Subhash Chandra Mandal

This study focuses on the development of FXR PREDICTOR, an application designed to guide researchers in determining the activity of chemical compounds against non‐alcoholic fatty liver disease (NAFLD) and non‐alcoholic steatohepatitis (NASH) through modulation of the farnesoid X receptor (FXR). From ChEMBL database 1217 unique compounds were retrieved which were analyzed by: i . conventional 2D‐QSAR (Quantitative Structure‐Activity Relationship) with Dragon descriptors and molecular fingerprints, ii . Transformer‐CNN, leveraging SMILES augmentation. Morgan fingerprint‐based model with random forest classifier algorithm produced the best predictive model with strong Matthews correlation coefficient (MCC). Although the descriptor‐based model had lower predictive quality, it provided important insights into the structural features of the ligands through permutation and SHAP analyses. Contour maps for fingerprint‐based model specify favourable regions for lead optimization. 85 new compounds from ChEMBL were deployed as validation set; retrieving more than 80% balanced accuracy, confirming model robustness. This model was incorporated in Streamlit‐based FXR PREDICTOR, a user‐friendly application for virtual screening.

Heat shock factor 1 (HSF1) masters cellular proteostasis under stress by upregulating the expression of molecular chaperones that help refold or degrade the misfolded proteins. HSF1 activation involves a monomer-to-oligomer transition and binding to its recognition sequence, the heat shock elements (HSEs) on its target gene promoters. HSF1 activity declines with age as well as in neurodegenerative disorders (NDs) such as Parkinson’s disease, highlighting the need for strategies to restore its function. Azadiradione (AZD), a limonoid isolated from Azadirachta indica seeds, directly activates HSF1 in cellular and preclinical ND models, unlike other small-molecule activators reported elsewhere. We investigated the molecular basis of AZD-mediated HSF1 activation using purified variants of this protein including those without its oligomerization and transactivation domain. Fluorescence polarization and dynamic light scattering assays revealed that AZD promotes the oligomerization of monomeric HSF1 to enhance its HSE-binding affinity by engaging with its DNA-binding domain (DBD). The oligomerization domain known to be required for stress-induced activation, appears redundant in AZD-mediated activation. Furthermore, evidence suggests AZD-induced conformational alterations in the HSE facilitate its binding to the HSF1 monomer. Notably, AZD reduces the DNA-binding ability of pre-assembled oligomeric HSF1 by triggering its amyloid-like aggregation. This finding also highlighted a potential anticancer effect of AZD, as cancer cells heavily depend on this HSF1 population for rapid proliferation and survival. Overall, these findings offer novel insights into the functional regulation of HSF1 and suggest a framework for developing small-molecule HSF1 activators with therapeutic potential for protein conformation disorders.

Boswellia serrata Roxb. Ex Colebr is a popular medicinal plant used traditionally in herbal medicinal preparations to treat a variety of diseases. The purpose of the present investigation was to investigate the anti‐hemorrhoidal property of the bark extract of B. serrata (BS). For this, the sequential Soxhlet extraction method was carried out by using different solvents such as hexane, chloroform, and methanol. After the extraction, the obtained dry extracts were tested for quantitative determinations such as total alkaloid content (TAC), total flavonoid content (TFC), total phenol content (TPC), and total tannin content (TTC) for all the extracts. Moreover, in vitro antioxidant activity was measured using 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) free radical scavenging activity and scavenging activity against 2,2′‐azino‐bis(3‐ethylbenzothiazoline‐6‐sulfonic acid (ABTS). Methanolic bark extract showed the highest TPC (67.10±1.83), TFC (372.73±4.45), TAC (9.732±1.06), and TTC (48.932±1.82), as well as the antioxidant assays DPPH (IC50=9.88 μg/ml) and ABTS (IC50=15.09 μg/ml). In this study, both LC–MS and GC–MS were performed to identify the chemical composition of all the extracts. Consequently, 19 compounds were identified by GC–MS and 27 compounds were identified by LC–MS analysis. The identified phytoconstituent(s) that could potentially interact with the target protein cyclooxygenase‐2 (COX‐2) (PDB: 4RRW) using molecular dynamics simulation and in silico docking were studied. Three compounds that have passed in drug‐likeness and ADME‐Tox properties are having more docking score than the standard. In this study, camptothecin, justicidin B, and taxiphyllin are identified as potential lead compounds with anti‐hemorrhoidal properties and may be helpful in the process of drug development and discovery of novel drugs. Hence, these results demonstrate that BS is a good source of pharmacologically active components with potential applications against hemorrhoidal disease.

