Comparative Molecular Mechanisms of Biosynthesis of Naringenin and Related Chalcones in Actinobacteria and Plants: Relevance for the Obtention of Potent Bioactive Metabolites

Naringenin and its glycosylated derivative naringin are flavonoids that are synthesized by the phenylpropanoid pathway in plants. We found that naringenin is also formed by the actinobacterium Streptomyces clavuligerus, a well-known microorganism used to industrially produce clavulanic acid. The production of naringenin in S. clavuligerus involves a chalcone synthase that uses p-coumaric as a starter unit and a P450 monoxygenase, encoded by two adjacent genes (ncs-ncyP). The p-coumaric acid starter unit is formed by a tyrosine ammonia lyase encoded by an unlinked, tal, gene. Deletion and complementation studies demonstrate that these three genes are required for biosynthesis of naringenin in S. clavuligerus. Other actinobacteria chalcone synthases use caffeic acid, ferulic acid, sinapic acid or benzoic acid as starter units in the formation of different antibiotics and antitumor agents. The biosynthesis of naringenin is restricted to a few Streptomycess species and the encoding gene cluster is present also in some Saccharotrix and Kitasatospora species. Phylogenetic comparison of S. clavuligerus naringenin chalcone synthase with homologous proteins of other actinobacteria reveal that this protein is closely related to chalcone synthases that use malonyl-CoA as a starter unit for the formation of red-brown pigment. The function of the core enzymes in the pathway, such as the chalcone synthase and the tyrosine ammonia lyase, is conserved in plants and actinobacteria. However, S. clavuligerus use a P450 monooxygenase proposed to complete the cyclization step of the naringenin chalcone, whereas this reaction in plants is performed by a chalcone isomerase. Comparison of the plant and S. clavuligerus chalcone synthases indicates that they have not been transmitted between these organisms by a recent horizontal gene transfer phenomenon. We provide a comprehensive view of the molecular genetics and biochemistry of chalcone synthases and their impact on the development of antibacterial and antitumor compounds. These advances allow new bioactive compounds to be obtained using combinatorial strategies. In addition, processes of heterologous expression and bioconversion for the production of naringenin and naringenin-derived compounds in yeasts are described.

Genome-wide sequence identification and expression analysis of N6-methyladenosine demethylase in sugar beet (Beta vulgaris L.) under salt stress

In eukaryotes, N6-methyladenosine (m6A) is the most abundant and highly conserved RNA modification. In vivo, m6A demethylase dynamically regulates the m6A level by removing the m6A marker where it plays an important role in plant growth, development and response to abiotic stress. The confirmed m6A demethylases in Arabidopsis thaliana include ALKBH9B and ALKBH10B, both belonging to the ALKB family. In this study, BvALKB family members were identified in sugar beet genome-wide database, and their conserved domains, gene structures, chromosomal locations, phylogeny, conserved motifs and expression of BvALKB genes were analyzed. Almost all BvALKB proteins contained the conserved domain of 2OG-Fe II-Oxy. Phylogenetic analysis suggested that the ten proteins were clustered into five groups, each of which had similar motifs and gene structures. Three Arabidopsis m6A demethylase-homologous proteins (BvALKBH6B, BvALKBH8B and BvALKBH10B) were of particular interest in our study. Expression profile analysis showed that almost all genes were up-regulated or down-regulated to varying degrees under salt stress. More specifically, BvALKBH10B homologous to AtALKBH10B was significantly up-regulated, suggesting that the transcriptional activity of this gene is responsive to salt stress. This study provides a theoretical basis for further screening of m6A demethylase in sugar beet, and also lays a foundation for studying the role of ALKB family proteins in growth, development and response to salinity stress.

Identification of Conserved Epitopes in SARS-CoV-2 Spike and Nucleocapsid Protein

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel virus that first occurred in Wuhan in December 2019. The spike glycoproteins and nucleocapsid proteins are the most common targets for the development of vaccines and antiviral drugs. Objective: We herein analyze the rate of evolution along with the sequences of spike and nucleocapsid proteins in relation to the spatial locations of their epitopes, previously suggested to contribute to the immune response caused by SARS-CoV-2 infections. Methods: We compare homologous proteins of seven human coronaviruses: HCoV-229E, HCoV-OC43, SARS-CoV, HCoV-NL63, HCoV-HKU1, MERS-CoV, and SARS-CoV-2. We then focus on the local, structural order-disorder propensity of the protein regions where the SARS-CoV-2 epitopes are located. Results : We show that most of nucleocapsid protein epitopes overlap the RNA-binding and dimerization domains, and some of them are characterized by a low rate of evolutions. Similarly, spike protein epitopes are preferentially located in regions that are predicted to be ordered and well-conserved, in correspondence of the heptad repeats 1 and 2. Interestingly, both the receptor-binding motif to ACE2 and the fusion peptide of spike protein are characterized by a high rate of evolution. Conclusion: Our results provide evidence for conserved epitopes that might help develop broad-spectrum SARS-CoV-2 vaccines.

