QSAR Studies Research Articles

Halloysite Nanotube-Based Delivery of Pyrazolo[3,4-d]pyrimidine Derivatives for Prostate and Bladder Cancer Treatment

Background/Objectives: The development of therapies targeting unregulated Src signaling through selective kinase inhibition using small-molecule inhibitors presents a significant challenge for the scientific community. Among these inhibitors, pyrazolo[3,4-d]pyrimidine heterocycles have emerged as potent agents; however, their clinical application is hindered by low solubility in water. To overcome this limitation, some carrier systems, such as halloysite nanotubes (HNTs), can be used. Methods: Herein, we report the development of HNT-based nanomaterials as carriers for pyrazolo[3,4-d]pyrimidine molecules. To achieve this objective, the clay was modified by two different approaches: supramolecular loading into the HNT lumen and covalent grafting onto the HNT external surface. The resulting nanomaterials were extensively characterized, and their morphology was imaged by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). In addition, the kinetic release of the molecules supramolecularly loaded into the HNTs was also evaluated. QSAR studies were conducted to elucidate the physicochemical and pharmacokinetic properties of these inhibitors, and structure-based virtual screening (SBVS) was performed to analyze their binding poses in protein kinases implicated in cancer. Results: The characterization methods demonstrate successful encapsulation of the drugs and the release properties under physiological conditions. Furthermore, QSAR studies and SBVS provide valuable insights into the physicochemical, pharmacokinetic, and binding properties of these inhibitors, reinforcing their potential efficacy. Conclusions: The cytotoxicity of these halloysite-based nanomaterials, and of pure molecules for comparison, was tested on RT112, UMUC3, and PC3 cancer cell lines, demonstrating their potential as effective agents for prostate and bladder cancer treatment.

Design, Synthesis, QSAR Studies, and Molecular Modeling of Some Novel Bis Methyl 2-[3-(benzo[d]thiazol-2-yl)-2-terephthaloyl-bis-4-oxo-thiazolidin- 5-ylidene]acetates and Screening of their Antioxidant and Enzyme Inhibition Properties.

Benzothiazolamine-based bisthiourea precursors were prepared in good yields. These bisthiourea derivatives were cyclized into symmetrical Bis Methyl 2-[3-(benzothiazol- 2-yl)-2-terephthaloyl-bis-4-oxo-thiazolidin-5-ylidene]acetates, by their condensation with (DMAD) dimethyl but-2-meditate in the presence of dry methanol. All these compounds were evaluated for their biological applications. Antioxidant activities were performed by adopting a DPPH radical assay, and an in vitro enzyme inhibition assay was performed to investigate their enzyme inhibitory potential against butyrylcholinesterase (BChE) and acetylcholinesterase (AChE). Molecular modeling and QSAR studies were performed to monitor the binding propensity of imidathiazolidinone derivatives with enzymes and DNA. Also, electronic and steric descriptors were calculated to determine the effect of structure on the activity of imidathiazolidinone derivatives. The characterization of all the synthesized compounds was done by their physical data, FT-IR, NMR and elemental analysis.

A Preliminary Antidepressant Assessment of a Novel Piperoyl Amide (Y3) Isolated and Elucidated from Piper nigrum Drupes Extract, Justifying Interaction Over MAO-A enzyme: An in vivo, in vitro and Molecular Docking Approach

