Exploring the potential of 2-arylbenzimidazole scaffolds as novel α-amylase inhibitors: QSAR, molecular docking, simulation and pharmacokinetic studies

Previous studies have shown that 2-arylbenzimidazole derivatives have a strong anti-diabetic effect. To further explore this potential, we develop new analogues of the compound using ligand-based drug design and tested their inhibitory and binding properties through QSAR analyses, molecular docking, dynamic simulations and pharmacokinetic studies. By using quantitative structure activity relationship and ligand-based modification, a highly precise predictive model and design of potent compounds was developed from the derivatives of 2-arylbenzimidazoles. Molecular docking and simulation studies were then conducted to identify the optimal binding poses and pharmacokinetic profiles of the newly generated therapeutic drugs. DFT was employed to optimize the chemical structures of 2-arylbenzimidazole derivatives using B3LYP/6-31G* as the basis set. The model with the highest R2trng set, R2adj, Q2cv, and R2test sets (0.926, 0.912, 0.903, and 0.709 respectively) was chosen to predict the inhibitory activities of the derivatives. Five analogues designed using ligand-based strategy had higher activity than the hit molecule. Additionally, the designed molecules had more favorable MolDock scores than the hit molecule and acarbose and simulation studies confirm on their stability and binding affinities towards the protein. The ADME and druglikeness properties of the analogues indicated that they are safe to consume orally and have a high potential for total clearance. The results of this study showed that the suggested analogues could act as α-amylase inhibitors, which could be used as a basis for the creation of new drugs to treat type 2 diabetes mellitus.

Vanadocene-functionalized mesoporous silica nanoparticles: platforms for the development of theranostic materials against breast cancer

Nanoscale materials have demonstrated a very high potential in anticancer therapy by properly adjusting their functionalization and physicochemical properties. Herein, we report the synthesis of some novel vanadocene-loaded silica-based nanomaterials incorporating four different S-containing amino acids (penicillamine, methionine, captopril, and cysteine) and different fluorophores (rhodamine B, coumarin 343 or Alexa Fluor™ 647), which have been characterized by diverse solid-state spectroscopic techniques viz; FTIR, diffuse reflectance spectroscopies,13C and51V solid-state NMR spectroscopy, thermogravimetry and TEM. The analysis of the biological activity of the novel vanadocene-based nanostructured silicas showed that the materials containing cysteine and captopril aminoacids demonstrated high cytotoxicity and selectivity against triple negative breast cancer cells, making them very promising antineoplastic drug candidates. According to the biological results it seems that vanadium activity is connected to its incorporation through the amino acid, resulting in synergy that increases the cytotoxic activity against cancer cells of the studied materials presumably by increasing cell internalization. The results presented herein hold significant potential for future developments in mesoporous silica-supported metallodrugs, which exhibit strong cytotoxicity while maintaining low metal loading. They also show potential for theranostic applications highlighted by the analysis of the optical properties of the studied systems after incorporating rhodamine B, coumarin 343 (possible)in vitroanticancer analysis, or Alexa Fluor™ 647 (in vivostudies of cancer models).

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.

Chemo-informatics applications in the design of novel 7-keto-sempervirol derivatives as SmCB1 inhibitors with potential for treatment of Schistosomiasis

The quest for a sound treatment on the vulnerable population suffering and dying as a result of the blood flukes, S. mansoni is on the increase because both Praziquantel and Oxamniquine widely used for the treatment of Schistosomiasis for over 51 years suffer resistance and recurrence. Here-in, chemo-informatics techniques such as QSAR modeling, pharmacokinetic, docking alongside MD simulation were harnessed in designing novel 7-keto- sempevirolsempevirol derivatives that are more competent against S. mansoni. Upon QSAR screening, compound 15, which appears to be in the model's acceptability space, emerges the best with a high predicted activity. 5 new analogues with improved activity against Schistosomiasis better than the standard drug PZQ were designed from compound 15 (template 15*) on an account of the descriptors significance from the model with robust and validated parameters. Also their pharmacokinetic profiles indicates that the designed compounds have the characteristics of a good drug. Furthermore, docking evaluation fulfilled ranges from -113.121 to -100.79 kcal/mol (moldock score), with compound U1 being the best (least moldock score of -113.121 compared to PZQ and 15* (template) having a moldock score value of (-87.21 and -83.37 kcal/mol). 100-ns MD Simulation on the U1-docked complex was run using Desmond 2019-4 package. The nature and steadiness of U1 compound within the enzyme active site was further confirmed by RMSD, RMSF, RoG and H-bond assessment. Hence, we recommend compound U1 targeting the SmCB1 enzyme (6YI7) for Schistosomiasis treatment and for further medicinal evaluation and utilization.

Molecular docking-based virtual screening, drug-likeness, and pharmacokinetic profiling of some anti-Salmonella typhimurium cephalosporin derivatives

Objective

The rising cases of resistance to existing antibiotic therapies in Salmonella typhimurium has made it necessary to search for novel drug candidates. The present study employed the molecular docking technique to screen a set of antibacterial cephalosporin analogues against penicillin-binding protein 1a (PBP1a) of the bacterium. This is the first study to screen cephalosporin analogues against PBP1a, a protein central to peptidoglycan synthesis in S. typhimurium.

Methods

Some cephalosporin analogues were retrieved from a drug repository. The structures of the molecules were optimized using the semi-empirical method of Spartan 14 software and were subsequently docked against the active sites of PBP1a using AutoDock vina software. The most potent ligands were chosen as the most promising leads and subsequently subjected to absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling using the SwissADME online server and DataWarrior chemoinformatics program. The CABSflex 2.0 server was used to carry out molecular dynamics (MD) simulation on the most stable ligand-protein complex.

Results

Compounds 3, 23, and 28 with binding affinity (ΔG) values of -9.2, -8.7, and -8.9 kcal/mol, respectively, were selected as the most promising leads. The ligands bound to the active sites of PBP1a via hydrophobic bonds, hydrogen bonds, and electrostatic interactions. Furthermore, ADMET analyses of the ligands revealed that they exhibited sound pharmacokinetic and toxicity profiles. In addition, an MD study revealed that the most active ligand bound favorably and dynamically to the target protein.

Conclusion

The findings of this research could provide an excellent platform for the discovery and rational design of novel antibiotics against S. typhimurium. Additional in vitro and in vivo studies should be carried out on the drug candidates to validate the findings of this study.

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.

Cheminformatics-based discovery of new organoselenium compounds with potential for the treatment of cutaneous and visceral leishmaniasis

Leishmaniasis affects more than 12 million humans globally and a further 1 billion people are at risk in leishmaniasis endemic areas. The lack of a vaccine for leishmaniasis coupled with the limitations of existing anti-leishmanial therapies prompted this study. Cheminformatic techniques are widely used in screening large libraries of compounds, studying protein-ligand interactions, analysing pharmacokinetic properties, and designing new drug molecules with great speed, accuracy, and precision. This study was undertaken to evaluate the anti-leishmanial potential of some organoselenium compounds by quantitative structure-activity relationship (QSAR) modeling, molecular docking, pharmacokinetic analysis, and molecular dynamic (MD) simulation. The built QSAR model was validated (R2train = 0.8646, R2test = 0.8864, Q2 = 0.5773) and the predicted inhibitory activity (pIC50) values of the newly designed compounds were higher than that of the template (Compound 6). The new analogues (6a, 6b, and 6c) showed good binding interactions with the target protein (Pyridoxal kinase, PdxK) while also presenting excellent drug-likeness and pharmacokinetic profiles. The results of density functional theory, MD simulation, and molecular mechanics generalized Born surface area (MM/GBSA) analyses suggest the favourability and stability of protein-ligand interactions of the new analogues with PdxK, comparing favourably well with the reference drug (Pentamidine). Conclusively, the newly designed compounds could be synthesized and tested experimentally as potential anti-leishmanial drug molecules.Communicated by Ramaswamy H. Sarma.

