Evolution and functional role prediction of the CYP6DE and CYP6DJ subfamilies in Dendroctonus (Curculionidae: Scolytinae) bark beetles.

Dendroctonus-bark beetles are natural components and key ecological agents of coniferous forests. They spend most of their lives under the bark, where they are exposed to highly toxic terpenes present in the oleoresin. Cytochrome P450 (CYP) is a multigene family involved in the detoxification of these compounds. It has been demonstrated that CYP6DE and CYP6DJ subfamilies hydroxylate monoterpenes, whose derivatives can act as pheromone synergist compounds or be pheromones themselves in these insects. Given the diversity and functional role of CYPs, we investigated whether these cytochromes have retained their function throughout the evolution of these insects. To test this hypothesis, we performed a Bayesian phylogenetic analysis to determine phylogenetic subgroups of cytochromes in these subfamilies. Subgroups were mapped and reconciled with the Dendroctonus phylogeny. Molecular docking analyses were performed with the cytochromes of each subgroup and enantiomers of α-pinene and ß-pinene, (+)-3-carene, ß-myrcene and R-(+)-limonene. In addition, functional divergence analysis was performed to identify critical amino acid sites that influence changes in catalytic site conformation and/or protein folding. Three and two phylogenetic subgroups were recovered for the CYP6DE and CYP6DJ subfamilies, respectively. Mapping and reconciliation analysis showed different gain and loss patterns for cytochromes of each subgroup. Functional predictions indicated that the cytochromes analyzed are able to hydroxylate all monoterpenes; however, they showed preferential affinities to different monoterpenes. Functional divergence analyses indicated that the CYP6DE subfamily has experimented type I and II divergence, whereas the CYP6DJ subfamily has evolved under strong functional constraints. Results suggest cytochromes of the CYP6DE subfamily evolve to reinforce their detoxifying capacity hydroxylating mainly α- and ß-pinene to (+) and (-)-trans-verbenol, being the negative enantiomer used as a pheromone by several Dendroctonus species; whereas cytochromes of the CYP6DJ subfamily appear to retain their original function related to the detoxification of these compounds.

In Silico Screening of Drugs That Target Different Forms of E Protein for Potential Treatment of COVID-19.

Recently the E protein of SARS-CoV-2 has become a very important target in the potential treatment of COVID-19 since it is known to regulate different stages of the viral cycle. There is biochemical evidence that E protein exists in two forms, as monomer and homopentamer. An in silico screening analysis was carried out employing 5852 ligands (from Zinc databases), and performing an ADMET analysis, remaining a set of 2155 compounds. Furthermore, docking analysis was performed on specific sites and different forms of the E protein. From this study we could identify that the following ligands showed the highest binding affinity: nilotinib, dutasteride, irinotecan, saquinavir and alectinib. We carried out some molecular dynamics simulations and free energy MM-PBSA calculations of the protein-ligand complexes (with the mentioned ligands). Of worthy interest is that saquinavir, nilotinib and alectinib are also considered as a promising multitarget ligand because it seems to inhibit three targets, which play an important role in the viral cycle. On the other side, saquinavir was shown to be able to bind to E protein both in its monomeric as well as pentameric forms. Finally, further experimental assays are needed to probe our hypothesis derived from in silico studies.

Two MP2CL5 Antigen Vaccines from Naegleria fowleri Stimulate the Immune Response against Meningitis in the BALB/c Model.

Naegleria fowleri is an etiological agent that generates primary amoebic meningoencephalitis; unfortunately, no effective treatment or vaccine is available. The objective of this work was to determine the immunoprotective response of two vaccine antigens, as follows: (i) the polypeptide band of 19 kDa or (ii) a predicted immunogenic peptide from the membrane protein MP2CL5 (Smp145). Both antigens were administered intranasally in mice using cholera toxin (CT) as an adjuvant. The survival rate and immune response of immunized mice with both antigens and challenged with N. fowleri trophozoites were measured in the nose-associated lymphoid tissue (NALT) and nasal passages (NPs) by flow cytometry and enzyme-linked immunosorbent assay (ELISA). We also determined the immunolocalization of both antigens in N. fowleri trophozoites by confocal microscopy. Immunization with the polypeptide band of 19 kDa alone or coadministered with CT was able to confer 80% and 100% of protection, respectively. The immunization with both antigens (alone or coadministered with CT) showed an increase in T and B lymphocytes. In addition, there was an increase in the expression of integrin α4ß1 and IgA in the nasal cavity of protected mice, and the IgA, IgG, and IgM levels were increased in serum and nasal washes. The immunolocalization of both antigens in N. fowleri trophozoites was observed in the plasma membrane, specifically in pseudopod-like structures. The MP2CL5 antigens evaluated in this work were capable of conferring protection which would lead us to consider them as potential candidates for vaccines against meningitis caused by N. fowleri.

The Advantage of Using Immunoinformatic Tools on Vaccine Design and Development for Coronavirus.

