Biology subjects

Rani, N. A.

Publications and source records attributed to Rani, N. A..

3 recordsLinked to original sources

bioRxiv2024

Exploring Effector Protein Dynamics and Natural Fungicidal Potential in Rice Blast Pathogen Magnaporthe oryzae

Rice blast, caused by Magnaporthe oryzae, is a severe agricultural disease leading to significant global economic losses. Genetic and genomic investigations have identified crucial genes and pathways involved in its pathogenesis, particularly highlighting effector proteins like AvrPik variants and MAX proteins. These proteins interact with specific Pik alleles on rice chromosome 11, influencing host immune responses. This study focused on 35 plant-derived metabolites known for their antifungal properties, evaluating their potential as fungicidal agents against M. oryzae. Molecular docking analyses identified Hecogenin and Cucurbitacin E as highly effective binders to MAX40 and APIKL2A proteins, respectively, which are pivotal for fungal virulence and immune evasion. Molecular dynamics simulations further validated strong and stable interactions, affirming the therapeutic potential of these compounds. Additional assessments including Lipinskis rule of five criteria and toxicity predictions indicated their suitability for agricultural use. These findings underscore the promise of Hecogenin and Cucurbitacin E as lead candidates in developing novel fungicidal strategies against rice blast, offering prospects for enhanced crop protection and agricultural sustainability.

bioinformatics↗

bioRxiv2023

Accelerating Cancer Vaccine Development for Human T-Lymphotropic Virus (HTLV) Using a High-Throughput Molecular Dynamics Approach

Human T-lymphotropic virus (HTLV), a retrovirus belonging to the oncovirus family, has long been linked to be associated with various inflammatory and immunosuppressive disorders. To combat the devastating impact of this virus, our study employed a reverse vaccinology approach to design a multi-epitope-based vaccine targeting the highly virulent subtypes of HTLV. We conducted a comprehensive analysis of the molecular interactions between the vaccine and Toll-like receptors (TLRs), providing valuable insights for future research on preventing and managing HTLV-related diseases and any possible outbreaks. The vaccine was designed by focusing on the envelope glycoprotein gp62, a crucial protein involved in the infectious process and immune mechanisms of HTLV inside the human body. Epitope mapping identified T cell and B cell epitopes with low binding energies, ensuring their immunogenicity and safety. Linkers and adjuvants were incorporated to enhance the vaccines stability, antigenicity, and immunogenicity. Two vaccine constructs were developed, both exhibiting high antigenicity and conferring safety. Vaccine construct 2 demonstrated expected solubility and structural stability after disulfide engineering. Molecular docking analyses revealed strong binding affinity between the vaccine construct 2 and both TLR2 and TLR4. Molecular dynamics simulations indicated that the TLR2-vaccine complex displayed enhanced stability, compactness, and consistent hydrogen bond formation, suggesting a favorable affinity. Contact analysis, Gibbs free energy landscapes, and DCC analysis further supported the stability of the TLR2-vaccine complex, while DSSP analysis confirmed stable secondary structures. MM-PBSA analysis revealed a more favorable binding affinity of the TLR4-vaccine complex, primarily due to lower electrostatic energy. In conclusion, our study successfully designed a multi-epitope-based vaccine targeting HTLV subtypes and provided valuable insights into the molecular interactions between the vaccine and TLRs. These findings should contribute to the development of effective preventive and treatment approaches against HTLV-related diseases.

bioinformatics↗

bioRxiv2022

In Silico Proteomics Approach Towards the Identification of Potential Novel Drug Targets Against Cryptococcus gattii

Cryptococcosis is a condition caused by inhaling Cryptococcus gattii, the tiny fungus from the environment. It is thought that the pathogen C. gattii is clinically more virulent than C. neoformans and could be a vicious agent in coming decades. It can enter the hosts brain and harm human peripheral blood mononuclear cells DNA (PBMCs). It is vital to investigate potential alternative medications to treat this disease since global antifungal resistance preventing Cryptococci infections is on the rise, leading to treatment failure. In order to find effective novel drug targets for C. gattii, a comprehensive novel approach has been used in conjunction with in silico analysis. Among 6561 proteins of C. gattii we have found three druggable proteins (XP 003194316.1, XP 003197297.1, XP 003197520.1) after completing a series of steps including exclusion of paralogs, human homologs, non-essential and human microbiome homologs proteins. These three proteins are involved in pathogen specific pathways, and can be targeted for drugs to eliminate the pathogen from the host. The subcellular locations and their interactions with a high number of proteins also demonstrate their eligibility as potential drug targets. We have approached their secondary, tertiary model and docked them with 21 potential antifungal plant metabolites. From the molecular docking analysis, we found Amentoflavone, Baicalin, Rutin and Viniferin to be the most effective drugs to stop such proteins because of their increased binding affinity. Correspondingly, the drugs showed proper ADME properties and also analyzed to be safe (Figure 9, Table 6). Moreover, these potential drugs can successfully be used in the treatment of Cryptococcosis caused by the fungus Cryptococcus gattii. In vivo trail is highly recommended for further prospection. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=185 SRC="FIGDIR/small/502060v1_fig9.gif" ALT="Figure 9"> View larger version (29K): org.highwire.dtl.DTLVardef@1e1d79borg.highwire.dtl.DTLVardef@122e30org.highwire.dtl.DTLVardef@19667eaorg.highwire.dtl.DTLVardef@18063a6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 9:C_FLOATNO SwissADME properties of top metabolites C_FIG O_TBL View this table: org.highwire.dtl.DTLVardef@e46d5org.highwire.dtl.DTLVardef@14c66b3org.highwire.dtl.DTLVardef@ea8b0eorg.highwire.dtl.DTLVardef@4f4bc8org.highwire.dtl.DTLVardef@1f85c8e_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 06:C_FLOATNO O_TABLECAPTIONTop metabolites with toxicity prediction C_TABLECAPTION C_TBL

bioinformatics↗