Identification of potential drug molecules against fibroblast growth factor receptor 3 (FGFR3) by multi-stage computational-biophysics correlate.

The fibroblast growth factor receptor 3 (FGFR3) is warranted as a promising therapeutic target in bladder cancer as it is described in 75% of papillary bladder tumors. Considering this, the present study was conducted to use different approaches of computer-aided drug discovery (CADD) to identify the best binding compounds against the active pocket of FGFR3. Compared to control pyrimidine derivative, the study identified three promising lead structures; BDC_24037121, BDC_21200852, and BDC_21206757 with binding energy value of -14.80 kcal/mol, -12.22 kcal/mol, and -11.67 kcal/mol, respectively. The control molecule binding energy score was -9.85 kcal/mol. The compounds achieved deep pocket binding and produced balanced interactions of hydrogen bonds and van der Waals. The FGFR3 enzyme residues such as Leu478, Lys508, Glu556, Asn562, Asn622, and Asp635. The molecular dynamic (MD) simulation studies additionally validated the docked conformation stability with respect to FGFR3 with a mean root mean square deviation (RMSD) value of < 3 Å. The root mean square fluctuation (RMSF) complements the complexes structural stability and the residues showed less fluctuation in the presence of compounds. The Poisson-Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods revalidated compounds better binding and highlighted van der Waals energy to dominate the overall net energy. The docked stability was additionally confirmed by WaterSwap and AMBER normal mode entropy energy analyses. In a nutshell, the compounds shortlisted in this study are promising in term of theoretical binding affinity for FGFR3 but experimental validation is needed.Communicated by Ramaswamy H. Sarma.

Exploring the hub genes and potential drugs involved in Fanconi anemia using microarray datasets and bioinformatics analysis.

Fanconi anemia (FA) is a genetic disorder that occurs when certain genes responsible for repairing DNA replication and promoting homologous recombination fail to function properly. This leads to severe clinical symptoms and a wide range of cancer-related characteristics. Recent treatment approaches for FA involve hematopoietic stem cell transplantation (HSCT), which helps restore the population of stem cells. A survival study using p-values indicated that specific hub genes play a significant role in diagnosing and predicting the disease. To find potential medications that interact with the identified hub genes, researchers inferred drugs. Among hub genes, TP53 was found to be particularly promising through computational analysis. Further investigation focused on two drugs, Topiramate and Tocofersolan predicted based on drug bank database analysis. Molecular docking strategies were employed to assess the best binding pose of these drugs with TP53. Topiramate showed a binding affinity of -6.5 kcal/mol, while Tocofersolan showed -8.5 kcal/mol against the active residues within the binding pocket. Molecular dynamics (MD) simulations were conducted to observe the stability of each drug's interaction with the TP53 protein over time. Both drugs exhibited stable confirmation with only slight changes in the loop region of the TP53 protein during the simulation intervals. Results also shows that there was a high fluctuation observed during apo-sate simulation time intervals as compared to complex system. Hence, it is suggested that the exploration of structure-based drug design holds promising results to specific target. This could potentially lead to a breakthrough in future experimental approaches for FA treatment.Communicated by Ramaswamy H. Sarma.

Network Pharmacology Approach for Medicinal Plants: Review and Assessment.

Natural products have played a critical role in medicine due to their ability to bind and modulate cellular targets involved in disease. Medicinal plants hold a variety of bioactive scaffolds for the treatment of multiple disorders. The less adverse effects, affordability, and easy accessibility highlight their potential in traditional remedies. Identifying pharmacological targets from active ingredients of medicinal plants has become a hot topic for biomedical research to generate innovative therapies. By developing an unprecedented opportunity for the systematic investigation of traditional medicines, network pharmacology is evolving as a systematic paradigm and becoming a frontier research field of drug discovery and development. The advancement of network pharmacology has opened up new avenues for understanding the complex bioactive components found in various medicinal plants. This study is attributed to a comprehensive summary of network pharmacology based on current research, highlighting various active ingredients, related techniques/tools/databases, and drug discovery and development applications. Moreover, this study would serve as a protocol for discovering novel compounds to explore the full range of biological potential of traditionally used plants. We have attempted to cover this vast topic in the review form. We hope it will serve as a significant pioneer for researchers working with medicinal plants by employing network pharmacology approaches.

Immunoinformatics and Immunogenetics-Based Design of Immunogenic Peptides Vaccine against the Emerging Tick-Borne Encephalitis Virus (TBEV) and Its Validation through In Silico Cloning and Immune Simulation.

