RESUMO
Streptococcus pneumoniae is a notorious Gram-positive pathogen present asymptomatically in the nasophayrnx of humans. According to the World Health Organization (W.H.O), pneumococcus causes approximately one million deaths yearly. Antibiotic resistance in S. pneumoniae is raising considerable concern around the world. There is an immediate need to address the major issues that have arisen as a result of persistent infections caused by S. pneumoniae. In the present study, subtractive proteomics was used in which the entire proteome of the pathogen consisting of 1947 proteins is effectively decreased to a finite number of possible targets. Various kinds of bioinformatics tools and software were applied for the discovery of novel inhibitors. The CD-HIT analysis revealed 1887 non-redundant sequences from the entire proteome. These non-redundant proteins were submitted to the BLASTp against the human proteome and 1423 proteins were screened as non-homologous. Further, databases of essential genes (DEGG) and J browser identified almost 171 essential proteins. Moreover, non-homologous, essential proteins were subjected in KEGG Pathway Database which shortlisted six unique proteins. In addition, the subcellular localization of these unique proteins was checked and cytoplasmic proteins were chosen for the druggability analysis, which resulted in three proteins, namely DNA binding response regulator (SPD_1085), UDP-N-acetylmuramate-L-alanine Ligase (SPD_1349) and RNA polymerase sigma factor (SPD_0958), which can act as a promising potent drug candidate to limit the toxicity caused by S. pneumoniae. The 3D structures of these proteins were predicted by Swiss Model, utilizing the homology modeling approach. Later, molecular docking by PyRx software 0.8 version was used to screen a library of phytochemicals retrieved from PubChem and ZINC databases and already approved drugs from DrugBank database against novel druggable targets to check their binding affinity with receptor proteins. The top two molecules from each receptor protein were selected based on the binding affinity, RMSD value, and the highest conformation. Finally, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses were carried out by utilizing the SWISS ADME and Protox tools. This research supported the discovery of cost-effective drugs against S. pneumoniae. However, more in vivo/in vitro research should be conducted on these targets to investigate their pharmacological efficacy and their function as efficient inhibitors.
RESUMO
Meteorological conditions may influence the incidence of many infectious diseases. Coronavirus disease-2019 (COVID-19) is a highly contagious, air-borne, emerging, viral disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). In 2020, the COVID-19 global pandemic affected more than 210 countries and territories worldwide including Saudi Arabia. There are contradictory research papers about the correlation between meteorological parameters and incidence of COVID-19 in some countries worldwide. The current study investigates the impact of outdoor and indoor meteorological conditions on the daily recorded COVID-19 cases in western region (Makkah and Madinah cities) of Saudi Arabia over a period of 8 months from March to October 2020. Reports of the daily confirmed COVID-19 cases from the webpage of Saudi Ministry of Health (MOH) were used. Considering, the incubation period of COVID-19 which ranged from 2 to 14 days, the relationships between daily COVID-19 cases and outdoor meteorological factors (temperature, relative humidity, and wind speed) using a lag time of 10 days are investigated. The results showed that the highest daily COVID-19 cases in Makkah and Madinah were reported during the hottest months of the year (April-July 2020) when outdoor temperature ranged from 26.51 to 40.71 °C in Makkah and of 23.89-41.20 °C in Madinah, respectively. Partial negative correlation was detected between outdoor relative humidity and daily recorded COVID-19 cases. No obvious correlation could be demonstrated between wind speed and daily COVID-19 cases. This indicated that most of SARS-CoV-2 infection occurred in the cool, air-conditioned, dry, and bad-ventilated indoor environment in the investigated cities. These results will help the epidemiologists to understand the correlation between both outdoor and indoor meteorological conditions and SARS-CoV-2 transmissibility. These findings would be also a useful supplement to assist the local healthcare policymakers to implement and apply a specific preventive measures and education programs for controlling of COVID-19 transmission.