Human soluble epoxide hydrolase (sEH), a dual-functioning homodimeric enzyme with hydrolase and phosphatase activities, is known for its pivotal role in the hydrolysis of epoxyeicosatrienoic acids. Inhibitors targeting sEH have shown promising potential in the treatment of various life-threatening diseases. In this study, we employed a range of in silico modeling approaches to investigate a diverse dataset of structurally distinct sEH inhibitors. Our primary aim was to develop predictive and validated models while gaining insights into the structural requirements necessary for achieving higher inhibitory potential. To accomplish this, we initially calculated molecular descriptors using nine different descriptor-calculating tools, coupled with stochastic and non-stochastic feature selection strategies, to identify the most statistically significant linear 2D-QSAR model. The resulting model highlighted the critical roles played by topological characteristics, 2D pharmacophore features, and specific physicochemical properties in enhancing inhibitory potential. In addition to conventional 2D-QSAR modeling, we implemented the Transformer-CNN methodology to develop QSAR models, enabling us to obtain structural interpretations based on the Layer-wise Relevance Propagation (LRP) algorithm. Moreover, a comprehensive 3D-QSAR analysis provided additional insights into the structural requirements of these compounds as potent sEH inhibitors. To validate the findings from the QSAR modeling studies, we performed molecular dynamics (MD) simulations using selected compounds from the dataset. The simulation results offered crucial insights into receptor–ligand interactions, supporting the predictions obtained from the QSAR models. Collectively, our work serves as an essential guideline for the rational design of novel sEH inhibitors with enhanced therapeutic potential. Importantly, all the in silico studies were performed using open-access tools to ensure reproducibility and accessibility.

Colorectal cancer (CRC) is the third most diagnosed and second leading cause of cancer-related death worldwide. Limitations with existing treatment regimens have demanded the search for better treatment options. Different phytochemicals with promising anti-CRC activities have been reported, with the molecular mechanism of actions still emerging. This review aims to summarize recent progress on the study of natural phenolic compounds in ameliorating CRC using in vivo models. This review followed the guidelines of the Preferred Reporting Items for Systematic Reporting and Meta-Analysis. Information on the relevant topic was gathered by searching the PubMed, Scopus, ScienceDirect, and Web of Science databases using keywords, such as “colorectal cancer” AND “phenolic compounds”, “colorectal cancer” AND “polyphenol”, “colorectal cancer” AND “phenolic acids”, “colorectal cancer” AND “flavonoids”, “colorectal cancer” AND “stilbene”, and “colorectal cancer” AND “lignan” from the reputed peer-reviewed journals published over the last 20 years. Publications that incorporated in vivo experimental designs and produced statistically significant results were considered for this review. Many of these polyphenols demonstrate anti-CRC activities by inhibiting key cellular factors. This inhibition has been demonstrated by antiapoptotic effects, antiproliferative effects, or by upregulating factors responsible for cell cycle arrest or cell death in various in vivo CRC models. Numerous studies from independent laboratories have highlighted different plant phenolic compounds for their anti-CRC activities. While promising anti-CRC activity in many of these agents has created interest in this area, in-depth mechanistic and well-designed clinical studies are needed to support the therapeutic use of these compounds for the prevention and treatment of CRC.

(1) Background: To assess the genetic makeup among the agro-economically important members of Euphorbiaceae, the present study was conducted to identify and characterize high-quality single-nucleotide polymorphism (SNP) markers and their comparative distribution in exonic and intronic regions from the publicly available expressed sequence tags (ESTs). (2) Methods: Quality sequences obtained after pre-processing by an EG assembler were assembled into contigs using the CAP3 program at 95% identity; the mining of SNP was performed by QualitySNP; GENSCAN (standalone) was used for detecting the distribution of SNPs in the exonic and intronic regions. (3) Results: A total of 25,432 potential SNPs (pSNP) and 14,351 high-quality SNPs (qSNP), including 2276 indels, were detected from 260,479 EST sequences. The ratio of quality SNP to potential SNP ranged from 0.22 to 0.75. A higher frequency of transitions and transversions was observed more in the exonic than the intronic region, while indels were present more in the intronic region. C↔T (transition) was the most dominant nucleotide substitution, while in transversion, A↔T was the dominant nucleotide substitution, and in indel, A/- was dominant. (4) Conclusions: Detected SNP markers may be useful for linkage mapping; marker-assisted breeding; studying genetic diversity; mapping important phenotypic traits, such as adaptation or oil production; or disease resistance by targeting and screening mutations in important genes.