Biology subjects

Hasnat, S.

Publications and source records attributed to Hasnat, S..

8 recordsLinked to original sources

bioRxiv2026

3-Methylpentanoic acid from Bacillus safensis suppresses wheat blast disease by targeting UDP-glucose 4-epimerase

Wheat blast, caused by Magnaporthe oryzae Triticum (MoT), is a devastating disease threatening global food security. Current reliance on chemical fungicides is unreliable due to the development of resistant MoT populations, highlighting the need for safe and eco-friendly alternatives. Naturally occurring volatile organic compounds (VOCs) possess potent antifungal potential thereby inhibiting phytopathogen. In this study, we investigated the fungicidal potential of 3-methylpentanoic acid (3-MP), a VOC produced by Bacillus safensis and also found in snake-fruit aroma, on MoT pathogen. In vitro assays revealed dose-dependent inhibition of MoT mycelial growth, conidiogenesis, conidial germination, and appressorium formation, with complete suppression achieved at 100-125 {micro}M. Detached leaf, seedling, and spike assays demonstrated robust preventive and curative protection, highlighting translational potential under field conditions. Mechanistic investigations showed that 3-MP compromises membrane integrity, as confirmed by fluorescein diacetate staining, and targets UDP-glucose 4-epimerase (UGE), a key enzyme required for galactose metabolism and cell wall integrity in fungi. Molecular dynamics simulations revealed stable binding of 3-MP within the NAD-associated Rossmann fold of UGE, sterically blocking substrate access and perturbing NAD orientation. RT-PCR gene expression analysis corroborated this model, showing early induction followed by repression of UGE expression, consistent with collapse of UDP-glucose metabolism and impaired cell wall biosynthesis. This study for the first time identified 3-MP as a natural inhibitor of UGE and provided new insight into the antifungal mechanism of the compound, highlighting its potential for integrated wheat blast management. ImportanceWheat blast, caused by Magnaporthe oryzae Triticum (MoT), poses a catastrophic threat to global food security, particularly in South America, Africa, and South Asia. With MoT rapidly developing resistance to conventional chemical fungicides, there is an urgent need for sustainable, eco-friendly alternatives. Our study identifies 3-methylpentanoic acid (3-MP), a volatile organic compound produced by Bacillus safensis, as a potent antifungal agent against MoT. We demonstrate that 3-MP inhibits multiple life stages of the pathogen, including mycelial growth, conidiation, and appressorium formation. Furthermore, we provide molecular insights through molecular docking and MD simulations, identifying UDP-glucose 4-epimerase as a likely target of 3-MP. By revealing a dual-action (preventive and curative) natural compound and its potential mechanism, this work offers a promising blueprint for developing bio-based fungicides to combat devastating plant diseases while reducing the environmental footprint of agriculture.

microbiology↗

bioRxiv2025

Temporal transcriptomics and molecular dynamics identify a serine-type endopeptidase as a key regulator of dengue virus infection in Aedes aegypti

The dengue virus (DENV), a major global pathogen causing over 400 million annual infections, relies on the mosquito Aedes aegypti as its primary vector. Intriguingly, A. aegypti sustains persistent DENV infection without exhibiting apparent pathology, indicating a highly adapted and regulated host-virus relationship. However, the temporal gene expression dynamics that govern this finely balanced interaction remain poorly understood. We performed a comprehensive transcriptomic analysis using 12 paired-end RNA-seq datasets from gene expression omnibus (GEO; GSE222893), comparing naive and DENV-infected A. aegypti samples at Days 1, 2, and 7 post-infection. A robust bioinformatics pipeline (STAR [->] FeatureCounts [->] DESeq2 [->] g:Profiler) was employed to identify differentially expressed genes (DEGs), explore functional annotations, and resolve temporal patterns via principal component analysis. Finally, a molecular dynamics simulation (MDS) was performed to check the molecular stability of the highly expressed gene. Our temporal analysis identified LOC5570687, a gene encoding a serine-type endopeptidase, as the most significantly differentially expressed transcript across all infection time points. Functional annotation confirmed its role in proteolysis, implicating it in the cleavage of flaviviral polyproteins, a critical step in viral replication. Principal component analysis revealed distinct transcriptional divergence at Day 1, immune modulation at Day 2, and convergence by Day 7--marking virion maturation. Downregulation of LOC5570687 in DENV-exposed mosquitoes was temporally associated with enhanced viral replication, indicating its potential role as a molecular switch between antiviral defense and viral exploitation. A 100 ns MDS was proof of the structural stability, compactness, and dynamic properties of the highly expressed protein. This study uncovers the temporally dynamic transcriptional landscape of A. aegypti during DENV infection and the serine-type endopeptidase LOC5570687 as a critical regulator of viral pathogenesis. These findings provide a molecular framework for understanding vector competence and propose the LOC5570687 as a promising target for vector-based intervention strategies to disrupt DENV transmission.

