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Nine viruses of the bean common mosaic virus subgroup of potyviruses are major international crop pathogens, but their phylogenetically closest relatives from non-crop plants have mostly been found only in SE Asia and Oceania, which is thus likely to be their "centre of emergence". We have compared over 700 of the complete genomic ORFs of the crop pandemic and the non-crop viruses in various ways. Only one-third of crop virus genomes are non-recombinant, but more than half the non-crop virus genomes are. Four of the viruses were from crops domesticated in the Old World (Africa to SE Asia), and the other five were from New World crops. There was a temporal signal in only three of the crop virus datasets, but it confirmed that the most recent common ancestors of all the crop viruses were before inter-continental marine trade started after 1492 CE, whereas all the crown clusters of the phylogenies are from after that date. The non-crop virus datasets are genetically more diverse than those of the crop viruses, and Tajima's D analyses showed that their populations were contracting, and only one of the crop viruses had a significantly expanding population. dN/dS analyses showed that most of the genes and codons in all the viruses were under significant negative selection, and the few that were under significant positive selection were mostly in the PIPO-encoding region of the P3 protein, or the PIPO protein itself. Interestingly, more positively selected codons were found in non-crop than in crop viruses, and, as the hosts of the former were taxonomically more diverse than the latter, this may indicate that the positively selected codons are involved in host range determination; AlphaFold3 modelling was used to investigate this possibility. [ABSTRACT FROM AUTHOR]

Eotaxin-3 is a key chemokine with a relevant role in eosinophilic esophagitis, a rare chronic immune/antigen-mediated inflammatory disorder. Eotaxin-3 is a potent activator of eosinophil emergence and migration, which may lead to allergic airway inflammation. We investigated, using bioinformatics tools, the protein structure and the possible effects of the known variations reported in public databases. Following a procedure already established, we created a 3D model of the whole protein and modeled the structure of 105 protein variants due to known point mutations. The effects of the amino acid substitution at the level of impact on protein structure, stability, and possibly function were detected by the bioinformatics procedure and described in detail. A web application was implemented to browse the results of the analysis and visualize the 3D models, with the opportunity of downloading the models and analyzing them using their own software. Among 105 amino acid substitutions investigated, the study evidenced in 44 cases at least one change in any of the investigated structural parameters. Other six variations are also relevant, although a structural effect was not detected by our analysis, because they affected amino acids highly conserved, which suggests a possible function role. All these variations should be the object of particular attention, as they may induce a loss of functionality in the protein. [ABSTRACT FROM AUTHOR]

The results of tertiary structure assessment at CASP15 are reported. For the first time, recognizing the outstanding performance of AlphaFold 2 (AF2) at CASP14, all single-chain predictions were assessed together, irrespective of whether a template was available. At CASP15, there was no single stand-out group, with most of the best-scoring groups-led by PEZYFoldings, UM-TBM, and Yang Server-employing AF2 in one way or another. Many top groups paid special attention to generating deep Multiple Sequence Alignments (MSAs) and testing variant MSAs, thereby allowing them to successfully address some of the hardest targets. Such difficult targets, as well as lacking templates, were typically proteins with few homologues. Local divergence between prediction and target correlated with localization at crystal lattice or chain interfaces, and with regions exhibiting high B-factor factors in crystal structure targets, and should not necessarily be considered as representing error in the prediction. However, analysis of exposed and buried side chain accuracy showed room for improvement even in the latter. Nevertheless, a majority of groups produced high-quality predictions for most targets, which are valuable for experimental structure determination, functional analysis, and many other tasks across biology. These include those applying methods similar to those used to generate major resources such as the AlphaFold Protein Structure Database and the ESM Metagenomic atlas: the confidence estimates of the former were also notably accurate.

Unlike animals, variability in transcription factors (TFs) and their binding regions (TFBRs) across the plants species is a major problem that most of the existing TFBR finding software fail to tackle, rendering them hardly of any use. This limitation has resulted into underdevelopment of plant regulatory research and rampant use of Arabidopsis -like model species, generating misleading results. Here, we report a revolutionary transformers-based deep-learning approach, PTFSpot, which learns from TF structures and their binding regions' co-variability to bring a universal TF-DNA interaction model to detect TFBR with complete freedom from TF and species-specific models' limitations. During a series of extensive benchmarking studies over multiple experimentally validated data, it not only outperformed the existing software by >30% lead but also delivered consistently >90% accuracy even for those species and TF families that were never encountered during the model-building process. PTFSpot makes it possible now to accurately annotate TFBRs across any plant genome even in the total lack of any TF information, completely free from the bottlenecks of species and TF-specific models. [ABSTRACT FROM AUTHOR]

The origin of flight and laryngeal echolocation in bats is likely to have been accompanied by evolutionary changes in other aspects of their sensory biology. Of all sensory modalities in bats, olfaction is perhaps the least well understood. Olfactory receptors (ORs) function in recognizing odour molecules, with crucial roles in evaluating food, as well as in processing social information. Here we compare OR repertoire sizes across taxa and apply a new pipeline that integrates comparative genome data with protein structure modelling and then we employ molecular docking techniques with small molecules to analyse OR functionality based on binding energies. Our results suggest a sharp contraction in odorant recognition of the functional OR repertoire during the origin of bats, consistent with a reduced dependence on olfaction. We also compared bat lineages with contrasting different ecological characteristics and found evidence of differences in OR gene expansion and contraction, and in the composition of ORs with different tuning breadths. The strongest binding energies of ORs in non‐echolocating fruit‐eating bats were seen to correspond to ester odorants, although we did not detect a quantitative advantage of functional OR repertoires in these bats compared with echolocating insectivorous species. Overall, our findings based on molecular modelling and computational docking suggest that bats have undergone olfactory evolution linked to dietary adaptation. Our results from extant and ancestral bats help to lay the groundwork for targeted experimental functional tests in the future. [ABSTRACT FROM AUTHOR]

Lipoxygenases make several biological functions in cells, based on the products of the catalyzed reactions. In diatoms, microalgae ubiquitous in aquatic ecosystems, lipoxygenases have been noted for the oxygenation of fatty acids with the production of oxylipins, which are involved in many physiological and pathological processes in marine organisms. The interest in diatoms' lipoxygenases and oxylipins has increased due to their possible biotechnological applications, ranging from ecology to medicine. We investigated using bioinformatics and molecular docking tools the lipoxygenases of diatoms and the possible interaction with substrates. A large-scale analysis of sequence resources allowed us to retrieve 45 sequences of lipoxygenases from diatoms. We compared and analyzed the sequences by multiple alignments and phylogenetic trees, suggesting the possible clustering in phylogenetic groups. Then, we modelled the 3D structure of representative enzymes from the different groups and investigated in detail the structural and functional properties by docking simulations with possible substrates. The results allowed us to propose a classification of the lipoxygenases from diatoms based on their sequence features, which may be reflected in specific structural differences and possible substrate specificity. [ABSTRACT FROM AUTHOR]