Pharmacokinetic profiling of quinazoline-4(3H)-one analogs as EGFR inhibitors: 3D-QSAR modeling, molecular docking studies and the design of therapeutic agents

Objectives

Breast tumor is ranked as the most common tumor type identified among women globally with over 1.7 million cases annually, representing 11.9% of the total number of cancer cases. Approved anti-breast tumor drugs exhibit several side effects and some patients develop resistance during the early treatment stage. This study aimed to use an in-silico approach to identify and design potential therapeutic agents.

Methods

Robust 3D-QSAR models were developed using quinazoline-4(3H)-one analogs as EGFR inhibitors. The best model was then selected based on statistical parameters and was subsequently used to design more potent therapeutic agents. Molecular docking simulation was executed using the data set and the designed compounds to identify lead compounds which were further screened by pharmacokinetic profiling by applying SwissADME and pkCSM software.

Results

Internal validations of the best CoMFA and CoMSIA models (R² = 0.855 and 0.895; Q² = 0.570 and 0.599) passed the threshold values for the establishment of a consistent QSAR model. The constructed models were further validated externally using six compounds as a test set, thus revealing a satisfactory predicted correlation coefficient (R² _pred = 0.657 and 0.681). The CoMSIA_SHE models with the best statistical parameters were further subjected to applicability domain checks and only three influentials were detected. These were then utilized to design five novel compounds with activities ranging from 5.62 to 6.03. Molecular docking studies confirmed that compounds 20 to 26, with docking scores ranging from -163.729 to -169.796, represented lead compounds with higher docking scores compared to Gefitinib (-127.495). Furthermore, the designed compounds exhibited better docking scores ranging from -171.379 to -179.138.

Conclusions

Pharmacological studies identified compounds 20, 24 26 and the designed compounds 2, 3, 5 as feasible drug candidates. However, these theoretical findings should now be validated experimentally.

Combining docking, molecular dynamics simulations, AD-MET pharmacokinetics properties, and MMGBSA calculations to create specialized protocols for running effective virtual screening campaigns on the autoimmune disorder and SARS-CoV-2 main protease

The development of novel medicines to treat autoimmune diseases and SARS-CoV-2 main protease (Mpro), a virus that can cause both acute and chronic illnesses, is an ongoing necessity for the global community. The primary objective of this research is to use CoMFA methods to evaluate the quantitative structure-activity relationship (QSAR) of a select group of chemicals concerning autoimmune illnesses. By performing a molecular docking analysis, we may verify previously observed tendencies and gain insight into how receptors and ligands interact. The results of the 3D QSAR models are quite satisfactory and give significant statistical results: Q_loo∧2 = 0.5548, Q_lto∧2 = 0.5278, R∧2 = 0.9990, F-test = 3,101.141, SDEC = 0.017 for the CoMFA FFDSEL, and Q_loo∧2 = 0.7033, Q_lto∧2 = 0.6827, Q_lmo∧2 = 0.6305, R∧2 = 0.9984, F-test = 1994.0374, SDEC = 0.0216 for CoMFA UVEPLS. The success of these two models in exceeding the external validation criteria used and adhering to the Tropsha and Glorbaikh criteria's upper and lower bounds can be noted. We report the docking simulation of the compounds as an inhibitor of the SARS-CoV-2 Mpro and an autoimmune disorder in this context. For a few chosen autoimmune disorder receptors (protein tyrosine phosphatase, nonreceptor type 22 (lymphoid) isoform 1 (PTPN22), type 1 diabetes, rheumatoid arthritis, and SARS-CoV-2 Mpro, the optimal binding characteristics of the compounds were described. According to their potential for effectiveness, the studied compounds were ranked, and those that demonstrated higher molecular docking scores than the reference drugs were suggested as potential new drug candidates for the treatment of autoimmune disease and SARS-CoV-2 Mpro. Additionally, the results of analyses of drug similarity, ADME (Absorption, Distribution, Metabolism, and Excretion), and toxicity were used to screen the best-docked compounds in which compound 4 scaled through. Finally, molecular dynamics (MD) simulation was used to verify compound 4's stability in the complex with the chosen autoimmune diseases and SARS-CoV-2 Mpro protein. This compound showed a steady trajectory and molecular characteristics with a predictable pattern of interactions. These findings suggest that compound 4 may hold potential as a therapy for autoimmune diseases and SARS-CoV-2 Mpro.

Ligand-based drug design of quinazolin-4(3H)-ones as breast cancer inhibitors using QSAR modeling, molecular docking, and pharmacological profiling

BACKGROUND

Breast cancer is the most common tumor among females globally. Its prevalence is growing around the world, and it is alleged to be the leading cause of cancer death. Approved anti-breast cancer drugs display several side effects and resistance during the early treatment stage. Hence, there is a need for the development of more effective and safer drugs. This research was aimed at designing more potent quinazolin-4(3H)-one molecules as breast cancer inhibitors using a ligand-based design approach, studying their modes of interaction with the target enzyme using molecular docking simulation, and predicting their pharmacological properties.

METHODS

The QSAR model was developed using a series of quinazoline-4(3H)-one derivatives by utilizing Material Studio v8.0 software and validated both internally and externally. Applicability domain virtual screening was utilized in selecting the template molecule, which was structurally modified to design more potent molecules. The inhibitive capacities of the design molecules were predicted using the developed model. Furthermore, molecular docking was performed with the EGFR target active site residues, which were obtained from the protein data bank online server (PDB ID: 2ITO) using Molegro Virtual Docker (MVD) software. SwissADME and pkCSM online sites were utilized in predicting the pharmacological properties of the designed molecules.

RESULTS

Four QSAR models were generated, and the first model was selected due to its excellent internal and external statistical parameters as follows: R2 = 0.919, R2adj = 0.898, Q2cv = 0.819, and R2pred = 0.7907. The robustness of the model was also confirmed by the result of the Y-scrambling test performed with cR2p = 0.7049. The selected model was employed to design seven molecules, with compound 4 (pIC50 = 5.18) adopted as the template. All the designed compounds exhibit better activities ranging from pIC50 = 5.43 to 5.91 compared to the template and Doruxybucin (pIC50 = 5.35). The results of molecular docking revealed better binding with the EGFR target compared with the template and Doruxybucin. The designed compounds exhibit encouraging therapeutic applicability, as evidenced by the findings of pharmacological property prediction.

CONCLUSIONS

The designed derivatives could be utilized as novel anti-breast cancer agents.

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.

Development of binary classification models for grouping hydroxylated polychlorinated biphenyls into active and inactive thyroid hormone receptor agonists

Some adverse effects of hydroxylated polychlorinated biphenyls (OH-PCBs) in humans are presumed to be initiated via thyroid hormone receptor (TR) binding. Due to the trial-and-error approach adopted for OH-PCB selection in previous studies, experiments designed to test the TR binding hypothesis mostly utilized inactive OH-PCBs, leading to considerable waste of time, effort and other material resources. In this paper, linear discriminant analysis (LDA) and binary logistic regression (LR) were used to develop classification models to group OH-PCBs into active and inactive TR agonists using radial distribution function (RDF) descriptors as predictor variables. The classifications made by both LDA and LR models on the training set compounds resulted in an accuracy of 84.3%, sensitivity of 72.2% and specificity of 90.9%. The areas under the ROC curves, constructed with the training set data, were found to be 0.872 and 0.880 for LDA and LR models, respectively. External validation of the models revealed that 76.5% of the test set compounds were correctly classified by both LDA and LR models. These findings suggest that the two models reported in this paper are good and reliable for classifying OH-PCB congeners into active and inactive TR agonists.