Effect of Mutations in GvpJ and GvpM on Gas Vesicle Formation of Halobacterium salinarum

The two haloarchaeal proteins, GvpM and GvpJ, are homologous to GvpA, the major gas vesicle structural protein. All three are hydrophobic and essential for gas vesicle formation. The effect of mutations in GvpJ and GvpM was studied in Haloferax volcanii transformants by complementing the respective mutated gene with the remaining gvp genes and inspecting the cells for the presence of gas vesicles (Vac+). In case of GvpJ, 56 of 66 substitutions analyzed yielded Vac– ΔJ + Jmut transformants, indicating that GvpJ is very sensitive to alterations, whereas ten of the 38 GvpM variants resulted in Vac– ΔM + Mmut transformants. The variants were also tested by split-GFP for their ability to interact with their partner protein GvpL. Some of the alterations leading to a Vac– phenotype affected the J/L or M/L interaction. Also, the interactions J/A and J/M were studied using fragments to exclude an unspecific aggregation of these hydrophobic proteins. Both fragments of GvpJ interacted with the M1–25 and M60–84 fragments of GvpM, and fragment J1–56 of GvpJ interacted with the N-terminal fragment A1–22 of GvpA. A comparison of the results on the three homologous proteins indicates that despite their relatedness, GvpA, GvpJ, and GvpM have unique features and cannot substitute each other.

Subtractive genomics and molecular docking approach to identify drug targets against Stenotrophomonas maltophilia

Stenotrophomonas maltophilia is a multidrug resistant pathogen associated with high mortality and morbidity in patients having compromised immunity. The efflux systems of S. maltophilia include SmeABC and SmeDEF proteins, which assist in acquisition of multiple-drug-resistance. In this study, proteome based mapping was utilized to find out the potential drug targets for S. maltophilia strain k279a. Various tools of computational biology were applied to remove the human-specific homologous and pathogen-specific paralogous sequences from the bacterial proteome. The CD-HIT analysis selected 4315 proteins from total proteome count of 4365 proteins. Geptop identified 407 essential proteins, while the BlastP revealed approximately 85 non-homologous proteins in the human genome. Moreover, metabolic pathway and subcellular location analysis were performed for essential bacterial genes, to describe their role in various cellular processes. Only two essential proteins (Acyl-[acyl-carrier-protein]—UDP-N acetyl glucosamine O-acyltransferase and D-alanine-D-alanine ligase) as candidate for potent targets were found in proteome of the pathogen, in order to design new drugs. An online tool, Swiss model was employed to model the 3D structures of both target proteins. A library of 5000 phytochemicals was docked against those proteins through the molecular operating environment (MOE). That resulted in to eight inhibitors for both proteins i.e. enterodiol, aloin, ononin and rhinacanthinF for the Acyl-[acyl-carrier-protein]—UDP-N acetyl glucosamine O-acyltransferase, and rhazin, alkannin beta, aloesin and ancistrocladine for the D-alanine-D-alanine ligase. Finally the ADMET was done through ADMETsar. This study supported the development of natural as well as cost-effective drugs against S. maltophilia. These inhibitors displayed the effective binding interactions and safe drug profiles. However, further in vivo and in vitro validation experiment might be performed to check their drug effectiveness, biocompatibility and their role as effective inhibitors.

Protein Receptors Evolved from Homologous Cohesion Modules That Self-Associated and Are Encoded by Interactive Networked Genes

Previously, it was proposed that protein receptors evolved from self-binding peptides that were encoded by self-interacting gene segments (inverted repeats) widely dispersed in the genome. In addition, self-association of the peptides was thought to be mediated by regions of amino acid sequence similarity. To extend these ideas, special features of receptors have been explored, such as their degree of homology to other proteins, and the arrangement of their genes for clues about their evolutionary origins and dynamics in the genome. As predicted, BLASTP searches for homologous proteins detected a greater number of unique hits for queries with receptor sequences than for sequences of randomly-selected, non-receptor proteins. This suggested that the building blocks (cohesion modules) for receptors were duplicated, dispersed, and maintained in the genome, due to structure/function relationships discussed here. Furthermore, the genes coding for a representative panel of receptors participated in a larger number of gene–gene interactions than for randomly-selected genes. This could conceivably reflect a greater evolutionary conservation of the receptor genes, with their more extensive integration into networks along with inherent properties of the genes themselves. In support of the latter possibility, some receptor genes were located in active areas of adaptive gene relocation/amalgamation to form functional blocks of related genes. It is suggested that adaptive relocation might allow for their joint regulation by common promoters and enhancers, and affect local chromatin structural domains to facilitate or repress gene expression. Speculation is included about the nature of the coordinated communication between receptors and the genes that encode them.