After the outbreak of SARS-CoV-2 by the end of 2019, the vaccine development strategies became a worldwide priority. Furthermore, the appearances of novel SARS-CoV-2 variants challenge researchers to develop new pharmacological or preventive strategies. However, vaccines still represent an efficient way to control the SARS-CoV-2 pandemic worldwide. This review describes the importance of bioinformatic and immunoinformatic tools (in silico) for guide vaccine design. In silico strategies permit the identification of epitopes (immunogenic peptides) which could be used as potential vaccines, as well as nonacarriers such as: vector viral based vaccines, RNA-based vaccines and dendrimers through immunoinformatics. Currently, nucleic acid and protein sequential as well structural analyses through bioinformatic tools allow us to get immunogenic epitopes which can induce immune response alone or in complex with nanocarriers. One of the advantages of in silico techniques is that they facilitate the identification of epitopes, while accelerating the process and helping to economize some stages of the development of safe vaccines.

The ß2-Subunit (AMOG) of Human Na+, K+-ATPase Is a Homophilic Adhesion Molecule.

The ß2 subunit of Na+, K+-ATPase was originally identified as the adhesion molecule on glia (AMOG) that mediates the adhesion of astrocytes to neurons in the central nervous system and that is implicated in the regulation of neurite outgrowth and neuronal migration. While ß1 isoform have been shown to trans-interact in a species-specific mode with the ß1 subunit on the epithelial neighboring cell, the ß2 subunit has been shown to act as a recognition molecule on the glia. Nevertheless, none of the works have identified the binding partner of ß2 or described its adhesion mechanism. Until now, the interactions pronounced for ß2/AMOG are heterophilic cis-interactions. In the present report we designed experiments that would clarify whether ß2 is a cell-cell homophilic adhesion molecule. For this purpose, we performed protein docking analysis, cell-cell aggregation, and protein-protein interaction assays. We observed that the glycosylated extracellular domain of ß2/AMOG can make an energetically stable trans-interacting dimer. We show that CHO (Chinese Hamster Ovary) fibroblasts transfected with the human ß2 subunit become more adhesive and make large aggregates. The treatment with Tunicamycin in vivo reduced cell aggregation, suggesting the participation of N-glycans in that process. Protein-protein interaction assay in vivo with MDCK (Madin-Darby canine kidney) or CHO cells expressing a recombinant ß2 subunit show that the ß2 subunits on the cell surface of the transfected cell lines interact with each other. Overall, our results suggest that the human ß2 subunit can form trans-dimers between neighboring cells when expressed in non-astrocytic cells, such as fibroblasts (CHO) and epithelial cells (MDCK).

Theophylline: Old Drug in a New Light, Application in COVID-19 through Computational Studies.

Theophylline (3-methyxanthine) is a historically prominent drug used to treat respiratory diseases, alone or in combination with other drugs. The rapid onset of the COVID-19 pandemic urged the development of effective pharmacological treatments to directly attack the development of new variants of the SARS-CoV-2 virus and possess a therapeutical battery of compounds that could improve the current management of the disease worldwide. In this context, theophylline, through bronchodilatory, immunomodulatory, and potentially antiviral mechanisms, is an interesting proposal as an adjuvant in the treatment of COVID-19 patients. Nevertheless, it is essential to understand how this compound could behave against such a disease, not only at a pharmacodynamic but also at a pharmacokinetic level. In this sense, the quickest approach in drug discovery is through different computational methods, either from network pharmacology or from quantitative systems pharmacology approaches. In the present review, we explore the possibility of using theophylline in the treatment of COVID-19 patients since it seems to be a relevant candidate by aiming at several immunological targets involved in the pathophysiology of the disease. Theophylline down-regulates the inflammatory processes activated by SARS-CoV-2 through various mechanisms, and herein, they are discussed by reviewing computational simulation studies and their different applications and effects.

Immunoinformatics study to search epitopes of spike glycoprotein from SARS-CoV-2 as potential vaccine.

The Coronavirus disease named COVID-19 is caused by the virus reported in 2019 first identified in China. The cases of this disease have increased and as of June 1st, 2020 there are more than 216 countries affected. Pharmacological treatments have been proposed based on the resemblance of the HIV virus. With regard to prevention there is no vaccine, thus, we proposed to explore the spike protein due to its presence on the viral surface, and it also contains the putative viral entry receptor as well as the fusion peptide (important in the genome release). In this work we have employed In Silico techniques such as immunoinformatics tools which permit the identification of potential immunogenic regions on the viral surface (spike glycoprotein). From these analyses, we identified four epitopes E332-370, E627-651, E440-464 and E694-715 that accomplish essential features such as promiscuity, conservation grade, exposure and universality, and they also form stable complexes with MHCII molecule. We suggest that these epitopes could generate a specific immune response, and thus, they could be used for future applications such as the design of new epitope vaccines against the SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Repositioning of Ligands That Target the Spike Glycoprotein as Potential Drugs for SARS-CoV-2 in an In Silico Study.

