Safety comparisons among monoamine oxidase inhibitors against Parkinson's disease using FDA adverse event reporting system.

Monoamine oxidase B (MAO-B) inhibitors are used to control Parkinson's disease (PD). Selegiline, rasagiline, and safinamide are widely used as MAO-B inhibitors worldwide. Although these drugs inhibit MAO-B, there are pharmacological and chemical differences, such as the inhibitory activity, the non-dopaminergic properties in safinamide, and the amphetamine-like structure in selegiline. MAO-B inhibitors may differ in adverse events (AEs). However, differences in actual practical clinics are not fully investigated. A retrospective study was conducted using FAERS, the largest database of spontaneous adverse events. AE signals for MAO-B inhibitors, including selegiline, rasagiline, and safinamide, were detected using the reporting odds ratio method and compared. Hypocomplementemia, hepatic cyst, hepatic function abnormal, liver disorder and cholangitis were detected for selegiline as drug-specific signals. The amphetamine effect was not confirmed for any of the three MAO-B inhibitors. The tyramine reaction was detected as an AE signal only for rasagiline. Moreover, the REM sleep behavior disorder was not detected as an AE signal for safinamide, suggesting that non-dopaminergic effects might be beneficial. Considering the differences in AEs for MAO-B inhibitors will assist with the appropriate PD medication.

DTAmetasa: An R shiny application for meta-analysis of diagnostic test accuracy and sensitivity analysis of publication bias.

Meta-analysis of diagnostic test accuracy (DTA) is a powerful statistical method for synthesizing and evaluating the diagnostic capacity of medical tests and has been extensively used by clinical physicians and healthcare decision-makers. However, publication bias (PB) threatens the validity of meta-analysis of DTA. Some statistical methods have been developed to deal with PB in meta-analysis of DTA, but implementing these methods requires high-level statistical knowledge and programming skill. To assist non-technical users in running most routines in meta-analysis of DTA and handling with PB, we developed an interactive application, DTAmetasa. DTAmetasa is developed as a web-based graphical user interface based on the R shiny framework. It allows users to upload data and conduct meta-analysis of DTA by "point and click" operations. Moreover, DTAmetasa provides the sensitivity analysis of PB and presents the graphical results to evaluate the magnitude of the PB under various publication mechanisms. In this study, we introduce the functionalities of DTAmetasa and use the real-world meta-analysis to show its capacity for dealing with PB.

Genetic algorithm-based feature selection with manifold learning for cancer classification using microarray data.

BACKGROUND: Microarray data have been widely utilized for cancer classification. The main characteristic of microarray data is "large p and small n" in that data contain a small number of subjects but a large number of genes. It may affect the validity of the classification. Thus, there is a pressing demand of techniques able to select genes relevant to cancer classification. RESULTS: This study proposed a novel feature (gene) selection method, Iso-GA, for cancer classification. Iso-GA hybrids the manifold learning algorithm, Isomap, in the genetic algorithm (GA) to account for the latent nonlinear structure of the gene expression in the microarray data. The Davies-Bouldin index is adopted to evaluate the candidate solutions in Isomap and to avoid the classifier dependency problem. Additionally, a probability-based framework is introduced to reduce the possibility of genes being randomly selected by GA. The performance of Iso-GA was evaluated on eight benchmark microarray datasets of cancers. Iso-GA outperformed other benchmarking gene selection methods, leading to good classification accuracy with fewer critical genes selected. CONCLUSIONS: The proposed Iso-GA method can effectively select fewer but critical genes from microarray data to achieve competitive classification performance.

The Efficacy of Golimumab Against Non-Infectious Uveitis: A PRISMA-Compliant Systematic Review and Meta-Analysis.

PURPOSE: In this PRISMA-compliant systematic review and meta-analysis, we aimed to assess the efficacy of golimumab (GOL) against non-infectious uveitis (NIU). METHODS: We included eight articles in the meta-analysis. The primary outcome was inflammation remission. Secondary outcomes were changes in the number of uveitis relapses/attacks, mean best-corrected visual acuity, central macular thickness, and systemic corticosteroid-sparing effects. RESULTS: In total, eight case series with 172 patients (43.6% female) were collected. Patients had 75% (95% CI: 56-87%) of remission; 42% (0.12-0.80) of patients showed improved visual acuity. The average central macular thickness decline was 38 µm (-56.51-18.54). The pooled results showed a significant decrease in the use of systemic corticosteroids. CONCLUSION: This study was limited by the use of non-RCT designs, limited sample sizes for outcomes, and heterogenetic underlying diseases. Our results suggest that GOL is effective against NIU. However, further evidence and analyses are required. (Funding: None; PROSPERO registration: CRD42021266214.).

