Pinpointing top inhibitors for GSK3β from pool of indirubin derivatives using rigorous computational workflow and their validation using molecular dynamics (MD) simulations

Pan-genome analysis and drug repurposing strategies for extensively drug-resistant Salmonella Typhi: Subtractive genomics and e-pharmacophore approaches

In the current study, we presented the genome sequence and taxonomic classification of the new extensively drug-resistant (XDR) Salmonella enterica serovar Typhi strain JRCGR-ST-AK02. Its genome size was found to be 4,780,534 bp, containing 4864 genes. Taxonomic classification was performed based on the Average Nucleotide Identity (ANI), Genome-to-Genome Distance Calculator (GGDC) and Average Amino Acid Identity (AAI) analysis. Pan-genome analysis revealed 34,4915 core genes, which are predominantly involved in general functions and carbohydrate metabolism. We used a subtractive genomics approach and identified the PocR protein as a drug target. Its 3D structure was built using homology modeling, and an e-pharmacophore hypothesis was created using its binding site. The pharmacophore hypothesis was screened against FDA-approved ligands library and a total of 2018 out 9392 drugs were selected for molecular docking. Cangrelor and Pentagastrin presented docking scores of -9.503 and -9.081 kcal/mol, respectively. The binding dynamics of these promising FDA-approved drugs were further confirmed through 200 ns molecular dynamics simulation, highlighting their stable and strong interactions with the PocR protein. Our study highlights the potential of Cangrelor and Pentagastrin for repurposing against XDR Salmonella Typhi. By identifying these drugs as promising candidates, we pave the way for new treatments for XDR Salmonella Typhi infections.

Repurposing FDA-Approved Drugs for Eumycetoma Treatment: Homology Modeling and Computational Screening of CYP51 Inhibitors

Eumycetoma, a chronic fungal infection caused by Madurella mycetomatis, is a neglected tropical disease characterized by tumor-like growths that can lead to permanent disability and deformities if untreated. Predominantly affecting regions in Africa, South America, and Asia, it imposes significant physical, social, and economic burdens. Current treatments, including antifungal drugs like itraconazole, often show variable efficacy, with severe cases necessitating surgical intervention or amputation. Drug discovery for eumycetoma faces challenges due to limited understanding of the disease's molecular mechanisms and the lack of 3D structures for key targets such as Madurella mycetomatis CYP51, a well-known target for azoles' antifungal agents. To address these challenges, this study employed computational approaches, including homology modeling, virtual screening, free energy calculations, and molecular dynamics simulations, to repurpose FDA-approved drugs as potential treatments for eumycetoma targeting Madurella mycetomatis CYP51. To this end, a library of 2619 FDA-approved drugs was screened, identifying three promising candidates: montelukast, vilanterol, and lidoflazine. These compounds demonstrated favorable binding affinities, strong interactions with critical residues of the homology model of Madurella mycetomatis CYP51, and stability in molecular dynamics simulations, offering potential for further investigation as effective therapeutic options for eumycetoma.

Integrative bioinformatic analysis to identify potential phytochemical candidates for glioblastoma

Glioblastoma (GBM) is one of the most malignant forms of cancer with the lowest survival ratio. Our study aims to utilize an integrated bioinformatic analysis to identify hub genes against GBM and explore the active phytochemicals with drug-like properties in treating GBM. The study employed databases of DisGenet, GeneCards, and Gene Expression Omnibus to retrieve GBM-associated genes, revealing 142 overlapping genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to analyze the role of these genes, which were involved in cancer-associated cell signaling pathways with tyrosine kinase activities and mainly enriched in the Nucleus. Furthermore, the hub genes identification through Cytoscape identified the top 10 ranked genes in a network, which were used as targets to dock against phytochemicals retrieved from the NPACT database having the ability to pass the blood-brain barrier and drug-likeness properties. The molecular docking and dynamics simulation studies predicted the binding of Isochaihulactone and VismioneB to the active site residues of EGFR and SRC genes. In contrast, Resveratrol binds to key residues of PIK3CA. Further, the binding free energy of the docked complex was calculated by performing MM-GBSA analysis, providing a detailed understanding of the underlying molecular interactions. The results offer interactional and structural insights into candidate phytochemicals towards GBM-associated top-ranked proteins. However, validation studies must be done through both in vitro and in vivo disease models to strengthen our computational results.

