Repositioning of anti-dengue compounds against SARS-CoV-2 as viral polyprotein processing inhibitor

Computational Insights into Papaveroline as an In Silico Drug Candidate for Alzheimer's Disease via Fyn Tyrosine Kinase Inhibition

Alzheimer's disease (AD) poses a significant global health challenge, necessitating the exploration of novel therapeutic strategies. Fyn Tyrosine Kinase has emerged as a key player in AD pathogenesis, making it an attractive target for drug development. This study focuses on investigating the potential of Papaveroline as a drug candidate for AD by targeting Fyn Tyrosine Kinase. The research employed high-throughput virtual screening and QSAR analysis were conducted to identify compounds with optimal drug-like properties, emphasizing adherence to ADMET parameters for further evaluation. Molecular dynamics simulations to analyze the binding interactions between Papaveroline and Staurosporine with Fyn Tyrosine Kinase over a 200-ns period. The study revealed detailed insights into the binding mechanisms and stability of the Papaveroline-Fyn complex, showcasing the compound's potential as an inhibitor of Fyn Tyrosine Kinase. Comparative analysis with natural compounds and a reference compound highlighted Papaveroline's unique characteristics and promising therapeutic implications for AD treatment. Overall, the findings underscore Papaveroline's potential as a valuable drug candidate for targeting Fyn Tyrosine Kinase in AD therapy, offering new avenues for drug discovery in neurodegenerative diseases. This study contributes to advancing our understanding of molecular interactions in AD pathogenesis and paves the way for further research and development in this critical area.

Exploring binding mechanisms of omicron spike protein with dolutegravir and etravirine by molecular dynamics simulation, principal component analysis, and free binding energy calculations

The COVID-19 pandemic was caused by the SARS-CoV-2 virus, frequent mutations occurred to the wild-type virus resulting in evolved new variants. The WHO classified the new variants as 'Variants of Concern'. SARS-CoV-2 omicron evolved as the dominating variant at the end of 2021. Dolutegravir and etravirine were identified as inhibitors of SARS-CoV-2 entry to host cells in Omicron variants. In this study, combined in silico methods such as molecular docking, molecular dynamics, Principal component analysis, binding-free energy calculations, and Per Residues calculations were applied to investigate the mechanism of the bindings of the two inhibitors. The molecular dynamics results revealed the stability of dolutegravir-spike and etravirine-spike complexes in a similar manner to apo-protein. Dolutegravir and etravirine formed H-bonds and salt bridges with Omicron spike protein. The 2,4-difluoro phenyl moiety of dolutegravir plays an important role in binding the ligand. The binding mode and interactions of the two compounds indicated that Arg403, Tyr449, Tyr453, Arg493, Ser496, Arg498, Thr500, Tyr501, Gln502 and His505 are the key residues. The Principal Component Analyses suggested that no significant conformational changes happened for the two complexes during the simulations. Binding-free energy calculations showed that van der Waals interactions were the most important interactions for ligands' binding. Per-residue free energy decomposition revealed residues Arg493, Arg498, and Tyr501 contributed to the binding of the ligands through H-bonds and salt bridges formation while His505 contributed to H-bonds and Pi-Pi stacking and Phe497 contributed to hydrophobic interactions between ligands and Omicron spike protein.Communicated by Ramaswamy H. Sarma.

Exploring the anti-protozoal mechanisms of Syzygium aromaticum phytochemicals targeting Cryptosporidium parvum lactate dehydrogenase through molecular dynamics simulations

Cryptosporidium parvum (C. parvum), a protozoan parasite, is known to induce significant gastrointestinal disease in humans. Lactate dehydrogenase (LDH), a protein of C. parvum, has been identified as a potential therapeutic target for developing effective drugs against infection. This study utilized a computational drug discovery approach to identify potential drug molecules against the LDH protein of C. parvum. In the present investigation, we conducted a structure-based virtual screening of 55 phytochemicals from the Syzygium aromaticum (S. aromaticum). This process identified four phytochemicals, including Gallotannin 23, Eugeniin, Strictinin, and Ellagitannin, that demonstrated significant binding affinity and dynamic stability with LDH protein. Interestingly, these four compounds have been documented to possess antibacterial, antiviral, anti-inflammatory, and antioxidant properties. The docked complexes were simulated for 100 ns using Desmond to check the dynamic stability. Finally, the free binding energy was computed from the last 10ns MD trajectories. Gallotannin 23 and Ellagitannin exhibited considerable binding affinity and stability with the target protein among all four phytochemicals. These findings suggest that these predicted phytochemicals from S. aromaticum could be further explored as potential hit candidates for developing effective drugs against C. parvum infection. The in vitro and in vivo experimental validation is still required to confirm their efficacy and safety as LDH inhibitors.