Molecular docking simulation, drug-likeness assessment, and pharmacokinetic study of some cephalosporin analogues against a penicillin-binding protein of Salmonella typhimurium

In pursuit of novel antibiotics that could curb the growing trend of multidrug resistance by Salmonella typhimurium, a data set of some cephalosporin analogues were subjected to Molecular Docking based virtual screening against a penicillin-binding protein (PBP 1b) of the bacterium to ascertain the binding affinity values of the bioactive ligands against the active sites of the PBP 1b protein target using the AutoDock Vina Software. Three compounds with binding affinity values ranging from -7.8 kcal/mol to -8.2 kcal/mol were selected as the most promising leads. The selected compounds also displayed better potencies against the bacterium when compared with Cefuroxime (binding affinity = -6.4 kcal/mol), a standard β-lactam antibiotic used herein for quality control and assurance. Furthermore, evaluation of the drug-likeness and ADMET properties of the three most promising leads revealed that they possess good oral bioavailability and excellent pharmacokinetic profiles. It is hoped that the findings of this study will provide an excellent template for developing more potent β-lactam antibiotics against Salmonella typhimurium.

Computational design, molecular properties, ADME, and toxicological analysis of substituted 2,6-diarylidene cyclohexanone analogs as potent pyridoxal kinase inhibitors

Leishmaniasis is one of the tropical diseases which affects over 12 million people mainly in the tropical regions of the world and is caused by the leishmanial parasites transmitted by the female sand fly. The lack of vaccines to prevent leishmaniasis, as well as limitations of existing therapies necessitated this study which was focused on a combined virtual docking screening and 3-D QSAR modeling approach to design some diarylidene cyclohexanone analogs, while also performing pharmacokinetic analysis and Molecular Dynamic (MD) simulation to ascertain their drug-ability. As a result, the built 3-D QSAR model was found to satisfy the requirement of a good model with R2 = 0.9777, SDEC = 0.0593, F-test = 105.028, and Q2 LOO = 0.6592. The template (compound 9, MolDock score =  - 161.064) and all seven newly designed analogs were found to possess higher docking scores than the reference drug (Pentamidine, Moldock score = - 137.827). The results of the pharmacokinetic analysis suggest 9 and the new molecules (9a, b, c, e, and f) as orally bioavailable with good ADME and safe toxicological profiles. These molecules also showed good binding interactions with the receptor (pyridoxal kinase). Additionally, the MD simulation result confirmed the stability of the tested protein-ligand complexes, with an estimated ∆G binding (MM/GBSA) of - 65.2177 kcal/mol and - 58.433 kcal/mol for 9_6K91 and 9a_6K91 respectively. Hence, the new compounds, especially 9a could be considered potential anti-leishmanial inhibitors.

Virtual screening of novel pyridine derivatives as effective inhibitors of DNA gyrase (GyrA) of salmonella typhi

In a bid to discovering novel antibiotics to combat growing trend of multi-drug resistance strains of Salmonella typhi, 48 new pyridine derivatives with significant inhibitory activities against the aforementioned bacterium were subjected to molecular docking against DNA gyrase protease of the bacterium, drug likeness evaluation and pharmacokinetics profiling. All the 48 leads displayed better binding affinity values when compared with Amoxicillin, Ciprofloxacin, Ceftriaxone, Ampicillin, and chloramphenicol, the standard antibiotics used herein for quality assurance. Furthermore, the majority of the compounds were, however, screened out due to their poor pharmacokinetics profiles and drug-likeness. Only five compounds emerged as the most promising leads and they include C4 with binding affinity of -8.0 kcal/mol, C8 (-8.6 kcal/mol), C9 (-8.1 kcal/mol), C26 (-8.3 kcal/mol), and C27 (-8.0 kcal/mol). These compounds not only displayed better binding affinity when compared with the reference antibiotics but also exhibit different modes of interactions with the target protease of the bacterium making them more potent and drug like. Toxicity evaluation of the leads also revealed that the compounds are neither tumorigenic nor mutagenic. In view of the excellent binding affinity, high pharmacokinetics profile and positive drug-likeness of the novel ligands, we recommend these promising compounds for in vitro and in vivo studies in order to discover novel antibiotics that could curb the dangerous trend of multiple drug resistance by Salmonella typhi.

Molecular Docking, Drug-Likeness and SwissADME Evaluations of the Interactions of 2’-Substituted Triclosan Derivatives with Plasmodium falciparum Enoyl-Acyl Carrier Protein Reductase

The orthodox process of investigating lead molecules is a lengthy and laborious one that in most cases leads to minimal success. Molecular docking analysis provides an alternative path to drug discovery through the interactions of two or more complexes. Molecular docking studies were performed on 12 theoretically designed derivatives of 2’-substituted triclosan against a Plasmodium falciparum (P. falciparum) enoyl-acyl carrier protein reductase (PfENR) protein target as well as predicting their drug-likeness and SwissADME properties. The docking studies were carried out using the Molegro Virtual Docker (MVD) where the molecular interactions between the ligands and the target protein were studied. The docking analysis revealed 5-(((5-chloro-2-(4-chloro-2-hydroxyphenoxy)benzyl)amino)methyl) benzofuran-6-ol (re-rank docking score = -145.497 kcal/mol) as the most stable derivative. The compounds were all found to completely concord with the Lipinski rule regulations, in addition to the molar refractivity as well as the number of rotatable bonds appearing within acceptable limits. All compounds except 2–5 and 7 show high gastrointestinal absorption, and are non-inhibitors of cytochrome P450; CYP1A2 and CYP2C19 except CYP2C9, lack BBB penetration, and only compounds 2–7 and 12 were found to inhibit permeabilityglycoprotein (P-gp) substrate. The findings suggest that some of the derivatives tend to increase the oral bioavailability of the substrate and most of them cannot be used in the treatment of cerebral malaria. These results may lead to future optimisation of the designed derivatives for improved antimalarial agents.

Molecular docking-based virtual screening, molecular dynamic simulation, and 3-D QSAR modeling of some pyrazolopyrimidine analogs as potent anti-filarial agents

Lymphatic filariasis and onchocerciasis are common filarial diseases caused by filarial worms, which co-habit symbiotically with the Wolbachia organism. One good treatment method seeks Wolbachia as a drug target. Here, a computer-aided molecular docking screening and 3-D QSAR modeling were conducted on a series of Fifty-two (52) pyrazolopyrimidine derivatives against four Wolbachia receptors, including a pharmacokinetics study and Molecular Dynamic (MD) investigation, to find a more potent anti-filarial drug. The DFT approach (B3LYP with 6-31G** option) was used for the structural optimization. Five ligand-protein interaction pairs with the highest binding affinities were identified in the order; 23_7ESX (-10.2 kcal/mol) > 14_6EEZ (- 9.0) > 29_3F4R (- 8.0) > 26_6W9O (- 7.7) ≈ doxycycline_7ESX (- 7.7), with good pharmacological interaction profiles. The built 3-D QSAR model satisfied the requirement of a good model with R2 = 0.9425, Q2 LOO = 0.5019, SDEC = 0.1446, and F test = 98.282. The selected molecules (14, 23, 26, and 29) perfectly obeyed Lipinski's RO5 for oral bio-availability, and showed excellent ADMET properties, except 14 with positive AMES toxicity. The result of the MD simulation showed the great stability associated with the binding of 23 onto 7ESX's binding pocket with an estimated binding free energy (MM/GBSA) of - 60.6552 kcal/mol. Therefore, 23 could be recommended as a potential anti-filarial drug molecule, and/or template for the design of more prominent inhibitors.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-022-00136-y.