The most favorite ornamental crop in Indonesia is orchid which benefited as floriculture. Therefore, the quality of this crop must be improved. Biotechnology is appropriate to be used to improve the quality and quantity of orchid plants. To conduct this method, researchers must know what genes function in plant development. In Phalaenopsis orchids, the gene has been identified as homeobox genes called Phalaenopsis Orchid Homeobox1 (POH1). This research aims to conduct in silico analysis of the gene. The materials were retrieved from mRNA and amino acid databases. Then, the materials are aligned, visualized, motif location analysis, motif function discovery, phylogenetic construction, and protein 3D structural modelling. Based on mRNA and amino acid alignment, there are 4 domain regions that are conserved in POH1 and other homologous genes, such as KNOX1, KNOX2, ELK Domain, and Homeobox KN Domain, which roles as a transcription factor involved in plant development. SWISS-MODEL and ColabFold were used in protein modelling of the protein. By ColabbFold modelling, the modelling prediction uses 325 residues, higher than SWISS-MODEL in 59 residues. ColabFold validation by Ramachandra Plot depicts having the most favourite regions is 68.6%, while SWISS -MODEL is 92.3%. Another validation parameter is overall quality factor and QMEAN Score. Protein modelling by ColabFold has overall quality factor 89.252 and QMEAN Score 0.41 ± 0.05. However, SWISS-MODEL 3D prediction has overall quality factor 98.039 and QMEAN score of 0.71 ± 0.11. [ABSTRACT FROM AUTHOR]

Introduction The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function. Methods nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221). Results Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 67 dangerous, and I-Mutant found 58 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type. Conclusions Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders.

INTRODUCTION: Idiopathic hypogonadotropic hypogonadism (IHH) is classified into two groups-Kalman syndrome and normosmic IHH (nIHH). Half of all cases can be explained by mutations in >50 genes. Targeted gene panel testing with nexrt generation sequencing (NGS) is required for patients without typical phenotypic findings. The aim was to determine the genetic etiologies of patients with IHH using NGS, including 54 IHH-associated genes, and to present protein homology modeling and protein stability analyzes of the detected variations. METHODS: Clinical and demographic data of 16 patients (eight female), aged between 11.6-17.8 years, from different families were assessed. All patients were followed up for a diagnosis of nIHH, had normal cranial imaging, were without anterior pituitary hormone deficiency other than gonadotropins, had no sex chromosome anomaly, had no additional disease, and underwent genetic analysis with NGS between the years 2008-2021. Rare variants were classified according to the variant interpretation framework of the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology. Changes in protein structure caused by variations were modeled using RoseTTAFold and changes in protein stability resulting from variation were analyzed. RESULTS: Half of the 16 had no detectable variation. Three (18.75%) had a homozygous (pathogenic) variant in the GNRHR gene, one (6.25%) had a compound heterozygous [likely pathogenic-variants of uncertain significance (VUS)] variant in PROK2 and four (25%) each had a heterozygous (VUS) variant in HESX1, FGF8, FLRT3 and DMXL2. Protein models showed that variants interpreted as VUS according to ACMG could account for the clinical IHH. DISCUSSION AND CONCLUSION: The frequency of variation detection was similar to the literature. Modelling showed that the variant in five different genes, interpreted as VUS according to ACMG, could explain the clinical IHH.

Introduction The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function. Methods nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221). Results Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 67 dangerous, and I-Mutant found 58 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type. Conclusions Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders.

The affinity of specific phenolic compounds (PCs) and capsaicinoids (CAPs) present in three Capsicum annuum varieties (Friariello, Cayenne and Dzuljunska Sipka) to the transient receptor potential vanilloid member 1 (TRPV1) was investigated by integrating an analytic approach for the simultaneous extraction and analysis through high-performance liquid chromatography coupled with ion trap mass spectrometry (HPLC/ITMS) and UV detection (HPLC-UV) of PCs and CAPs and structural bioinformatics based on the protein modelling and molecular simulations of protein–ligand docking. Overall, a total of 35 compounds were identified in the different samples and CAPs were quantified. The highest content of total polyphenols was recorded in the pungent Dzuljunska Sipka variety (8.91 ± 0.05 gGAE/Kg DW) while the lowest was found in the non-pungent variety Friariello (3.58 ± 0.02 gGAE/Kg DW). Protein modelling generated for the first time a complete model of the homotetrameric human TRPV1, and it was used for docking simulations with the compounds detected via the analytic approach, as well as with other compounds, as an inhibitor reference. The simulations indicate that different capsaicinoids can interact with the receptor, providing details on the molecular interaction, with similar predicted binding energy values. These results offer new insights into the interaction of capsaicinoids with TRPV1 and their possible actions. [ABSTRACT FROM AUTHOR]

Microscopic, photosynthetic prokaryotes and eukaryotes, collectively referred to as microalgae, are widely studied to improve our understanding of key metabolic pathways (e.g., photosynthesis) and for the development of biotechnological applications. Omics technologies, which are now common tools in biological research, have been shown to be critical in microalgal research. In the past decade, significant technological advancements have allowed omics technologies to become more affordable and efficient, with huge datasets being generated. In particular, where studies focused on a single or few proteins decades ago, it is now possible to study the whole proteome of a microalgae. The development of mass spectrometry-based methods has provided this leap forward with the high-throughput identification and quantification of proteins. This review specifically provides an overview of the use of proteomics in fundamental (e.g., photosynthesis) and applied (e.g., lipid production for biofuel) microalgal research, and presents future research directions in this field.

Lipoxygenases make several biological functions in cells, based on the products of the catalyzed reactions. In diatoms, microalgae ubiquitous in aquatic ecosystems, lipoxygenases have been noted for the oxygenation of fatty acids with the production of oxylipins, which are involved in many physiological and pathological processes in marine organisms. The interest in diatoms’ lipoxygenases and oxylipins has increased due to their possible biotechnological applications, ranging from ecology to medicine. We investigated using bioinformatics and molecular docking tools the lipoxygenases of diatoms and the possible interaction with substrates. A large-scale analysis of sequence resources allowed us to retrieve 45 sequences of lipoxygenases from diatoms. We compared and analyzed the sequences by multiple alignments and phylogenetic trees, suggesting the possible clustering in phylogenetic groups. Then, we modelled the 3D structure of representative enzymes from the different groups and investigated in detail the structural and functional properties by docking simulations with possible substrates. The results allowed us to propose a classification of the lipoxygenases from diatoms based on their sequence features, which may be reflected in specific structural differences and possible substrate specificity.