The worldwide health emergency of the SARS-CoV-2 pandemic and the absence of a specific treatment for this new coronavirus have led to the use of computational strategies (drug repositioning) to search for treatments. The aim of this work is to identify FDA (Food and Drug Administration)-approved drugs with the potential for binding to the spike structural glycoprotein at the hinge site, receptor binding motif (RBM), and fusion peptide (FP) using molecular docking simulations. Drugs that bind to amino acids are crucial for conformational changes, receptor recognition, and fusion of the viral membrane with the cell membrane. The results revealed some drugs that bind to hinge site amino acids (varenicline, or steroids such as betamethasone while other drugs bind to crucial amino acids in the RBM (naldemedine, atovaquone, cefotetan) or FP (azilsartan, maraviroc, and difluprednate); saquinavir binds both the RBM and the FP. Therefore, these drugs could inhibit spike glycoprotein and prevent viral entry as possible anti-COVID-19 drugs. Several drugs are in clinical studies; by focusing on other pharmacological agents (candesartan, atovaquone, losartan, maviroc and ritonavir) in this work we propose an additional target: the spike glycoprotein. These results can impact the proposed use of treatments that inhibit the first steps of the virus replication cycle.

Molecular modeling studies demonstrate key mutations that could affect the ligand recognition by influenza AH1N1 neuraminidase.

The goal of this study was to identify neuraminidase (NA) residue mutants from human influenza AH1N1 using sequences from 1918 to 2012. Multiple alignment studies of complete NA sequences (5732) were performed. Subsequently, the crystallographic structure of the 1918 influenza (PDB ID: 3BEQ-A) was used as a wild-type structure and three-dimensional (3-D) template for homology modeling of the mutated selected NA sequences. The 3-D mutated NAs were refined using molecular dynamics (MD) simulations (50 ns). The refined 3-D models were used to perform docking studies using oseltamivir. Multiple sequence alignment studies showed seven representative mutations (A232V, K262R, V263I, T264V, S367L, S369N, and S369K). MD simulations applied to 3-D NAs showed that each NA had different active-site shapes according to structural surface visualization and docking results. Moreover, Cartesian principal component analyses (cPCA) show structural differences among these NA structures caused by mutations. These theoretical results suggest that the selected mutations that are located outside of the active site of NA could affect oseltamivir recognition and could be associated with resistance to oseltamivir.

Identification of the antiepileptic racetam binding site in the synaptic vesicle protein 2A by molecular dynamics and docking simulations.

Synaptic vesicle protein 2A (SV2A) is an integral membrane protein necessary for the proper function of the central nervous system and is associated to the physiopathology of epilepsy. SV2A is the molecular target of the anti-epileptic drug levetiracetam and its racetam analogs. The racetam binding site in SV2A and the non-covalent interactions between racetams and SV2A are currently unknown; therefore, an in silico study was performed to explore these issues. Since SV2A has not been structurally characterized with X-ray crystallography or nuclear magnetic resonance, a three-dimensional (3D) model was built. The model was refined by performing a molecular dynamics simulation (MDS) and the interactions of SV2A with the racetams were determined by docking studies. A reliable 3D model of SV2A was obtained; it reached structural equilibrium during the last 15 ns of the MDS (50 ns) with remaining structural motions in the N-terminus and long cytoplasmic loop. The docking studies revealed that hydrophobic interactions and hydrogen bonds participate importantly in ligand recognition within the binding site. Residues T456, S665, W666, D670 and L689 were important for racetam binding within the trans-membrane hydrophilic core of SV2A. Identifying the racetam binding site within SV2A should facilitate the synthesis of suitable radio-ligands to study treatment response and possibly epilepsy progression.

Exploring the ligand recognition properties of the human vasopressin V1a receptor using QSAR and molecular modeling studies.

Vaptans are compounds that act as non-peptide vasopressin receptor antagonists. These compounds have diverse chemical structures. In this study, we used a combined approach of protein folding, molecular dynamics simulations, docking, and quantitative structure-activity relationship (QSAR) to elucidate the detailed interaction of the vasopressin receptor V1a (V1aR) with some of its blockers (134). QSAR studies were performed using MLR analysis and were gathered into one group to perform an artificial neural network (ANN) analysis. For each molecule, 1481 molecular descriptors were calculated. Additionally, 15 quantum chemical descriptors were calculated. The final equation was developed by choosing the optimal combination of descriptors after removing the outliers. Molecular modeling enabled us to obtain a reliable tridimensional model of V1aR. The docking results indicated that the great majority of ligands reach the binding site under π-π, π-cation, and hydrophobic interactions. The QSAR studies demonstrated that the heteroatoms N and O are important for ligand recognition, which could explain the structural diversity of ligands that reach V1aR.