E-Volve: understanding the impact of mutations in SARS-CoV-2 variants spike protein on antibodies and ACE2 affinity through patterns of chemical interactions at protein interfaces.

Background: The SARS-CoV-2 pandemic reverberated, posing health and social hygiene obstacles throughout the globe. Mutant lineages of the virus have concerned scientists because of convergent amino acid alterations, mainly on the viral spike protein. Studies have shown that mutants have diminished activity of neutralizing antibodies and enhanced affinity with its human cell receptor, the ACE2 protein. Methods: Hence, for real-time measuring of the impacts caused by variant strains in such complexes, we implemented E-Volve, a tool designed to model a structure with a list of mutations requested by users and return analyses of the variant protein. As a proof of concept, we scrutinized the spike-antibody and spike-ACE2 complexes formed in the variants of concern, B.1.1.7 (Alpha), B.1.351 (Beta), and P.1 (Gamma), by using contact maps depicting the interactions made amid them, along with heat maps to quantify these major interactions. Results: The results found in this study depict the highly frequent interface changes made by the entire set of mutations, mainly conducted by N501Y and E484K. In the spike-Antibody complex, we have noticed alterations concerning electrostatic surface complementarity, breaching essential sites in the P17 and BD-368-2 antibodies. Alongside, the spike-ACE2 complex has presented new hydrophobic bonds. Discussion: Molecular dynamics simulations followed by Poisson-Boltzmann calculations corroborate the higher complementarity to the receptor and lower to the antibodies for the K417T/E484K/N501Y (Gamma) mutant compared to the wild-type strain, as pointed by E-Volve, as well as an intensification of this effect by changes at the protein conformational equilibrium in solution. A local disorder of the loop α1'/ß1', as well its possible effects on the affinity to the BD-368-2 antibody were also incorporated to the final conclusions after this analysis. Moreover, E-Volve can depict the main alterations in important biological structures, as shown in the SARS-CoV-2 complexes, marking a major step in the real-time tracking of the virus mutant lineages. E-Volve is available at http://bioinfo.dcc.ufmg.br/evolve.

Whole-genome sequencing as a tool for studying the microevolution of drug-resistant serial Mycobacterium tuberculosis isolates.

Treatment of drug-resistant tuberculosis requires extended use of more toxic and less effective drugs and may result in retreatment cases due to failure, abandonment or disease recurrence. It is therefore important to understand the evolutionary process of drug resistance in Mycobacterium tuberculosis. We here in describe the microevolution of drug resistance in serial isolates from six previously treated patients. Drug resistance was initially investigated through phenotypic methods, followed by genotypic approaches. The use of whole-genome sequencing allowed the identification of mutations in the katG, rpsL and rpoB genes associated with drug resistance, including the detection of rare mutations in katG and mixed populations of strains. Molecular docking simulation studies of the impact of observed mutations on isoniazid binding were also performed. Whole-genome sequencing detected 266 single nucleotide polymorphisms between two isolates obtained from one patient, suggesting a case of exogenous reinfection. In conclusion, sequencing technologies can detect rare mutations related to drug resistance, identify subpopulations of resistant strains, and identify diverse populations of strains due to exogenous reinfection, thus improving tuberculosis control by guiding early implementation of appropriate clinical and therapeutic interventions.

Mefloquine synergism with anti-tuberculosis drugs and correlation to membrane effects: Biologic, spectroscopic and molecular dynamics simulations studies.

Studies displaying the combination of mefloquine (MFL) with anti-tuberculosis (TB) substances are limited in the literature. In this work, the effect of MFL-association with two first-line anti-TB drugs and six fluoroquinolones was evaluated against Mycobacterium tuberculosis drug resistant strains. MFL showed synergistic interaction with isoniazid, pyrazinamide, and several fluoroquinolones, reaching fractional inhibitory concentration indexes (FICIs) ranging from 0.03 to 0.5. In order to better understand the observed results, two approaches have been explored: (i) spectroscopic responses attributed to the effect of MFL on physicochemical properties related to a liposomal membrane model composed by soybean asolectin; (ii) molecular dynamics (MD) simulation data regarding MFL interaction with a membrane model based on PIM2, a lipid constituent of the mycobacterial cell wall. FTIR and NMR data showed that MFL affects expressively the region between the phosphate and the first methylene groups of soybean asolectin membranes, disordering these regions. MD simulations results detected high MFL density in the glycolipid interface and showed that the drug increases the membrane lateral diffusion, enhancing its permeability. The obtained results suggest that synergistic activities related to MFL are attributed to its effect of lipid disorder and membrane permeability enhancement.

Long-chain fatty dihydropyridines: Docking calcium channel studies and antihypertensive activity.