The most favorite ornamental crop in Indonesia is orchid which benefited as floriculture. Therefore, the quality of this crop must be improved. Biotechnology is appropriate to be used to improve the quality and quantity of orchid plants. To conduct this method, researchers must know what genes function in plant development. In Phalaenopsis orchids, the gene has been identified as homeobox genes called Phalaenopsis Orchid Homeobox1 (POH1). This research aims to conduct in silico analysis of the gene. The materials were retrieved from mRNA and amino acid databases. Then, the materials are aligned, visualized, motif location analysis, motif function discovery, phylogenetic construction, and protein 3D structural modelling. Based on mRNA and amino acid alignment, there are 4 domain regions that are conserved in POH1 and other homologous genes, such as KNOX1, KNOX2, ELK Domain, and Homeobox KN Domain, which roles as a transcription factor involved in plant development. SWISS-MODEL and ColabFold were used in protein modelling of the protein. By ColabbFold modelling, the modelling prediction uses 325 residues, higher than SWISS-MODEL in 59 residues. ColabFold validation by Ramachandra Plot depicts having the most favourite regions is 68.6%, while SWISS-MODEL is 92.3%. Another validation parameter is overall quality factor and QMEAN Score. Protein modelling by ColabFold has overall quality factor 89.252 and QMEAN Score 0.41 ± 0.05. However, SWISS-MODEL 3D prediction has overall quality factor 98.039 and QMEAN score of 0.71 ± 0.11.

Objective: Idiopathic hypogonadotropic hypogonadism (IHH) is classified into two groups-Kalman syndrome and normosmic IHH (nIHH). Half of all cases can be explained by mutations in >50 genes. Targeted gene panel testing with nexrt generation sequencing (NGS) is required for patients without typical phenotypic findings. The aim was to determine the genetic etiologies of patients with IHH using NGS, including 54 IHH-associated genes, and to present protein homology modeling and protein stability analyzes of the detected variations. Methods: Clinical and demographic data of 16 patients (eight female), aged between 11.6-17.8 years, from different families were assessed. All patients were followed up for a diagnosis of nIHH, had normal cranial imaging, were without anterior pituitary hormone deficiency other than gonadotropins, had no sex chromosome anomaly, had no additional disease, and underwent genetic analysis with NGS between the years 2008-2021. Rare variants were classified according to the variant interpretation framework of the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology. Changes in protein structure caused by variations were modeled using Rose TTA Fold and changes in protein stability resulting from variation were analyzed. Results: Half of the 16 had no detectable variation. Three (18.75%) had a homozygous (pathogenic) variant in the GNRHR gene, one (6.25%) had a compound heterozygous [likely pathogenic-variants of uncertain significance (VUS)] variant in PROK2 and four (25%) each had a heterozygous (VUS) variant in HESX1, FGF8, FLRT3 and DMXL2. Protein models showed that variants interpreted as VUS according to ACMG could account for the clinical IHH. Conclusion: The frequency of variation detection was similar to the literature. Modelling showed that the variant in five different genes, interpreted as VUS according to ACMG, could explain the clinical IHH. [ABSTRACT FROM AUTHOR]

Isoflavonoid synthase (IFS) is a critical enzyme for the biosynthesis of over 2400 isoflavonoids. Isoflavonoids are an important class of plant secondary metabolites that have a range of pharmaceutical and nutraceutical properties. With growing interest in isoflavonoids from both research and industrial perspectives, efforts are being forwarded to enhance isoflavonoid production in-planta and ex-planta; therefore, in-silico analysis and characterisation of available IFS protein sequences are needed. The present study is the first-ever attempt toward phylogenetic analysis and protein modelling of available IFS protein sequences. Phylogenetic analysis has shown that IFS amino acid sequences have 86.4% pairwise identity and 26.5% identical sites, and the sequences were grouped into six different clades. The presence of a β-hairpin and extra loop at catalytic sites of Trifolium pratense, Beta vulgaris and Medicago truncatula, respectively, compared with Glycyrrhiza echinata are critical structural differences that may affect catalytic function. Protein docking highlighted the preference of selected IFS for liquiritigenin compared with naringenin and has listed T. pratense as the most efficient candidate for heterologous biosynthesis of isoflavonoids. The in-silico characterisation of IFS represented in this study is vital in realising the new bioengineering endeavours and will help in the characterisation and selection of IFS candidate enzymes for heterologous biosynthesis of isoflavonoids. [ABSTRACT FROM AUTHOR]

Main conclusion: Genetic variation in seed protein composition, seed protein gene expression and predictions of seed protein physiochemical properties were documented in C. sativa and other Camelina species. Seed protein diversity was examined in six Camelina species (C. hispida, C. laxa, C. microcarpa, C. neglecta, C. rumelica and C. sativa). Differences were observed in seed protein electrophoretic profiles, total seed protein content and amino acid composition between the species. Genes encoding major seed proteins (cruciferins, napins, oleosins and vicilins) were catalogued for C. sativa and RNA-Seq analysis established the expression patterns of these and other genes in developing seed from anthesis through to maturation. Examination of 187 C. sativa accessions revealed limited variation in seed protein electrophoretic profiles, though sufficient to group the majority into classes based on high MW protein profiles corresponding to the cruciferin region. C. sativa possessed four distinct types of cruciferins, named CsCRA, CsCRB, CsCRC and CsCRD, which corresponded to orthologues in Arabidopsis thaliana with members of each type encoded by homeologous genes on the three C. sativa sub-genomes. Total protein content and amino acid composition varied only slightly; however, RNA-Seq analysis revealed that CsCRA and CsCRB genes contributed > 95% of the cruciferin transcripts in most lines, whereas CsCRC genes were the most highly expressed cruciferin genes in others, including the type cultivar DH55. This was confirmed by proteomics analyses. Cruciferin is the most abundant seed protein and contributes the most to functionality. Modelling of the C. sativa cruciferins indicated that each type possesses different physiochemical attributes that were predicted to impart unique functional properties. As such, opportunities exist to create C. sativa cultivars with seed protein profiles tailored to specific technical applications. [ABSTRACT FROM AUTHOR]

Introduction: The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function. Methods: nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221). Results: Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 76 dangerous, and I-Mutant found 66 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type. Conclusions: Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders.