Phosphorylation at the D56 residue of MtrA in Mycobacterium tuberculosis enhances its DNA binding affinity by modulating inter-domain interaction

The response regulator, MtrA, plays a major role in adaptation to the host environment, cell division, replication, and dormancy activation of Mycobacterium tuberculosis (Mtb). The phosphorylation of the response regulator MtrA alters the downstream activity, typically involving changes in DNA binding activity. However, there is a substantial knowledge gap in understanding the phosphorylation-mediated structural changes in MtrA. Additionally, the active conformation of the protein has yet to be determined. Therefore, in this study, we have investigated the phosphorylation-induced conformational changes of MtrA using all-atom molecular dynamics simulations under various phosphorylation conditions. The results from this study demonstrate that the phosphorylation at D56 (pD56-MtrA) increases the compactness of the MtrA protein by stabilizing the inter-domain interaction between the regulatory domain and DNA binding domain. Notably, the higher occupancy H-bond (over 95 %) between Arg200-Asn100 in case of the pD56-MtrA condition, which is otherwise absent in the non-phosphorylated (uMtrA) condition, suggests the importance of this interaction in the active conformation of the protein. The dynamic cross-correlation analysis reveals that phosphorylation (especially pD56-MtrA) reduces the anti-correlated motions and increases correlated motions between different domains. Moreover, the higher DNA binding affinity of pD56-MtrA compared to uMtrA supported by molecular docking and MD simulation followed by MMPBSA analysis suggests that pD56-MtrA is the possible active conformation of the MtrA protein. Overall, this investigation elucidates the key structural changes in MtrA under different phosphorylated conditions, which might help in designing novel therapeutics against tuberculosis.

In silico screening of phytochemicals against chromatin modifier, SETD7 for remodeling of the immunosuppressive tumor microenvironment in renal cancer

The tumor microenvironment and immune evasion function in a complex cellular network profoundly challenge the clinical outcome of promising therapies. Our recently published study reported that the subset of genes upregulated in ccRCC due to H3K4me1 and DNA demethylation potentially leads to an immunosuppressive environment. Thus, modulating H3K4me1 chromatin modifier SETD7 with a natural inhibitor in combination with immunotherapy might improve the immune landscape for a better therapeutic outcome. The present study was conducted via virtual screening and MD simulation using compounds from the literature, IMPPAT, and SuperNatural database. The phytochemical IMPHY002979 showed better binding affinity and lower energy than the reported R-PFI-2 and cyproheptadine inhibitors. The phytochemicals interact with the SET domain through H-bonding, as confirmed by MD simulation and molecular interaction analysis. Further, the compound was assessed using ADME parameters and free energy estimation, showing better pharmacokinetic properties. Therefore, the non-accessibility of the histone methyltransferase activity domain of SET7 with IMPHY002979 can downregulate H3K4me1 and, thereby, the expression of genes potentially responsible for immunosuppressive TME. Thus, patient stratification based on molecular markers for immunotherapy and combining epigenetic modulators with therapeutic drugs will improve the efficacy of immunotherapy in ccRCC.

Morphological and biochemical characteristics of wild red-fleshed apples (Malus sieversii f. niedzwetzkyana) in the North and Northeast of Iran

BACKGROUND

Red-flesh apples (Malus sieversii f. niedzwetzkyana) have attracted attention from consumers and researchers due to their pleasant appearance and taste. These exotic apples are rich sources of nutrients and health-promoting polyphenols and phenolics. This study aimed to investigate morphological (40 quantitative and 13 qualitative traits) and biochemical (5 traits) characteristics of four socioeconomically important red-fleshed apple populations in North and Northeast region of Iran, which are understudied and under serious extinction risk.