This research aims to confirm the preliminary antidepressant activity of a newly discovered piperoyl amide (Y3) obtained from the extract of Piper nigrum (P. nigrum) drupes, through the inhibition of MAO-A enzyme. Column chromatography was employed for isolation and purification of Novel piperoyl-alkyl amide (Y3) which was eluted in a solvent mixture of Chloroform-Methanol (97:3). Structure elucidation was performed by implying spectroscopic techniques. Invitro in-comparison MAO activity assessment was performed between Y3 and piperine further confirmed by Molecular docking via Auto Dock Tools 1.5.6, Vina, and PyMOL. Invivo antidepressant activity was evaluated by the Despair Test in albino mice. Novel piperoyl-alkyl amide (Y3) was isolated and purified by column chromatography and elucidated spectroscopically. The antidepressant activity of Y3 at 10 and 20 mg/kg doses shown a significant decrease in immobility-time (IT) in contrast to stressed-control group at 107.0±7.6 sec (P<0.05) and 96.0±7.6 sec (P<0.01), respectively. Y3 shown a decent MAO-A inhibitory activity but lower than piperine showing IC50=20.24 µM, Vmax=1.375±0.3 nM/min/mg, Km=1.379×10-16 µM with a stronger interaction and better affinity (-12.6 kcal/mol) towards the active-site of MAO-A. Y3 was isolated and elucidated as (12E,14E)-15-(benzo[d] [1,3] dioxol-5-yl)-N-ethylpentadeca-12,14-dienamide. It proved a good antidepressant at 10 and 20 mg/kg doses. Molecular docking over MAO-A and QSAR studies depicted a better affinity score of Y3 than Piperine. Keywords: Piperoyl amide, Structure elucidation, antidepressant activity, molecular modeling, Piperine

Synthesis of Novel Indolyl Aryl Sulfone-clubbed Hydrazone Derivatives as Potential HIV-1 Non-Nucleoside Reverse Transcriptase Inhibitors: Molecular Modeling and QSAR Studies.

Non-Nucleoside Reverse Transcriptases Inhibitors (NNRTIs) are among the most extensively studied enzymes for understanding the biology of Human Immunodeficiency Viruses (HIV) and designing inhibitors for managing HIV infections. Indolyl aryl sulfones (IASs), an underexplored class of potent NNRTIs, require further exploration for the development of newer drugs for HIV. In this context, we synthesized a series of novels by Indolyl Aryl Sulfones with a hydrazone moiety at the carboxylate site of the indole nucleus. A 2D-QSAR model was developed to predict Reverse Transcriptase inhibitory activity against wild-type RT (WT-RT) enzyme. The model was successfully applied to predict the HIV-1 inhibitory activity of known Indolyl Aryl Sulfones. Considering the reliability, robustness, and reproducibility of the 2D-QSAR model, we made an in-silico prediction of the RT inhibition for our synthesized compounds (1-14). Molecular docking and dynamics simulations established our synthesized Indolyl Aryl Sulfones, particularly compounds 23, 24, and 28, as effective NNRTIs by stabilizing HIV reverse transcriptase's structure. Binding energy calculations revealed compound 28 as the strongest inhibitor (-43.21 ± 0.09 kcal/mol), followed by 23 (-40.94 ± 0.10 kcal/mol) and 24 (-39.18±0.08 kcal/mol), emphasizing their binding affinity towards HIV reverse transcriptase. In summary, the synthesized Indolyl Aryl Sulfones, particularly compounds 23, 24, and 28, demonstrate significant potential as Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs) against HIV. These results highlight the promising role of these compounds in developing novel NNRTIs for managing HIV infections.

Analysis of implicit and explicit uncertainties in QSAR prediction of chemical toxicity: A case study of neurotoxicity

Although uncertainties expressed in texts within QSAR studies can guide quantitative uncertainty estimations, they are often overlooked during uncertainty analysis. Using neurotoxicity as an example, this study developed a method to support analysis of implicitly and explicitly expressed uncertainties in QSAR modeling studies. Text content analysis was employed to identify implicit and explicit uncertainty indicators, whereafter uncertainties within the indicator-containing sentences were identified and systematically categorized according to 20 uncertainty sources. Our results show that implicit uncertainty was more frequent within most uncertainty sources (13/20), while explicit uncertainty was more frequent in only three sources, indicating that uncertainty is predominantly expressed implicitly in the field. The most highly cited sources included Mechanistic plausibility, Model relevance and Model performance, suggesting they constitute sources of most concern. The fact that other sources like Data balance were not mentioned, although it is recognized in the broader QSAR literature as an area of concern, demonstrates that the output from the type of analysis conducted here must be interpreted in the context of the broader QSAR literature before conclusions are drawn. Overall, the method established here can be applied in other QSAR modeling contexts and ultimately guide efforts targeted towards addressing the identified uncertainty sources.