Abstract Mutations in the RYR1 gene, encoding ryanodine receptor 1 (RyR1), are a well-known cause of Central Core Disease (CCD) and Multi-minicore Disease (MmD). We screened a cohort of 153 patients carrying an histopathological diagnosis of core myopathy (cores and minicores) for RYR1 mutation. At least one RYR1 mutation was identified in 69 of them and these patients were further studied. Clinical and histopathological features were collected. Clinical phenotype was highly heterogeneous ranging from asymptomatic or paucisymptomatic hyperCKemia to severe muscle weakness and skeletal deformity with loss of ambulation. Sixty-eight RYR1 mutations, generally missense, were identified, of which 16 were novel. The combined analysis of the clinical presentation, disease progression and the structural bioinformatic analyses of RYR1 allowed to associate some phenotypes to mutations in specific domains. In addition, this study highlighted the structural bioinformatics potential in the prediction of the pathogenicity of RYR1 mutations. Further improvement in the comprehension of genotype–phenotype relationship of core myopathies can be expected in the next future: the actual lack of the human RyR1 crystal structure paired with the presence of large intrinsically disordered regions in RyR1, and the frequent presence of more than one RYR1 mutation in core myopathy patients, require designing novel investigation strategies to completely address RyR1 mutation effect.

Visual opsins of vertebrates and invertebrates diversified independently and converged to detect ultraviolet to long wavelengths (LW) of green or red light. In both groups, colour vision largely derives from opsin number, expression patterns and changes in amino acids interacting with the chromophore. Functional insights regarding invertebrate opsin evolution have lagged behind those for vertebrates because of the disparity in genomic resources and the lack of robust in vitro systems to characterize spectral sensitivities. Here, we review bioinformatic approaches to identify and model functional variation in opsins as well as recently developed assays to measure spectral phenotypes. In particular, we discuss how transgenic lines, cAMP-spectroscopy and sensitive heterologous expression platforms are starting to decouple genotype–phenotype relationships of LW opsins to complement the classical physiological-behavioural-phylogenetic toolbox of invertebrate visual sensory studies. We illustrate the use of one heterologous method by characterizing novel LW Gq opsins from 10 species, including diurnal and nocturnal Lepidoptera, a terrestrial dragonfly and an aquatic crustacean, expressing them in HEK293T cells, and showing that their maximum absorbance spectra (λmax) range from 518 to 611 nm. We discuss the advantages of molecular approaches for arthropods with complications such as restricted availability, lateral filters, specialized photochemistry and/or electrophysiological constraints. This article is part of the theme issue 'Understanding colour vision: molecular, physiological, neuronal and behavioural studies in arthropods'. [ABSTRACT FROM AUTHOR]

Multi-drug resistant (MDR) Shigella flexneri 2a, one of the leading bacterial agents of diarrhoeal mortality, has posed challenges in treatment strategies. The present study was conducted to identify potential therapeutic biomarkers using gene interaction network (GIN) in order to understand the cellular and molecular level interactions of both antimicrobial resistance (AMR) and virulence genes through topological and clustering metrics. Statistically significant differential gene expression (DGE), structural chemistry and dynamics were incorporated to elucidate biomarker for sustainable therapeutic regimen against MDR S. flexneri. Functional enrichments and topological metrics revealed evgS, ybjZ, tolC, gyrA, parC and their direct interactors to be associated with diverse AMR mechanisms. Histidine kinase EvgS was considered as the hub protein due to its highest prevalence in the molecular interactome profiles of both the AMR (71.6%) and virulence (45.8%) clusters interconnecting several genes concerning two-component system (TCS). DGE profiles of ΔPhoPQ (deleted regulatory PhoP and sensor PhoQ) led to the upregulation of TCS comprising EvgSA thereby validating EvgS as a promising therapeutic biomarker. Druggability and structural stability of EvgS was assessed through thermal shifts, backbone stability and coarse dynamics refinement. Structure–function relationship was established revealing the C-terminal extracellular domain as the drug-binding site which was further validated through molecular dynamics simulation. Structure elucidation of identified biomarker followed by secondary and tertiary structural validation would prove pivotal for future therapeutic interventions against subverting both AMR and virulence posed by this strain. [ABSTRACT FROM AUTHOR]

Aluminum (Al) toxicity poses a significant challenge for the yield improvement of chickpea, which is an economically important legume crop with high nutritional value in human diets. The genetic basis of Al-tolerance in chickpea remains unclear. Here, we assessed the Al-tolerance of 8 wild Cicer and one cultivated chickpea (PBA Pistol) accessions by measuring the root elongation in solution culture under control (0 μM Al3+) and Al treatments (15, 30 mM Al3+). Compared to PBA Pistol, the wild Cicer accessions displayed both tolerant and sensitive phenotypes, supporting wild Cicer as a potential genetic pool for Al-tolerance improvement. To identify potential genes related to Al-tolerance in chickpea, genome-wide screening of multidrug and toxic compound extrusion (MATE) encoding genes was performed. Fifty-six MATE genes were identified in total, which can be divided into 4 major phylogenetic groups. Four chickpea MATE genes (CaMATE1-4) were clustered with the previously characterized citrate transporters MtMATE66 and MtMATE69 in Medicago truncatula. Transcriptome data showed that CaMATE1-4 have diverse expression profiles, with CaMATE2 being rootspecific. qRT-PCR analyses confirmed that CaMATE2 and CaMATE4 were highly expressed in root tips and were up-regulated upon Al treatment in all chickpea lines. Further measurement of carboxylic acids showed that malonic acid, instead of malate or citrate, is the major extruded acid by Cicer spp. root. Protein structural modeling analyses revealed that CaMATE2 has a divergent substrate-binding cavity from Arabidopsis AtFRD3, which may explain the different acid-secretion profile for chickpea. Pangenome survey showed that CaMATE1-4 have much higher genetic diversity in wild Cicer than that in cultivated chickpea. This first identification of CaMATE2 and CaMATE4 responsive to Al3+ treatment in Cicer paves the way for future functional characterization of MATE genes in Cicer spp., and to facilitate future design of gene-specific markers for Al-tolerant line selection in chickpea breeding programs. [ABSTRACT FROM AUTHOR]

Abstract Background Boltzmann machines are energy-based models that have been shown to provide an accurate statistical description of domains of evolutionary-related protein and RNA families. They are parametrized in terms of local biases accounting for residue conservation, and pairwise terms to model epistatic coevolution between residues. From the model parameters, it is possible to extract an accurate prediction of the three-dimensional contact map of the target domain. More recently, the accuracy of these models has been also assessed in terms of their ability in predicting mutational effects and generating in silico functional sequences. Results Our adaptive implementation of Boltzmann machine learning, adabmDCA, can be generally applied to both protein and RNA families and accomplishes several learning set-ups, depending on the complexity of the input data and on the user requirements. The code is fully available at https://github.com/anna-pa-m/adabmDCA . As an example, we have performed the learning of three Boltzmann machines modeling the Kunitz and Beta-lactamase2 protein domains and TPP-riboswitch RNA domain. Conclusions The models learned by adabmDCA are comparable to those obtained by state-of-the-art techniques for this task, in terms of the quality of the inferred contact map as well as of the synthetically generated sequences. In addition, the code implements both equilibrium and out-of-equilibrium learning, which allows for an accurate and lossless training when the equilibrium one is prohibitive in terms of computational time, and allows for pruning irrelevant parameters using an information-based criterion.

