Is Aspartate Aminotransferase to Platelet Ratio Index a Better Noninvasive Score for Predicting Advanced Fibrosis in Nonalcoholic Fatty Liver Disease Patients?

Background: In the 21st century, nonalcoholic fatty liver disease (NAFLD) is the most prevalent liver disorder. The prevalence of NAFLD within the general population in India ranges from 9 to 53%. The gold standard for assessing the severity of liver fibrosis is liver biopsy. However, due to various difficulties involved with liver biopsy, it is imperative to identify different non-invasive tools that can replace liver biopsy. Methodology: A prospective observational study of 130 patients meeting the inclusion criteria for NAFLD was done for a period of 18 months. We aimed to compare the performance characteristics of different noninvasive scores [fibrosis-4 (FIB-4) score, nonalcoholic fatty liver disease fibrosis score (NFS), and aspartate aminotransferase to platelet ratio index (APRI)] in predicting advanced fibrosis as assessed by FibroScan. Results: In the study, 76.9% of patients were male. Advanced fibrosis was seen in 12.3% of the patients. Majority of the patients with advanced fibrosis had metabolic syndrome. Based on the area under the receiver operating characteristic curve (AUROC), the new cut-off for ruling out advanced fibrosis for FIB-4, NFS, and APRI were 1.18, -0.9, and 0.65, respectively, and APRI had the best AUROC (0.768). Conclusion: Abnormal glycemic status and metabolic syndrome were risk factors for advanced fibrosis. The newly derived cut-offs for the FIB-4 score, NFS score, and APRI score had a better Negative predictive value compared to the original cut-offs. How to cite this article: Bhayani PD, Parameswaran SA, Palaniswamy KR, et al. Is Aspartate Aminotransferase to Platelet Ratio Index a Better Noninvasive Score for Predicting Advanced Fibrosis in Nonalcoholic Fatty Liver Disease Patients? Euroasian J Hepato-Gastroenterol 2024;14(1):35-39.

Unlocking The Mysteries of DNA Adducts with Artificial Intelligence.

Cellular genome is considered a dynamic blueprint of a cell since it encodes genetic information that gets temporally altered due to various endogenous and exogenous insults. Largely, the extent of genomic dynamicity is controlled by the trade-off between DNA repair processes and the genotoxic potential of the causative agent (genotoxins or potential carcinogens). A subset of genotoxins form DNA adducts by covalently binding to the cellular DNA, triggering structural or functional changes that lead to significant alterations in cellular processes via genetic (e. g., mutations) or non-genetic (e. g., epigenome) routes. Identification, quantification, and characterization of DNA adducts are indispensable for their comprehensive understanding and could expedite the ongoing efforts in predicting carcinogenicity and their mode of action. In this review, we elaborate on using Artificial Intelligence (AI)-based modeling in adducts biology and present multiple computational strategies to gain advancements in decoding DNA adducts. The proposed AI-based strategies encompass predictive modeling for adduct formation via metabolic activation, novel adducts' identification, prediction of biochemical routes for adduct formation, adducts' half-life predictions within biological ecosystems, and, establishing methods to predict the link between adducts chemistry and its location within the genomic DNA. In summary, we discuss some futuristic AI-based approaches in DNA adduct biology.

Amelioration of Amyloid-ß Induced Alzheimer's Disease by Bacopa monnieri through Modulation of Mitochondrial Dysfunction and GSK-3ß/Wnt/ß-Catenin Signaling.

