In silico investigation and potential therapeutic approaches of isoquinoline alkaloids for neurodegenerative diseases: computer-aided drug design perspective.

Microtubule affinity regulating kinase (MARK4) has been proposed as a potential therapeutic target for diabetes, cancer, and neurological diseases. We used a variety of computational studies techniques to examine the binding affinity and MARK4 inhibitory potential of several isoquinoline alkaloids. MARK4 has been associated with tau protein phosphorylation and, consequently, Alzheimer's disease. The three molecules with the highest binding affinities inside the 5ES1 receptor, according to molecular docking experiments, are isoliensinine, liensinine, and methylcorypalline. Isoliensinine had the highest drug score and drug likeness, coming in at 1.17, while Liensinine and Methylcorypalline came in at 1.15 and 1.07, respectively. The thesis claims that three compounds have a better chance than the others of being identified as therapeutic leads. The bulk of the compounds under investigation didn't break any of Lipinski's five rules, especially methylcorypalline, which did and is probably orally active. The majority of the compounds under investigation, particularly Isoliensinine, Liensinine, and Methylcorypalline, show the potential to exhibit drug-like behaviour, which is strongly confirmed by ADMET characteristics estimates. The chemicals Isoliensinine, Liensinine, and Methylcorypalline, especially Methylcorypalline, form the most stable combination with the 5ES1, according to a 100 ns molecular dynamics simulation of these compounds docked inside 5ES1 complexes. Methylcorypalline has a higher binding affinity inside 5ES1, according to additional MM/GBSA experiments using MD trajectories. Overall, research supports the use of the drug development tool methylcolipalin for its ability to inhibit MARK4, which may have implications for the treatment of neurodegenerative diseases.Communicated by Ramaswamy H. Sarma.

A subunit vaccine against pneumonia: targeting Streptococcus pneumoniae and Klebsiella pneumoniae.

Community-acquired pneumonia is primarily caused by Streptococcus pneumoniae and Klebsiella pneumoniae, two pathogens that have high morbidity and mortality rates. This is largely due to bacterial resistance development against current antibiotics and the lack of effective vaccines. The objective of this work was to develop an immunogenic multi-epitope subunit vaccine capable of eliciting a robust immune response against S. pneumoniae and K. pneumoniae. The targeted proteins were the pneumococcal surface proteins (PspA and PspC) and choline-binding protein (CbpA) of S. pneumoniae and the outer membrane proteins (OmpA and OmpW) of K. pneumoniae. Different computational approaches and various immune filters were employed for designing a vaccine. The immunogenicity and safety of the vaccine were evaluated by utilizing many physicochemical and antigenic profiles. To improve structural stability, disulfide engineering was applied to a portion of the vaccine structure with high mobility. Molecular docking was performed to examine the binding affinities and biological interactions at the atomic level between the vaccine and Toll-like receptors (TLR2 and 4). Further, the dynamic stabilities of the vaccine and TLRs complexes were investigated by molecular dynamics simulations. While the immune response induction capability of the vaccine was assessed by the immune simulation study. Vaccine translation and expression efficiency was determined through an in silico cloning experiment utilizing the pET28a(+) plasmid vector. The obtained results revealed that the designed vaccine is structurally stable and able to generate an effective immune response to combat pneumococcal infection. Supplementary Information: The online version contains supplementary material available at 10.1007/s13721-023-00416-3.

Identification of potent COVID-19 main protease inhibitors by loading of favipiravir on Mg12O12 and Zn12O12 nanoclusters: an in silico strategy for COVID-19 treatment.

