In-silico molecular modelling studies of some camphor imine based compounds as anti-influenza A (H1N1) pdm09 virus agents.

The advent of influenza A (H1N1) drug-resistant strains led to the search quest for more potent inhibitors of the influenza A virus, especially in this devastating COVID-19 pandemic era. Hence, the present research utilized some molecular modelling strategies to unveil new camphor imine-based compounds as anti-influenza A (H1N1) pdm09 agents. The 2D-QSAR results revealed GFA-MLR (R2train = 0.9158, Q2=0.8475) and GFA-ANN (R2train = 0.9264, Q2=0.9238) models for the anti-influenza A (H1N1) pdm09 activity prediction which have passed the QSAR model acceptability thresholds. The results from the 3D-QSAR studies also revealed CoMFA (R2train =0.977, Q2=0.509) and CoMSIA_S (R2train =0.976, Q2=0.527) models for activity predictions. Based on the notable information derived from the 2D-QSAR, 3D-QSAR, and docking analysis, ten (10) new camphor imine-based compounds (22a-22j) were designed using the most active compound 22 as the template. Furthermore, the high predicted activity and binding scores of compound 22j were further justified by the high reactive sites shown in the electrostatic potential maps and other quantum chemical calculations. The MD simulation of 22j in the active site of the influenza hemagglutinin (HA) receptor confirmed the dynamic stability of the complex. Moreover, the appraisals of drug-likeness and ADMET properties of the proposed compounds showed zero violation of Lipinski's criteria with good pharmacokinetic profiles. Hence, the outcomes in this work recommend further in-depth in vivo and in-vitro investigations to validate these theoretical findings.Communicated by Ramaswamy H. Sarma.

Molecular modelling studies of substituted indole derivatives as novel influenza a virus inhibitors.

The emergence of drug-resistant strains motivate researchers to find new innovative anti-IAV candidates with a different mode of action. In this work, molecular modelling strategies, such as 2D-QSAR, 3D-QSAR, molecular docking, molecular dynamics, FMOs, and ADMET were applied to some substituted indoles as IAV inhibitors. The best-developed 2D-QSAR models, MLR (Q2 = 0.7634, R2train = 0.8666) and ANN[4-3-1] (Q2 = 0.8699, R2train = 0.8705) revealed good statistical validation for the inhibitory response predictions. The 3D-QSAR models, CoMFA (Q2 = 0.504, R2train = 0.805) and CoMSIA/SEDHA (Q2 = 0.619, R2train = 0.813) are selected as the best 3D models following the global thresholds. In addition, the contour maps generated from the CoMFA and CoMSIA models illustrate the relationship between the molecular fields and the inhibitory effects of the studied molecules. The results of the studies led to the design of five new molecules (24a-e) with enhanced anti-IAV activities and binding potentials using the most active molecule (24) as the template scaffold. The conformational stability of the best-designed molecules with the NA protein showed hydrophobic and H-bonds with the key residues from the molecular dynamics simulations of 100 ns. Furthermore, the global reactivity indices from the DFT calculations portrayed the relevance of 24c in view of its smaller band gap as also justified by our QSAR and molecular simulation studies.Communicated by Ramaswamy H. Sarma.

Retraction notice to "In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions" [Heliyon 8, 2022 Article e10101].

[This retracts the article DOI: 10.1016/j.heliyon.2022.e10101.].

Structure-based drug design, molecular dynamics simulation, ADMET, and quantum chemical studies of some thiazolinones targeting influenza neuraminidase.

The genetic mutability of the influenza virus leads to the existence of drug-resistant strains which is dangerous, particularly with the lingering coronavirus disease (COVID-19). This necessitated the need for the search and discovery of more potential anti-influenza agents to avert future outbreaks. In furtherance of our previous in-silico studies on 5-benzyl-4-thiazolinones as anti-influenza neuraminidase (NA) inhibitors, molecule 11 was selected as the template scaffold for the structure-based drug design due to its good binding, pharmacokinetic profiling, and better NA inhibitory activity. As such, eighteen (18) new molecules (11a-r) were designed with better MolDock scores as compared with the template scaffold and the zanamivir reference drug. However, the dynamic stability of molecule 11a in the binding cavity of the NA target (3TI5) showed water-mediated hydrogen and hydrophobic bondings with the active residues such as Arg118, Ile149, Arg152, Ile222, Trp403, and Ile427 after the MD simulation for 100 ns. The drug-likeness and ADMET assessment of all designed molecules predicted non-violation of the stipulated thresholds of Lipinski's rule and good pharmacokinetic properties respectively. In addition, the quantum chemical calculations also suggested the significant chemical reactivity of molecules with their smaller band energy gap, high electrophilicity, high softness, and low hardness. The results obtained in this study proposed a reliable in-silico viewpoint for anti-influenza drug discovery and development.Communicated by Ramaswamy H. Sarma.