Safety, efficacy, and cost-effectiveness of insulin degludec U100 versus insulin glargine U300 in adults with type 1 diabetes: a systematic review and indirect treatment comparison.

BACKGROUND: Clinical differences between degludec U100 (Deg-100) and glargine U300 (Gla-300) in type 1 diabetes (T1D) were unknown. AIM: To indirectly compare the safety, efficacy, and cost-effectiveness between Deg-100 and Gla-300 in T1D adults via systematic review. METHOD: Medline, the Cochrane Library, ClinicalTrials.gov, and Google Scholar were searched (October 2021). Randomized controlled trials comparing Deg-100 or Gla-300 vs. glargine U100 in T1D adults (follow-up ≥ 12 weeks) were selected and analyzed using a frequentist network meta-analysis. Cost-effectiveness analysis (CEA) was conducted over a 1-year time horizon from societal perspectives. RESULTS: Nine trials were included. Efficacy analysis suggested that Deg-100 was non-inferior to Gla-300 in reducing HbA1c (MD 0.03 [95% CI - 0.09 to 0.15]; P = 0.60), FPG (MD - 1.12 [- 2.19 to - 0.04]; P = 0.04), and pre-breakfast SMBG (MD - 0.71 [- 1.46 to 0.03]; P = 0.06). Safety analysis suggested that Deg-100 appeared to have lower rates of both severe (HR 0.44 [0.25-0.78]; P = 0.005) and nocturnal severe (HR 0.19 [0.08-0.44]; P < 0.001) hypoglycemia, with lower total (MD - 0.07 [- 0.13 to - 0.01]; P = 0.02) and basal (MD - 0.08 [- 0.12 to - 0.04]; P < 0.001) insulin doses compared with Gla-300. No significant differences were observed for other hypoglycemia outcomes, adverse events, serious adverse events, bolus insulin dose, and body weight. The CEA showed that Deg-100 appeared to be a dominant treatment in Japan (+ 0.0283 QALYs, ¥26,266 [$228] per patient) and the United States (+ 0.0267 QALYs, $986 per patient). CONCLUSION: Low-certainty indirect evidence suggested that Deg-100 appeared to have a favorable reduction in rates of severe hypoglycemia and more cost-effective compared with Gla-300 in T1D adults.

Predicting the side effects of drugs using matrix factorization on spontaneous reporting database.

The severe side effects of some drugs can threaten the lives of patients and financially jeopardize pharmaceutical companies. Computational methods utilizing chemical, biological, and phenotypic features have been used to address this problem by predicting the side effects. Among these methods, the matrix factorization method, which utilizes the side-effect history of different drugs, has yielded promising results. However, approaches that encapsulate all the characteristics of side-effect prediction have not been investigated to date. To address this gap, we applied the logistic matrix factorization algorithm to a database of spontaneous reports to construct a prediction with higher accuracy. We expressed the distinction in the importance of drug-side effect pairs by a weighting strategy and addressed the cold-start problem via an attribute-to-feature mapping method. Consequently, our proposed model improved the prediction accuracy by 2.5% and efficiently handled the cold-start problem. The proposed methodology is expected to benefit applications such as warning systems in clinical settings.

Efficacy and safety among second-generation and other basal insulins in adult patients with type 1 diabetes: a systematic review and network meta-analysis.

