Toward the Identification of Natural Antiviral Drug Candidates against Merkel Cell Polyomavirus: Computational Drug Design Approaches

New N-(1,3,4-thiadiazole-2-yl)acetamide derivatives as human carbonic anhydrase I and II and acetylcholinesterase inhibitors

Various carbonic anhydrase (CA) enzyme isoforms are known today. In addition to the use of CA inhibitors as diuretics, antiepileptics and antiglaucoma agents, the inhibition of other specific isoforms of CA was reported to have clinical benefits in cancers. In this study, two groups of 1,3,4-thiadiazole derivatives were designed and synthesized to act as human CA I and II (hCA I and hCA II) inhibitors. The activities of these compounds were tested in vitro and evaluated in silico studies. The activity of the synthesized compounds was also tested against acetylcholinesterase (AChE) to evaluate the relation of the newly designed structures to the activity against AChE. The synthesized compounds were analyzed by 1H NMR,13C NMR and high-resolution mass spectroscopy (HRMS). The results displayed a better activity of all the synthesized compounds against hCA I than that of the commonly used standard drug, Acetazolamide (AAZ). The compounds also showed better activity against hCA II, except for compounds 5b and 6b. Only compounds 6a and 6c showed superior activity against AChE compared to the standard agent, tacrine (THA). In silico studies, including absorption, distribution, metabolism and excretion (ADME) and drug-likeness evaluation, molecular docking, molecular dynamic simulations (MDSs) and density functional theory (DFT) calculations, were compatible with the in vitro results and presented details regarding the structure-activity relationship.Communicated by Ramaswamy H. Sarma.

Pharmacoinformatic screening of phytoconstituent and evaluation of its anti-PDAC effect using in vitro studies

With no prominent treatment for pancreatic ductal adenocarcinoma (PDAC) in conventional chemotherapy, recent studies have focused on uniting conventional and traditional medicines including plant phytoconstituents. Herein, we used pharmacoinformatic studies to identify potent phytoconstituent as ligand having inhibition activities against canonical anticancer targets, and evaluated its effect on PDAC cell lines. SwissTargetPrediction and SuperPred tools were utilized to segregate protein targets of ligand in humans, following which FunRich was applied to garner its targets in PDAC. STRING analysis predicted protein-protein interactions and dynamic simulation studies confirmed stability of ligand-protein complex. For in vitro cytotoxic potential, ligand treatment at different concentrations was given to PDAC cell lines both alone and combined with gemcitabine, followed by evaluation of effects on migration. Differential gene expression was checked using PCR for evaluating mechanism of cytotoxicity. Results showed pentagalloylglucose (PGG) with highest docking and MMGBSA scores for Cyclooxygenase 2 (Cox2) inhibition site. SwissTargetPrediction and SuperPred analysis detected 40 targets of PGG in PDAC. Simulation data showed stability of protein-ligand complex. In in vitro experiments Mia-PaCa-2 was more sensitive to PGG than Panc-1. PGG successfully inhibited migration both alone and in combination with gemcitabine. Additionally, PGG treatment induced apoptosis in both the cell lines; but showed antagonism when combined with gemcitabine. In conclusion, our report demonstrates PGG has good binding with Cox2 and showed anti-PDAC activity by inhibiting migration and inducing apoptosis, thus it can be used as a therapy option. But further studies are required to confirm its behaviour as a combination therapy drug.Communicated by Ramaswamy H. Sarma.

Computational formulation of a multiepitope vaccine unveils an exceptional prophylactic candidate against Merkel cell polyomavirus

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin malignancy caused by human Merkel cell polyomavirus (MCV), leading to the most aggressive skin cancer in humans. MCV has been identified in approximately 43%-100% of MCC cases, contributing to the highly aggressive nature of primary cutaneous carcinoma and leading to a notable mortality rate. Currently, no existing vaccines or drug candidates have shown efficacy in addressing the ailment caused by this specific pathogen. Therefore, this study aimed to design a novel multiepitope vaccine candidate against the virus using integrated immunoinformatics and vaccinomics approaches. Initially, the highest antigenic, immunogenic, and non-allergenic epitopes of cytotoxic T lymphocytes, helper T lymphocytes, and linear B lymphocytes corresponding to the virus whole protein sequences were identified and retrieved for vaccine construction. Subsequently, the selected epitopes were linked with appropriate linkers and added an adjuvant in front of the construct to enhance the immunogenicity of the vaccine candidates. Additionally, molecular docking and dynamics simulations identified strong and stable binding interactions between vaccine candidates and human Toll-like receptor 4. Furthermore, computer-aided immune simulation found the real-life-like immune response of vaccine candidates upon administration to the human body. Finally, codon optimization was conducted on the vaccine candidates to facilitate the in silico cloning of the vaccine into the pET28+(a) cloning vector. In conclusion, the vaccine candidate developed in this study is anticipated to augment the immune response in humans and effectively combat the virus. Nevertheless, it is imperative to conduct in vitro and in vivo assays to evaluate the efficacy of these vaccine candidates thoroughly. These evaluations will provide critical insights into the vaccine's effectiveness and potential for further development.

