PM3 and DFT Computational Studies of the Reaction Mechanism of Formaldehyde and Isoleucine

The reaction of formaldehyde and Isoleucine was studied using semi-empirical and density functional theory methods. Possible reactive sites are proposed and reaction mechanism postulated. It was found that the Isoleucine nitrogen attacks the carbonyl carbon of formaldehyde and forms a methylol intermediate that undergoes a condensation with another Isoleucine to produce a Methylenediisoleucine through a methylene bridge (cross-linking). The enthalpies of the reaction are -78.79 kJ/mol and -39.14kJ/mol for PM3 and DFT respectively also ΔSo and ΔGo, for the PM3 and DFT studies predicted. The reaction was found to be exothermic and second order

Emergence and spread of two SARS-CoV-2 variants of interest in Nigeria.

Identifying the dissemination patterns and impacts of a virus of economic or health importance during a pandemic is crucial, as it informs the public on policies for containment in order to reduce the spread of the virus. In this study, we integrated genomic and travel data to investigate the emergence and spread of the SARS-CoV-2 B.1.1.318 and B.1.525 (Eta) variants of interest in Nigeria and the wider Africa region. By integrating travel data and phylogeographic reconstructions, we find that these two variants that arose during the second wave in Nigeria emerged from within Africa, with the B.1.525 from Nigeria, and then spread to other parts of the world. Data from this study show how regional connectivity of Nigeria drove the spread of these variants of interest to surrounding countries and those connected by air-traffic. Our findings demonstrate the power of genomic analysis when combined with mobility and epidemiological data to identify the drivers of transmission, as bidirectional transmission within and between African nations are grossly underestimated as seen in our import risk index estimates

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

A year of genomic surveillance reveals how the SARS-CoV-2 pandemic unfolded in Africa.

The progression of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in Africa has so far been heterogeneous, and the full impact is not yet well understood. In this study, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations predominantly from Europe, which diminished after the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1, and C.1.1. Although distorted by low sampling numbers and blind spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a source for new variants

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Mechanism and rate constant of proline-catalysed asymmetric aldol reaction of acetone and p-nitrobenzaldehyde in solution medium: Density-functional theory computation

In search of new ways to improve catalyst design, the current research focused on using quantum mechanical descriptors to investigate the effect of proline as a catalyst for mechanism and rate of asymmetric aldol reaction. A plausible mechanism of reaction between acetone and 4-nitrobenzaldehyde in acetone medium was developed using highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies calculated via density functional theory (DFT) at the 6-31G∗/B3LYP level of theory. New mechanistic steps were proposed and found to follow, with expansion, the previously reported iminium-enamine route of typical class 1 aldolase enzymes. From the elementary steps, the first step which involves a bimolecular collision of acetone and proline was considered as the rate-determining step, having the highest activation energy of 59.07 kJ mol−1. The mechanism was used to develop the rate law from which the overall rate constant was calculated and found to be 4.04×10-8dm3mol-1s-1. The new mechanistic insights and the explicit computation of the rate constant further improve the kinetic knowledge of the reaction. Keywords: HOMO, LUMO, DFT, Proline, Catalyst, Mechanis

QSAR AND MOLECULAR DOCKING BASED DESIGN OF SOME N-BENZYLACETAMIDE AS Γ-AMINOBUTYRATE-AMINOTRANSFERASE INHIBITORS

Quantitative structure activity relationship study (QSAR) and molecular docking were used to design and virtually screen some new N-benzylacetamide derivatives for their ability to inhibit γ-amino butyrate-aminotransferase. Ninety compounds with anticonvulsant activity against maximal electroshock induced seizures were used for QSAR study. B3LYP/6-31G** quantum mechanical method was employed to optimize/minimize the molecular structure of these compounds. Genetic Function Algorithm (GFA) method was used to develop the QSAR models. Each model gave an octa-parametric equation with good statistical qualities (R2 ranged from 0.823 to 0.893, Q2 from 0.772 to 0.854, F from 36.53 to 37.10, R2pred(test) from 0.768 to 0.893). Information obtained from the parameter contained in the model suggested that increasing the molecular mass and linearity of molecule would lead to increase in anticonvulsant activity of studied compounds. These informed the design and virtual screening of 118 new N-benzylacetamide derivatives using 2-acetamido-N-benzyl-2-(5-methylfuran-2-yl)acetamides as the template. The designed molecules were docked with γ-amino butyrate-aminotransferase (GABA_AT; PDB: 1OHV) using Internal Coordinate Mechanics Program (ICM-pro 3.8-3). The binding affinity of the designed compounds with GABA_AT were comparable to that of 4-aminohex-5-enoic acid (vigabatrin) and 3, 3-diphenylpyrrolidine-2, 5-dione (phenytoin) and 5H-dibenzo [b,f]azepine-5-carboxamide (carbamazepine), which are known inhibitors of GABA_AT. Therefore, the designed molecules have potential as inhibitors of GABA_AT and consequently as anticonvulsant agent