Background: Aldehyde dehydrogenases (ALDHs) are a family of NAD(P)+ dependent enzymes that detoxify aldehydes by promoting their oxidation to respective carboxylic acids. The role of ALDH enzymes in various plant species has been extensively studied, revealing their critical role in salinity, drought, heat, and heavy metal stress tolerance. Despite their physiological significance, ALDH genes in Sorghum bicolor have yet to be studied thoroughly. Results: In this study, a total of 19 ALDH genes have been identified that have been grouped into ten families based on the criteria of the ALDH gene nomenclature committee. Segmental duplication assisted more in the enhancement of SbALDH gene family members than tandem duplication. All the identified SbALDH members made a cluster with monocot rice and maize in the phylogenetic tree rather than dicot species, suggesting the pre-eudicot-monocot separation of the ALDH superfamily members. The gene structure and protein domain were found to be mostly conserved in separate phylogenetic classes, indicating that each family played an important role in evolution. Expression analysis revealed that several SbALDHs were expressed in various tissues, developmental stages, and in response to abiotic stresses, indicating that they can play roles in plant growth, development, or stress adaptation. Interestingly, the majority of the SbALDH genes were found to be highly responsive to drought stress, and the SbALDH18B1 transcript showed maximum enhancement in all the stress conditions. The presence of cis-acting elements (mainly ABRE and MBS) in the promoter region of these genes might have a significant role in drought tolerance. Conclusions: Our findings add to the current understanding, evolutionary history, and contribution of SbALDHs in stress tolerance, and smooth the path of further functional validation of these genes. [ABSTRACT FROM AUTHOR]

Protease inhibitors are widely studied since the unrestricted activity of proteases can cause extensive organ lesions. In particular, elastase activity is involved in the pathophysiology of acute lung injury, for example during SARS-CoV-2 infection, while serine proteases and thrombin-like proteases are involved in the development and/or pathology of the nervous system. Natural protease inhibitors have the advantage to be reversible and with few side effects and thus are increasingly considered as new drugs. Kunitz-type protease inhibitors (KTPIs), reported in the venom of various organisms, such as wasps, spiders, scorpions, and snakes, have been studied for their potent anticoagulant activity and widespread protease inhibitor activity. Putative KTPI anticoagulants have been identified in transcriptomic resources obtained for two blister beetle species, Lydus trimaculatus and Mylabris variabilis. The KTPIs of L. trimaculatus and M. variabilis were characterized by combined transcriptomic and bioinformatics methodologies. The full-length mRNA sequences were divided on the base of the sequence of the active sites of the putative proteins. In silico protein structure analyses of each group of translational products show the biochemical features of the active sites and the potential protease targets. Validation of these genes is the first step for considering these molecules as new drugs for use in medicine. [ABSTRACT FROM AUTHOR]

Antifreeze proteins (AFPs) from the model crop, Brachypodium distachyon, allow freeze survival and attenuate pathogen-mediated ice nucleation. Intriguingly, Brachypodium AFP genes encode two proteins, an autonomous AFP and a leucine-rich repeat (LRR). We present structural models which indicate that ice-binding motifs on the ~13 kDa AFPs can "spoil" nucleating arrays on the ~120 kDa bacterial ice nucleating proteins used to form ice at high sub-zero temperatures. These models are consistent with the experimentally demonstrated decreases in ice nucleating activity by lysates from wildtype compared to transgenic Brachypodium lines. Additionally, the expression of Brachypodium LRRs in transgenic Arabidopsis inhibited an immune response to pathogen flagella peptides (flg22). Structural models suggested that this was due to the affinity of the LRR domains to flg22. Overall, it is remarkable that the Brachypodium genes play multiple distinctive roles in connecting freeze survival and anti-pathogenic systems via their encoded proteins' ability to adsorb to ice as well as to attenuate bacterial ice nucleation and the host immune response. [ABSTRACT FROM AUTHOR]

Abstract Background Animal mitochondria play a central role in energy production in the cells through the oxidative phosphorylation (OXPHOS) pathway. Recent studies of selection on different mitochondrial OXPHOS genes have revealed the adaptive implications of amino acid changes in these subunits. In hares, climatic variation and/or introgression were suggested to be at the origin of such adaptation. Here we looked for evidence of positive selection in three mitochondrial OXPHOS genes, using tests of selection, protein structure modelling and effects of amino acid substitutions on the protein function and stability. We also used statistical models to test for climate and introgression effects on sites under positive selection. Results Our results revealed seven sites under positive selection in ND4 and three sites in Cytb. However, no sites under positive selection were observed in the COX1 gene. All three subunits presented a high number of codons under negative selection. Sites under positive selection were mapped on the tridimensional structure of the predicted models for the respective mitochondrial subunit. Of the ten amino acid replacements inferred to have evolved under positive selection for both subunits, six were located in the transmembrane domain. On the other hand, three codons were identified as sites lining proton translocation channels. Furthermore, four codons were identified as destabilizing with a significant variation of Δ vibrational entropy energy between wild and mutant type. Moreover, our PROVEAN analysis suggested that among all positively selected sites two fixed amino acid replacements altered the protein functioning. Our statistical models indicated significant effects of climate on the presence of ND4 and Cytb protein variants, but no effect by trans-specific mitochondrial DNA introgression, which is not uncommon in a number of hare species. Conclusions Positive selection was observed in several codons in two OXPHOS genes. We found that substitutions in the positively selected codons have structural and functional impacts on the encoded proteins. Our results are concordantly suggesting that adaptations have strongly affected the evolution of mtDNA of hare species with potential effects on the protein function. Environmental/climatic changes appear to be a major trigger of this adaptation, whereas trans-specific introgressive hybridization seems to play no major role for the occurrence of protein variants.

