Biology subjects

Patil, R. B.

Publications and source records attributed to Patil, R. B..

6 recordsLinked to original sources

bioRxiv2024

Exploring Harmala Alkaloids as Novel Antimalarial Agents against Plasmodium falciparum through Bioinformatics Approaches

Malaria, caused by the Plasmodium falciparum, remains a significant global health challenge, with Plasmodium falciparum accounting for approximately 50% of cases and posing a considerable threat. Despite advances in control measures, malaria continues to cause an estimated one million deaths annually. The complex lifecycle of P. falciparum, involving both vertebrate hosts and Anopheles mosquitoes, complicates eradication efforts. The parasites resistance to existing antimalarial drugs, along with medication toxicity, necessitates innovative therapeutic approaches. Recent research has revealed that harmine, an alkaloid produced by an endophytic gut bacterium of Anopheles mosquitoes, can impede the transmission of the malarial parasite to humans by inhibiting a crucial life stage. This study investigates harmala alkaloids, sourced from plants and bacteria such as Peganum harmala, as potential alternatives to conventional antimalarial drugs. Notably, harmine and harmaline have shown promising antimalarial activity by inhibiting the essential enzyme protein kinase 4 (PK4), which is vital for the parasites survival. These compounds exhibit lower toxicity, effectively inhibiting both the blood stage growth and transmission of the parasite. Using in silico methodologies, including ADME analysis, molecular docking, MD simulation, and toxicity analysis, this study identifies harmala alkaloids as potential inhibitors against crucial P. falciparum proteins. Targeting proteins essential for the parasites survival, similar to established drugs like pfCRT protein, lays the foundation for developing effective antimalarial treatments. The comprehensive screening of harmala alkaloid molecules opens avenues for the pharmaceutical industry to tackle challenges related to drug resistance and toxicity, offering a promising route for the biorational management of malaria.

bioinformatics↗

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

Integrated Computational Biophysics approach for Drug Discovery against Nipah Virus

The Nipah virus (NiV) poses a pressing global threat to public health due to its high mortality rate, multiple modes of transmission, and lack of effective treatments. NiV glycoprotein G (NiV-G) emerges as a promising target for NiV drug discovery due to its essential role in viral entry and membrane fusion. Therefore, in this study we applied an integrated computational and biophysics approach to identify potential inhibitors of NiV-G within a curated dataset of Peruvian phytochemicals. Our virtual screening results indicated that these compounds could represent a natural source of potential NiV-G inhibitors with {Delta}G values ranging from -8 to -11 kcal/mol. Among them, Procyanidin B2, B3, B7, and C1 exhibited the highest binding affinities and formed the most molecular interactions with NiV-G. Molecular dynamics simulations revealed the induced-fit mechanism of NiV-G pocket interaction with these procyanidins, primarily driven by its hydrophobic nature. Non-equilibrium free energy calculations were employed to determine binding affinities, highlighting Procyanidin B3 and B2 as the ligands with the most substantial interactions. Overall, this work underscores the potential of Peruvian phytochemicals, particularly procyanidins B2, B3, B7, and C1, as lead compounds for developing anti-NiV drugs through an integrated computational biophysics approach. Key pointsO_LINipah Virus (NiV) Threat: NiV is a severe public health risk due to its high mortality rate, broad host range, multiple transmission modes, and lack of effective treatment. Outbreaks have occurred frequently in South and Southeast Asia, particularly in Bangladesh and India, leading to high fatality rates. C_LIO_LICross-Border Concerns: NiVs ability to transmit between humans and domestic animals raises concerns about its potential to cross regional borders and cause pandemics. It has been recognized as a high-priority pathogen by the World Health Organization. C_LIO_LILack of Treatment: Currently, there are no approved specific antiviral treatments or vaccines for NiV. Patients receive supportive care and some drugs used for other viruses, despite their side effects. C_LIO_LITargeting NiV Glycoprotein G: The study focuses on NiV glycoprotein G (NiV-G) as a target for potential anti-Nipah drugs due to its crucial role in viral entry. This glycoprotein mediates viral attachment and entry into host cells. C_LIO_LIComputational Drug Discovery: The research employs computational methods, including virtual screening and molecular dynamics simulations, to identify potential inhibitors of NiV-G from a dataset of Peruvian phytochemicals, particularly procyanidins B2, B3, B7, and C1. These compounds showed promising binding affinities, stable interactions, and favorable binding energies with NiV-G, making them potential lead compounds for drug development. C_LI