Pegivirus, HPgV, earlier known as Gb virus and hepatitis G virus, is an enveloped, positive-stranded RNA and lymphotropic virus classified into the Flaviviridae family. The transmission routes primarily involve blood products, with infections worldwide, leading up to 25% of persistent infections. To date, no effective therapeutic means are available to resolve Pegivirus infections. Effective vaccine therapeutics are the best alternative to manage this disease and any associated potential pandemic. Thus, whole proteome-based mining of immunogenic peptides, i.e., CTL (cytotoxic T lymphocytes), HTL (helper T lymphocytes) and B cell epitopes were mapped to design a vaccine ensemble. Our investigation revealed that 29 different epitopes impart a critical role in immune response induction, which was also validated by exploring its physiochemical properties and experimental feasibility. In silico expression and host immune simulation using an agent-based modeling approach confirmed the induction of both primary and secondary immune factors such as IL, cytokines and antibodies. The current study warrants further lab experiments to demonstrate its efficacy and safety.

Emerging Treatment Strategies for Diabetes Mellitus and Associated Complications: An Update.

The occurrence of diabetes mellitus (DM) is increasing rapidly at an accelerating rate worldwide. The status of diabetes has changed over the last three generations; whereas before it was deemed a minor disease of older people but currently it is now one of the leading causes of morbidity and mortality among middle-aged and young people. High blood glucose-mediated functional loss, insulin sensitivity, and insulin deficiency lead to chronic disorders such as Type 1 and Type 2 DM. Traditional treatments of DM, such as insulin sensitization and insulin secretion cause undesirable side effects, leading to patient incompliance and lack of treatment. Nanotechnology in diabetes studies has encouraged the development of new modalities for measuring glucose and supplying insulin that hold the potential to improve the quality of life of diabetics. Other therapies, such as ß-cells regeneration and gene therapy, in addition to insulin and oral hypoglycemic drugs, are currently used to control diabetes. The present review highlights the nanocarrier-based drug delivery systems and emerging treatment strategies of DM.

Spectroscopic, calorimetric and in silico insight into the molecular interactions of Memantine with human transferrin: Implications of Alzheimer's drugs.

Human transferrin (Tf) is an iron-binding blood plasma glycoprotein that controls free iron in biological fluids. Tf is a liver-produced protein that binds iron very tightly but reversibly and is the most significant iron pool. Memantine is an orally administrative N-methyl-d-aspartate glutamate receptor antagonist used to slow the progression of moderate-to-severe Alzheimer's disease (AD) and dementia. Here, we have investigated the molecular interactions of Memantine with Tf using molecular docking, dynamics simulation and in vitro binding studies. Molecular docking study revealed many close interactions of Memantine towards Tf with an appreciable binding affinity. The docking results were further validated by molecular dynamics (MD) simulation studies, followed by essential dynamics and free energy landscapes analyses. Memantine shows a good binding affinity to the Tf with a binding constant (K) of 105 M-1. Isothermal titration calorimetry (ITC) also advocated the spontaneous binding of memantine to Tf. The study proposed that the Memantine in complex with Tf is stable in the simulated trajectory with minimal structural changes. The study suggested that the Tf-Memantine interactions can be further explored in AD therapy after critical exploration.

Integrated Core Proteomics, Subtractive Proteomics, and Immunoinformatics Investigation to Unveil a Potential Multi-Epitope Vaccine against Schistosomiasis.

Schistosomiasis is a parasitic infection that causes considerable morbidity and mortality in the world. Infections of parasitic blood flukes, known as schistosomes, cause the disease. No vaccine is available yet and thus there is a need to design an effective vaccine against schistosomiasis. Schistosoma japonicum, Schistosoma mansoni, and Schistosoma haematobium are the main pathogenic species that infect humans. In this research, core proteomics was combined with a subtractive proteomics pipeline to identify suitable antigenic proteins for the construction of a multi-epitope vaccine (MEV) against human-infecting Schistosoma species. The pipeline revealed two antigenic proteins-calcium binding and mycosubtilin synthase subunit C-as promising vaccine targets. T and B cell epitopes from the targeted proteins were predicted using multiple bioinformatics and immunoinformatics databases. Seven cytotoxic T cell lymphocytes (CTL), three helper T cell lymphocytes (HTL), and four linear B cell lymphocytes (LBL) epitopes were fused with a suitable adjuvant and linkers to design a 217 amino-acid-long MEV. The vaccine was coupled with a TLR-4 agonist (RS-09; Sequence: APPHALS) adjuvant to enhance the immune responses. The designed MEV was stable, highly antigenic, and non-allergenic to human use. Molecular docking, molecular dynamics (MD) simulations, and molecular mechanics/generalized Born surface area (MMGBSA) analysis were performed to study the binding affinity and molecular interactions of the MEV with human immune receptors (TLR2 and TLR4) and MHC molecules (MHC I and MHC II). The MEV expression capability was tested in an Escherichia coli (strain-K12) plasmid vector pET-28a(+). Findings of these computer assays proved the MEV as highly promising in establishing protective immunity against the pathogens; nevertheless, additional validation by in vivo and in vitro experiments is required to discuss its real immune-protective efficacy.