We aimed to assess the comparative efficacy and safety of second-generation basal insulins (glargine U300 and degludec U100) vs. neutral protamine Hagedorn (NPH) and first-generation basal insulins (glargine U100 and detemir) in type 1 diabetes (T1D) adults.PubMed, the Cochrane Library, ClinicalTrials.gov, and Google Scholar (until January 2021) were systematically searched. Randomized controlled trials (RCTs) with ≥ 12 weeks of follow-up comparing efficacy (HbA1c) or safety (hypoglycemia and weight gain) between second-generation basal insulins vs. other basal insulins in T1D adults were included. Bayesian network meta-analyses were used to estimate risk ratio, hazard ratio, and mean difference. Grading of Recommendations, Assessment, Development and Evaluation (GRADE) was used to appraise evidence certainty.Eighteen RCTs (≥ 24 weeks of follow-up) involving 7283 randomized participants were included for main analysis. Moderate to high certainty evidence suggested that second-generation basal insulins showed equivalent HbA1c reduction compared with NPH and first-generation basal insulins. Compared with second-generation basal insulins, low to high certainty evidence suggested that NPH was associated with a higher risk of patients experiencing severe hypoglycemia; NPH and first-generation basal insulins were associated with a higher rate of nocturnal confirmed hypoglycemic events. For the weight gain, glargine U300 was comparable to detemir (low certainty), but degludec U100 was greater than detemir (moderate certainty).In conclusion, second-generation basal insulins maintained equivalent efficacy of glycemic control (moderate to high certainty), with differences in safety (low to high certainty) compared with NPH and first-generation basal insulins during ≥ 24 weeks of follow-up in T1D adults.

Intermolecular Interaction Analyses on SARS-CoV-2 Spike Protein Receptor Binding Domain and Human Angiotensin-Converting Enzyme 2 Receptor-Blocking Antibody/Peptide Using Fragment Molecular Orbital Calculation.

The spike glycoprotein (S-protein) mediates SARS-CoV-2 entry via intermolecular interaction with human angiotensin-converting enzyme 2. The receptor binding domain (RBD) of the S-protein has been considered critical for this interaction and acts as the target of numerous neutralizing antibodies and antiviral peptides. This study used the fragment molecular orbital method to analyze the interactions between the RBD and antibodies/peptides and extracted crucial residues that can be used as epitopes. The interactions evaluated as interfragment interaction energy values between the RBD and 12 antibodies/peptides showed a fairly good correlation with the experimental activity pIC50 (R2 = 0.540). Nine residues (T415, K417, Y421, F456, A475, F486, N487, N501, and Y505) were confirmed as being crucial. Pair interaction energy decomposition analyses showed that hydrogen bonds, electrostatic interactions, and π-orbital interactions are important. Our results provide essential information for understanding SARS-CoV-2-antibody/peptide binding and may play roles in future antibody/antiviral drug design.

Knowledge, attitudes, and practices toward COVID-19 among university students in Japan and associated factors: An online cross-sectional survey.

The coronavirus disease (COVID-19) pandemic has greatly altered peoples' daily lives, and it continues spreading as a crucial concern globally. Knowledge, attitudes, and practices (KAP) toward COVID-19 are related to individuals' adherence to government measures. This study evaluated KAP toward COVID-19 among university students in Japan between May 22 and July 16, 2020, via an online questionnaire, and it further investigated the associated determining KAP factors. Among the eligible respondents (n = 362), 52.8% were female, 79.0% were undergraduate students, 32.9% were students whose major university subjects were biology-related, 35.4% were from the capital region, and 83.7% were Japanese. The overall KAP of university students in Japan was high. All respondents (100%) showed they possessed knowledge on avoiding enclosed spaces, crowded areas, and close situations. Most respondents showed a moderate or higher frequency of washing their hands or wearing masks (both at 96.4%). In addition, 68.5% of respondents showed a positive attitude toward early drug administration. In the logistic regressions, gender, major subjects, education level, nationality, residence, and psychological factors (private self-consciousness and extroversion) were associated with knowledge or attitudes toward COVD-19 (p < 0.05). In the logistic and multiple linear regressions, capital regions, high basic knowledge, high information acquisition, correct information explanations contributed positively to preventative action (p < 0.05). Non-capital regions, male gender, non-bio-backgrounds, high public self-consciousness, high advanced knowledge, incorrect information explanations, and high extroversion contributed negatively to self-restraint (p < 0.05). Moreover, self-restraint was decreasing over time. These findings clarify the Japanese university students' KAP and the related factors in the early period of the COVID-19 pandemic, and they may help university managers, experts, and policymakers control the future spread of COVID-19 and other emerging infections.

A Comparison between the Cycloadditions of Allenyl- and Vinyl-Cyclopentanes Using Density Functional Theory and GRRM Program.