Crystal structures of coronaviral main proteases in complex with the non-covalent inhibitor X77

Main proteases (Mpros) are a class of conserved cysteine hydrolases among coronaviruses and play a crucial role in viral replication. Therefore, Mpros are ideal targets for the development of pan-coronavirus drugs. X77, previously developed against SARS-CoV Mpro, was repurposed as a non-covalent tight binder inhibitor against SARS-CoV-2 Mpro during COVID-19 pandemic. Many novel inhibitors with favorable efficacy have been discovered using X77 as a reference, suggesting that X77 could be a valuable scaffold for drug design. However, the broad-spectrum performance of X77 and underlying mechanism remain less understood. Here, we reported the crystal structures of Mpros from SARS-CoV-2, SARS-CoV, and MERS-CoV, and several Mpro mutants from SARS-CoV-2 variants bound to X77. A detailed analysis of these structures revealed key structural determinants essential for interaction and elucidated the binding modes of X77 with different coronaviral Mpros. The potencies of X77 against these investigated Mpros were further evaluated through molecular dynamic simulation and binding free energy calculation. These data provide molecular insights into broad-spectrum inhibition against coronaviral Mpros by X77 and the similarities and differences of X77 when bound to various Mpros, which will promote X77-based design of novel antivirals with broad-spectrum efficacy against different coronaviruses and SARS-CoV-2 variants.

In Silico and In Vitro Screening of Some Pregnane Glycosides Isolated from Certain Caralluma Species as SARS-COV-2 Main Protease Inhibitors

SARS-CoV-2 caused pandemic represented a major risk for the worldwide human health, animal health and economy, forcing extraordinary efforts to discover drugs for its prevention and cure. Considering the extensive interest in the pregnane glycosides because of their diverse structures and excellent biological activities, we investigated them as antiviral agents against SARS-COV-2. We selected 21 pregnane glycosides previously isolated from the genus Caralluma from Asclepiadaceae family to be tested through virtual screening molecular docking simulations for their potential inhibition of SARS-CoV-2 Mpro. Almost all target compounds showed a more or equally negative docking energy score relative to the co-crystallized inhibitor X77 (S=-12.53 kcal/mol) with docking score range of (-12.55 to -19.76 kcal/mol) and so with a potent predicted binding affinity to the target enzyme. The activity of the most promising candidates was validated by in vitro testing. Arabincoside C showed the highest activity (IC50=35.42 μg/ml) and the highest selectivity index (SI=9.9) followed by Russelioside B (IC50=50.80 μg/ml), and Arabincoside B (IC50=53.31 μg/ml).

Application of temperature-dependent and steered molecular dynamics simulation to screen anti-dengue compounds against Marburg virus

Marburg virus infections are extremely fatal with a fatality range of 23% to 90%, therefore there is an urgent requirement to design and develop efficient therapeutic molecules. Here, a comprehensive temperature-dependent molecular dynamics (MD) simulation method was implemented to identify the potential molecule from the anti-dengue compound library that can inhibit the function of the VP24 protein of Marburg. Virtual high throughput screening identified five effective binders of VP24 after screening 484 anti-dengue compounds. These compounds were treated in MD simulation at four different temperatures: 300, 340, 380, and 420 K. Higher temperatures showed dissociation of hit compounds from the protein. Further, triplicates of 100 ns MD simulation were conducted which showed that compounds ID = 118717693, and ID = 5361 showed strong stability with the protein molecule. These compounds were further validated using Δ G binding free energies and they showed: -30.38 kcal/mol, and -67.83 kcal/mol binding free energies, respectively. Later, these two compounds were used in steered MD simulation to detect its dissociation. Compound ID = 5361 showed the maximum pulling force of 199.02 kcal/mol/nm to dissociate the protein-ligand complex while ID = 118717693 had a pulling force of 101.11 kcal/mol/nm, respectively. This ligand highest number of hydrogen bonds with varying occupancies at 89.93%, 69.80%, 57.93%, 52.33%, and 50.63%. This study showed that ID = 5361 can bind with the VP24 strongly and has the potential to inhibit its function which can be validated in the in-vitro experiment.Communicated by Ramaswamy H. Sarma.

