Lung surfactant proteins as potential targets of prallethrin: An in silico approach

Breaking boundaries: Artificial intelligence for pesticide detection and eco-friendly degradation

Pesticides are extensively used agrochemicals across the world to control pest populations. However, irrational application of pesticides leads to contamination of various components of the environment, like air, soil, water, and vegetation, all of which build up significant levels of pesticide residues. Further, these environmental contaminants fuel objectionable human toxicity and impose a greater risk to the ecosystem. Therefore, search of methodologies having potential to detect and degrade pesticides in different environmental media is currently receiving profound global attention. Beyond the conventional approaches, Artificial Intelligence (AI) coupled with machine learning and artificial neural networks are rapidly growing branches of science that enable quick data analysis and precise detection of pesticides in various environmental components. Interestingly, nanoparticle (NP)-mediated detection and degradation of pesticides could be linked to AI algorithms to achieve superior performance. NP-based sensors stand out for their operational simplicity as well as their high sensitivity and low detection limits when compared to conventional, time-consuming spectrophotometric assays. NPs coated with fluorophores or conjugated with antibody or enzyme-anchored sensors can be used through Surface-Enhanced Raman Spectrometry, fluorescence, or chemiluminescence methodologies for selective and more precise detection of pesticides. Moreover, NPs assist in the photocatalytic breakdown of various organic and inorganic pesticides. Here, AI models are ideal means to identify, classify, characterize, and even predict the data of pesticides obtained through NP sensors. The present study aims to discuss the environmental contamination and negative impacts of pesticides on the ecosystem. The article also elaborates the AI and NP-assisted approaches for detecting and degrading a wide range of pesticide residues in various environmental and agrecultural sources including fruits and vegetables. Finally, the prevailing limitations and future goals of AI-NP-assisted techniques have also been dissected.

In Silico Analysis Reveals the Inhibitory Potential of Madecassic Acid against Entry Factors of SARS-CoV-2

Coronavirus disease 19 (COVID-19) is the ongoing global health emergency caused by SARS-CoV-2 infection. The virus is highly contagious, affecting millions of people worldwide. SARS-CoV-2, with its trimeric spike glycoprotein, interacts with the angiotensin-converting enzyme 2 (ACE2) receptor and other co-receptors like basigin to invade the host cell. Moreover, certain host proteases like transmembrane serine proteases, furin, neuropilin 1 (NRP1), and endosomal cathepsins are involved in the priming of spike glycoproteins at the S1/S2 interface. This is critical for the entry of viral genome and its replication in the host cytoplasm. Vaccines and anti-SARS-CoV-2 drugs have been developed to overcome the infection. Nonetheless, the frequent emergence of mutant variants of the virus has imposed serious concerns regarding the efficacy of therapeutic agents, including vaccines that were developed for previous strains. Thus, screening and development of pharmaceutical agents with multi-target potency could be a better choice to restrain SARS-CoV-2 infection. Madecassic acid (MDCA) is a pentacyclic triterpenoid found in Centella asiatica. It has multiple medicinal properties like anti-oxidative, anti-inflammatory, and anti-diabetic potential. However, its implication as an anti- SARS-CoV-2 agent is still obscure. Hence, in the present in silico study, the binding affinities of MDCA for spike proteins, their receptors, and proteases were investigated. Results indicated that MDCA interacts with ligand-binding pockets of the spike receptor binding domain, ACE2, basigin, and host proteases, viz. transmembrane serine proteinase, furin, NRP1, and endosomal cathepsins, with greater affinities. Moreover, the MDCA-protein interface was strengthened by prominent hydrogen bonds and several hydrophobic interactions. Therefore, MDCA could be a promising multi-target therapeutic agent against SARS-CoV-2 infection.

Synergistic action of organophosphates and COVID-19 on inflammation, oxidative stress, and renin-angiotensin system can amplify the risk of cardiovascular maladies

Organophosphates (OPs) are ubiquitous environmental contaminants, widely used as pesticides in agricultural fields. In addition, they serve as flame-retardants, plasticizers, antifoaming or antiwear agents in lacquers, hydraulic fluids, and floor polishing agents. Therefore, world-wide and massive application of these compounds have increased the risk of unintentional exposure to non-targets including the human beings. OPs are neurotoxic agents as they inhibit the activity of acetylcholinesterase at synaptic cleft. Moreover, they can fuel cardiovascular issues in the form of myocardities, cardiac oedema, arrhythmia, systolic malfunction, infarction, and altered electrophysiology. Such pathological outcomes might increase the severity of cardiovascular diseases which are the leading cause of mortality in the developing world. Coronavirus disease-19 (COVID-19) is the ongoing global health emergency caused by SARS-CoV-2 infection. Similar to OPs, SARS-CoV-2 disrupts cytokine homeostasis, redox-balance, and angiotensin-II/AT₁R axis to promote cardiovascular injuries. Therefore, during the current pandemic milieu, unintentional exposure to OPs through several environmental sources could escalate cardiac maladies in patients with COVID-19.