Cycloaddition catalyzed by transition metals such as rhodium (I) is an important way to synthesize functionalized molecules in medicinal chemistry. When the reagent has a saturated ring containing more than five carbons (or heavy atoms), the reaction can progress when the compound has an allenyl group, but not for a vinyl group. Here, we constructed two computational models for allenylcyclopentane-alkyne and vinylcyclopentane-alkyne, and obtained their reaction pathways using density functional theory (DFT). From the reaction pathways, we confirmed that the former model has a much lower reaction energy than the latter. We also found that the molecular orbitals of the transition state structure at the rate-controlling step contribute significantly to the difference in reactivity between the two models.

MEPHAS: an interactive graphical user interface for medical and pharmaceutical statistical analysis with R and Shiny.

BACKGROUND: Even though R is one of the most commonly used statistical computing environments, it lacks a graphical user interface (GUI) that appeals to students, researchers, lecturers, and practitioners in medicine and pharmacy for conducting standard data analytics. Current GUIs built on top of R, such as EZR and R-Commander, aim to facilitate R coding and visualization, but most of the functionalities are still accessed through a command-line interface (CLI). To assist practitioners of medicine and pharmacy and researchers to run most routines in fundamental statistical analysis, we developed an interactive GUI; i.e., MEPHAS, to support various web-based systems that are accessible from laptops, workstations, or tablets, under Windows, macOS (and IOS), or Linux. In addition to fundamental statistical analysis, advanced statistics such as the extended Cox regression and dimensional analyses including partial least squares regression (PLS-R) and sparse partial least squares regression (SPLS-R), are also available in MEPHAS. RESULTS: MEPHAS is a web-based GUI (https://alain003.phs.osaka-u.ac.jp/mephas/) that is based on a shiny framework. We also created the corresponding R package mephas (https://mephas.github.io/). Thus far, MEPHAS has supported four categories of statistics, including probability, hypothesis testing, regression models, and dimensional analyses. Instructions and help menus were accessible during the entire analytical process via the web-based GUI, particularly advanced dimensional data analysis that required much explanation. The GUI was designed to be intuitive for non-technical users to perform various statistical functions, e.g., managing data, customizing plots, setting parameters, and monitoring real-time results, without any R coding from users. All generated graphs can be saved to local machines, and tables can be downloaded as CSV files. CONCLUSION: MEPHAS is a free and open-source web-interactive GUI that was designed to support statistical data analyses and prediction for medical and pharmaceutical practitioners and researchers. It enables various medical and pharmaceutical statistical analyses through interactive parameter settings and dynamic visualization of the results.

Vonoprazan vs proton pump inhibitors in treating post-endoscopic submucosal dissection ulcers and preventing bleeding: A meta-analysis of randomized controlled trials and observational studies.

BACKGROUND: Vonoprazan is a potassium-competitive acid blocker (P-CAB) that is frequently used in Japan for Helicobacter pylori (H. pylori) eradication, treatment of gastroesophageal reflux disease, and treatment of post endoscopic submucosal dissection (ESD) complications. We sought to determine if vonoprazan was superior to proton pump inhibitors (PPIs) for treating ESD-induced ulcers (as assessed by ulcer healing and shrinkage ratios) and preventing delayed bleeding over various treatment durations (2, 4, and 8 weeks). METHODS: We collected randomized controlled trials (RCTs) and observational studies that discussed the effectiveness of vonoprazan and PPIs on ESD-induced ulcers and bleeding from PubMed, Cochrane Library, ClinicalTrials.gov, and Google Scholar. Studies were selected according to pre-established eligibility criteria and data were extracted separately by 2 researchers with double-check. We used the Cochrane risk of bias tool to assess RCTs and the Newcastle-Ottawa Quality Assessment Scale to assess observational studies. Meta-analyses, based on the random-effects model, were conducted to compare differences in ulcer shrinkage ratios (%) and odds ratios (ORs) for ulcer healing and delayed bleeding. Publication bias was evaluated using funnel plots and Egger regression test. Heterogeneity was assessed using I statistics. A sensitivity analysis was conducted to check the robustness of results. The evidential quality of the findings was assessed using the GRADE profiler. RESULTS: Thirteen studies were included in this meta-analysis. The OR effect sizes of vonoprazan relative to PPIs for ulcer healing were 1.33 (P = .13) with a 95% CI (0.33-3.21) at 4 weeks and 1.48 (P = .09) with a 95% CI (0.81-5.20) at 8 weeks. The overall effect size for the shrinkage ratio was 12.24% (P = .16) with a 95% CI (-4.96-29.44) at 2 weeks. The effect size of its subgroup of H. pylori-positive patients was 19.51% (P < .001) with a 95% CI (11.91-27.12). The overall OR for the occurrence of delayed bleeding was 0.66 (P = .26) with a 95% CI (0.32-1.35). After excluding combination drug studies, the overall ORs between vonoprazan and PPIs on ulcer healing and delayed bleeding were 1.44 and 0.76, respectively. CONCLUSION: During the first 2 weeks of treatment, vonoprazan was more effective than PPIs for treating H. pylori-positive patients with ESD-induced gastric ulcers.