Screening of Novel Hydroxamic Acid Derivatives as ASM Inhibitors for the Treatment of Depression

AbstractIn the present work, we performed a computational study on hydroxamic acid containing compounds as acid sphingomyelinase (ASM) inhibitors. The study starts from the development of 3D‐QSAR and pharmacophore models, which were further taken as a source for the enumeration and virtual screening study. The 3D‐QSAR results showed the best statistical model with Q2, R2, and R2 scrambling values of 0.7175, 0.9019, and 0.7128, respectively. The pharmacophore hypothesis generated one of the best hypotheses including five features such as 2 aromatic rings, 2 hydrogen bond donors, and 1 hydrogen bond acceptor. The enumeration study paved the path in the discovery of novel compounds where pharmacophore hypothesis and 3D QSAR study data was used for the identification of novel compounds. Compound 9f_20 showed good docking score −11.399 and binding interactions with amino acids HIP317, ASN316, GLH386, Zn701, Zn702, HIP317, and HIP280 required for ASM inhibitory activity. The virtual screening study was performed on the basis of developed pharmacophore ADDRR_1 where ZINC000013941849 showed good binding interactions with receptor including amino acids Zn701, Zn702, HIP280, LYS103, HIP317, ASN316, and ILE487. ZINC000013941849 with docking score −13.101. The screened compounds may be taken for the further development of novel antidepressant agents.

Novel Approaches and Emerging Trends in Hydrotropic Solubilization Technology

Hydrotropic solubilization technology enhances the solubility and bioavailability of poorly water-soluble drugs, a major challenge in pharmaceutical research. This review discusses hydrotropic agents’ structures, the solubilization process, and factors affecting drug solubility. It explores optimizing agent concentrations, the role of computer modeling and QSAR studies, and hydrotropes’ impact on overcoming biological barriers and improving pharmacokinetics and pharmacodynamics. The review highlights hydrotropic compounds’ potential in advancing pharmaceutical formulations and clinical applications.

In silico design and ADMET evaluation of new inhibitors for PIM1 kinase using QSAR studies, molecular docking, and molecular dynamic simulation

The proviral Integration site of Moloney (PIM) kinase is highly expressed in various diseases, including cancer, making the development of selective inhibitors for this protein important. A series of PIM1 inhibitors, triazolo [4, 3-b] pyridazin-3-yl-quinoline derivatives, have been studied to design new inhibitors. The activity and structural features of these derivatives were investigated to understand their interactions with PIM1 using molecular docking, molecular dynamic simulation, and QSAR techniques.In a study of 30 compounds using the structure-activity technique and the MLR method, a linear model with R2train = 0.91 and R2test = 0.96 was obtained. The model utilized descriptors such as RDF080v, RDF105v, RDF135v, Mor03v, and H046 to express the structural characteristics of the inhibitors. To enhance the model, the SVR non-linear method with the RBF function was also used, resulting in an improved model with R2train = 0.98 and R2test = 0.98.Furthermore, the molecular docking technique was employed to investigate the interaction of compounds with high (compound 25) and low (compound 13) inhibitory activity. It was observed that the rings with nitrogen atoms interacted with the protein. The molecular binding results indicate that groups such as OMe and rings with Nitrogen can enhance the inhibitory activity of the compounds. Additionally, oxygen and nitrogen atoms contribute to an increased number of hydrogen bonds, thereby increasing the inhibitory activity of the compounds.Additionally, the stability and bonding modes of active and inactive compounds were studied using molecular dynamic simulation. Based on the results, four new inhibitors were designed, demonstrating better inhibition efficiency with the PIM1 kinase compared to the reference compounds. Moreover, the designed compounds underwent evaluation for ADMET, yielding promising results.