Pandemic new severe acute respiratory syndrome coronavirus (SARS-CoV-2) virus has increased throughout the world. There is no effective treatment against this virus until now. Since its appearance in Wuhan, China in December 2019, SARS-CoV-2 becomes the largest challenge the world is opposite today, including the discovery of an antiviral drug for this virus. Several viral proteins have been prioritized as SARS-CoV-2 antiviral drug targets, among them the papain-like protease (PLpro) and the main protease (Mpro). Inhibition of these proteases would target viral replication, viral maturation and suppression of host innate immune responses. Potential candidates have been identified to show inhibitory effects against Mpro, both in biochemical assays and viral replication in cells. There are different molecules such as lopinavir and favipiravir considerably inhibit the activity of Mpro in vitro. Different studies have shown that structurally improved favipiravir and other similar compounds can inhibit SARS-CoV-2 main protease. In this work, we study the interactions between favipiravir with Mg12O12 and Zn12O12 nanoclusters by density functional theory (DFT) and quantum mechanics atoms in molecules (QMAIM) methods to summarize the ability to load favipiravir onto Mg12O12 and Zn12O12 nanoclusters. Favipiravir-Mg12O12 and favipiravir-Zn12O12 lowest structures complexes were chosen to dock inside the SARS-CoV-2 main protease by molecular docking study. The molecular docking analysis revealed that the binding affinity of Mg12O12 and Zn12O12 nanoclusters inside the Mpro receptor is larger than that of favipiravir. Also, the loading of favipiravir on the surface of Mg12O12 and Zn12O12 nanoclusters increased the binding affinity against the Mpro receptor. Subsequently, 100 ns molecular dynamics simulation of the favipiravir-Mg12O12, and favipiravir-Zn12O12 docked inside the Mpro complexes established that favipiravir-Mg12O12, forms the most stable complex with the Mpro. Further molecular mechanics Poisson Boltzmann surface area (MMPBSA) analyses using the MD trajectories also demonstrated the higher binding affinity of favipiravir-Mg12O12 inside the Mpro. In summary, this study demonstrates a new way to characterize leads for novel anti-viral drugs against SARS-CoV-2, by improving the drug ability of favipiravir via loading it on Mg12O12 and Zn12O12 nanoclusters.Communicated by Ramaswamy H. Sarma.

Impact of Prolonged COVID-19 Lockdown on Body Mass Index, Eating Habits, and Physical Activity of University Students in Bangladesh: A Web-Based Cross-Sectional Study.

Objectives: This current study aims to assess the prevalence and factors associated with body mass index (BMI), dietary patterns, and the extent of physical activities among university students following the prolonged coronavirus disease 2019 (COVID-19) lockdown in Bangladesh. Methods: A cross-sectional web-based survey was conducted between July 10 to August 10, 2021, through a pre-designed Google Form to collect the data from Bangladeshi university students (age: ≥18 years). Informed consent was electronically obtained from each participant, and a simple snowball technique was employed during the sampling. Frequency and percentage distribution, paired t-test, chi-square [χ2] test, and multinomial and binary logistic regression analyses were consecutively applied to analyze the collected data. Results: Among the total participants (n = 1,602), 45.1% were female and 55.6% were 22-25 years' age group students. The BMI (mean ± standard deviation, SD) during the COVID-19 lockdown was 23.52 ± 7.68 kg/m2, which was 22.77 ± 4.11 kg/m2 during the pre-lockdown period (mean difference = 0.753; p < 0.001). The multinomial logistic regression analysis found a significant impact of gender [male vs. female: adjusted relative risk ratio (RRR) = 1.448; 95% confidence interval (CI) = 1.022, 2.053; p = 0.037], age (years) (<22 vs. >25: RRR =0.389, 95% CI = 0.213,0.710; p = 0.002, and 22-25 vs. >25: RRR = 0.473, 95% CI = 0.290, 0.772; p = 0.003), monthly family income (BDT) (<25,000 vs. >50,000: RRR = 0.525, 95% CI = 0.334,0.826; p = 0.005), university type (public vs. private: RRR = 0.540, 95% CI = 0.369, 0.791; p = 0.002), eating larger meals/snacks (increased vs. unchanged: RRR = 2.401, 95% CI = 1.597, 3.610; p < 0.001 and decreased vs. unchanged: RRR = 1.893, 95% CI = 1.218, 2.942; p = 0.005), and verbally or physically abuse (yes vs. no: RRR = 1.438, 95% CI = 0.977, 2.116; p = 0.066) on obesity during COVID-19 pandemic. Besides, the female students and those who have constant eating habits, were more likely to be underweight. Additionally, the binary logistic regression analysis found that the students from private universities [others vs. private: adjusted odds ratio (AOR) = 0.461, 95% CI = 0.313, 0.680; p < 0.001], urban areas (urban vs. rural: AOR = 1.451, 95% CI = 1.165, 1.806; p = 0.001), wealthier families (<25,000 BDT vs. >50,000 BDT: AOR = 0.727, 95% CI = 0.540, 0.979; p = 0.036), and who were taking larger meals/snacks (increased vs. unchanged: AOR = 2.806, 95% CI = 2.190, 3.596; p < 0.001) and had conflicts/arguments with others (no vs. yes: AOR = 0.524, 95% CI = 0.418, 0.657; p < 0.001), were significantly more physically inactive. Finally, the level of education and smoking habits significantly influenced the eating habits of university students during the extended strict lockdown in Bangladesh. Conclusion: The current findings would be helpful tools and evidence for local and international public health experts and policymakers to reverse these worsening effects on students mediated by the prolonged lockdown. Several effective plans, programs, and combined attempts must be earnestly implemented to promote a smooth academic and daily life.

Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods.

A novel infectious agent, SARS-CoV-2, is responsible for causing the severe respiratory disease COVID-19 and death in humans. Spike glycoprotein plays a key role in viral particles entering host cells, mediating receptor recognition and membrane fusion, and are considered useful targets for antiviral vaccine candidates. Therefore, computational techniques can be used to design a safe, antigenic, immunogenic, and stable vaccine against this pathogen. Drawing upon the structure of the S glycoprotein, we are trying to develop a potent multi-epitope subunit vaccine against SARS-CoV-2. The vaccine was designed based on cytotoxic T-lymphocyte and helper T-lymphocyte epitopes with an N-terminal adjuvant via conducting immune filters and an extensive immunoinformatic investigation. The safety and immunogenicity of the designed vaccine were further evaluated via using various physicochemical, allergenic, and antigenic characteristics. Vaccine-target (toll-like receptors: TLR2 and TLR4) interactions, binding affinities, and dynamical stabilities were inspected through molecular docking and molecular dynamic (MD) simulation methods. Moreover, MD simulations for dimeric TLRs/vaccine in the membrane-aqueous environment were performed to understand the differential domain organization of TLRs/vaccine. Further, dynamical behaviors of vaccine/TLR systems were inspected via identifying the key residues (named HUB nodes) that control interaction stability and provide a clear molecular mechanism. The obtained results from molecular docking and MD simulation revealed a strong and stable interaction between vaccine and TLRs. The vaccine's ability to stimulate the immune response was assessed by using computational immune simulation. This predicted a significant level of cytotoxic T cell and helper T cell activation, as well as IgG, interleukin 2, and interferon-gamma production. This study shows that the designed vaccine is structurally and dynamically stable and can trigger an effective immune response against viral infections.

Identification of the most damaging nsSNPs in the human CFL1 gene and their functional and structural impacts on cofilin-1 protein.