Three-Dimensional Classification Structure-Activity Relationship Analysis Using Convolutional Neural Network.

Quantitative structure-activity relationship (QSAR) techniques, especially those that possess three-dimensional attributes, such as the comparative molecular field analysis (CoMFA), are frequently used in modern-day drug design and other related research domains. However, the requirement for accurate alignment of compounds in CoMFA increases the difficulties encountered in its use. This has led to the development of several techniques-such as VolSurf, Grid-independent descriptors (GRIND), and Anchor-GRIND-which do not require such an alignment. We propose a technique to construct the prediction model that uses molecular interaction field grid potentials as inputs to convolutional neural network. The proposed model has been found to demonstrate higher accuracy compared to the conventional descriptor-based QSAR models as well as Anchor-GRIND techniques. In addition, the method is target independent, and is capable of providing useful information regarding the importance of individual atoms constituting the compounds contained in the chemical dataset used in the proposed analysis. In view of these advantages, the proposed technique is expected to find wide applications in future drug-design operations.

Vonoprazan versus proton pump inhibitors in treating post-endoscopic submucosal dissection ulcers and preventing bleeding: Protocol for meta-analysis of randomized controlled trials and observational studies.

BACKGROUND: Vonoprazan is a potassium-competitive acid blocker (P-CAB). It is often used in Japan for Helicobacter pylori (H pylori) eradication, gastroesophageal reflux disease, and endoscopic submucosal dissection (ESD) ulcers and bleeding. This meta-analysis aims to evaluate whether vonoprazan has better therapeutic effect on ESD-induced ulcers and bleeding than proton pump inhibitors (PPIs) at different length of treatment periods (2, 4, and 8 weeks). METHODS: This meta-analysis will include both randomized controlled trials (RCTs) and observational studies discussing the effectiveness of vonoprazan and PPIs on ESD-induced ulcers and bleeding. Information of studies will be collected from PubMed, Cochrane Library, ClinicalTrials.gov, and Google Scholar. Studies will be selected according to the eligibility criteria and data will be extracted by 2 people and compared with each other to keep in consistency. Cochrane risk of bias tool will be used to assess RCTs and the Newcastle-Ottawa Quality Assessment Scale will be used to assess the observational studies. Meta-analysis based on the random-effects model will be conducted to compare the differences of ulcers' shrinkage ratios (%) and the odds ratios (OR) of scars' stages and delayed bleeding. Publication bias will be evaluated using funnel plots and Egger's regression test. Heterogeneity will be assessed with the I statistics. Sensitivity analysis will be conducted on follow-up periods. The evidential quality of the findings will be assessed with the Grading of Recommendations Assessment Development and Evaluation (GRADE) profiler. DISCUSSION: The findings of the present systematic review will be critical for physicians, patients, and policymakers regarding the use of vonoprazan in ESD-induced ulcers. STUDY REGISTRATION: PROSPERO registration number: CRD42018116855.

Dengue Virus and Its Inhibitors: A Brief Review.

The global occurrence of viral infectious diseases poses a significant threat to human health. Dengue virus (DENV) infection is one of the most noteworthy of these infections. According to a WHO survey, approximately 400 million people are infected annually; symptoms deteriorate in approximately one percent of cases. Numerous foundational and clinical investigations on viral epidemiology, structure and function analysis, infection source and route, therapeutic targets, vaccines, and therapeutic drugs have been conducted by both academic and industrial researchers. At present, CYD-TDV or Dengvaxia® is the only approved vaccine, but potent inhibitors are currently under development. In this review, an overview of the viral life circle and the history of DENVs is presented, and the most recently reported antiviral candidates and newly discovered promising targets are focused and summarized. We believe that these successes and failures have enabled progress in anti-DENV drug discovery and hope that our review will stimulate further innovation in this area.