Clinical Application of Artificial Intelligence for Non-melanoma Skin Cancer

OPINION STATEMENT

The development and implementation of artificial intelligence is beginning to impact the care of dermatology patients. Although the clinical application of AI in dermatology to date has largely focused on melanoma, the prevalence of non-melanoma skin cancers, including basal cell and squamous cell cancers, is a critical application for this technology. The need for a timely diagnosis and treatment of skin cancers makes finding more time efficient diagnostic methods a top priority, and AI may help improve dermatologists' performance and facilitate care in the absence of dermatology expertise. Beyond diagnosis, for more severe cases, AI may help in predicting therapeutic response and replacing or reinforcing input from multidisciplinary teams. AI may also help in designing novel therapeutics. Despite this potential, enthusiasm in AI must be tempered by realistic expectations regarding performance. AI can only perform as well as the information that is used to train it, and development and implementation of new guidelines to improve transparency around training and performance of algorithms is key for promoting confidence in new systems. Special emphasis should be placed on the role of dermatologists in curating high-quality datasets that reflect a range of skin tones, diagnoses, and clinical scenarios. For ultimate success, dermatologists must not be wary of AI as a potential replacement for their expertise, but as a new tool to complement their diagnostic acumen and extend patient care.

In Silico Screening and Molecular Dynamics Simulation Studies in the Identification of Natural Compound Inhibitors Targeting the Human Norovirus RdRp Protein to Fight Gastroenteritis

Norovirus (HNoV) is a leading cause of gastroenteritis globally, and there are currently no treatment options or vaccines available to combat it. RNA-dependent RNA polymerase (RdRp), one of the viral proteins that direct viral replication, is a feasible target for therapeutic development. Despite the discovery of a small number of HNoV RdRp inhibitors, the majority of them have been found to possess a little effect on viral replication, owing to low cell penetrability and drug-likeness. Therefore, antiviral agents that target RdRp are in high demand. For this purpose, we used in silico screening of a library of 473 natural compounds targeting the RdRp active site. The top two compounds, ZINC66112069 and ZINC69481850, were chosen based on their binding energy (BE), physicochemical and drug-likeness properties, and molecular interactions. ZINC66112069 and ZINC69481850 interacted with key residues of RdRp with BEs of -9.7, and -9.4 kcal/mol, respectively, while the positive control had a BE of -9.0 kcal/mol with RdRp. In addition, hits interacted with key residues of RdRp and shared several residues with the PPNDS, the positive control. Furthermore, the docked complexes showed good stability during the molecular dynamic simulation of 100 ns. ZINC66112069 and ZINC69481850 could be proven as potential inhibitors of the HNoV RdRp in future antiviral medication development investigations.

Soaud S, Huang Q, M. Saleh A, A. S. Abourehab M, Wan L, Cheng GT, Liu J, Ihtisham M, Noor Z, Rouf Mir R, Zhao X, Yan K, Abbas M, Li J. Natural resistance of tomato plants to Tomato yellow leaf curl virus

Tomato yellow leaf curl virus (TYLCV) is one of the most harmful afflictions in the world that affects tomato growth and production. Six regular antagonistic genes (Ty-1, Ty-2, Ty-3, Ty-4, ty-5, and Ty-6) have been transferred from wild germplasms to commercial cultivars as TYLCV protections. With Ty-1 serving as an appropriate source of TYLCV resistance, only Ty-1, Ty-2, and Ty-3 displayed substantial levels of opposition in a few strains. It has been possible to clone three TYLCV opposition genes (Ty-1/Ty-3, Ty-2, and ty-5) that target three antiviral safety mechanisms. However, it significantly impacts obtaining permanent resistance to TYLCV, trying to maintain opposition whenever possible, and spreading opposition globally. Utilizing novel methods, such as using resistance genes and identifying new resistance resources, protects against TYLCV in tomato production. To facilitate the breeders make an informed decision and testing methods for TYLCV blockage, this study highlights the portrayal of typical obstruction genes, common opposition sources, and subatomic indicators. The main goal is to provide a fictitious starting point for the identification and application of resistance genes as well as the maturation of tomato varieties that are TYLCV-resistant.

Most frequently harboured missense variants of hACE2 across different populations exhibit varying patterns of binding interaction with spike glycoproteins of emerging SARS-CoV-2 of different lineages

Since the emergence of SARS-CoV-2 at Wuhan in the Hubei province of China in 2019, the virus has accumulated various mutations, giving rise to many variants. According to the combinations of mutations acquired, these variants are classified into lineages and greatly differ in infectivity and transmissibility. In 2021 alone, a variant of interest (VoI) Mu (B.1.621), as well as, variants of concern (VoC) Delta (B.1.617.2) and Omicron (BA.1, BA.2) and later in 2022, BA.4, BA.5, and BA.2.12.1 have emerged. Since then, the world has seen prominent surges in the rate of infection during short periods of time. However, not all populations have suffered equally, which suggests a possible role of host genetic factors. Here, we investigated the strength of binding of the spike glycoprotein receptor-binding domain (RBD) of the SARS-CoV-2 variants: Mu, Delta, Delta Plus (AY.1), Omicron sub-variants BA.1, BA.2, BA.4, BA.5, and BA.2.12.1 with the human angiotensin-converting enzyme 2 (hACE2) missense variants prevalent in major populations. In this purpose, molecular docking analysis, as well as, molecular dynamics simulation was performed of the above-mentioned SARS-CoV-2 RBD variants with the hACE2 containing the single amino acid substitutions prevalent in African (E37K), Latin American (F40L), non-Finnish European (D355 N), and South Asian (P84T) populations, in order to predict the effects of the lineage-defining mutations of the viral variants on receptor binding. The effects of these mutations on protein stability were also explored. The protein-protein docking and molecular dynamics simulation analyses have revealed variable strength of attachment and exhibited altered interactions in the case of different hACE2-RBD complexes. In vitro studies are warranted to confirm these findings which may enable early prediction regarding the risk of transmissibility of newly emerging variants across different populations in the future.