microbiology↗

bioRxiv2025

Computational investigation unveils pathogenic LIG3 non-synonymous mutations and therapeutic targets in acute myeloid leukemia

Single nucleotide polymorphisms (SNPs) in DNA repair genes can impair protein structure and function, contributing to disease development, including cancer. Non-synonymous SNPs (nsSNPs) in the LIG3 gene are linked to genomic instability and increased cancer risk, particularly acute myeloid leukemia (AML). This study aims to identify the most deleterious nsSNPs in the LIG3 gene and potential therapeutic targets for DNA repair restoration in AML. We employed in-silico computational methods to analyze LIG3 nsSNPs, using PredictSNP and Mutation3D to assess pathogenicity. Subsequently, molecular docking and dynamics simulations were conducted to evaluate ligand-binding affinities and protein stability. Out of the 12,191 mapped SNPs, 132 were nsSNPs located in the coding region. Among these, 18 nsSNPs were identified as detrimental including 12 destabilizing and 6 stabilizing nsSNPs. Nine cancer-associated nsSNPs, including L381R and R528C, were predicted due to their structural and functional impacts. Further analysis revealed key phosphorylation and methylation sites, such as 529S and 224R. Molecular dynamics simulations highlighted stable interactions of compounds AHP-MPC and DM-BFC with wild-type and R528C mutant LIG3 proteins, while R671G and V781M mutants showed instability. Protein-protein interaction networks and functional enrichment linked LIG3 to DNA repair pathways. Kaplan-Meier analysis associated high LIG3 expression with improved survival in breast cancer and AML, suggesting its role as a prognostic biomarker. This study emphasizes the mutation-specific effects of LIG3 nsSNPs on protein stability and ligand interactions. We recommend identifying DM-BFC to advance personalized medicine approaches for targeting deleterious variants, following in vitro and in vivo validation for AML treatment.

cancer biology↗

bioRxiv2025

Enterococcus faecium MBBL3 Exhibits Promising Probiotic Potential and Antimicrobial Efficacy Against Bovine Mastitis-Associated Escherichia coli and Klebsiella pneumoniae

Enterococcus faecium, a promising probiotic, combats pathogens, supports gut health, strengthens immunity, and provides a natural approach to address the escalating global challenge of antimicrobial resistance. This study aimed to investigate the genome of E. faecium MBBL3, isolated from healthy cow milk, to assess its probiotic potential and antimicrobial activity against pathogens causing bovine mastitis. The strain was analyzed through whole genome sequencing, along with in-vitro and in-silico assessments were conducted to determine its antimicrobial efficacy against bovine mastitis pathogens, Klebsiella pneumoniae MBBL2 (Kp MBBL2) and Escherichia coli MBBL4 (Ec MBBL4). The genome assembly and functional annotations uncovered many important probiotic traits in MBBL3, where genome comparison revealed its high genetic similarity with other Enterococcus strains. MBBL3 demonstrated the ability to ferment a wide range of carbohydrates and possessed 76 carbohydrate-active enzyme-related genes, including five key CAZy families namely GH73, GH18, CBM50, CE4, and AA10. It also possessed importance genes for bile salt and acid tolerance, stress resistance, and surface adhesion. Additionally, MBBL3 contained metabolite regions involved in the biosynthesis of antimicrobial compounds such as 2,4-DAPG, aborycin, enterocin NKR-5-3B, and sodorifen, and bacteriocin gene clusters for sactipeptides, Enterolysin_A, and UviB. Safety assessments indicated low pathogenic potential, while in-vitro assays demonstrated antibiotic susceptibility and suppressed the growth of Kp MBBL2 and Ec MBBL4, respectively. Its bacteriocin compound Enterolysin_A exhibited strong molecular interactions with virulence proteins of these mastitis pathogens. Therefore, the promising probiotic potential and antimicrobial efficacy of E. faecium MBBL3, especially against mastitis pathogens combined with its safety, position it as a valuable candidate for therapeutic applications. Key pointsO_LIE. faecium MBBL3 genosme showed high similarity with other species of this genera. C_LIO_LIGenetic makeup of MBBL3 revealed its ability to survival and adaptation in different niches including hosts gut. C_LIO_LIIn-vitro and in-silico study results, along with several genes linked to antimicrobials demonstrated its ability to combat against mastitis pathogens. C_LI