Computational Study of Aminoglycoside and Fluoroquinolone Antibiotics

Molecular Docking has become an important component of the drug discovery process. Since first being developed in the 1980s, advancements in the power of computer hardware and the increasing number of and ease of access to small molecule and protein structures have contributed to the development of improved methods, making docking more popular in both industrial and academic settings. In this research Molecular Docking performed on Ciprofloxacin and Streptomycin by using Auto dock and Discovery Studio Software. QSAR study revealed that substitution of different electron donating or withdrawing group at different position on Ciprofloxacin and Streptomycin. Lead nucleus elaborate change in pharmacological activity. Molecular docking done by substituting or replacing different group at different position affected the potency of drug. On addition of methyl and nitro group decreases the activity of Ciprofloxacin while replacement of Guanidino groups from streptidine ringincreases its antibiotic activity.

Crotalaria quinquefolia L. Revealed as a Potential Source of Neuropharmacophore in Both Experimental and Computational Studies.

Herbal remedies have shown great promise for improving human health. The plant Crotalaria quinquefolia is used in folk medicine to cure different diseases, including scabies, fever, discomfort, and lung infections. The present research was designed to explore bioactive compounds and evaluate the neuropharmacological effects of C. quinquefolia through in vivo and in silico approaches. Different secondary metabolites as well as the antioxidant activity were measured. Furthermore, chemical compounds were identified by HPLC and GCMS analysis. The neuropharmacological activity was examined by hole cross, hole board, open field, Y-maze, elevated plus maze, and thiopental sodium induced sleeping time tests in mice at doses of 100 mg/kg and 200 mg/kg body weight. Besides, an in-silico study was performed on proteins related to Alzheimer disease. The extract showed a significant content of secondary metabolites and antioxidant potential. The in-silico analysis showed that myricetin, quercetin, rutin, and kaempferol have good binding affinity with studied proteins, and QSAR studies revealed potential benefits for treating dementia, age-related macular degeneration, and more. The findings of the present neurological activity collectively imply that the extract has strong CNS depressant and anxiolytic activity. Therefore, C. quinquefolia can be a potential source of secondary metabolites to treat Alzheimer disease.

Cheminformatics approaches to predict the bioactivity and to discover the pharmacophoric traits crucial to block NF-κB

Many human disorders include NF-kB signaling pathways, making IKK a therapeutic target in cancer treatment. Inflammatory illnesses and cancer are examples. COVID-19 is one of several triggers that stimulate NF-kB signaling. The activation of the NF-kB pathway is necessary for COVID-19 to cease its development. To learn more about the mechanism and structural features essential to IKK inhibition (IC50), molecular modeling studies have been undertaken on experimentally reported 503. QSAR analysis explores certain reported and hidden structural features critical for IKKβ inhibition. The OECD guidelines guided the construction of the QSAR model, which achieved all the endorsed threshold values for all validation parameters (R2tr:0.81, R2LMO:0.80, and R2ext:0.78). The present QSAR study shows that IKK inhibitory activity is linked to the following structural features: lipophilic hydrogen atoms within 2 A units of the molecule's center of mass; ring nitrogen atoms within one bond of planar nitrogen atoms; ring carbon atoms exactly four bonds from the non-ring nitrogen atoms; planar nitrogen atoms exactly four bonds from sp2 hybridized carbon atoms; and so on. Pharmacophore modeling highlighted QSAR-identified structural characteristics. To investigate binding, we docked all 503 molecules. The observation indicates that the QSAR and molecular docking/pharmacophore modeling findings are in agreement. Following this, we conducted 200 ns of molecular dynamics simulation to validate the molecular docking protocol. MMGBSA analysis determined the binding energy of the dock complex. Thus, the current study found unique pharmacophoric properties that may assist in optimizing lead/hit compounds for anti-IKKβ activity.

QSAR Studies on a Class of Benzofuranene Cyanide Derivatives as Potential Inhibitors Targeting Staphylococcus aureus Sortase A.