ABO Blood Group Genotypes and Demographic Traits in Susceptibility to Type 1 Diabetes Mellitus in Lagos, Southwest, Nigeria.

Studies have shown that ABO blood groups and demographic traits influence susceptibility to type 1 diabetes mellitus (T1DM) and can be used in combination with insulin therapy to reduce the disease's burden. However, geographical variations exist in the influence of demographic traits and ABO blood groups on susceptibility to diseases and thus require establishing it in every locality. This study determined the influence of demographic traits and ABO blood groups on the prevalence of T1DM in Lagos, Nigeria. A structured checklist was used to collect data from the health records of non-obese 150 type 1 diabetic patients at Ayobo Primary Health Center, Lagos. The results revealed that males, with 88 participants (52.7%), constituted the majority, while females had 62 (41.3%). The age group 40 years and older had the highest proportion of participants with 37 (24.7%), followed by 31-40 years with 32 (21.30%), 21-30 years with 30 (20%), 11-20 years with 27 (18%), and 1-10 years with 24 (16%). Christianity had the highest with 74 participants (49.3%), followed by Islam with 71 participants (47.3%), and traditional religion with 5 participants (3.3%). Eight (5.3%) of the participants were primary school graduates; 34 (22.7%) were secondary school graduates; and 108 (72%) were tertiary school graduates. The Yoruba ethnic group, with 77 participants (51.3%), was the most prevalent, followed by Igbo with 50 (33.3%), and Hausa with 3 (2.0%). ABO blood group A and B (positive and negative) individuals were the most diabetic and expressed the most severe cases, while group O positive and AB negative individuals were the least diabetic. T1DM prevention should be a priority for blood group A and B residents.

Airway Management During Diagnostic Laparoscopic Surgery: A Comparison of I-Gel and Proseal Laryngeal Mask Airway.

Background: Supraglottic airway devices (SADs) may be used during laparoscopic procedures in place of the often utilised endotracheal tube. The Proseal laryngeal mask airway (PLMA) is designed with an inflatable cuff, which provides an excellent oropharyngeal seal, and the I-gel is a newer SAD designed with a softer and noninflatable cuff and sharing similar features with PLMA. Aim and Objectives: This study compared the ease of insertion, haemodynamic and ventilatory parameters as well as morbidities associated with these SADs when used for airway management during diagnostic laparoscopic procedures. Patients and Methods: Eighty American Society of Anaesthesiologist I and II patients aged 18-60 years undergoing diagnostic laparoscopic surgery under controlled ventilation had either I-gel or PLMA used for airway management. Anaesthesia was induced with standard dose of propofol, patient received atracurium, fentanyl and the SAD inserted. Pulse oximetry, capnography, noninvasive blood pressure, oropharyngeal leak pressure (OLP), and evidence of pharyngolaryngeal morbidity were assessed. Data were analysed using the Statistical Package for Social Sciences version 21.0. The quantitative variables were analysed using the Student's t test and the qualitative using the Chi-square test. A P value of less than 0.05 was considered significant. Results: The success rates at first insertion for I-gel and PLMA were 95% and 80%, respectively (P = 0.04). The mean changes in mean arterial pressure following insertion were 9.6 mmHg (±4.7) and 10.6 mmHg (±8) for I-gel and PLMA, respectively (P = 0.02). The OLP during insufflation was higher in the PLMA (35.8 cmH2O) than in the I-gel group (27.9 cmH2O) (P = 0.57). In the I-gel group, 12.5% of the patients had oropharyngeal morbidities compared with 37.5% in the PLMA group (P = 0.009). Conclusion: Both I-gel and PLMA provide optimal ventilation during abdominal insufflation, with PLMA providing a better oropharyngeal seal, whereas I-gel has a better haemodynamic profile.

Computational modelling studies of some 1,3-thiazine derivatives as anti-influenza inhibitors targeting H1N1 neuraminidase via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions.