GCMS, FTIR, SEM, Physiochemical and Rheological Studies on Albizia zygia Gum

GCMS (Gas Chromatography Mass Spectrometry), FTIR (Fourier Transformed Infra-Red Spectroscopy), SEM (Scanning Electron Microscopy), physiochemical and rheological analysis of Albizia zygia gum have been carried out. Albizia zygia exudate is a brownish in colour, acidic and ionic gum. GCMS spectra of the gum indicated the presence of (E)-methyl octadec-7-enoate (41.18 %), methyl palmitate (18.64 %), methyl stearate (19.13 %), (9E,12E)-methyl octadeca-9,12-dienoate (11.88 %), methyl icosanoate (1.85 %), 2,3-dihydroxypropyl oleate (2.05 %), (Z)-octadec-13-enal (1.63 %), 2-hydroxy-3-(palmitoyloxy)propyl stearate (1.55 %), 2,3-dihydroxypropyl stearate (0.82 %), dimethyl phthalate (0.58 %) and 3-((aminomethoxy) (hydroxy)phosphoryloxy)propane-1,2-diyl dipalmitate (0.70 %). The FTIR spectrum of the gum indicated several functional groups, including –OH, C-O and C=O. From the scanning electron micrograph, the morphology of the gum shows irregular shapes embedded on the surface. Rheological studies indicated that the viscosity of the gum increased with increasing pH but decreased with an increase in temperature. Application of Huggins, Kraemer and Tanglertpaibul and Rao models indicated that the intrinsic viscosity of the gum is in the range of 0.5 - 0.8. Plots obtained for the variation of viscosity with shear rate and shear rate with shear stress confirmed that Albizia zygia gum is a non Newtonian dilatant polymer with a characteristic shear thickening property

Virtual screening and pharmacokinetics analysis of inhibitors against tuberculosis: Structure and ligand-based approach

Life-threatening diseases like tuberculosis have raised concerns in the medical and scientific communities. The damage-causing disease makes the scientific community employ the in-silico approach for design of new inhibitors that can inhibit or retard the havoc caused by this deadly disease. The insilico approach was used in this study to create a mathematical model with promising molecular properties, and receptors from the library were used to screen compounds and estimate the kinetic ability of the screened inhibitors that can cure this disease. 2D molecular properties evolved in the built model with high predictive ability. Three inhibitors x, y, and z emerged with better and higher molecular properties, the lowest binding energy (and higher binding affinity), and a better pharmacokinetic assessment compared to the template used in designing the effective compounds, with binding affinities of -15.56 kcal/mol, -18.51 kcal/mol, and -18.58 kcal/mol, respectively. Virtual screening of these compounds showed that they have good binding energy and excellent docking positions with the inhibiting potential of the receptor. Also, pharmacokinetic predictions and ADMET, depict orally active ability of the inhibitors, possess good human intestinal absorption, and violate none of the RO5 as potential drug candidates to cure this disease. Hence, further laboratory tests are recommended for these to determine their toxicities and biological assays

Identification of estrogen receptor agonists among hydroxylated polychlorinated biphenyls using classification-based quantitative structure–activity relationship models

Identification of estrogen receptor (ER) agonists among environmental toxicants is essential for assessing the potential impact of toxicants on human health. Using 2D autocorrelation descriptors as predictor variables, two binary logistic regression models were developed to identify active ER agonists among hydroxylated polychlorinated biphenyls (OH-PCBs). The classifications made by the two models on the training set compounds resulted in accuracy, sensitivity and specificity of 95.9 %, 93.9 % and 97.6 % for ERα dataset and 91.9 %, 90.9 % and 92.7 % for ERβ dataset. The areas under the ROC curves, constructed with the training set data, were found to be 0.985 and 0.987 for the two models. Predictions made by models I and II correctly classified 84.0 % and 88.0 % of the test set compounds and 89.8 % and 85.8% of the cross-validation set compounds respectively. The two classification-based QSAR models proposed in this paper are considered robust and reliable for rapid identification of ERα and ERβ agonists among OH-PCB congeners