microbiology↗

bioRxiv2023

Repurposing Remdesivir for COVID-19: Computational Drug Design Targeting SARS-CoV-2 RNA Polymerase and Main Protease using Molecular Dynamics Approach

The coronavirus disease of 2019 (COVID-19) is a highly contagious respiratory illness that has become a global health crisis with new variants, an unprecedented number of infections, and deaths and demands urgent manufacturing of potent therapeutics. Despite the success of vaccination campaigns around the globe, there is no particular therapeutics approved to date for efficiently treating infected individuals. Repositioning or repurposing previously effective antivirals against RNA viruses to treat COVID-19 patients is a feasible option. Remdesivir is a broad-spectrum antiviral drug that the Food and Drug Administration (FDA) licenses for treating COVID-19 patients who are critically ill patients. Remdesivirs low efficacy, which has been shown in some clinical trials, possible adverse effects, and dose-related toxicities are issues with its use in clinical use. Our study aimed to design potent derivatives of remdesivir through the functional group modification of the parent drug targeting RNA-dependent RNA polymerase (RdRp) and main protease (MPro) of SARS-CoV-2. The efficacy and stability of the proposed derivatives were assessed by molecular docking and extended molecular dynamics simulation analyses. Furthermore, the pharmacokinetic activity was measured to ensure the safety and drug potential of the designed derivatives. The derivatives were non-carcinogenic, chemically reactive, highly interactive, and stable with the target proteins. D-CF3 is one of the designed derivatives that finally showed stronger interaction than the parent drug, according to the docking and dynamics simulation analyses, with both target proteins. However, in vitro and in vivo investigations are guaranteed to validate the findings in the future.

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

Exploring different virulent proteins of human respiratory syncytial virus for designing a novel epitope-based polyvalent vaccine: Immunoinformatics and molecular dynamics approaches

Human Respiratory Syncytial Virus (RSV) is one of the most prominent causes of lower respiratory tract infections (LRTI), contributory to infecting people from all age groups - a majority of which comprises infants and children. The implicated severe RSV infections lead to numerous deaths of multitudes of the overall population, predominantly the children, every year. Consequently, despite several distinctive efforts to develop a vaccine against the RSV as a potential countermeasure, there is no approved or licensed vaccine available yet, to control the RSV infection effectively. Therefore, through the utilization of immunoinformatics tools, a computational approach was taken in this study, to design and construct a multi-epitope polyvalent vaccine against the RSV-A and RSV-B strains of the virus. Potential predictions of the T-cell and B-cell epitopes were followed by extensive tests of antigenicity, allergenicity, toxicity, conservancy, homology to human proteome, transmembrane topology, and cytokine-inducing ability. The most promising epitopes (i.e. 13 CTL epitopes, 9 HTL epitopes, and 10 LBL epitopes) exhibiting full conservancy were then selected for designing the peptide fusion with appropriate linkers, having hBD-3 as the adjuvant. The peptide vaccine was modeled, refined, and validated to further improve the structural attributes. Following this, molecular docking analysis with specific TLRs was carried out which revealed excellent interactions and global binding energies. Additionally, molecular dynamics (MD) simulation was conducted which ensured the stability of the interactions between vaccine and TLR. Furthermore, mechanistic approaches to imitate and predict the potential immune response generated by the administration of vaccines were determined through immune simulations. Owing to an overall evaluation, in silico cloning was carried out in efforts to generate recombinant pETite plasmid vectors for subsequent mass production of the vaccine peptide, incorporated within E.coli. However, more in vitro and in vivo experiments can further validate its efficacy against RSV infections.

immunology↗