Mutations in the RYR1 gene, encoding ryanodine receptor 1 (RyR1), are a well-known cause of Central Core Disease (CCD) and Multi-minicore Disease (MmD). We screened a cohort of 153 patients carrying an histopathological diagnosis of core myopathy (cores and minicores) for RYR1 mutation. At least one RYR1 mutation was identified in 69 of them and these patients were further studied. Clinical and histopathological features were collected. Clinical phenotype was highly heterogeneous ranging from asymptomatic or paucisymptomatic hyperCKemia to severe muscle weakness and skeletal deformity with loss of ambulation. Sixty-eight RYR1 mutations, generally missense, were identified, of which 16 were novel. The combined analysis of the clinical presentation, disease progression and the structural bioinformatic analyses of RYR1 allowed to associate some phenotypes to mutations in specific domains. In addition, this study highlighted the structural bioinformatics potential in the prediction of the pathogenicity of RYR1 mutations. Further improvement in the comprehension of genotype–phenotype relationship of core myopathies can be expected in the next future: the actual lack of the human RyR1 crystal structure paired with the presence of large intrinsically disordered regions in RyR1, and the frequent presence of more than one RYR1 mutation in core myopathy patients, require designing novel investigation strategies to completely address RyR1 mutation effect. [ABSTRACT FROM AUTHOR]

G555F mutant of Fibrinogen A alpha-chain (FGA) is reported to be associated with kidney amyloidosis. In the current study, we have modelled the G555F mutant and examined the mutation's effect on the structural and functional level. We have also docked Vitamin C and D3 on the mutant's amyloidogenic region to identify if these vitamins can bind amyloidogenic regions. Further, we analyzed if they could prevent or modulate amyloid formation by stopping critical interactions in amyloidogenic regions in FGA. We used the wild type FGA model protein as a control. Our docking and molecular dynamics simulation results indicate stronger Vitamin D3 binding than Vitamin C to the amyloidogenic region of the mutant protein. The RMSD, radius of gyration, and RMSF values were higher for the G555F mutant than the FGA wild type protein. Overall, the results support these vitamins' potential as a therapeutic and anti-amyloidogenic agent for FGA renal amyloidosis. [ABSTRACT FROM AUTHOR]

Human menin is a nuclear protein that participates in many cellular processes, as transcriptional regulation, DNA damage repair, cell signaling, cell division, proliferation, and migration, by interacting with many other proteins. Mutations of the gene encoding menin cause multiple endocrine neoplasia type 1 (MEN1), a rare autosomal dominant disorder associated with tumors of the endocrine glands. In order to characterize the structural and functional effects at protein level of the hundreds of missense variations, we investigated by computational methods the wild-type menin and more than 200 variants, predicting the amino acid variations that change secondary structure, solvent accessibility, salt-bridge and H-bond interactions, protein thermostability, and altering the capability to bind known protein interactors. The structural analyses are freely accessible online by means of a web interface that integrates also a 3D visualization of the structure of the wild-type and variant proteins. The results of the study offer insight into the effects of the amino acid variations in view of a more complete understanding of their pathological role. [ABSTRACT FROM AUTHOR]

Background and Objectives: The pathogenic variants of SLC9A6 are a known cause of a rare, X-linked neurological disorder called Christianson syndrome (CS). The main characteristics of CS are developmental delay, intellectual disability, and neurological findings. This study investigated the genetic basis and explored the molecular changes that led to CS in two male siblings presenting with intellectual disability, epilepsy, behavioural problems, gastrointestinal dysfunction, poor height, and weight gain. Materials and Methods: Next-generation sequencing of a tetrad was applied to identify the DNA changes and Sanger sequencing of proband's cDNA was used to evaluate the impact of a splice site variant on mRNA structure. Bioinformatical tools were used to investigate SLC9A6 protein structure changes. Results: Sequencing and bioinformatical analysis revealed a novel donor splice site variant (NC_000023.11(NM_001042537.1):c.899 + 1G > A) that leads to a frameshift and a premature stop codon. Protein structure modelling showed that the truncated protein is unlikely to form any functionally relevant SLC9A6 dimers. Conclusions: Molecular and bioinformatical analysis revealed the impact of a novel donor splice site variant in the SLC9A6 gene that leads to truncated and functionally disrupted protein causing the phenotype of CS in the affected individuals. [ABSTRACT FROM AUTHOR]

Since its discovery, bovine theileriosis has caused major socioeconomic losses in sub-Saharan Africa. Acaricide resistance of the intermediate host, paucity of therapeutics, and lack of sufficiently cross-protective vaccines increase the risk of parasite spread due to global warming. Here, we highlight three important areas that require investigation to develop next-generation vaccines. [ABSTRACT FROM AUTHOR]

The rapid developments in gene sequencing technologies achieved in the recent decades, along with the expansion of knowledge on the three-dimensional structures of proteins, have enabled the construction of proteome-scale databases of protein models such as the Genome3D and ModBase. Nevertheless, although gene products are usually expressed as individual polypeptide chains, most biological processes are associated with either transient or stable oligomerisation. In the PDB databank, for example, ~40% of the deposited structures contain at least one homo-oligomeric interface. Unfortunately, databases of protein models are generally devoid of multimeric structures. To tackle this particular issue, we have developed ProtCHOIR, a tool that is able to generate homo-oligomeric structures in an automated fashion, providing detailed information for the input protein and output complex. ProtCHOIR requires input of either a sequence or a protomeric structure that is queried against a pre-constructed local database of homo-oligomeric structures, then extensively analyzed using well-established tools such as PSI-Blast, MAFFT, PISA and Molprobity. Finally, MODELLER is employed to achieve the construction of the homo-oligomers. The output complex is thoroughly analyzed taking into account its stereochemical quality, interfacial stabilities, hydrophobicity and conservation profile. All these data are then summarized in a user-friendly HTML report that can be saved or printed as a PDF file. The software is easily parallelizable and also outputs a comma-separated file with summary statistics that can straightforwardly be concatenated as a spreadsheet-like document for large-scale data analyses. As a proof-of-concept, we built oligomeric models for the Mabellini Mycobacterium abscessus structural proteome database. ProtCHOIR can be run as a web-service and the code can be obtained free-of-charge at http://lmdm.biof.ufrj.br/protchoir. [ABSTRACT FROM AUTHOR]

Abstract Background Coronavirus disease 2019 (COVID-19) is an emerging zoonotic viral infection, which was started in Wuhan, China, in December 2019 and transmitted to other countries worldwide as a pandemic outbreak. Iran is one of the top ranked countries in the tables of COVID-19-infected and -mortality cases that make the Iranian patients as the potential targets for diversity of studies including epidemiology, biomedical, biodata, and viral proteins computational modelling studies. Results In this study, we applied bioinformatic biodata mining methods to detect CDS and protein sequences of ORF1ab polyprotein of SARS-CoV-2 isolated from oronasopharynx of an Iranian patient. Then through the computational modelling and antigenicity prediction approaches, the identified polyprotein sequence was analyzed. The results revealed that the identified ORF1ab polyprotein belongs to a part of nonstructural protein 1 (nsp1) with the high antigenicity residues in a glycine-proline or hydrophobic amino acid rich domain. Conclusions The results revealed that nsp1 as a virulence factor and crucial agent in spreading of the COVID-19 among the society can be a potential target for the future epidemiology, drug, and vaccine studies.