Prediction of Protein Sites and Physicochemical Properties Related to Functional Specificity

Specificity Determining Positions (SDPs) are protein sites responsible for functional specificity within a family of homologous proteins. These positions are extracted from a family’s multiple sequence alignment and complement the fully conserved positions as predictors of functional sites. SDP analysis is now routinely used for locating these specificity-related sites in families of proteins of biomedical or biotechnological interest with the aim of mutating them to switch specificities or design new ones. There are many different approaches for detecting these positions in multiple sequence alignments. Nevertheless, existing methods report the potential SDP positions but they do not provide any clue on the physicochemical basis behind the functional specificity, which has to be inferred a-posteriori by manually inspecting these positions in the alignment. In this work, a new methodology is presented that, concomitantly with the detection of the SDPs, automatically provides information on the amino-acid physicochemical properties more related to the change in specificity. This new method is applied to two different multiple sequence alignments of homologous of the well-studied RasH protein representing different cases of functional specificity and the results discussed in detail.

Pathophysiological Mechanisms in Neurodevelopmental Disorders Caused by Rac GTPases Dysregulation: What’s behind Neuro-RACopathies

Rho family guanosine triphosphatases (GTPases) regulate cellular signaling and cytoskeletal dynamics, playing a pivotal role in cell adhesion, migration, and cell cycle progression. The Rac subfamily of Rho GTPases consists of three highly homologous proteins, Rac 1–3. The proper function of Rac1 and Rac3, and their correct interaction with guanine nucleotide-exchange factors (GEFs) and GTPase-activating proteins (GAPs) are crucial for neural development. Pathogenic variants affecting these delicate biological processes are implicated in different medical conditions in humans, primarily neurodevelopmental disorders (NDDs). In addition to a direct deleterious effect produced by genetic variants in the RAC genes, a dysregulated GTPase activity resulting from an abnormal function of GEFs and GAPs has been involved in the pathogenesis of distinctive emerging conditions. In this study, we reviewed the current pertinent literature on Rac-related disorders with a primary neurological involvement, providing an overview of the current knowledge on the pathophysiological mechanisms involved in the neuro-RACopathies.

The evolved divergence of γ-secretase-susceptibility of homologous proteins Ngfrb and Nradd in zebrafish

Objective NGFR/p75NTR and NRADD/NRH proteins are closely related structurally and are encoded by genes that arose from a duplication event early in vertebrate evolution. The transmembrane domain (TMD) of NGFR is cleaved by γ-secretase but there is conflicting data around the susceptibility to γ-secretase cleavage of NRADD proteins. If NGFR and NRADD show differential susceptibility to γ-secretase, then they can be used to dissect the structural constraints determining substrate susceptibility. We sought to test this differential susceptibility. Results We developed labelled, lumenally-truncated forms of zebrafish Ngfrb and Nradd and a chimeric protein in which the TMD of Nradd was replaced with the TMD of Ngfrb. We expressed these in zebrafish embryos to test their susceptibility to γ-secretase cleavage by monitoring their stability using western immunoblotting. Inhibition of γ-secretase activity using DAPT increased the stability of only the Ngfrb construct. Our results support that only NGFR is cleaved by γ-secretase. Either NGFR evolved γ-secretase-susceptibility since its creation by gene duplication, or NRADD evolved to be refractory to γ-secretase. Protein structure outside of the TMD of NGFR is likely required for susceptibility to γ-secretase.

pyKVFinder: an efficient and integrable Python package for biomolecular cavity detection and characterization in data science

Background Biomolecular interactions that modulate biological processes occur mainly in cavities throughout the surface of biomolecular structures. In the data science era, structural biology has benefited from the increasing availability of biostructural data due to advances in structural determination and computational methods. In this scenario, data-intensive cavity analysis demands efficient scripting routines built on easily manipulated data structures. To fulfill this need, we developed pyKVFinder, a Python package to detect and characterize cavities in biomolecular structures for data science and automated pipelines. Results pyKVFinder efficiently detects cavities in biomolecular structures and computes their volume, area, depth and hydropathy, storing these cavity properties in NumPy arrays. Benefited from Python ecosystem interoperability and data structures, pyKVFinder can be integrated with third-party scientific packages and libraries for mathematical calculations, machine learning and 3D visualization in automated workflows. As proof of pyKVFinder’s capabilities, we successfully identified and compared ADRP substrate-binding site of SARS-CoV-2 and a set of homologous proteins with pyKVFinder, showing its integrability with data science packages such as matplotlib, NGL Viewer, SciPy and Jupyter notebook. Conclusions We introduce an efficient, highly versatile and easily integrable software for detecting and characterizing biomolecular cavities in data science applications and automated protocols. pyKVFinder facilitates biostructural data analysis with scripting routines in the Python ecosystem and can be building blocks for data science and drug design applications.