RESULTS

The examined characters exhibited wide and statistically significant variations, especially in leaf color (68.86%) and the number of seeds per fruit (61.61%), and more dramatically in the total flavonoids (146.64%) and total phenolics contents (105.81%). There were also strong variations in fresh fruit weight and fruit length, diameter, and flesh thickness. Red, with 34 accessions, was the dominant ripe fruit skin color. All biochemical traits also showed high variations, particularly in total flavonoid content. Red-fleshed Gavramak and Kalateh Khij apples contained the highest biochemical and morphological values, respectively. Principal component analysis (PCA) revealed that the first five principal components together accounted for more than 60.83% variation of the total observed variations. Moreover, the cluster dendrogram analysis based on Ward's method indicated three different clusters based on the characters measured, indicating high variation among the accessions.

CONCLUSION

red-flesh apples can be considered suitable sources of natural antioxidants with great potential as healthy foods and nutraceutical applications. Based on the commercial characters, Red-fleshed Gavramak and Kalateh Khij apples showed the highest fruit quality with proper size and thus can be suggested as superior for cultivation or use in breeding programs due to having higher quality fruits.

An Ensemble Classifiers for Improved Prediction of Native-Non-Native Protein-Protein Interaction

In this study, we present an innovative approach to improve the prediction of protein-protein interactions (PPIs) through the utilization of an ensemble classifier, specifically focusing on distinguishing between native and non-native interactions. Leveraging the strengths of various base models, including random forest, gradient boosting, extreme gradient boosting, and light gradient boosting, our ensemble classifier integrates these diverse predictions using a logistic regression meta-classifier. Our model was evaluated using a comprehensive dataset generated from molecular dynamics simulations. While the gains in AUC and other metrics might seem modest, they contribute to a model that is more robust, consistent, and adaptable. To assess the effectiveness of various approaches, we compared the performance of logistic regression to four baseline models. Our results indicate that logistic regression consistently underperforms across all evaluated metrics. This suggests that it may not be well-suited to capture the complex relationships within this dataset. Tree-based models, on the other hand, appear to be more effective for problems involving molecular dynamics simulations. Extreme gradient boosting (XGBoost) and light gradient boosting (LightGBM) are optimized for performance and speed, handling datasets effectively and incorporating regularizations to avoid over-fitting. Our findings indicate that the ensemble method enhances the predictive capability of PPIs, offering a promising tool for computational biology and drug discovery by accurately identifying potential interaction sites and facilitating the understanding of complex protein functions within biological systems.

Deciphering the mechanisms and interactions of the endocrine disruptor bisphenol A and its analogs with the androgen receptor

Bisphenol A (BPA) and its various forms used as BPA alternatives in industries are recognized toxic compounds and antiandrogenic endocrine disruptors. These chemicals are widespread in the environment and frequently detected in biological samples. Concerns exist about their impact on hormones, disrupting natural biological processes in humans, together with their negative impacts on the environment and biotic life. This study aims to characterize the interaction between BPA analogs and the androgen receptor (AR) and the effect on the receptor's normal activity. To achieve this goal, molecular docking was conducted with BPA and its analogs and dihydrotestosterone (DHT) as a reference ligand. Four BPA analogs exhibited higher affinity (-10.2 to -8.7 kcal/mol) for AR compared to BPA (-8.6 kcal/mol), displaying distinct interaction patterns. Interestingly, DHT (-11.0 kcal/mol) shared a binding pattern with BPA. ADMET analysis of the top 10 compounds, followed by molecular dynamics simulations, revealed toxicity and dynamic behavior. Experimental studies demonstrated that only BPA disrupts DHT-induced AR dimerization, thereby affecting AR's function due to its binding nature. This similarity to DHT was observed during computational analysis. These findings emphasize the importance of targeted strategies to mitigate BPA toxicity, offering crucial insights for interventions in human health and environmental well-being.