Theoretical Investigation of the Cooperation of Iminoguanidine with the Enzymes-Binding Domain of Covid-19 and Bacterial Lysozyme Inhibitors and their Pharmacokinetic Properties

Abstract. The investigation for innovative treatments for Pseudomonas aeruginosa and SARS-CoV-2 is a burgeoning field. Even though scientists and pharmaceutical companies have made significant contributions to the research of multi-drug resistance infections from a variety of perspectives, these diseases remain incurable. As a result, developing novel and more effective drugs for proteins associated with Pseudomonas aeruginosa and SARS-CoV-2 has become a top priority in recent years. In this regard, the protein is known as a putative inhibitor of vertebrate lysozyme [Pseudomonas aeruginosa] and chain A, spike protein S1 [SARS-CoV-2], and it is one of the key targets for the development of new drug candidates that could be used as inhibitors in both Pseudomonas aeruginosa and SARS-CoV-2 chemotherapies. The structural characteristics and binding mechanism of certain inhibitors of Pseudomonas aeruginosa and SARS-CoV-2 receptor were investigated using Quantitative-Structure Activity Relationship (QSAR), homology modeling, molecular docking, and molecular dynamics simulation in this study. To create a 3D model of the receptors, a homology modeling approach was used. The X-ray crystal structures of chain A inhibitor of vertebrate lysozyme (PDB: 4PS6) and chain A spike protein S1 (PDB: 7MZF), respectively, were employed as templates for this technique. The final projected structure is obtained and examined by the programs ERRAT, VERIFY3D, and PROCHECK, confirming that the final model is credible. The anticipated structure was fine-tuned before being employed in docking simulations. The results of the structure-based virtual screening show that two potent new lead molecules, compounds 7 and 15, have the most noteworthy affinity to the predicted 3D receptors. The docked compound 15 was subjected to a 1 ns molecular dynamics (MD) simulation. Compound 15 produced more hydrophobic and van der Waal's contacts, according to MD simulations, and binds to SARS-CoV-2 spike protein S1 more closely. The Lipinski rule of five assessment revealed that these lead compounds had significant pharmacological characteristics. As a result, the current research will aid in the development and synthesis of another class of chain A inhibitors of vertebrate lysozyme and chain A spike protein S1 inhibitors that restore drug compound susceptibilities.   Resumen. La investigación de tratamientos innovadores para Pseudomonas aeruginosa y SARS-CoV-2 es un campo floreciente. A pesar de que los científicos y las compañías farmacéuticas han hecho contribuciones significativas a la investigación de infecciones por resistencia a múltiples medicamentos desde una variedad de perspectivas, estas enfermedades siguen siendo incurables. Como resultado, el desarrollo de fármacos novedosos y más eficaces para las proteínas asociadas con Pseudomonas aeruginosa y SARS-CoV-2 se ha convertido en una prioridad en los últimos años. En este sentido, la proteína es conocida como un supuesto inhibidor de la lisozima de vertebrados [Pseudomonas aeruginosa] y de la cadena A, proteína espiga S1 [SARS-CoV-2], y es uno de los objetivos clave para el desarrollo de nuevos fármacos candidatos que podrían utilizarse como inhibidores tanto en pseudomonas aeruginosa como en quimioterapias de SARS-CoV-2. Las características estructurales y el mecanismo de unión de ciertos inhibidores de Pseudomonas aeruginosa y el receptor SARS-CoV-2 se investigaron utilizando la Relaciones Cuantitativas de Estructura-Actividad - (QSAR, por sus siglas en inglés), el modelado por homología, el acoplamiento molecular y la simulación de dinámica molecular. Para crear un modelo 3D de los receptores, se utilizó un enfoque de modelado por homología. Las estructuras cristalinas de rayos X del inhibidor de la cadena A de la lisozima de vertebrados (PDB: 4PS6) y la proteína de espiga de cadena A S1 (PDB: 7MZF), respectivamente, se emplearon como plantillas para esta técnica. La estructura final proyectada se obtuvo y examinó con los programas ERRAT, VERIFY3D y PROCHECK, confirmando que el modelo final es creíble. La estructura anticipada se afinó antes de ser empleada en simulaciones de acoplamiento. Los resultados del cribado virtual basado en la estructura generaron dos nuevas y potentes moléculas líderes, los compuestos 7 y 15, que tienen la afinidad más notable con los receptores 3D predichos. El compuesto acoplado 15 fue sometido a una simulación de dinámica molecular (DM) de 1 ns. El compuesto 15 produjo más contactos hidrófobos y de van der Waals, según las simulaciones de MD, y se une más de cerca a la proteína espiga S1 del SARS-CoV-2. La evaluación de la regla de cinco de Lipinski reveló que estos compuestos líderes tenían características farmacológicas significativas. Como resultado, la investigación actual ayudará en el desarrollo y la síntesis de otra clase de inhibidores de la cadena A de la lisozima de vertebrados y los inhibidores de la proteína de espiga de cadena A S1 que restauran las susceptibilidades de los compuestos farmacológicos.

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 ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.9192, Q2 = 0.8767, R2adj = 0.8991, RMSE = 0.0959, $$R_{{{\text{test}}}}^{2}$$ R test 2  = 0.8943, $$R_{{{\text{pred}}}}^{2}$$ R pred 2  = 0.7745) and GFA-ANN ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.9227, Q2 = 0.9212, RMSE = 0.0940, $$R_{{{\text{test}}}}^{2}$$ R test 2  = 0.8831, $$R_{{{\text{pred}}}}^{2}$$ 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 ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.9620, Q2 = 0.643) and CoMSIA_SED ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.8770, Q2 = 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.

Virtual screening and molecular dynamic simulations of the antimalarial derivatives of 2-anilino 4-amino substituted quinazolines docked against a Pf-DHODH protein target

Background

The processes of drug development and validation are too expensive to be subjected to experimental trial and errors. Hence, the use of the insilico approach becomes imperative. To this effect, the drug-likeness and pharmacokinetic properties of the ten (10) previously designed derivatives of 2-anilino 4-amino substituted quinazolines were carried out. Their predicted ligand binding interactions were also carried out by docking them against the Plasmodium falciparum dihydroorotate dehydrogenase (Pf-DHODH) protein target, and the stability of the complex was determined through dynamic simulations. The drug-likeness and pharmacokinetic characteristics were estimated using the online SwissADME software, while the Molegro Virtual Docker (MVD) software was used for molecular docking. And the dynamic simulation was performed for the duration of 100 ns to verify the stability of the docked complex, with the aid of a Schrödinger program, Desmond.

Results

The designed derivatives were all found to pass the Lipinski test of drug likeness, while the pharmacokinetic studies result that the skin permeability and molar refractivity values of the derivatives are both within the limits. In addition, except for derivative C-01, most of the derivatives have strong gastrointestinal absorptions and lack Pgp substrate. Furthermore, no derivative inhibited CYP1A2, CYP2C9, or CYP2C19. The docking studies show the better binding affinities between the ligands and Pf-DHODH than those between the atovaquone or chloroquine standards. The derivative C-02, {5-((6,7-dimethoxy-4-((3-nitrobenzyl)amino)quinazolin-2-yl)amino)-2-fluorobenzaldehyde} was found to be the most stable derivative, with a re-rank docking score of - 173.528 kcal/mol and interaction energy of - 225.112 kcal/mol. The dynamic simulation analysis shows that the derivative C-02 forms a stable complex with the protein target over the simulation time.

Conclusions

The ability of these ligands to form hydrogen bonds, as well as various other interactions, was cited as a factor responsible for their better binding affinity. These findings could aid further the development of enhanced antimalarial drugs.

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 ​ 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 ​ 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.

QSAR, homology modeling, and docking simulation on SARS-CoV-2 and pseudomonas aeruginosa inhibitors, ADMET, and molecular dynamic simulations to find a possible oral lead candidate

Background

In seek of potent and non-toxic iminoguanidine derivatives formerly assessed as active Pseudomonas aeruginosa inhibitors, a combined mathematical approach of quantitative structure-activity relationship (QSAR), homology modeling, docking simulation, ADMET, and molecular dynamics simulations were executed on iminoguanidine derivatives.

