The structural basis of acid resistance in Mycobacterium tuberculosis: insights from multiple pH regime molecular dynamics simulations

Metagenomic analysis characterizes resistomes of an acidic, multimetal(loid)-enriched coal source mine drainage treatment system

Heavy metal(loid) contaminations caused by mine activities are potential hot spots of antibiotic resistance genes (ARGs) because of heavy metal(loid)-induced co-selection of ARGs and heavy metal(loid) resistance genes (MRGs). This study used high-throughput metagenomic sequencing to analyze the resistome characteristics of a coal source acid mine drainage passive treatment system. The multidrug efflux mechanism dominated the antibiotic resistome, and a highly diverse heavy metal(loid) resistome was dominated by mercury-, iron-, and arsenic--associated resistance. Correlation analysis indicated that mobile gene elements had a greater influence on the dynamic of MRGs than ARGs. Among the metagenome-assembled genomes, six potential pathogens carrying multiple resistance genes resistant to several antibiotics and heavy metal(loid)s were recovered. Pseudomonas spp. contained the highest numbers of resistance genes, with resistance to two types of antibiotics and 12 types of heavy metal(loid)s. Thus, high contents of heavy metal(loid)s drove the co-selection of ARGs and MRGs. The occurrence of potential pathogens containing multiple resistance genes might increase the risk of ARG dissemination in the environment.

Identification of natural compounds as potent inhibitors of SARS-CoV-2 main protease using combined docking and molecular dynamics simulations

Coronavirus disease 2019 (COVID-19) has emerged from China and globally affected the entire population through the human-to-human transmission of a newly emerged virus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The genome of SARS-CoV-2 encodes several proteins that are essential for multiplication and pathogenesis. The main protease (Mpro or 3CLpro) of SARS-CoV-2 plays a central role in its pathogenesis and thus is considered as an attractive drug target for the drug design and development of small-molecule inhibitors. We have employed an extensive structure-based high-throughput virtual screening to discover potential natural compounds from the ZINC database which could inhibit the Mpro of SARS-CoV-2. Initially, the hits were selected on the basis of their physicochemical and drug-like properties. Subsequently, the PAINS filter, estimation of binding affinities using molecular docking, and interaction analyses were performed to find safe and potential inhibitors of SARS-CoV-2 Mpro. We have identified ZINC02123811 (1-(3-(2,5,9-trimethyl-7-oxo-3-phenyl-7H-furo[3,2-g]chromen-6-yl)propanoyl)piperidine-4-carboxamide), a natural compound bearing appreciable affinity, efficiency, and specificity towards the binding pocket of SARS-CoV-2 Mpro. The identified compound showed a set of drug-like properties and preferentially binds to the active site of SARS-CoV-2 Mpro. All-atom molecular dynamics (MD) simulations were performed to evaluate the conformational dynamics, stability and interaction mechanism of Mpro with ZINC02123811. MD simulation results indicated that Mpro with ZINC02123811 forms a stable complex throughout the trajectory of 100 ns. These findings suggest that ZINC02123811 may be further exploited as a promising scaffold for the development of potential inhibitors of SARS-CoV-2 Mpro to address COVID-19.