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

Natural Products in Precision Neurological Disease (Cryptococcal Meningitis): Structure-Based Phytochemical Screening of Glycyrrhiza glabra Plant Against Cryptococcus neoformans Farnesyltransferase (FTase)

Cryptococcus neoformans causes cryptococcal meningitis, which is lethal to immune-compromised people, especially AIDS patients. This study employed diverse in silico techniques to find the best phytochemical to block farnesyltransferase (FTase). Based on molecular docking, the top two compounds selected from a screening of 5807 phytochemical compounds from 29 medicinal plants were CID_8299 (hydroxyacetone) and CID_71346280 (1,7-bis (4-hydroxyphenyl)-1,4,6-heptatrien-3-one), with docking scores of -5.786 and -0.078 kcal/mol, respectively, indicating stronger binding affinities than the control CID_3365 (fluconazole), which scored -4.2 kcal/mol. The control and lead compounds bind at the common active site of protein by interacting with common amino acid residues (HIS97, GLN408, PHE93, and TRP94). Post-docking MM-GBSA verified docking score where CID_8299 and CID_71346280 had negative binding free energies of -19.81 and -0.27 kcal/mol, respectively. These two lead compounds were reassessed through molecular dynamics simulation (100 ns), and several post-dynamics analyses were conducted. CID_71346280, 8299, and 3365 (control) showed average RSMD values of 3.17, 1.904, and 2.08; average root mean square fluctuation values of 1.167, 0.886, and 1.028 Å; average radius of gyration values of 5.13, 1.58, and 3.54 Å; average solvent accessible surface area values of 121.16, 3.51, and 183.81 Å2; average H-bond values of 466.05, 470.84, and 456.84 Å, respectively. The results revealed that CID_8299 had the highest stability and consistent interaction with the target protein throughout the simulation period. According to the toxicity analysis, CID_8299, which is found in the Glycyrrhiza glabra plant, can also cross the BBB, which makes it unbeatable in treating neuro-disease caused by C. neoformans and may potentially block FTase protein's activity inhibiting post-translational lipidation of essential signal transduction protein.

Using the power of artificial intelligence to improve the diagnosis and management of nonmelanoma skin cancer

Nonmelanoma skin cancer (NMSC), including basal cell carcinoma and squamous cell carcinoma, is the most prevalent type of skin cancer. While generally less aggressive than melanoma, early detection and treatment are crucial to prevent the complications. Artificial intelligence (AI) systems show promise in enhancing the accuracy, efficiency, and accessibility of NMSC diagnosis and management. These systems can facilitate early interventions, reduce unnecessary procedures, and promote collaboration among healthcare providers. Despite AI algorithms demonstrating moderate-to-high performance in diagnosing NMSC, several challenges remain. Ensuring the robustness, explainability, and generalizability of these models is vital. Collaborative efforts focusing on data diversity, image quality standards, and ethical considerations are necessary to address these issues. Building patient trust is also essential for the successful implementation of AI in the clinical settings. AI algorithms may outperform experts in controlled environments but can fall short in the real-world clinical applications, indicating a need for more prospective studies to evaluate their effectiveness in the practical scenarios. Continued research and development are essential to fully realize AI's potential in improving NMSC diagnosis and management by overcoming the existing challenges and conducting comprehensive studies.

High-throughput screening of natural antiviral drug candidates against white spot syndrome virus targeting VP28 in Penaeus monodon: Computational drug design approaches

The white spot syndrome virus (WSSV), considered the deadliest pathogen impacting Penaeid shrimp (Penaeus monodon), remains worrisome for the global shrimp industry due to its extreme virulence and mortality rate of up to 100%. To date, there has been no breakthrough in effective antivirals or vaccines that can mitigate the financial damage caused by the pathogen. The distinctive structure of VP28 facilitates its role as a trimer, serving as the primary envelope protein of WSSV. It anchors to the viral envelope, directly interacts with PmRab7, a membrane protein in P. monodon, and aids in entry into the host. This research aims to discover antiviral drug candidates targeting VP28 trimer by screening a virtual library of 187 bioactive compounds derived from the medicinal herbs Azadirachta indica and Bacopa monnieri. To evaluate the drug ability of compounds in restricting VP28 trimer interaction within the endocytic pathway, a computational strategy was employed, including virtual screening, pharmacokinetics and toxicity analysis, and molecular dynamics (MD) simulation. The four strongest compounds, epicatechin, luteolin, kaempferol, and apigenin, exhibited binding affinities of -8.8, -8.8, -8.7, and -8.5 Kcal/mol, respectively, and demonstrated excellent pharmacokinetic properties. Furthermore, we employed 100 nanoseconds MD simulations and MM-PBSA binding free energy calculations to examine intermolecular interactions and confirmed the structural stability of the compounds at the VP28 binding site. The findings of this research suggest that these compounds hold promise in combating WSSV infection, reducing economic losses, and contributing to the sustainability of the shrimp industry.

In-vitro and in-silico evaluation of rue herb for SARS-CoV-2 treatment

SARS-CoV-2, a β-coronavirus responsible for the COVID-19 pandemic, has resulted in approximately 4.9 million fatalities worldwide. Despite the urgent need, there is currently no specific therapeutic developed for treating or preventing SARS-CoV-2 infections. The virus enters the host by engaging in a molecular interaction between the viral Spike glycoprotein (S protein) and the host ACE2 receptor, facilitating membrane fusion and initiating infection. Inhibiting this interaction could impede viral activity. Therefore, this study aimed to identify natural small molecules from perennial rue herb (Ruta graveolens) as potential inhibitors against the S protein, thus preventing virus infection. Initially, a screening process was conducted on 53 compounds identified from rue herbs, utilizing pharmacophore-based virtual screening approaches. This analysis resulted in the identification of 12 hit compounds. Four compounds, namely Amentoflavone (CID: 5281600), Agathisflavone (CID: 5281599), Vitamin P (CID: 24832108), and Daphnoretin (CID: 5281406), emerged as potential S protein inhibitors through molecular docking simulations, exhibiting binding energies in kcal/mol of -9.2, -8.8, -8.2, and -8.0, respectively. ADMET analysis revealed favorable pharmacokinetics and toxicity profiles for these compounds. The compounds' stability with respect to the target S protein was evaluated using MD simulation and MM-GBSA approaches. The analysis revealed the stability of the selected compounds with the target protein. Also, PCA revealed distinctive movement patterns in four selected compounds, offered valuable insights into their functional behaviors and potential interactions. In-vitro assays revealed that rue herb extracts containing these compounds displayed potential inhibitory properties against the virus, with an IC50 value of 1.299 mg/mL and a cytotoxic concentration (CC50) value of 11.991 mg/mL. The compounds derived from rue herb, specifically Amentoflavone, Agathisflavone, Vitamin P, and Daphnoretin, show promise as candidates for the therapeutic intervention of SARS-CoV-2-related complications.

Solvent-dependent chemoselective synthesis of different isoquinolinones mediated by the hypervalent iodine(III) reagent PISA

Isoquinolinone is an important heterocyclic framework in natural products and biologically active molecules, and the efficient synthesis of this structural motif has received much attention in recent years. Herein, we report a (phenyliodonio)sulfamate (PISA)-mediated, solvent-dependent synthesis of different isoquinolinone derivatives. The method provides highly chemoselective access to 3- or 4-substituted isoquinolinone derivatives by reacting o-alkenylbenzamide derivatives with PISA in either acetonitrile or wet hexafluoro-2-isopropanol.

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.

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.