Results

The QSAR method was employed to statistically analyze the structure-activity relationships (SAR) and had conceded good statistical significance for eminent predictive model; (GA-MLR: Q² _LOO = 0.8027; R ² = 0.8735; R ² _ext = 0.7536). Thorough scrutiny of the predictive models disclosed that the Centered Broto-Moreau autocorrelation - lag 1/weighted by I-state and 3D topological distance-based autocorrelation-lag 9/weighted by I-state oversee the biological activity and rendered much useful information to realize the properties required to develop new potent Pseudomonas aeruginosa inhibitors. The next mathematical model work accomplished here emphasizes finding a potential drug that could aid in curing Pseudomonas aeruginosa and SARS-CoV-2 as the drug targets Pseudomonas aeruginosa. This involves homology modeling of RNA polymerase-binding transcription factor DksA and COVID-19 main protease receptors, docking simulations, and pharmacokinetic screening studies of hits compounds against the receptor to identify potential inhibitors that can serve to regulate the modeled enzymes. The modeled protein exhibits the most favorable regions more than 90% with a minimum disallowed region less than 5% and is simulated under a hydrophilic environment. The docking simulations of all the series to the binding pocket of the built protein model were done to demonstrate their binding style and to recognize critical interacting residues inside the binding site. Their binding constancy for the modeled receptors has been assessed through RMSD, RMSF, and SASA analysis from 1-ns molecular dynamics simulations (MDS) run.

Conclusion

Our acknowledged drugs could be a proficient cure for SARS-CoV-2 and Pseudomonas aeruginosa drug discovery, having said that extra testing (in vitro and in vivo) is essential to explain their latent as novel drugs and manner of action.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-022-00362-z.

Theoretical modeling and design of some pyrazolopyrimidine derivatives as Wolbachia inhibitors, targeting lymphatic filariasis and onchocerciasis

Lymphatic filariasis and onchocerciasis are two common filarial diseases caused by a group of parasitic nematodes called filarial worms, which play host to the bacteria organism Wolbachia. One good treatment approach seeks Wolbachia as drug target. Here, a QSAR study was conducted to investigate the anti-wolbachia activities (pEC₅₀) of 52 pyrazolopyrimidine analogues, while using the built model to predict the pEC₅₀ values of the newly designed analogues. Density Functional Theory was used for the structural optimization, while the model building was based on Genetic Function Algorithm approach. The built QSAR model was validated thus: R² = 0.8104, R² _adj = 0.7629, Q² _cv = 0.6981, R² _test = 0.7501 and cRp² = 0.7476. The predicted pEC₅₀ of all newly designed compounds were higher than that of the template (43). The new compounds were; observed to pass the drug-likeness criteria, uniformly distributed to the brain, and found to be non-mutagenic. Also, the new compounds and the reference drug (doxycycline), were docked onto Ovarian Tumor (OTU) deubiquitinase receptor (PDB ID: 6W9O) using iGEMDOCK tool. This protein is known to help Wolbachia subvert host ubiquitin signaling. The resulting binding scores of the newly designed compounds except A5 were higher than that of doxycycline, while the protein-ligand interactions were majorly characterized by Hydrogen-bonding and hydrophobic interaction types. Therefore, the newly designed molecules could be developed as potential drug candidates for the treatment of lymphatic filariasis and onchocerciasis.

Ligand-based drug design and molecular docking simulation studies of some novel anticancer compounds on MALME-3M melanoma cell line

Background

Melanoma cancer causes serious health problem worldwide because of its rapid invasion to other organs and lack of satisfactory chemotherapy. The pGI50 anticancer activity values of 70 compounds from the NCI (National Cancer Institute) on MALME-3M cell line was modeled to describe the quantitative structure-activity relationships (QSARs) of the compounds, and some selected compounds were docked.

Results

The generated QSAR model was found to be statistically significant based on the obtained values of the validation keys such as R2 (0.885), $$ {R}_{\mathrm{adjusted}}^2 $$ R adjusted 2 (0.868), Q2cv (0.842), and $$ {R}_{pred}^2 $$ R pred 2 (0.738) required to evaluate the strength and robustness of QSAR model. Compound 39 was selected as a template due to its good pGI50 (9.205) and was modified to design new potent compounds. The predicted pGI50 activity of the designed compounds by the built model was N1 (9.836), N2 (12.876), N3 (10.901), and N4 (11.263) respectively. These proposed compounds were docked with V600E-BRAF receptor and the result shows that, N1, N2, N3, and N4 with free binding energy (FBE) of − 11.7 kcal mol−1, − 12.8 kcal mol−1, − 12.7 kcal mol−1, and − 12.9 kcal mol−1 respectively were better than the parent structure of the template (compound 39, FBE = − 7.0 kcal mol−1) and the standard V600E-BRAF inhibitor (Vemurafenib, FBE = − 11.3 kcal mol−1). Additionally, these compounds passed the drug-likeness criteria successfully to be orally bioavailable.

Conclusion

The proposed compounds were considered optimal as their performances are comparable to vemurafenib and possessed enhanced physicochemical properties. Thus recommends further research such as synthesis, in vivo, and ex-vivo evaluation.

Computer-aided design of some quinazoline analogues as epidermal growth factor receptor inhibitors

Background

The treatment of epidermal growth factor receptor (EGFR)-muted non-small cell lung cancer (NSCLC) remains among the utmost important unachieved therapeutic need worldwide. Development of EGFR inhibitors to treat NSCLC mutations has been among the difficult tasks faced by researchers in this area. As such, there is a need to discover more EGFR inhibitors. The purpose of this work is to perform computer-aided/structure-based design of novel EGFR inhibitors, elucidate their nature of interactions with their target, and also assess their ADMET properties as well as their drug-likeness, respectively. Compound 17 with a highest binding affinity of −9.5kcal/mol was identified as the template hit compound using molecular docking virtual screening in our previous work. The compound interacted with the active site of the EGFR receptor via hydrogen bond with the following amino acid residues MET793, MET793, THR854, and ASP855 with bond distances of 2.61394 (Å), 2.18464 (Å), 2.57601 (Å), and 2.68794 (Å), respectively. It also interacted with the active site of the EGFR receptor via halogen bond (GLN791), hydrophobic bond (LEU718, CYS797, LYS745, ALA743, ALA743, and VAL726), electrostatic bond (LYS745), and others (MET766), respectively. Furthermore, from our previous study, the following descriptors (ATSC6m, ATSC8e, MATS7m, SpMax3_Bhp, SpMax5_Bhs, and MaxHBint10) contained in the reported model were found to be responsible for the inhibitory activities of the studied compounds. In this research, the template (compound 17) was modified manually by attaching halo-phenyl and halo-phenyl-amino rings on the para position of the flouro-nitro-benzamide moiety of the template compound, respectively.

Results

A computer-aided design/structure-based approach was used to design six new EGFR inhibitors using molecule 17 as the template compound for the design identified in our previously reported work. Molecular docking investigation was performed to elucidate the binding mode of these newly designed EGFR inhibitors with the binding pose of EGFR receptor (pdb code 4ZAU) and found to have better affinities which range from −9.5 to −10.4 kcal/mol than the template compound and gefitinib, the control, respectively. The ADMET property assessment of these newly designed EGFR inhibitors indicated that they were orally bioavailable with good absorption, distribution, metabolism, and excretory properties with no toxicity. And for their drug-likeness, they were seen to have a higher molecular weight which might be as a result of halo-phenyl-amino ring attachments. Based on this finding, halo-phenyl-amino rings might be responsible for the inhibitory activities of these newly designed compounds.

Conclusion

The six newly designed EGFR inhibitors were found to have higher binding affinities toward their target EGFR receptor than the template compound and gefitinib which was used as the control in this research. They were seen to have good ADMET and drug-like properties which indicate that they might be orally bioavailable. Furthermore, according to their synthetic accessibility score, they can be easily synthesized in the laboratory because the values were found to be less than five which fall within the easy portion of the scale. Therefore, this research recommends that these newly designed EGFR inhibitors should be synthesized most especially those with higher binding affinities, good ADMET, and drug-likeness properties than the template compound.