Burkholderia pseudomallei is regarded as a global threat because of its ability to cause melioidosis, and potential as bioweapon. Intrinsic resistance to frontline antibiotics remains a major challenge in treating melioidosis. The increasing global burden of B. pseudomallei triggers the need to develop effective drugs and vaccine for controlling this pathogen. Therefore, we analyzed the whole proteome of B. pseudomallei K96243 using subtractive proteomic and immune-informatic analysis to find out potential drug target and vaccine candidate. Our analysis revealed 45 essential and non-homologous metabolic proteins, involved in different unique metabolic pathways. 36 out of 45 proteins can serve as novel drug targets and the remaining proteins had already been targeted with experimental drugs. 2 novel targets of cytoplasmic localization, namely dihydroneopterin aldolase and phosphoribosyl transferase were subjected to molecular docking with 14 antibiotics, which revealed the strong binding affinity of cefiderocol and tetracycline to the identified targets. Moreover, 100 ns molecular dynamic simulation and MM-PBSA calculation revealed the stability of drug-protein complexes. On the contrary, highly antigenic, non-allergic and non-toxic epitopes from three essential outer membrane proteins were joined by linkers and adjuvant to construct a chimeric peptide vaccine. The vaccine construct could efficiently bind to TLR-4 and generated robust immune response. The vaccine-receptor complex showed minimum deformability and good stability. Overall, our findings will aid in designing new inhibitors that disrupts the functionality of proposed targets and in the development of subunit vaccine for the therapeutic and prophylactic management of B. pseudomallei.

Background: Boltzmann machines are energy-based models that have been shown to provide an accurate statistical description of domains of evolutionary-related protein and RNA families. They are parametrized in terms of local biases accounting for residue conservation, and pairwise terms to model epistatic coevolution between residues. From the model parameters, it is possible to extract an accurate prediction of the three-dimensional contact map of the target domain. More recently, the accuracy of these models has been also assessed in terms of their ability in predicting mutational effects and generating in silico functional sequences. Results: Our adaptive implementation of Boltzmann machine learning, adabmDCA, can be generally applied to both protein and RNA families and accomplishes several learning set-ups, depending on the complexity of the input data and on the user requirements. The code is fully available at https://github.com/anna-pa-m/adabmDCA. As an example, we have performed the learning of three Boltzmann machines modeling the Kunitz and Beta-lactamase2 protein domains and TPP-riboswitch RNA domain. Conclusions: The models learned by adabmDCA are comparable to those obtained by state-of-the-art techniques for this task, in terms of the quality of the inferred contact map as well as of the synthetically generated sequences. In addition, the code implements both equilibrium and out-of-equilibrium learning, which allows for an accurate and lossless training when the equilibrium one is prohibitive in terms of computational time, and allows for pruning irrelevant parameters using an information-based criterion. [ABSTRACT FROM AUTHOR]

This study describes the identification of two new mutations of the fibrinogen beta-chain in patients with inherited fibrinogen deficiency. Modelling of the impact of the mutations predict that these single amino acid substitutions are sufficient to abolish secretion of the mutant chains into the circulation, resulting in low fibrinogen levels in the patients. In addition, whole exome sequencing identified genetic modifiers for both patients which could contribute to the patients' global hemostatic function. Our results yield clinically relevant information for the personalised management of patients and eventually precision medicine for fibrinogen disorders. [ABSTRACT FROM AUTHOR]

The metabolism of polyphenolic polymers is essential to the development and response to environmental changes of organisms from all kingdoms of life, but shows particular diversity in plants. In contrast to other biopolymers, whose polymerisation is catalysed by homologous gene families, polyphenolic metabolism depends on phenoloxidases, a group of heterogeneous oxidases that share little beyond the eponymous common substrate. In this review, we provide an overview of the differences and similarities between phenoloxidases in their protein structure, reaction mechanism, substrate specificity, and functional roles. Using the example of laccases (LACs), we also performed a meta-analysis of enzyme kinetics, a comprehensive phylogenetic analysis and machine-learning based protein structure modelling to link functions, evolution, and structures in this group of phenoloxidases. With these approaches, we generated a framework to explain the reported functional differences between paralogs, while also hinting at the likely diversity of yet undescribed LAC functions. Altogether, this review provides a basis to better understand the functional overlaps and specificities between and within the three major families of phenoloxidases, their evolutionary trajectories, and their importance for plant primary and secondary metabolism. [ABSTRACT FROM AUTHOR]

Isoflavonoid synthase (IFS) is a critical enzyme for the biosynthesis of over 2400 isoflavonoids. Isoflavonoids are an important class of plant secondary metabolites that have a range of pharmaceutical and nutraceutical properties. With growing interest in isoflavonoids from both research and industrial perspectives, efforts are being forwarded to enhance isoflavonoid production in-planta and ex-planta; therefore, in-silico analysis and characterisation of available IFS protein sequences are needed. The present study is the first-ever attempt toward phylogenetic analysis and protein modelling of available IFS protein sequences. Phylogenetic analysis has shown that IFS amino acid sequences have 86.4% pairwise identity and 26.5% identical sites, and the sequences were grouped into six different clades. The presence of a β-hairpin and extra loop at catalytic sites of Trifolium pratense, Beta vulgaris and Medicago truncatula, respectively, compared with Glycyrrhiza echinata are critical structural differences that may affect catalytic function. Protein docking highlighted the preference of selected IFS for liquiritigenin compared with naringenin and has listed T. pratense as the most efficient candidate for heterologous biosynthesis of isoflavonoids. The in-silico characterisation of IFS represented in this study is vital in realising the new bioengineering endeavours and will help in the characterisation and selection of IFS candidate enzymes for heterologous biosynthesis of isoflavonoids.

Background: Animal mitochondria play a central role in energy production in the cells through the oxidative phosphorylation (OXPHOS) pathway. Recent studies of selection on different mitochondrial OXPHOS genes have revealed the adaptive implications of amino acid changes in these subunits. In hares, climatic variation and/or introgression were suggested to be at the origin of such adaptation. Here we looked for evidence of positive selection in three mitochondrial OXPHOS genes, using tests of selection, protein structure modelling and effects of amino acid substitutions on the protein function and stability. We also used statistical models to test for climate and introgression effects on sites under positive selection. Results: Our results revealed seven sites under positive selection in ND4 and three sites in Cytb. However, no sites under positive selection were observed in the COX1 gene. All three subunits presented a high number of codons under negative selection. Sites under positive selection were mapped on the tridimensional structure of the predicted models for the respective mitochondrial subunit. Of the ten amino acid replacements inferred to have evolved under positive selection for both subunits, six were located in the transmembrane domain. On the other hand, three codons were identified as sites lining proton translocation channels. Furthermore, four codons were identified as destabilizing with a significant variation of - vibrational entropy energy between wild and mutant type. Moreover, our PROVEAN analysis suggested that among all positively selected sites two fixed amino acid replacements altered the protein functioning. Our statistical models indicated significant effects of climate on the presence of ND4 and Cytb protein variants, but no effect by trans-specific mitochondrial DNA introgression, which is not uncommon in a number of hare species. Conclusions: Positive selection was observed in several codons in two OXPHOS genes. We found that substitutions in the positively selected codons have structural and functional impacts on the encoded proteins. Our results are concordantly suggesting that adaptations have strongly affected the evolution of mtDNA of hare species with potential effects on the protein function. Environmental/climatic changes appear to be a major trigger of this adaptation, whereas trans-specific introgressive hybridization seems to play no major role for the occurrence of protein variants. [ABSTRACT FROM AUTHOR]