AIMS: From the synthesis of 43 lipophilic dihydropyridines, the aim of this study was to verify whether the new dihydropyridines have calcium channel affinity using coupling studies and to determine antihypertensive and antioxidant properties, as well as toxicology and toxicity nifedipine and three new compounds, were chosen from the previous results. MATERIALS AND METHODS: The animals were treated for 56 days, 28 days with N (ω) -nitro-L-arginine methyl ester to induce hypertension, and then treated for another 28 days with the new di- hydropyridine and the standard drug nifedipine. Throughout the treatment the animals had their blood pressure measured and their heart rate checked by pletysmography. After treatment the animals were euthanised, blood samples were collected for creatine kinase and urea analysis, and the brain, heart and liver were collected for oxidative status analysis (quantification of reactive oxygen species, total antioxidant capacity, and lipid peroxidation). KEY FINDINGS: Compounds 2c, and 9a, and nifedipine significantly reduced blood pressure to control group levels. The tachycardia caused by the induction of hypertension was reversed by 2c and 9a compounds. Regarding oxidative stress analyzes, the compounds that had the best performances were also 2c and 9a. Overall the results demonstrate that two of the three new dihydropyridines tested demonstrated performance equal to or superior to the standard drug nifedipine. SIGNIFICANCE: In this study, for the first time, docking was applied to analyse 43 fatty dihydropyridines regarding their calcium channel binding. Afterwards, three fatty dihydropyridines were chosen and their antihypertensive and antioxidant properties.

A Computational Method to Propose Mutations in Enzymes Based on Structural Signature Variation (SSV).

With the use of genetic engineering, modified and sometimes more efficient enzymes can be created for different purposes, including industrial applications. However, building modified enzymes depends on several in vitro experiments, which may result in the process being expensive and time-consuming. Therefore, computational approaches could reduce costs and accelerate the discovery of new technological products. In this study, we present a method, called structural signature variation (SSV), to propose mutations for improving enzymes' activity. SSV uses the structural signature variation between target enzymes and template enzymes (obtained from the literature) to determine if randomly suggested mutations may provide some benefit for an enzyme, such as improvement of catalytic activity, half-life, and thermostability, or resistance to inhibition. To evaluate SSV, we carried out a case study that suggested mutations in ß-glucosidases: Essential enzymes used in biofuel production that suffer inhibition by their product. We collected 27 mutations described in the literature, and manually classified them as beneficial or not. SSV was able to classify the mutations with values of 0.89 and 0.92 for precision and specificity, respectively. Then, we used SSV to propose mutations for Bgl1B, a low-performance ß-glucosidase. We detected 15 mutations that could be beneficial. Three of these mutations (H228C, H228T, and H228V) have been related in the literature to the mechanism of glucose tolerance and stimulation in GH1 ß-glucosidase. Hence, SSV was capable of detecting promising mutations, already validated by in vitro experiments, that improved the inhibition resistance of a ß-glucosidase and, consequently, its catalytic activity. SSV might be useful for the engineering of enzymes used in biofuel production or other industrial applications.

Molecular modelling and competitive inhibition of a Mycobacterium tuberculosis multidrug-resistance efflux pump.

Tuberculosis is a major cause of mortality and morbidity in developing countries, and the emergency of multidrug and extensive drug resistance cases is an utmost issue on the control of the disease. Despite the efforts on the development of new antibiotics, eventually there will be strains resistant to them as well. Efflux plays an important role in the evolution of resistance in Mycobacterium tuberculosis. Tap is an important efflux pump associated with tuberculosis resistant to isoniazid, rifampicine and ofloxacin and with multidrug resistance. The development of efflux inhibitors for Tap could raise the effectiveness of second line drugs and reduce the duration of the current treatment. Therefore the objective of this study is to build a reliable molecular model of Tap efflux pump and test the possible competitive inhibition between efflux inhibitors and antibiotics in the optimized structure. We built twenty five Tap models with molecular modelling to elect the best according to the results of the validation analysis. The elected model went through to a 100 ns molecular dynamics simulation in a lipid bilayer, and the resulting optimized structure was used in docking studies to test if the used efflux inhibitors may act via competitive inhibition on antibiotics. The validation results pointed the model built by Phyre2 as the closest to a possible native Tap structure, and therefore it was the elected model. RSMD analysis revealed the model is stable, where the predicted binding site stabilized between 15 and 20 ns, maintaining the RMSD at around 0.35 Šthroughout the molecular dynamics simulation in a lipid bilayer. Therefore this model is reliable and can also be used for further studies. The docking studies showed a possibility of competitive inhibition by NUNL02 on ofloxacin and bedaquiline, and by verapamil on ofloxacin and rifampicin. This presents the possibility that NUNL02 and verapamil are possible inhibitors of Tap efflux and highlights the importance of including efflux inhibitors as adjuvants to the tuberculosis therapy, as it indicates a possible extrusion of ofloxacin, rifampicin and bedaquilin by Tap.