Mordred: a molecular descriptor calculator.

Molecular descriptors are widely employed to present molecular characteristics in cheminformatics. Various molecular-descriptor-calculation software programs have been developed. However, users of those programs must contend with several issues, including software bugs, insufficient update frequencies, and software licensing constraints. To address these issues, we propose Mordred, a developed descriptor-calculation software application that can calculate more than 1800 two- and three-dimensional descriptors. It is freely available via GitHub. Mordred can be easily installed and used in the command line interface, as a web application, or as a high-flexibility Python package on all major platforms (Windows, Linux, and macOS). Performance benchmark results show that Mordred is at least twice as fast as the well-known PaDEL-Descriptor and it can calculate descriptors for large molecules, which cannot be accomplished by other software. Owing to its good performance, convenience, number of descriptors, and a lax licensing constraint, Mordred is a promising choice of molecular descriptor calculation software that can be utilized for cheminformatics studies, such as those on quantitative structure-property relationships.

Novel Concepts for Drug Hypersensitivity Based on the Use of Long-Time Scale Molecular Dynamic Simulation.

The discovery that several drug hypersensitivity reactions (DHRs) are associated with specific human leukocyte antigen (HLA) alleles has attracted increasing research interest. However, the underlying mechanisms of these HLA-induced DHRs remain unclear, especially for drug-induced immediate activation of T-cell clones (TCCs). Recently, a novel hypothesis involving partial detachment between self-peptide(s) and the HLA molecule (altered peptide-HLA (pHLA) model) has been proposed to explain these phenomena. In order to clarify this hypothesis, we performed long-timescale molecular dynamics (MD) simulations. We focused on HLA-B⁎57:01-restricted abacavir hypersensitivity reactions (AHRs), one of the most famous DHRs. One of the simulation results showed that this altered-pHLA model might be driven by an increase in the distance not only between HLA and self-peptides but also between the α1 and α2 helices of HLA. Our findings provide novel insights into abacavir-induced immediate activation of TCCs and these findings might also be applied to other DHRs, such as HLA-B⁎58:01-restricted allopurinol hypersensitivity reactions.

In silico analysis of enantioselective binding of immunomodulatory imide drugs to cereblon.

BACKGROUND: Thalidomide and its analogs, lenalidomide and pomalidomide (referred to as immunomodulatory imide drugs or IMiDs) have been known to treat multiple myeloma and other hematologic malignancies as well as to cause teratogenicity. Recently the protein cereblon was identified as the primary target of IMiDs, and crystallographic studies of the cereblon-IMiDs complex showed strong enantioselective binding for the (S)-enantiomer of IMiDs. RESULTS: Using the structures of cereblon and IMiDs [both (S)-enantiomers and (R)-enantiomers] we performed docking simulations in order to replicate this enantiomeric selectivity and to identify the region(s) contributing to this selectivity. We confirmed the enantioselective binding of IMiDs to cereblon with high accuracy, and propose that the hairpin connecting the ß10-ß11 region of cereblon (residues 351-355) contributes to this selectivity and to the increased affinity with IMiDs. CONCLUSIONS: Our docking results provide novel insights into the binding mode of IMiD-like molecules and contribute to a deeper understanding of cereblon-related biology.

Pharmacophore Modeling and Molecular Docking Studies of potential inhibitors to E6 PBM-PDZ from Human Papilloma Virus (HPV).

High-risk human papillomaviruses (HPVs) are known to cause cervical cancer. Vaccines are now available to prevent HPV infection. However, a clinically approved drug is yet not available to treat HPV. The PDZ(PSD-95/Dlg/ZO-1)-binding motif (PBM) in the E6 protein of HPVs targets the PDZ domain (known to be associated with oncogenesis) for degradation. Therefore, it is of interest to study PBM-PDZ interaction towards its possible inhibition with a potential inhibitor. Thus, four pharmocophore models of PBM-PDZ complex were developed. In order to obtain potent small molecules for its inhibition, a commercial compound database was screened using both these pharmacophore models and molecule docking method. These efforts identified four potential compounds (1-4) towards its inhibition with the docking scores range -18.2 to -15.0.