Exploration of human pancreatic alpha-amylase inhibitors from Physalis peruviana for the treatment of type 2 diabetes

Type 2 Diabetes (T2D), a chronic metabolic disorder characterized by persistent hyperglycemia, accounts for ∼90% of all types of diabetes. Pancreatic α-amylase is a potential drug target for preventing postprandial hyperglycemia and inhibiting T2D in humans. Although many synthetic drugs have been identified against pancreatic α-amylase, however, reported several side effects, and plant-derived natural products are less explored against T2D. This study tested 34 flavonoids derived from the plant Physalis peruviana against the human pancreatic α-amylase (HPA) using in silico computational approaches such as molecular docking and molecular dynamics simulation approaches. Schrödinger, a drug discovery package with modules applicable for molecular docking, protein-ligand interaction analysis, molecular dynamics, post-dynamics simulation, and binding free energy calculation, was employed for all computational studies. Four flavonoids, namely, Chlorogenic acid, Withaperuvin F, Withaperuvin H, and Rutin, were picked based on their docking score ranging between -7.03 kcal/mol and -11.35 kcal/mol compared to the docking score -7.3 kcal/mol of reference ligand, i.e. Myricetin. The molecular dynamics analysis suggested that all flavonoids showed considerable stability within the protein's catalytic pocket, except chlorogenic acid, which showed high deviation during the last 15 ns. However, the interactions observed in initial docking and extracted from the simulation trajectory involved > 90% identical residues, indicating the affinity and stability of the docked flavonoids with the protein. Therefore, all four compounds identified in this study are proposed as promising antidiabetic candidates and should be further considered for their in vitro and in vivo validation.Communicated by Ramaswamy H. Sarma.

Multilayer precision-based screening of potential inhibitors targeting Mycobacterium tuberculosis acetate kinase using in silico approaches

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), remains a major threat to global health, with the emergence of multi-drug and extensively drug-resistant strains posing a serious challenge. Thereby, understanding the molecular basis of MTB virulence and disease pathogenesis is critical for developing effective therapeutic strategies. Targeting proteins involved in central metabolism has been recognized as a promising therapeutic approach to combat MTB. In this regard, the enzyme AckA of the acetate metabolic pathway which produces acetate from acetyl phosphate, is an important drug target for various pathogenic organisms. Therefore, this study aimed to identify potential AckA inhibitors through in silico methods, including molecular modeling, molecular dynamics simulation (MDS), and high-throughput virtual screening (HTVS) followed by ADMETox, MMGBSA, Density Functional Theory (DFT) calculations. HTVS of one million compounds from the ZINC database against AckA resulted in the top five hits (ZINC82048449, ZINC1219737510, ZINC1771921358, ZINC119699567, and ZINC1427100376) with better binding affinity and optimal binding free energy. MDS studies on complexes revealed that key residues, Asn195, Asp266, Phe267, Gly314, and Asn318 played a significant role in stable interactions of the top-ranked compounds to AckA. These outcomes provide insights into the optimal binding of the leads to inhibit the acetate pathway and aid in the rational design of novel therapeutic agents. Thus, the identified leads may act as promising compounds for targeting AckA and may serve as a potential therapeutic modality for treating TB. Our findings offer valuable insights into the inhibition of the acetate pathway, while also serving as a blueprint for rational drug design. The identified leads hold promise as compelling compounds for targeting AckA, thereby offering a potential therapeutic avenue for tackling TB. Thus, our study uncovers a pathway toward promising TB therapeutics by elucidating AckA inhibitors. By leveraging in silico methodologies, potent compounds that hold the potential to thwart AckA's role in MTB's acetate pathway have been unveiled. This breakthrough fosters optimism in the quest for novel and effective TB treatments, addressing a global health challenge with renewed vigor.

Investigating the Mechanism of Action of Anti-Dengue Compounds as Potential Binders of Zika Virus RNA-Dependent RNA Polymerase

The World Health Organization (WHO) has designated the Zika virus (ZIKV) as a significant risk to the general public's health. Currently, there are no vaccinations or medications available to treat or prevent infection with the Zika virus. Thus, it is urgently required to develop a highly efficient therapeutic molecule. In the presented study, a computationally intensive search was carried out to identify potent compounds that have the potential to bind and block the activity of ZIKV NS5 RNA-dependent RNA polymerase (RdRp). The anti-dengue chemical library was subjected to high-throughput virtual screening and MM/GBSA analysis in order to rate the potential candidates. The top three compounds were then chosen. According to the MM/GBSA analysis, compound 127042987 from the database had the highest binding affinity to the protein with a minimum binding free energy of -77.16 kcal/mole. Compound 127042987 had the most stable RMSD trend and the greatest number of hydrogen bond interactions when these chemical complexes were evaluated further under a 100 ns molecular dynamics simulation. Compound 127042987 displayed the best binding free energy (GBind) of -96.50 kcal/mol, surpassing the native ligand binding energy (-66.17 kcal/mole). Thereafter, an MM/GBSA binding free energy study was conducted to validate the stability of selected chemical complexes. Overall, this study illustrated that compound 127042987 showed preferred binding free energies, suggesting a possible inhibitory mechanism against ZIKV-RdRp. As per this study, it was proposed that compound 127042987 could be used as a therapeutic option to prevent Zika virus infection. These compounds need to be tested in experiments for further validation.