The majority of picornaviral 3C proteinases (3Cpro) cleavage sites possess glutamine at the P1 position. Plant nepovirus 3C-like proteinases (3CLpro) show however much broader specificity, cleaving not only after glutamine, but also after several basic and hydrophobic residues. To investigate this difference, we employed AlphaFold to generate structural models of twelve selected 3CLpro, representing six substrate specificities. Generally, we observed favorable correlations between the architecture and charge of nepovirus proteinase S1 subsites and their ability to accept or restrict larger residues. The models identified a conserved aspartate residue close to the P1 residue in the S1 subsites of all nepovirus proteinases examined, consistent with the observed strong bias against negatively-charged residues at the P1 position of nepovirus cleavage sites. Finally, a cramped S4 subsite along with the presence of two unique histidine and serine residues explains the strict requirement of the grapevine fanleaf virus proteinase for serine at the P4 position. • We used AlphaFold to generate models of twelve nepovirus proteinases. • All models show close relationships to picornavirus 3C proteinases. • The residues found in the S1 pockets of the nepovirus proteinases differ. • These differences can explain the varied specificities of the nepovirus proteinases. • Comparison of the models illuminates the evolution of the proteinases. [ABSTRACT FROM AUTHOR]

A strain of Microbacterium kitamiense capable of decomposing cellulose was obtained from the soil of Shigatse region in Tibet. Low temperature and cellulase gene MkCel5 was cloned and sequenced. The size of the open-reading frame was 1449 bp; it was predicted to encode a polypeptide with 482 residues with a molecular weight of 51.38 kDa. Sequence analysis indicated that it belongs to the glycoside hydrolase family 5 (GH5), which has high homology with reported endoglucanases. The predicted protein structure had a typical carbohydrate-binding domain and a catalytic domain of cellulase. Site mutagenesis experiments showed that the two glutamates at positions 312 and 404 were crucial in the catalytic process. MkCel5 was identified as a cold-adaptive and neutral enzyme with a maximum activity at 25 °C and pH 7.0. These properties suggested that MkCel5 has potential for application in the cellulose processing industry requiring low temperature.

Protease inhibitors are widely studied since the unrestricted activity of proteases can cause extensive organ lesions. In particular, elastase activity is involved in the pathophysiology of acute lung injury, for example during SARS-CoV-2 infection, while serine proteases and thrombin-like proteases are involved in the development and/or pathology of the nervous system. Natural protease inhibitors have the advantage to be reversible and with few side effects and thus are increasingly considered as new drugs. Kunitz-type protease inhibitors (KTPIs), reported in the venom of various organisms, such as wasps, spiders, scorpions, and snakes, have been studied for their potent anticoagulant activity and widespread protease inhibitor activity. Putative KTPI anticoagulants have been identified in transcriptomic resources obtained for two blister beetle species, Lydus trimaculatus and Mylabris variabilis. The KTPIs of L. trimaculatus and M. variabilis were characterized by combined transcriptomic and bioinformatics methodologies. The full-length mRNA sequences were divided on the base of the sequence of the active sites of the putative proteins. In silico protein structure analyses of each group of translational products show the biochemical features of the active sites and the potential protease targets. Validation of these genes is the first step for considering these molecules as new drugs for use in medicine.

Antifreeze proteins (AFPs) from the model crop, Brachypodium distachyon, allow freeze survival and attenuate pathogen-mediated ice nucleation. Intriguingly, Brachypodium AFP genes encode two proteins, an autonomous AFP and a leucine-rich repeat (LRR). We present structural models which indicate that ice-binding motifs on the ~13 kDa AFPs can “spoil” nucleating arrays on the ~120 kDa bacterial ice nucleating proteins used to form ice at high sub-zero temperatures. These models are consistent with the experimentally demonstrated decreases in ice nucleating activity by lysates from wildtype compared to transgenic Brachypodium lines. Additionally, the expression of Brachypodium LRRs in transgenic Arabidopsis inhibited an immune response to pathogen flagella peptides (flg22). Structural models suggested that this was due to the affinity of the LRR domains to flg22. Overall, it is remarkable that the Brachypodium genes play multiple distinctive roles in connecting freeze survival and anti-pathogenic systems via their encoded proteins’ ability to adsorb to ice as well as to attenuate bacterial ice nucleation and the host immune response.

The causative agent of the viral pneumonia outbreak in the world identified as SARS-CoV-2 leads to a severe respiratory illness like SARS and MERS. The pathogen spreading has turned into a pandemic dissemination and increased the mortality rate. Therefore, any useful information is essential for effective control of the disease. Our findings show the existence of unvarying sequence with no mutation in ORFlab regions from 134 high-quality filtered genome sequences ofSARS-CoV-2 downloaded from the GISAID database. We have detected this sequence region by using MAUVE analysis and pairwise alignment using Global Needleman Wunsch algorithm. All these results were also confirmed with the Clustal W analysis. The first 6500 bp of the consensus genome including ORFlab region is an unvarying sequence in SARS-CoV-2 genome. Unvarying sequence in SARS-Co V-2 genome has been very similar to another spike protein, which belongs to feline infectious peritonitis virus strain UU4 (PDB 6JX7), depending on amino acid sequences encoded, and N-acetyl-D-glucosamine is the ligand of this protein according to the highest TM-score of predicted protein structure analysis. These results have confirmed that N-acetyl-D-glucosamine could play an important effect on pathogenicity of SARS-Co V- 2. Also, our molecular docking analysis data supports a strong protein-ligand interaction ofN-acetylD- glucosamine with spike receptor-binding domain bound with ACE2 (PDB 6MOJ) and RNA-binding domain of nucleocapsid phosphoprotein (PDB 6WKP) from SARS-CoV-2. Therefore, binding of N-acetyl-D-glucosamine to these proteins could inhibit SARS-CoV-2's replication. In the present work, we have suggested providing a repurposing compound for further in vitro and in vivo studies and new insights for ongoing clinical treatments as a new strategy to control of SARS-Co V-2 infections. [ABSTRACT FROM AUTHOR]