Virtual screening, pharmacokinetics, and molecular dynamics simulations studies to identify potent approved drugs for Chlamydia trachomatis treatment

Background

The most frequent bacterial sexually transmitted disease is Chlamydia trachomatis (STD). In 2010, the Centers for Disease Control and Prevention (CDC) received 1.3 million reports of cases (CDC). Human chlamydial infections are linked to a variety of clinical symptoms. Inclusion (IncA) membranes are a promising drug target for the treatment of Chlamydia trachomatis. In the present study, molecular docking, ADMET, golden triangle, and molecular dynamics (MD) simulation studies were performed on a series of salicylidene acylhydrazides derivatives against Chlamydia trachomatis. Three types of docking software with different algorithms were used to screen the potential candidate against Chlamydia trachomatis.

Results

The results obtained from the docking analysis succeeded in screening nine novel hit compounds with high affinity to IncA membranes. Then, pharmacokinetics properties were calculated to spot out the drug-likeness of the selected compounds. Also, golden triangles were performed on the selected compounds. Compounds outside the golden triangle indicate that they would have clearance problems. Out of the nine novel hits drugs, four compounds pass the golden triangle screening and virtually all the quality assurance tests proposed by the model and were used for further analysis. One-ns molecular dynamics simulations on the docked complex of compound 44 (one of the highly active selected compounds of the dataset) aided in the further exploration of the binding interactions. Some crucial residues such as Ser111, Gln114, Asn107, Leu142, Gly144, Gln143, Lys104, Tyr149, Phe108, Phe145, and Arg146 were identified. Conventional and carbon–hydrogen bond interactions with amino residues Arg146, Asn107, Phe145, and Ser111 were critical for the binding of inclusion (IncA) membranes inhibitors.

Conclusion

Outcomes of the study can further be exploited to develop potent inclusion (IncA) membranes inhibitors.

Computer-aided molecular design of 2-anilino 4-amino substituted quinazolines derivatives as malarial inhibitors

Quantitative structure–activity relationship studies conducted on forty-five (45) derivatives of 2-anilino 4-amino substituted quinazolines as malaria inhibitors to determine the structures responsible for their antimalarial properties and design novel derivatives with improved activities. The molecular descriptors generated were selected to develop the theoretical model using the genetic approximation component of the material studio. The developed model found to be a function of ATSC8c, GATS8i, SpMin1_Bhi, JGI10, and TDB6u descriptors, shows excellent statistical parameters (R2 = 0.7913, R2adj = 0.7553, Q2cv = 0.7112, LOF = 0.2125, and R2pred = 0.7650). The mean effect (MF) analysis revealed the descriptor SpMin1_Bhi, as the most influential by its largest percentage contribution (54%) to the developed model. The descriptor decodes the information on the first ionization potentials and was found to have positive MF. Hence, activity increases with increases the descriptor value. Structural modifications of the template (compound 13; pEC50 = 7.387) using electron-withdrawing groups increases the descriptor value (first ionization potentials) of the template, which by extension increases the antimalarial activity lead to the design of ten (10) novel theoretical derivatives with improve antimalarial activities. Compound 3, N4-(3-bromo-5-fluorobenzyl)-N2-(4-fluorophenyl)-6,7-dimethoxyquinazoline-2,4-diamine was found to have the highest antimalarial activities among all the designed derivatives (pEC50 = 8.0515).

Design of more potent quinazoline derivatives as EGFRWT inhibitors for the treatment of NSCLC: a computational approach

Background

Lung cancer remains the leading and deadly type of cancer worldwide. It was estimated to account for about 25% of the 7 million people that died as a result of cancer-related issues/mortality every year in the world. Non-small cell lung cancer (NSCLC) is the lethal/deadly class of lung cancer with nearly 1.5 million reported cases and less than 20% survival rate. Therefore, it becomes necessary to explore more effective NSCLC drugs.

Result

A computational approach was employed here to design ten new EGFRWT inhibitors using compound 18 as a template for the design identified with the best binding affinity and good pharmacokinetic properties previously reported in our work. The modeled inhibitory activities of these newly designed EGFRWT inhibitors (range from 7.746966 to 11.09261) were better than that of the hit compound with pIC50 of 7.5639 and gefitinib the positive control with pIC50 of 5.879426. The ligand-binding interaction between these newly designed EGFRWT inhibitors and the EGFR tyrosine kinase receptor as shown in Table 3 was investigated and elucidated using molecular docking protocol. Based on the molecular docking results, the binding affinities of these newly designed EGFRWT inhibitors were found to be between − 8.8 and − 9.5 kcal/mol. The designed compound SFD10 has the highest binding affinity of − 9.5 kcal/mol followed by compound SFD8 (with a binding affinity of − 9.3 kcal/mol), then by compound SFD9 and 4 (each with a binding affinity of − 9.3 kcal/mol). None of them was found to have more than one violation of the filtering criterion used in this study thereby showing good ADMET properties.

Conclusion

The modeled inhibitory activities and binding affinities of these newly designed EGFRWT inhibitors were found to be higher than that of the template compound and the control (gefitinib) used in this research. They were also seen to be non-toxic with good pharmacokinetic properties.

Pharmacokinetic predictions and docking studies of substituted aryl amine-based triazolopyrimidine designed inhibitors of Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH)

Background

The sixteen (16) designed data set of substituted aryl amine-based triazolopyrimidine were docked against Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) employing Molegro Virtual Docker (MVD) software and their pharmacokinetic property determined through SwissADME predictor.

Results

The docking studies shows compound D16, 5-((6-methoxy-5-methyl-[1,2,4]triazolo[1,5-a]pyrimidin-7-yl)amino)benzo[b]thiophen-4-ol to be the most interactive and stable derivative (re-rank score = − 114.205 kcal/mol) resulting from the hydrophobic as well as hydrogen interactions. The hydrogen interaction produced one hydrogen bond with the active residues LEU359 (H∙∙H∙∙O) at a bond distances of 2.2874 Å. All the designed derivatives were found to pass the Lipinski rule of five tests, supporting the drug-likeliness of the designed compounds.

Conclusion

The ADME analysis revealed a perfect concurrence with the Lipinski Ro5, where the derivatives were found to possess good pharmacokinetic properties such as molar refractivity (MR), number of rotatable bonds (nRotb), log of skin permeability (log Kp), blood-brain barrier (BBB). These results could a deciding factor for the optimization of novel antimalarial compounds.

Binding profile of protein-ligand inhibitor complex and structure based design of new potent compounds via computer-aided virtual screening

Background

Mycobacterium tuberculosis protein target (DNA gyrase) is a type II topoisomerase target present in all bacteria. The enzyme comprises of two subunits A and B. DNA binding domain is located in the subunits A while the catalysis and cleavage of two DNA strands occur in the subunits A using ATP hydrolysis. This enzyme has been reported to emerge in extensively drug resistant tuberculosis. Therefore this research aimed to design new potent compounds against the target and establish the analysis of protein–ligand binding interaction between the target and novel quinoline analogues via the application of in silicovirtual screening to predict the inhibition binding affinities the analogues.

Result

The docking results revealed that compound ID 17 with efficient inhibition activity has a noticeable binding affinity of −18.8 kcal/mol. Hence compound 17 was designated as the reference template to designed novel fourteen compounds with higher binding affinities as a promising compounds.

Conclusion

Designed compound 17i, 17j and 17n with lead binding affinities among the designed compounds were observed with the most perceptible binding affinity which ranges from (−21.2 to −26.8) kcal/mol compared to low binding affinity (-5.8 kcal/mol) computed for ethambutol.

Unveiling novel inhibitors of dopamine transporter via in silico drug design, molecular docking, and bioavailability predictions as potential antischizophrenic agents

Background

The inhibition of dopamine transporter is known to play a significant role in the treatment of schizophrenia-related and other mental disorders. In a continuing from our previous study, computational drug design approach, molecular docking simulation, and pharmacokinetics study were explored for the identification of novel inhibitors dopamine transporter as potential Antischizophrenic agents. Consequently, thirteen (13) new inhibitors of dopamine transporter were designed by selecting the molecule with serial number 39 from our previous study as the template molecule because  it exhibits good pharmacological attributes.