Background: Influenza virus disease remains one of the most contagious diseases that aided the deaths of many patients, especially in this COVID-19 pandemic era. Recent discoveries have shown that the high prevalence of influenza and SARS-CoV-2 coinfection can rapidly increase the death rate of patients. Hence, it became necessary to search for more potent inhibitors for influenza disease therapy. The present study utilized some computational modeling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions of some 1,3-thiazine derivatives as inhibitors of influenza neuraminidase (NA). Results: The 2D-QSAR modeling results showed GFA-MLR ( R train 2 = 0.9192, Q 2 = 0.8767, R 2 adj = 0.8991, RMSE = 0.0959, R test 2 = 0.8943, R pred 2 = 0.7745) and GFA-ANN ( R train 2 = 0.9227, Q 2 = 0.9212, RMSE = 0.0940, R test 2 = 0.8831, R pred 2 = 0.7763) models with the computed descriptors as ATS7s, SpMax5_Bhv, nHBint6, and TDB9m for predicting the NA inhibitory activities of compounds which have passed the global criteria of accepting QSAR model. The 3D-QSAR modeling was carried out based on the comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA). The CoMFA_ES ( R train 2 = 0.9620, Q 2 = 0.643) and CoMSIA_SED ( R train 2 = 0.8770, Q 2 = 0.702) models were found to also have good and reliable predicting ability. The compounds were also virtually screened based on their binding scores via molecular docking simulations with the active site of the NA (H1N1) target receptor which also confirms their resilient potency. Four potential lead compounds (4, 7, 14, and 15) with the relatively high inhibitory rate (> 50%) and docking (> - 6.3 kcal/mol) scores were identified as the possible lead candidates for in silico exploration of improved anti-influenza agents. Conclusion: The drug-likeness and ADMET predictions of the lead compounds revealed non-violation of Lipinski's rule and good pharmacokinetic profiles as important guidelines for rational drug design. Hence, the outcome of this research set a course for the in silico design and exploration of novel NA inhibitors with improved potency.

In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions.

Influenza virus disease is one of the most infectious diseases responsible for many human deaths, and the high mutability of the virus causes drug resistance effects in recent times. As such, it became necessary to explore more inhibitors that could avert future influenza pandemics. The present research utilized some in-silico modelling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions on some 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase (NA) inhibitors. The 2D-QSAR modelling results revealed GFA-MLR ( R train 2 =0.8414, Q2 = 0.7680) and GFA-ANN ( R train â€‹ 2 =0.8754, Q2 = 0.8753) models with the most relevant descriptors (MATS3i, SpMax5_Bhe, minsOH and VE3_D) for predicting the inhibitory activities of the molecules which has passed the global criteria of accepting QSAR models. The results of the 3D-QSAR modelling results showed that CoMFA_ES ( R train â€‹ 2 =0.9030, Q2 = 0.5390) and CoMSIA_EA ( R train 2 =0.880, Q2 = 0.547) models are having good predicting ability among other developed models. The molecules were virtually screened via molecular docking simulation with the active site of NA protein receptor (pH1N1) which confirms their resilient potency when compared with zanamivir standard drug. Molecule 11 as the most potent molecule formed more H-bond interactions with the key residues such as TRP178, ARG152, ARG292, ARG371, and TYR406 that triggered the catalytic reactions for NA inhibition. Furthermore, six (6) molecules (9, 10, 11, 17, 22, and 31) with relatively high inhibitory activities and docking scores were identified as the possible leads for in-silico exploration of novel NA inhibitors. The drug-likeness and ADMET predictions of the lead molecules revealed non-violation of Lipinski's rule and good pharmacokinetic profiles respectively, which are important guidelines for rational drug design. Hence, the outcome of this study overlaid a solid foundation for the in-silico design and exploration of novel NA inhibitors with improved potency.

Computer-aided modeling of triazole analogues, docking studies of the compounds on DNA gyrase enzyme and design of new hypothetical compounds with efficient activities.

The increasing problem of multi-drug resistant-tuberculosis has focused attention on developing new drugs that are not only active against drug-resistant tuberculosis, but also shorten the lengthy therapy. Therefore, this work employs the application of modeling technique to predict the inhibition activities of some prominent compounds which been reported to be efficient against Mycobacterium tuberculosis. To accomplish the purpose of this work, multiple regression and genetic function approximation were adopted to create the model. The established model was swayed with topological descriptors; MATS7s, SpMin4_Bhv, TDB3v and RDF70v. More also, interactions between the compounds and the target protein 'DNA gyrase' were evaluated via molecular docking approach utilizing the PyRx and discovery studio simulation software. Based on the docking analysis, compound 20 has the most noticeable binding affinity of -16.5 kcal/mol. Therefore, compound 20 served as a reference structural template and insight to design fourteen novel hypothetical agents with more prominent anti-tubercular activities. More also, compound 20j was observed with the highest activity among the designed compounds with a prominent binding affinity of -24.3 kcal/mol. Therefore, this research recommends in-vivo, in-vitro screening and pharmacokinetic properties to be carried out in order to determine the toxicity of the designed compounds.Communicated by Ramaswamy H. Sarma.

In-silico design and ADMET predictions of some new imidazo[1,2-a]pyridine-3-carboxamides (IPAs) as anti-tubercular agents.