BACKGROUND: Alzheimer's disease (AD) is the most prevalent dementia, affecting a large number of populations. Despite being under scrutiny for decades, an effective therapeutic option is still not available. METHODS AND RESULTS: This study explores the therapeutic role of a nootropic herb Bacopa monnieri (BM) in AD-like pathological conditions produced by injecting preformed amyloid-ß42 (Aß42) fibril bilaterally into hippocampus of Wistar rats, and ethanolic extract of BM is orally administered for 4 weeks. Assessment of behavioral changes reveals that BM treatment ameliorates Aß42-induced cognitive impairment and compromised explorative behavior. Supplementation of BM also reduces oxidative stress biomarkers, proinflammatory cytokines, and cholinesterase activity in the AD rats. Additionally, BM treatment restores Bcl-2-associated X protein (Bax)/ B-cell lymphoma 2 (Bcl-2) imbalance, increases neurotrophic factors expression, and prevents neurodegeneration validated by quantifying Nissl-positive hippocampal neurons. Interestingly, BM administration eliminates amyloid plaques in the hippocampal region and normalizes the Aß42-induced increase in phospho-tau and total tau expression. Mechanistic investigations reveal that BM interacts with glycogen synthase kinase (GSK-3ß) and restores Wnt/ß-catenin signaling. CONCLUSION: BM has been used in diet as a nootropic herb for several centuries. This study highlights the anti-Alzheimer activity of BM from the behavioral to the molecular level by modulating mitochondrial dysfunction, and GSK-3ß mediates the Wnt/ß-catenin signaling pathway.

Applying polypharmacology approach for drug repurposing for SARS-CoV2.

Exploring the new therapeutic indications of known drugs for treating COVID-19, popularly known as drug repurposing, is emerging as a pragmatic approach especially owing to the mounting pressure to control the pandemic. Targeting multiple targets with a single drug by employing drug repurposing known as the polypharmacology approach may be an optimised strategy for the development of effective therapeutics. In this study, virtual screening has been carried out on seven popular SARS-CoV-2 targets (3CLpro, PLpro, RdRp (NSP12), NSP13, NSP14, NSP15, and NSP16). A total of 4015 approved drugs were screened against these targets. Four drugs namely venetoclax, tirilazad, acetyldigitoxin, and ledipasvir have been selected based on the docking score, ability to interact with four or more targets and having a reasonably good number of interactions with key residues in the targets. The MD simulations and MM-PBSA studies showed reasonable stability of protein-drug complexes and sustainability of key interactions between the drugs with their respective targets throughout the course of MD simulations. The identified four drug molecules were also compared with the known drugs namely elbasvir and nafamostat. While the study has provided a detailed account of the chosen protein-drug complexes, it has explored the nature of seven important targets of SARS-CoV-2 by evaluating the protein-drug complexation process in great detail. Graphical abstract: Drug repurposing strategy against SARS-CoV2 drug targets. Computational analysis was performed to identify repurposable approved drug candidates against SARS-CoV2 using approaches such as virtual screening, molecular dynamics simulation and MM-PBSA calculations. Four drugs namely venetoclax, tirilazad, acetyldigitoxin, and ledipasvir have been selected as potential candidates. Supplementary Information: The online version contains supplementary material available at 10.1007/s12039-022-02046-0.

Searching for target-specific and multi-targeting organics for Covid-19 in the Drugbank database with a double scoring approach.

The current outbreak of Covid-19 infection due to SARS-CoV-2, a virus from the coronavirus family, has become a major threat to human healthcare. The virus has already infected more than 44 M people and the number of deaths reported has reached more than 1.1 M which may be attributed to lack of medicine. The traditional drug discovery approach involves many years of rigorous research and development and demands for a huge investment which cannot be adopted for the ongoing pandemic infection. Rather we need a swift and cost-effective approach to inhibit and control the viral infection. With the help of computational screening approaches and by choosing appropriate chemical space, it is possible to identify lead drug-like compounds for Covid-19. In this study, we have used the Drugbank database to screen compounds against the most important viral targets namely 3C-like protease (3CLpro), papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp) and the spike (S) protein. These targets play a major role in the replication/transcription and host cell recognition, therefore, are vital for the viral reproduction and spread of infection. As the structure based computational screening approaches are more reliable, we used the crystal structures for 3C-like main protease and spike protein. For the remaining targets, we used the structures based on homology modeling. Further, we employed two scoring methods based on binding free energies implemented in AutoDock Vina and molecular mechanics-generalized Born surface area approach. Based on these results, we propose drug cocktails active against the three viral targets namely 3CLpro, PLpro and RdRp. Interestingly, one of the identified compounds in this study i.e. Baloxavir marboxil has been under clinical trial for the treatment of Covid-19 infection. In addition, we have identified a few compounds such as Phthalocyanine, Tadalafil, Lonafarnib, Nilotinib, Dihydroergotamine, R-428 which can bind to all three targets simultaneously and can serve as multi-targeting drugs. Our study also included calculation of binding energies for various compounds currently under drug trials. Among these compounds, it is found that Remdesivir binds to targets, 3CLpro and RdRp with high binding affinity. Moreover, Baricitinib and Umifenovir were found to have superior target-specific binding while Darunavir is found to be a potential multi-targeting drug. As far as we know this is the first study where the compounds from the Drugbank database are screened against four vital targets of SARS-CoV-2 and illustrates that the computational screening using a double scoring approach can yield potential drug-like compounds against Covid-19 infection.