The cofilin-1 protein, encoded by CFL1, is an actin-binding protein that regulates F-actin depolymerization and nucleation activity through phosphorylation and dephosphorylation. CFL1 has been implicated in the development of neurodegenerative diseases (Alzheimer's disease and Huntington's disease), neuronal migration disorders (lissencephaly, epilepsy, and schizophrenia), and neural tube closure defects. Mutations in CFL1 have been associated with impaired neural crest cell migration and neural tube closure defects. In our study, various computational approaches were utilized to explore single-nucleotide polymorphisms (SNPs) in CFL1. The Variation Viewer and gnomAD databases were used to retrieve CFL1 SNPs, including 46 nonsynonymous SNPs (nsSNPs). The functional and structural annotation of SNPs was performed using 12 sequence-based web applications, which identified 20 nsSNPs as being the most likely to be deleterious or disease-causing. The conservation of cofilin-1 protein structures was illustrated using the ConSurf and PROSITE web servers, which projected the 12 most deleterious nsSNPs onto conserved domains, with the potential to disrupt the protein's functionality. These 12 nsSNPs were selected for protein structure construction, and the DynaMut/DUET servers predicted that the protein variants V7G, L84P, and L99A were the most likely to be damaging to the cofilin-1 protein structure or function. The evaluation of molecular docking studies demonstrated that the L99A and L84P cofilin-1 variants reduce the binding affinity for actin compared with the native cofilin-1 structure, and molecular dynamic simulation studies confirmed that these variants might destabilize the protein structure. The consequences of putative mutations on protein-protein interactions and post-translational modification sites in the cofilin-1 protein structure were analyzed. This study represents the first complete approach to understanding the effects of nsSNPs within the actin-depolymerizing factor/cofilin family, which suggested that SNPs resulting in L84P (rs199716082) and L99A (rs267603119) variants represent significant CFL1 mutations associated with disease development.

Combination of QSAR, molecular docking, molecular dynamic simulation and MM-PBSA: analogues of lopinavir and favipiravir as potential drug candidates against COVID-19.

Pandemic COVID-19 infections have spread throughout the world. There is no effective treatment against this disease. Viral RNA-dependent RNA polymerase (RdRp) catalyzes the replication of RNA from RNA and the main protease (Mpro) has a role in the processing of polyproteins that are translated from the RNA of SARS-CoV-2, and thus these two enzymes are strong candidates for targeting by anti-viral drugs. Small molecules such as lopinavir and favipiravir significantly inhibit the activity of Mpro and RdRp in vitro. Studies have shown that structurally modified lopinavir, favipiravir, and other similar compounds can inhibit COVID-19 main protease (Mpro) and RNA-dependent RNA polymerase (RdRp). In this study, lopinavir and its structurally similar compounds were chosen to bind the main protease, and favipiravir was chosen to target RNA-dependent RNA polymerase. Molecular docking and the quantitative structure-activity relationships (QSAR) study revealed that the selected candidates have favorable binding affinity but less druggable properties. To improve the druggability, four structural analogues of lopinavir and one structural analogue of favipiravir was designed by structural modification. Molecular interaction analyses have displayed that lopinavir and favipiravir analogues interact with the active site residues of Mpro and RdRp, respectively. Absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, medicinal chemistry profile, and physicochemical features were shown that all structurally modified analogues are less toxic and contain high druggable properties than the selected candidates. Subsequently, 50 ns molecular dynamics simulation of the top four docked complexes demonstrated that CID44271905, a lopinavir analogue, forms the most stable complex with the Mpro. Further MMPBSA analyses using the MD trajectories also confirmed the higher binding affinity of CID44271905 towards Mpro. In summary, this study demonstrates a new way to identify leads for novel anti-viral drugs against COVID-19. Communicated by Ramaswamy H. Sarma.

Computer-based identification of potential compounds from Salviae miltiorrhizae against Neirisaral adhesion A regulatory protein.