Tuberculosis (TB) is one of the leading infectious diseases worldwide even with the ravaging COVID-19 pandemic in recent times. This mandated further search and exploration of more possible anti-TB drug candidates against M. tuberculosis strains. As an extension of our previous work on the homology modeled cytochrome b subunit of the bc1 complex (QcrB) of Mycobacterium tuberculosis, an in-silico design was carried out in order to further explore more newly potential anti-TB compounds. Ligand 26 was selected as the lead template (scaffold A) based on our previous docking results and its less bulky structure. Successively, eight (8) new ligands (A1-A8) were designed with better binding affinities in comparison to the scaffold template (-6.8 kcal/mol) and isoniazid standard drug (-6.00 kcal/mol) respectively. In addition, three (3) designed ligands namely, A6, A2, and A7 with higher binding affinities were validated via ADME and toxicity prediction analysis, and the results showed zero violations of Lipinski rules with similar bioavailability, and high rate in gastrointestinal absorption, while toxicity parameters such as carcinogenicity and cytotoxicity were all predicted as non-toxic (inactiveness). The designed IPA compounds in the present study could serve as a promising gateway that could help the medicinal and synthetic chemist in the exploration of a new set of derivatives as anti-TB agents. Therefore, this research strongly recommends further experimental consideration of the newly designed IPA compounds through synthesis, in-vitro and in-vivo studies to validate the theoretical findings.

Homology modeling and molecular docking simulation of some novel imidazo[1,2-a]pyridine-3-carboxamide (IPA) series as inhibitors of Mycobacterium tuberculosis.

BACKGROUND: Tuberculosis (TB) remains a serious global health challenge that is caused by Mycobacterium tuberculosis and has killed numerous people. This necessitated the urgent need for the hunt and development of more potent drugs against the fast-emerging extensively drug-resistant (XDR) and multiple-drug-resistant (MDR) M. tuberculosis strains. Mycobacterium tuberculosis cytochrome b subunit of the cytochrome bc1 complex (QcrB) was recognized as a potential drug target in M. tuberculosis (25618/H37Rv) for imidazo[1,2-a]pyridine-3-carboxamides whose crystal strucuture is not yet reported in the Protein Data Bank (PDB). The concept of homology modeling as a powerful and useful computational method can be applied, since the M. tuberculosis QcrB protein sequence data are available. RESULTS: The homology model of QcrB protein in M. tuberculosis was built from the X-ray structure of QcrB in M. smegmatis as a template using the Swiss-Model online workspace. The modeled protein was assessed, validated, and prepared for the molecular docking simulation of 35 ligands of N-(2-phenoxy)ethyl imidazo[1,2-a] pyridine-3-carboxamide (IPA) to analyze their theoretical binding affinities and modes. The docking results showed that the binding affinity values ranged from - 6.5 to - 10.1 kcal/mol which confirms their resilience potency when compared with 6.0kcal/mol of isoniazid standard drug. However, ligands 2, 7, 22, 26, and 35 scored higher binding affinity values of - 9.60, - 9.80, - 10.10, - 10.00, and - 10.00 kcal/mol, and are respectively considered as the best ligands among others with better binding modes in the active site of the modeled QcrB protein. CONCLUSION: The information derived in this research revealed some potential hits and paved a route for structure-based drug discovery of new hypothetical imidazo pyridine amide analogs as anti-tubercular drug candidates.

Quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents.

Mycobacterium tuberculosis has instigated a serious challenge toward the effective treatment of tuberculosis. The reoccurrence of the resistant strains of the disease to accessible drugs/medications has mandate for the development of more effective anti-tubercular agents with efficient activities. Time expended and costs in discovering and synthesizing new hypothetical drugs with improved biological activity have been a major challenge toward the treatment of multi-drug resistance strain M. tuberculosis (TB). Meanwhile, to solve the problem stated, a new approach i.e. QSAR which establish connection between novel drugs with a better biological against M. tuberculosis is adopted. The anti-tubercular model established in this study to forecast the biological activities of some anti-tubercular compounds selected and to design new hypothetical drugs is subjective to the molecular descriptors; AATS7s, VE2_Dzi, SpMin7-Bhe and RDF110i. The significant of the model were observed with R2 of 0.8738, R2 adj of 0.8351 Q_cvˆ2 of 0.7127 which served as criteria to substantiate the QSAR model. More also, the model significant with the QSAR external validation criterial ''(R2test) of 0.7532. Ligand-receptor interactions between quinoline derivatives and the receptor (DNA gyrase) was carried out using molecular docking technique by employing the PyRx virtual screening software and discovery studio visualizer software. Furthermore, docking study indicates that compounds 10 of the derivatives with promising biological activity have the utmost binding energy of -18.8 kcal/mol. Meanwhile, the interaction of the standard drug; isoniazid with the target enzyme was observed with the binding energy -14.6 kcal/mol which was significantly lesser than the binding energy of the ligand (compound 10). This implies that ligand 10 could be used as a structural template to design better hypothetical anti-tubercular drugs with more efficient activities. The presumption of this research aid the medicinal chemists and pharmacist to design and synthesis a novel drug candidate against the tuberculosis. Moreover, in-vitro and in-vivo test could be carried out to validate the computational results.