Comparative Host-Pathogen Interaction Analyses of SARS-CoV2 and Aspergillus fumigatus, and Pathogenesis of COVID-19-Associated Aspergillosis.

COVID-19 caused a global catastrophe with a large number of cases making it one of the major pandemics of the human history. The clinical presentations of the disease are continuously challenging healthcare workers with the variation of pandemic waves and viral variants. Recently, SARS-CoV2 patients have shown increased occurrence of invasive pulmonary aspergillosis infection even in the absence of traditional risk factors. The mechanism of COVID-19-associated aspergillosis is not completely understood and therefore, we performed this system biological study in order to identify mechanistic implications of aspergillosis susceptibility in COVID-19 patients and the important targets associated with this disease. We performed host-pathogen interaction (HPI) analysis of SARS-CoV2, and most common COVID-19-associated aspergillosis pathogen, Aspergillus fumigatus, using in silico approaches. The known host-pathogen interactions data of SARS-CoV2 was obtained from BIOGRID database. In addition, A. fumigatus host-pathogen interactions were predicted through homology modeling. The human targets interacting with both pathogens were separately analyzed for their involvement in aspergillosis. The aspergillosis human targets were screened from DisGeNet and GeneCards. The aspergillosis targets involved in both HPI were further analyzed for functional overrepresentation analysis using PANTHER. The results indicate that both pathogens interact with a number of aspergillosis targets and altogether they recruit more aspergillosis targets in host-pathogen interaction than alone. Common aspergillosis targets involved in HPI with both SARS-CoV2 and A. fumigatus can indicate strategies for the management of both conditions by modulating these common disease targets.

QSPR Modeling of Fungicides Using Topological Descriptors.

A topological index is a real number that is obtained from a chemical graph's structure. Determining the physiochemical and biological characteristics of a variety of medications is useful since it more accurately represents the theoretical characteristics of organic molecules. This is accomplished using degree-based topological indices. The QSPR research has improved the structural understanding of the physiochemical properties of fungicides. Thirteen fungicides are examined for some of their physiochemical properties, and a QSPR model is built using nine of the drugs' topological indices. Here, we examine the degree to which the topological indices and physiochemical attributes are connected. To do this, we create networks connecting each of the topological indices to the properties of fungicides and computationally construct topological indices of the drugs mentioned above. According to this QSPR model, the melting point, boiling point, flash point, complexity, surface tension, etc. of fungicides are strongly connected. It was discovered that the topological indices (TIs) applied to the fungicides more accurately represent their theoretical features and show a strong correlation with their physical attributes.

Topological Indices of Novel Drugs Used in Autoimmune Disease Vitiligo Treatment and Its QSPR Modeling.

A topological index is a real number derived from the structure of a chemical graph. It is helpful to determine the physicochemical and biological properties of a wide range of drugs, and it better reflects the theoretical properties of organic compounds. This is accomplished using degree-based topological indices. Vitiligo is a common, acquired skin pigmentation disorder that significantly impacts the quality of life. It frequently embodies a therapeutic challenge, resulting in interest in alternative treatments based on vitamin and herbal supplements. In this article, azathioprine, clobetasol, desonide, hydrocortisone valerate, and other drugs utilized to cure vitiligo have discoursed, and the goal of QSPR revision is to determine the mathematical relationship between properties under investigation (e.g., polarity and enthalpy) and diverse descriptors associated with the drugs' molecule. The QSPR model will help to predict physical properties. In this study, topological indices (TIs) imposed on said drugs were found to have a good correlation with physicochemical properties in this course. Finally, this work can be helpful to design and synthesize new vitiligo treatments and other disease drugs.

Fighting COVID-19 at the Expense of Malaria in Africa: The Consequences and Policy Options.

Malaria remains a major global health burden, killing hundreds of thousands annually, especially in sub-Saharan Africa. In December 2019, a novel illness termed COVID-19, caused by SARS-CoV-2, was reported in China. This disease soon spread around the world and was declared a pandemic by the WHO on March 11, 2020. Considering that the malaria burden is high in many low-income tropical countries with little capacity to fund malaria control and eradication programs, the fight against malaria in these regions is likely to be hindered by COVID-19. Indeed, access to health care has generally been limited during the pandemic, whereas malaria interventions, such as seasonal malaria chemoprevention, and distribution of long-lasting insecticide-treated bed nets, have been suspended because of lockdowns. Likewise, the repurposing of antimalarials for the treatment of COVID-19 and a shift in focus from the production of malaria rapid diagnostic tests to COVID-19 rapid diagnostic tests are causes for concern in malaria-endemic regions. COVID-19 has disproportionately affected developed countries, threatening their capacity to aid in malaria control efforts. Here, we address impacts of the COVID-19 pandemic on the management and control of malaria in Africa.

Omega, Sadhana, and PI Polynomials of Quasi-Hexagonal Benzenoid Chain.

Counting polynomials are important graph invariants whose coefficients and exponents are related to different properties of chemical graphs. Three closely related polynomials, i.e., Omega, Sadhana, and PI polynomials, dependent upon the equidistant edges and nonequidistant edges of graphs, are studied for quasi-hexagonal benzenoid chains. Analytical closed expressions for these polynomials are derived. Moreover, relation between Padmakar-Ivan (PI) index of quasi-hexagonal chain and that of corresponding linear chain is also established.