Discovery of biphenyl pyrazole scaffold for neurodegenerative diseases: A novel class of acetylcholinesterase-centered multitargeted ligands.

Multitargeted ligands have demonstrated remarkable efficiency as potential therapeutics for neurodegenerative diseases as they target multiple pathways involved in the progression of these diseases. Herein, we report first-in-class dual inhibitor of acetylcholinesterase (AChE) and tau aggregation as a novel class of multitargeted ligands for neurodegenerative diseases. The reported biphenyl pyrazole scaffold binds monomeric tau with submicromolar affinity and impedes the formation of tau oligomers at early stages. Additionally, the lead compound inhibited AChE activity with an IC50 value of 0.35 ± 0.02 µM. Remarkably, the neuroprotective effect of this lead in induced cytotoxicity model of SH-SY5Y neuroblastoma cells is superior to single-targeted AChE and tau-aggregation inhibitors. This scaffold would enable development of new generation of multitargeted ligands for neurodegenerative diseases that function through dual targeting of AChE and monomeric tau.

Structure-based drug designing and immunoinformatics approach for SARS-CoV-2.

The prevalence of respiratory illness caused by the novel SARS-CoV-2 virus associated with multiple organ failures is spreading rapidly because of its contagious human-to-human transmission and inadequate globalhealth care systems. Pharmaceutical repurposing, an effective drug development technique using existing drugs, could shorten development time and reduce costs compared to those of de novo drug discovery. We carried out virtual screening of antiviral compounds targeting the spike glycoprotein (S), main protease (Mpro), and the SARS-CoV-2 receptor binding domain (RBD)-angiotensin-converting enzyme 2 (ACE2) complex of SARS-CoV-2. PC786, an antiviral polymerase inhibitor, showed enhanced binding affinity to all the targets. Furthermore, the postfusion conformation of the trimeric S protein RBD with ACE2 revealed conformational changes associated with PC786 drug binding. Exploiting immunoinformatics to identify T cell and B cell epitopes could guide future experimental studies with a higher probability of discovering appropriate vaccine candidates with fewer experiments and higher reliability.

INASL Guidelines on Management of Hepatitis B Virus Infection in Patients receiving Chemotherapy, Biologicals, Immunosupressants, or Corticosteroids.

Hepatitis B Virus (HBV) reactivation in patients receiving chemotherapy, biologicals, immunosupressants, or corticosteroids is emerging to be an important cause of morbidity and mortality in patients with current or prior exposure to HBV infection. These patients suffer a dual onslaught of illness: one from the primary disease for which they are receiving the culprit drug that led to HBV reactivation, and the other from HBV reactivation itself. The HBV reactivation not only leads to a compromised liver function, which may culminate into hepatic failure; it also adversely impacts the treatment outcome of the primary illness. Hence, identification of patients at risk of reactivation before starting these drugs, and starting treatment aimed at prevention of HBV reactivation is the best strategy of managing these patients. There are no Indian guidelines on management of HBV infection in patients receiving chemotherapy, biologicals, immunosupressants, or corticosteroids for the treatment of rheumatologic conditions, malignancies, inflammatory bowel disease, dermatologic conditions, or solid-organ or bone marrow transplantation. The Indian National Association for Study of the Liver (INASL) had set up a taskforce on HBV in 2016, with a mandate to develop consensus guidelines for management of various aspects of HBV infection, relevant to India. In 2017 the taskforce had published the first INASL guidelines on management of HBV infection in India. In the present guidelines, which are in continuation with the previous guidelines, the issues on management of HBV infection in patients receiving chemotherapy, biologicals, immunosupressants, or corticosteroids are addressed.