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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.
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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.
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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.
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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.
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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 ß-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 ß-amino alcohol grafted 1,4,5-trisubstituted 1,2,3-triazoles derivatives. The five design derivatives of ß-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.
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The thermodynamics of free radical scavenge of 1,3,4-oxadiazole derivatives towards oxygen-centred free radicals were investigated by the density functional theory (DFT) method in the gas phase and aqueous solution. Three mechanisms of free radical scavenge namely, hydrogen atom transfer (HAT), single electron transfer followed by proton transfer (SET-PT) and sequential proton loss electron transfer (SPLET) were considered. The antioxidant descriptors that characterize these mechanisms such as, bond dissociation enthalpy (BDE), adiabatic ionization potential (AIP), proton dissociation enthalpy (PDE), proton affinity (PA) and electron transfer enthalpy (ETE) were evaluated. The sequence of electron donation as predicted by the HOMO results were in good agreement with the sequence of ETE for the considered molecules at their favoured sites of free radical scavenge. The reaction Gibbs free energy for inactivation of the selected peroxyl radicals, show that 1,3,4-oxadiazole antioxidants are more efficient radical scavengers by HAT and SPLET mechanisms than SET-PT mechanism in vacuum. In aqueous solution, the SET-PT mechanism was observed to be the dominant reaction pathway.
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The prevalence of degenerative diseases in recent time has triggered extensive research on their control. This condition could be prevented if the body has an efficient antioxidant mechanism to scavenge the free radicals which are their main causes. Curcumin and its derivatives are widely employed as antioxidants. The free radical scavenging activities of curcumin and its derivatives have been explored in this research by the application of quantitative structure activity relationship (QSAR). The entire data set was optimized at the density functional theory (DFT) level using the Becke's three-parameter Lee-Yang-Parr hybrid functional (B3LYP) in combination with the 6-311G∗ basis set. The training set was subjected to QSAR studies by genetic function algorithm (GFA). Five predictive QSAR models were developed and statistically subjected to both internal and external validations. Also the applicability domain of the developed model was accessed by the leverage approach. Furthermore, the variation inflation factor, (VIF), mean effect (MF) and the degree of contribution (DC) of each descriptor in the resulting model were calculated. The developed models met all the standard requirements for acceptability upon validation with highly impressive results ( R=0.965,R2=0.931,Q2(RCV2)=0.887,Rpred2=0.844,cRp2=0.842s=0.226,rmsep=0.362 ). Based on the results of this research, the most crucial descriptor that influence the free radical scavenge of the curcumins is the nsssN (count of atom-type E-state: >N-) descriptor with DC and MF values of 12.980 and 0.965 respectively.