Results

Molecular docking simulation results revealed excellent molecular interactions between the protein target (PDB: 4m48) and the ligands (designed inhibitors) with major interactions that involved hydrogen bonding and hydrophobic interactions. Also, some of the designed inhibitors displayed a superior binding affinity range from − 10.0 to − 10.7 kcal/mol compared to the referenced drug (Lumateperone) with a binding affinity of − 9.7 kcal/mol. Computed physicochemical parameters showed that none of the designed inhibitors including the referenced drug violate Lipinski’s rule of five indicating that all the designed inhibitors would be orally bioavailable as potential drug candidates. Similarly, the ADMET/pharmacokinetics evaluations of some designed inhibitors revealed that they possessed good absorption, distribution, metabolism and excretion properties and none of the inhibitors is neither carcinogens nor toxic toward human ether-a-go-go related gene (hERG I) inhibitor or skin sensitization. Likewise, the BOILED-Egg graphics unveils that all the designed inhibitors demonstrate a high probability to be absorbed by the human gastrointestinal tract and could permeate into the brain. Besides, the predicted bioactive parameters suggested that all the selected inhibitors would be active as drug candidates. Furthermore, the synthetic accessibility scores for all the selected inhibitors and referenced drug lied within the easy zone (i.e., between 1–4) with their computed values range from 2.55 to 3.92, this implies that all the selected inhibitors would be very easy to synthesize in the laboratory.

Conclusions

Hence, all the designed inhibitors having shown excellent pharmacokinetics properties and good bioavailabilities attributes with remarkable biochemical interactions could be developed and optimized as novel Antischizophrenic agents after the conclusion of other experimental investigations.

Molecular modeling and design of some β-amino alcohol grafted 1,4,5-trisubstituted 1,2,3-triazoles derivatives against chloroquine sensitive, 3D7 strain of Plasmodium falciparum

Resistance nature of Plasmodium falciparum (P. falciparum) to the most effective antimalarial drug, Artemisinin, intimidate the global goal of total eradication of malarial. In an attempt to overcome this challenge, the research was aimed at designing derivatives of β-amino alcohol grafted 1,4,5-trisubstituted 1,2,3-triazoles with improve activity against the P. falciparum through structural modifications of the most active compound (design template), and their activity determined using the developed theoretical predictive model. To achieve this, the geometries were optimized via density functional theory (DFT) using B3LYP/6-31G^∗ basis set to generate molecular descriptors for model development. Analysis of the developed model and the descriptors mean effect lead to the design of derivatives with improved activity. Five (5) theoretical models were developed, where the model {pIC₅₀ = 5.95067(SpMin5_Bhi) - 0.0323461(RDF45m) + 0.0203865 (RDF95e) + 0.0499285 (L1m) - 3.50822} with the highest coefficient of determination (R²) of 0.9367, cross-validated R² (Q²cv) of 0.8242, and the external validated R² (R²_pred) of 0.9462, selected as the best model. The mean effect analysis revealed descriptor SpMin5_Bhi as the most contributive. The descriptor encodes the first ionization potentials of the compounds and are influenced by electron-withdrawing/donating substituents. Hence, structural modifications of the compound with the highest activity (a design template) using electron-withdrawing substituents such as –NO₂, –SO₃H, -Br, –I, –CH₂CH₃, and –CH₃ was done at a different positions, to obtain five (5) hypothetical novel compounds. The statistical results, shows the robustness, excellent prediction power, and validity of the selected model. Descriptor analysis revealed the first ionization potential (SpMin5_Bhi) to play a significant role in the activity of β-amino alcohol grafted 1,4,5-trisubstituted 1,2,3-triazoles derivatives. The five design derivatives of β-amino alcohol grafted 1,4,5-trisubstituted 1,2,3-triazoles with higher activities revealed compound 21C to have an antimalarial activity of pIC₅₀ = 6.7573 higher than it co-designed compounds and even the standard drug. This claim could be verified through molecular docking to determine their interaction with the target protein.

Application of QSAR Method in the Design of Enhanced Antimalarial Derivatives of Azetidine-2-carbonitriles, their Molecular Docking, Drug-likeness, and SwissADME Properties

The resistance of the P. falciparum strain to some of the antimalarial drugs has been a dominant dilemma facing the treatment of this fetid disease. This necessitates the detection and development of new antimalarial agents targeting the P. falciparum. Azetidine-2-carbonitriles reported for its antimalarial activities, could provide an alternative to the customized antimalarial drugs. Leading to the use of quantitative structure-activity relationship (QSAR) studies, which relates the structures of Azetidine-2-carbonitriles with their activities to generate predictive models. The structures were optimized using density functional theory (DFT) DFT/B3LYP/6-31G* basis set to generate their molecular descriptors, where five predictive models were constructed using the generated descriptors. The models were constructed using the genetic function algorithm component of a material studio, where the model with good statistical parameters, high coefficient of determination (R2) = 0.9465, cross-validated R2 (Q2cv) = 0.8981, Q2 (L4O)cv = 0.9272, and highest external validated R2 (R2 pred) = 0.6915 was selected as the best model. These statistical results show the robustness, excellent power of prediction, and validity of the selected model. The descriptor, SpMax2_Bhp (the maximum absolute eigenvalue of Barysz matrix for n = 2 was weighted by polarizability), was revealed to be the most influential in the model due to its highest mean effect. The descriptor played a role in the design of sixteen (16) theoretical derivatives of Azetidine-2-carbonitriles using compound 25 as the design template by increasing polarizability of the compounds through substitution of the various group with electron deactivating groups (F, I, Cl, SO3H, CN, NO2, etc.) at different position of the template. The designed compounds were docked with Plasmodium falciparum dihydroorotate dehydrogenase (Pf-DHODH), giving compound D9 the highest binding energy. The designed compounds were further screened for their drug-likeness, where they all pass Lipinski's RO5. All the compounds show good skin permeability coefficient and have low Gastrointestinal absorption while few compounds D1, D2, D3, D14, and D15 inhibiting the CYP1A2.

Quantitative structure-activity relationship, molecular docking, drug-likeness, and pharmacokinetic studies of some non-small cell lung cancer therapeutic agents

Background

Lung cancer has been reported to be among the leading cancer cases in the world. It was also reported to have caused a lot of death every year and accounted for about one-third of the whole cancer deaths in the globe. The main subset of lung cancers that accounts for about 85% of the problems of lung cancer raised above was non-small cell lung cancer (NSCLC). The most common cause of NSCLCs that mostly affects women and cigarette smokers was recognized to be overexpression of epidermal growth factor receptor tyrosine kinase (EGFR TK).

Results

Five models on thirty five (35) NSCLC therapeutic agents were developed via quantitative structure-activity relationship (QSAR) technique. The best model among them was selected and reported due to its fitness statistically with the following validation parameters: R2 of 0.8764, R2adj of 0.8370, Qcv2 of 0.7655, R2test of 0.7024, and LOF of 0.3312. Molecular docking was used to elucidate the mode of binding interactions between the thirty five (35) NSCLC therapeutic agents and the binding pose of EGFR tyrosine kinase receptor (3IKA) in this research. Compound 29 was recognized to have the most excellent binding affinity of − 8.8 kcal/mol among others. The drug-likeness and pharmacokinetic properties of all the NSCLC therapeutic agents were predicted using SWISSADME, and none among the molecules under investigation violated more than the permissible limit of the conditions stated by Lipinski’s RO5 filters. Five hit compounds were identified using molecular docking virtual screening. The five (5) hit compounds were further screened and identified compound 16 and 27 as excellent among them using their pharmacokinetic profiles and drug-likeness properties.