microbiology↗

bioRxiv2024

High-Throughput Screening Reveals Potential Inhibitors Targeting Trimethoprim-Resistant DfrA1 Protein in Klebsiella pneumoniae and Escherichia coli

The DfrA1 protein provides trimethoprim resistance in bacteria, especially Klebsiella pneumoniae and Escherichia coli, by modifying dihydrofolate reductase, which reduces the binding efficacy of the antibiotic. Thus, this study aimed to identify inhibitors of the trimethoprim-resistant DfrA1 protein through high-throughput computational screening of 3,601 newly synthesized chemical compounds sourced from the ChemDiv database. We conducted high-throughput computational optimization and screening of a library containing 3,601 compounds against the DfrA1 protein from K. pneumoniae and E. coli to identify potential drug candidates (DCs). Through this extensive approach, we identified six promising DCs, labeled DC1 to DC6, as potential inhibitors of DfrA1. Each DC demonstrated strong initial binding affinity and favorable chemical interactions with the DfrA1 binding sites when compared to the effective drug Iclaprim (effective antibiotic against DfrA1), used as a control. To validate these findings, we further investigated the molecular mechanisms of inhibition, focusing on the thermodynamic properties of the promising DCs. Furthermore, molecular dynamics simulation (MDS) validated the inhibitory efficacy of these six DCs against the DfrA1 protein. Our results showed that DC4 (an organoflourinated compound) and DC6 (a benzimidazol compound) showed superior efficacy against the DfrA1 protein than the control drug, particularly regarding stability, solvent-accessible surface area, solvent exposure, polarity, and binding site interactions, which influence their residence time and efficacy. Overall, findings of this study suggest that DC4 and DC6 have the potential to act as inhibitors against the DfrA1, offering promising prospects for the treatment and management of infections caused by trimethoprim-resistant K. pneumoniae and E. coli in both humans and animals.

bioinformatics↗

bioRxiv2024

In silico Identification of Novel Common Drug Targets Against Four Infectious Acinetobacter Species

The global emergence of multidrug-resistant Acinetobacter species has become a major concern in the management of hospital-acquired infections. Moreover, misdiagnosis of one species of Acinetobacter with another has been reported, making it difficult to choose appropriate treatment. World Health Organization emphasizes the urgent need to develop new antibiotics to combat Acinetobacter infections. This study aimed to discover novel common drug targets that will be effective against Acinetobacter nosocomialis, Acinetobacter baumannii, Acinetobacter pittii, and Acinetobacter haemolyticus. We utilized a cluster-based subtractive genomics approach to identify potential drug targets. The main focus was to find drug targets that are absent in humans and essential for pathogens. We also performed metabolic pathway and subcellular localization analyses. Furthermore, protein structure-based studies and druggability analyses were conducted to identify viable therapeutic options. Out of 1245 protein clusters (minimum 4 proteins/cluster), 204 clusters were human non-homologous and essential for bacteria. Among them, 39 clusters were cytoplasmic and involved in unique metabolic pathways which are specific to the pathogens. After analyzing the drug target sequences of DrugBank database, 12 clusters were found to be novel drug targets. Eventually, proteins of one cluster were identified as advantageous drug targets having drug-binding pockets at very similar regions with high druggability scores. These proteins can be inhibited to disrupt the Lysine/DAP biosynthetic pathway of Acinetobacter. Our research might open up a new possibility for drug discovery against these pathogens.