In silico studies are attracting considerable interest due to their ability to understand protein-ligand interactions at the atomic level. The main principal tools of this in silico analyses are molecular docking and molecular dynamic (MD) simulation. This paper examines how can natural compounds that are derived from Salviae miltiorrhizae to block Neisseria adhesion A Regulatory protein (NadR). In molecular docking analysis, only four compounds were found in higher binding affinity with NadR among 10 candidates (tanshinol B, tanshinol A, lithospermic acid and tournefolal were -7.61, -7.56, -8.22 and -7.81 kcal/mol, respectively, compared to -7.23 kcal/mol of native ligand). Absorption, distribution, metabolism, excretion (ADME) and toxicity properties, medicinal chemistry profile, and physicochemical features were displayed that tournefolal contains good properties to work as a safe and good anti-adhesive drug. Therefore, the complexes of these four ligands with NadR protein were subjected to 100 ns of MD simulation. RMSD, RMSF, RG and hydrogen bonding exhibited that tournefolal showed stable binding affinity and molecular interaction with NadR protein. In light of these results, there is now a need to conduct much more in vitro and in vivo studies about the efficacy of tournefolal.Communicated by Ramaswamy H. Sarma.

Designing a multi-epitope vaccine candidate to combat MERS-CoV by employing an immunoinformatics approach.

Currently, no approved vaccine is available against the Middle East respiratory syndrome coronavirus (MERS-CoV), which causes severe respiratory disease. The spike glycoprotein is typically considered a suitable target for MERS-CoV vaccine candidates. A computational strategy can be used to design an antigenic vaccine against a pathogen. Therefore, we used immunoinformatics and computational approaches to design a multi-epitope vaccine that targets the spike glycoprotein of MERS-CoV. After using numerous immunoinformatics tools and applying several immune filters, a poly-epitope vaccine was constructed comprising cytotoxic T-cell lymphocyte (CTL)-, helper T-cell lymphocyte (HTL)-, and interferon-gamma (IFN-γ)-inducing epitopes. In addition, various physicochemical, allergenic, and antigenic profiles were evaluated to confirm the immunogenicity and safety of the vaccine. Molecular interactions, binding affinities, and the thermodynamic stability of the vaccine were examined through molecular docking and dynamic simulation approaches, during which we identified a stable and strong interaction with Toll-like receptors (TLRs). In silico immune simulations were performed to assess the immune-response triggering capabilities of the vaccine. This computational analysis suggested that the proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat viral infections; however, experimental evaluations remain necessary to verify the exact safety and immunogenicity profile of this vaccine.

Factors Associated With Underprivileged E-Learning, Session Jam Phobia, and the Subsequent Mental Distress Among Students Following the Extended University Closure in Bangladesh.

Severe session jam phobia (SJP), the extent of underprivileged online education, and subsequent mental health disorders among students have emerged as distinguished global problems due to the overwhelming effects of coronavirus disease 2019 (COVID-19). The purpose of this research was to evaluate the impact of extended COVID-19 lockdown and its mediating factors on current e-Learning activities, the prevalence of severe SJP and psychological distress among university students in Bangladesh. A web-based cross-sectional study was conducted to assemble responses through Google Form by applying a simple snowball sampling technique among university students aged 18 years or above in Bangladesh. All ethical considerations were maintained, and univariate, bivariate, and multivariate analyses were employed to analyze the acquired data set. Among the total analyzed data (n = 1,122), the male and female ratio was almost 1:1, and a remarkable segment (63.7%) was aged between 21-24 years. Alarmingly, around 50-60% of the students were suffering from severe SJP, prevailing underprivileged education in the e-Learning platform, and severe mental distress. Logistic regression analyses demonstrated that the students from public universities, lower- and mid-income families, lower-aged, and junior years education groups were significantly (p < 0.05) more underprivileged than their counter groups. Besides, the monthly family income and university type significantly influenced the extent of severe SJP. Finally, the students who were female, rustic, come from low-income families (below 25,000 BDT), who had academic uncertainty, job insecurity, online exam phobia, and dissatisfaction with e-Learning education, were significantly suffering from moderate to severe mental distress. The current evidence demonstrates that a substantial number of Bangladeshi university students are struggling with extreme session jam phobia, underprivileged e-Learning education, and subsequent psychological distress, which need to be immediately addressed through concerted efforts by the government, parents, and university authorities.