Conclusion

QSAR technique was used to build five models on thirty five (35) NSCLC therapeutic agents. The best model among them was reported because it is statistically significant with good validation parameters. The molecular docking result has identified five (5) hit compounds. The most common amino acid residues to all hit compounds under investigation were Glu762, Leu718, Lys745, and Val726 which might be responsible for the higher inhibitory activities/binding affinities of the compounds under investigation. Furthermore, these five (5) hit compounds were further subjected to drug-likeness and pharmacokinetic properties prediction to determine which among them have the best pharmacokinetic profile. Compounds 16 and 27 among the hit compounds were observed to have high chance of passive absorption by the gastrointestinal tract while the other three have low tendency of passive absorption. More so, only compounds 16 and 27 have higher bioavailability scores, and none of the two have more than one violation of the RO5 criteria. The cause of efficiency of compounds 16 and 27 might be as a result of good pharmacokinetic profiles and drug-likeness properties possessed by the molecules when compared to other hit compounds.

Computational evaluation of potent 2-(1H-imidazol-2-yl) pyridine derivatives as potential V600E-BRAF inhibitors

Background

V600E-BRAF is a major protein target involved in various types of human cancers. However, the acquired resistance of the V600E-BRAF kinase to the vemurafenib and the side effects of other identified drugs initiate the search for efficient inhibitors. In the current paper, virtual docking screening combined with drug likeness and ADMET properties predictions were jointly applied to evaluate potent 2-(1H-imidazol-2-yl) pyridines as V600E-BRAF kinase inhibitors.

Results

Most of the studied compounds showed better docking scores and favorable interactions with theiV600E-BRAF target. Among the screened compounds, the two most potent (14 and 30) with good rerank scores (−124.079 and − 122.290) emerged as the most effective, and potent V600E-BRAF kinase inhibitors which performed better than vemurafenib (−116.174), an approved V600E-BRAF kinase inhibitor. Thus, the docking studies exhibited that these compounds have shown competing inhibition of V600E-BRAF kinase with vemurafenib at the active site and revealed better pharmacological properties based on Lipinski’s and Veber’s drug-likeness rules for oral bioavailability and ADMET properties.

Conclusion

The docking result, drug-likeness rules, and ADMET parameters identified compounds (14 and 30) as the best hits against V600E-BRAF kinase with better pharmacological properties. This suggests that these compounds may be developed as potent V600E-BRAF inhibitors.

Structure-based design of some quinazoline derivatives as epidermal growth factor receptor inhibitors

Background

The discovery of epidermal growth factor receptor (EGFR) inhibitors for the treatment of lung cancer, most especially non-small cell lung cancer (NSCLC), was one of the major challenges encountered by the medicinal chemist in the world. The treatment of EGFR tyrosine kinase to manage NSCLCs becomes an urgent therapeutic necessity. NSCLC was the foremost cause of cancer mortality worldwide. Therefore, there is a need to develop more EGFR inhibitors due to the development of drug resistance by the mutation. This research is aimed at designing new EGFR inhibitors using a structure-based design approach. Structure-based drug design comprises several steps such as protein structure retrieval and preparation, ligand library preparation, docking, and structural modification on the best hit compound to design new ones.

Result

Molecular docking virtual screening on fifty sets of quinazoline derivatives/epidermal growth factor receptor inhibitors against their target protein (EGFR tyrosine kinase receptor PDB entry: 3IKA) and pharmacokinetic profile predictions were performed to identify hit compounds with promising affinities toward their target and good pharmacokinetic profiles. The hit compounds identified were compound 6 with a binding affinity of − 9.3 kcal/mol, compounds 5 and 8, each with a binding affinity of − 9.1 kcal/mol, respectively. The three hit compounds bound to EGFR tyrosine kinase receptor via four different types of interactions which include conventional hydrogen bond, carbon-hydrogen bond, electrostatic, and hydrophobic interactions, respectively. The best hit (compound 6) among the 3 hit compounds was retained as a template and used to design sixteen new EGFR inhibitors. The sixteen newly designed compounds were also docked into the active site of EGFR tyrosine kinase receptor to study their mode of interactions with the receptor. The binding affinities of these newly designed compounds range from − 9.5 kcal/mol to − 10.2 kcal/mol. The pharmacokinetic profile predictions of these newly designed compounds were further examined and found to be orally bioavailable with good absorption, low toxicity level, and permeable properties.

Conclusion

The sixteen newly designed EGFR inhibitors were found to have better binding affinities than the template used in the designing process and afatinib the positive control (an FDA approved EGFR inhibitor). None of these designed compounds was found to violate more than the permissible limit set by RO5. More so, the newly designed compounds were found to have good synthetic accessibility which indicates that these newly designed compounds can be easily synthesized in the laboratory.

Computational virtual screening and structure-based design of some epidermal growth factor receptor inhibitors

Background

The foremost cause of cancer mortality worldwide was lung cancer. Lung cancer is divided into small cell lung cancer and non-small cell lung cancer (NSCLC). The latter is the main type of lung cancer that account for about 90% of the cancer issues and estimate about 25% of the cancer mortality each year in the world. Among the types of lung cancer with about 1.5 million patients and less than 20% survival rate is NSCLC. Overexpression of EGFR tyrosine kinase was recognized to be the cause of NSCLC. Therefore, there is a need to develop more EGFR inhibitors due to drug-resistance development by the mutation.

Result

Computational virtual screening on some epidermal growth factor receptor inhibitors (EGFRL858R/T790M inhibitors or NSCLC therapeutic agents) against their target protein (EGFR tyrosine kinase receptor pdb entry 3IKA) was performed via molecular docking simulation and pharmacokinetics to identify hit compounds with a promising affinity toward their target. The hit compounds discovered were compound 22 with −9.8 kcal/mol, 24 with −9.7 kcal/mol, 17 with −9.7 kcal/mol, and 19 with −9.5 kcal/mol respectively. These lead compounds were further subjected to drug-likeness and ADME prediction and found to be orally bioavailable. Six (6) new EGFRL858R/T790M inhibitors using compound 22 with the highest binding affinity as a template were designed.

Conclusion

The six newly EGFRL858R/T790M inhibitors were found to have a better binding affinity than the template used in the designing process and AZD9291 (the positive control). None of the designed compounds was found to violate more than the permissible limit set by RO5 thereby predicting their easy transportation, absorption, and diffusion. More so, the designed compounds were found to have good synthetic accessibility which indicates that these designed compounds can be easily synthesized in the laboratory.

Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents

Chemoinformatic studies were carried on some inhibitors of dopamine transporter to develop a predictive and robust QSAR model and also to elucidate binding mode and molecular interactions between the ligands (inhibitors) and the receptor targeting schizophrenia as novel Antipsychotic agents. Density Functional Theory (DFT) approach was utilized to optimize the ligands at B3LYP/6-31G∗ at the ground state and Multi-linear regression of the genetic function approximation (MLR-GFA) method was employed in building Penta-parametric linear equation models. The best model with statistically significant parameters has squared correlation coefficient R²= 0.802, adjusted squared correlation coefficient R²_adj = 0.767, Leave one out (LOO) cross-validation coefficient (Q²) = 0.693, lack of fit score (LOF) = 0.406, R²_Test = 0.77, Y-randomization test (cR²p) = 0.714, Chi-squared (χ²) =0.026, bootstrapping (Systematic errors = 0.272) and Variance Inflation Factor (VIF) <2 . The obtained results were compared with standard validation parameters to ascertain the predictivity, reliability, and robustness of the model. Also, the mechanistic interpretation of the descriptors found in the model revealed that two out of five descriptors; MATS7s (32.3%) and RDF95m (30.4%) having pronounced influence on the observed antipsychotic property of the compounds evidenced by their highest percentage contributions. More so, the molecular docking investigation showed that the binding affinity of the selected ligands ranges from -10.05 to -9.0 kcal/mol and with ligand 21 possessed the highest binding affinity (-10.05 kcal/mol). Furthermore, all the selected ligands displayed hydrogen bonds and hydrophobic interactions with the amino acid residues of the target (4M48) which could account for their higher binding energy. Our findings revealed that the developed model passed the general requirements for an acceptable QSAR model and also satisfied the OECD principles for model development. Hence, the developed model would be practically useful as a blueprint in developing novel antipsychotic agents with improved activity for the treatment of schizophrenia mental disorder.