bioinformatics↗

bioRxiv2024

Natural Bacteriocins as Potential Drug Candidates Targeting Core Proteins in Mastitis Pathogens of Dairy Cattle

Mastitis poses a major challenge in the dairy industry, with rising antibiotic-resistant strains underscoring the urgent need for alternative antimicrobial strategies. This study aimed to (i) identify essential core proteins in clinical mastitis (CM)-causing pathogens using genomic approach, and (ii) assess the efficacy of natural antimicrobial peptides as novel therapeutic agents targeting the selected core proteins for the rational management of mastitis in dairy cows. Through a core genomic analysis of 16 CM-causing pathogens, including strains of Staphylococcus aureus, S. warneri, Streptococcus agalactiae, S. uberis, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, P. putida, and P. asiatica, we identified 65 core proteins shared among these pathogens. Among them, ten proteins including PhoH, TrpB, FtsZ, HslV, HupB, RibH, InfA, MurA, GlxK, and Rho were found to be essential for the survival and virulence of these pathogens. Importantly, further novelty, resistance, and virulence assessments identified Rho and HupB as potential therapeutic targets. A comprehensive screening of 70 bacteriocin peptides (BPs) revealed 14 BPs that effectively interacted with both Rho and HupB proteins. Further analysis showed that BP8 and BP32 disrupt Rho protein function by blocking transcription termination process, while BP8, BP39, and BP40 prevent HupB from binding to DNA. These findings confirm the promising stability and efficacy of BP8 against both target proteins in CM-pathogens, highlighting it as a promising broad-spectrum therapeutic agent. Our computational study identified Rho and HupB as key proteins in CM-causing pathogens, which can be targeted by natural bacteriocins like BP8, suggesting its potential for developing effective and sustainable therapeutics against mastitis in dairy cattle. Author SummaryMastitis poses a significant threat to the global dairy industry, with rising antibiotic resistance necessitating alternative therapeutic strategies. This study identified essential core proteins in clinical mastitis-causing pathogens through a genomic approach and evaluated natural antimicrobial peptides (bacteriocins) as novel therapeutic agents. Through a core-genomic analysis, Rho and HupB were identified as key therapeutic targets. Bacteriocin peptides such as BP8 demonstrated promising efficacy by disrupting regular transcription termination process and DNA replication, offering a promising solution for next-generation mastitis therapies. The findings underscore the potential of BP8 as a sustainable, broad-spectrum antimicrobial agent, contributing to the rational management of mastitis in dairy cattle.

bioinformatics↗

bioRxiv2024

A Framework for Accurate Prediction of Plastic-Degrading Enzymes using Convolutional Neural Networks

The growing accumulation of plastic waste presents a significant environmental challenge, necessitating innovative approaches to mitigate its impact. Enzymatic degradation has emerged as a promising solution for addressing plastic pollution. However, the isolation and characterization of plastic-degrading enzymes (PDEs) through laboratory experiments are costly, time-consuming, and often complicated by nonculturable microorganisms. Consequently, accurate in silico identification of PDEs is desirable to explore the diversity of natural enzymes and harness their potential for combating plastic pollution. This study introduces a novel feature extraction strategy for identifying plastic-degrading enzymes, incorporating Autocorrelation (AAutoCor), Composition of k-spaced Amino Acid Pairs (KSAP), Dipeptide Deviation from Expected Mean (DDE), Composition/Transition/Distribution (C/T/D), Conjoint Triad, and Secondary Structure. A combination of ANOVA and XGBoost, feature selection methods, was applied to optimize the feature dimensions for improved performance. Seven supervised machine learning models were employed to evaluate the dataset: Convolutional Neural Network, Random Forest Classifier, Feedforward Neural Network, Logistic Regression, Naive Bayes Classifier, K-nearest Neighbor, and XGBoost Classifier. Among these models, the CNN model demonstrated the best performance, achieving an accuracy of 0.96, an F1 score of 0.80, and an ROC-AUC score of 0.96. These findings underscore the potential of the proposed system as an accurate predictor of plastic-degrading enzymes from environmental sequences. This approach significantly enhances efforts to develop sustainable solutions to plastic waste by accelerating the discovery of novel PDEs.

bioinformatics↗