistent with the predicted evolution pattern following gene duplication. Protein structural modelling and substrate docking analyses identified putative catalytic amino acid residues for HvHPT1 and HvHPT2, which are strictly conserved and consistent with their function in vitamin E biosynthesis.ConclusionsWe confirmed the presence of two lineages of HPT in Triticeae and Aveninae, including hexaploid oat, and characterized their transcriptional profiles based on transcriptome and qRT-PCR data. HPT1s were ubiquitously transcribed in various tissues, whilst HPT2s were highly expressed in specific stages and tissue. The active transcription of HPT2s, together with its conserved cis-elements and protein structural features, support HPT2s’ role in tocopherol production in Triticeae. This study is the first protein structural analysis on the membrane-bound plant HPTs and provides valuable insights into its catalytic mechanism.