Staphylococcus aureus is a widely distributed and highly pathogenic zoonotic bacterium. Sortase A represents a crucial target for the research and development of novel antibacterial drugs. This study aims to establish quantitative structure-activity relationship models based on the chemical structures of a class of benzofuranene cyanide derivatives. The models will be used to screen new antibacterial agents and predict the properties of these molecules. The compounds were randomly divided into a training set and a test set. A large number of descriptors were calculated using the software, and then the appropriate descriptors were selected to build the models through the heuristic method and the gene expression programming algorithm. In the heuristic method, the determination coefficient, determination coefficient of cross-validation, F-test, and mean squared error values were 0.530, 0.395, 9.006, and 0.047, respectively. In the gene expression programming algorithm, the determination coefficient and the mean squared error values in the training set were 0.937 and 0.008, respectively, while in the test set, they were 0.849 and 0.035. The results showed that the minimum bond order of a C atom and the relative number of benzene rings had a significant positive contribution to the activity of compounds. In this study, two quantitative structure-activity relationship models were successfully established to predict the inhibitory activity of a series of compounds targeting Staphylococcus aureus Sortase A, providing insights for further development of novel anti-Staphylococcus aureus drugs.

Pyrrole-Indoline-2-Ones as Aurora Kinase Inhibitors: Pharmacophore Modeling, 3D QSAR Studies and Molecular Dynamics

Pyrrole-Indoline-2-Ones as Aurora Kinase Inhibitors: Pharmacophore Modeling, 3D QSAR Studies and Molecular Dynamics

Multicellular target QSAR models for predicting of novel inhibitors against pancreatic cancer by Monte Carlo approach

Pancreatic cancer is one of the most fatal malignant tumors, with a poor prognosis. Nowadays, computational methods for designing and predicting anticancer agents have gained increased attention. In this work, a QSAR study is conducted to further investigate the activity of 5797 agents against pancreatic cancer cell lines. QSAR models are a system of classification approaches that are used to construct and validate the predictive potential of created models. This approach demonstrates the prediction in the active (1) and inactive (−1) format. Here, the classification QSAR technique is employed to construct and evaluate models. The classification QSAR model has been constructed by the Monte Carlo method based on the representation of the molecular structure by SMILES (simplified molecular input line entry systems) using the CORAL software. Four random splits of data by making four sets such as active training, passive training, calibration, and validation sets are assessed. The numerical values of sensitivity, specificity, and accuracy for the validation set of splits 1 to 4 are in the range of 0.7726–0.7901, 0.9007–0.9220, and 0.8548–0.8730 respectively. The Matthews correlation coefficient (MCC) of these models for external validation sets is found to be in the range of 0.6832 to 0.7215.

Benzyloxychalcone Hybrids as Prospective Acetylcholinesterase Inhibitors against Alzheimer's Disease: Rational Design, Synthesis, In Silico ADMET Prediction, QSAR, Molecular Docking, DFT, and Molecular Dynamic Simulation Studies.

Acetylcholinesterase inhibitors (AChEIs) are crucial therapeutic targets for both the early and severe stages of Alzheimer's disease (AD). Chalcones and their chromone-based derivatives are well-known building blocks with anti-Alzheimer properties. This study synthesized 4-benzyloxychalcone derivatives and characterized their structures using IR, 1H NMR, 13C NMR, and HRMS. Additionally, the synthesized 4-benzyloxychalcone derivatives were tested for anti-acetylcholinesterase (AChE) activity. The synthesized compounds outperformed galantamine, which is used as a positive control against acetylcholinesterase. Utilizing an acetylcholinesterase (AChE) receptor (PDB ID: 4EY7)-chalcone derivative (12a-c), a molecular docking investigation was performed on the synthesized compounds. The goal was to predict the binding sites and energies of the derivatives with respect to the receptor amino acids. The dynamic behavior of the ligand-receptor complex resulting from the interaction of the best docking compounds 12a and 12c with the acetylcholinesterase receptor was used to analyze the stability via MD simulation. MM/GBSA and MM/PBSA were used to calculate free binding energies using snapshots from system trajectories. Advanced computational approaches incorporating long-range corrections were utilized to calculate the molecular characteristics of chalcone derivatives 12a-c at the DFT/wB97XD/6-311++G(d,p) level. We used the molecular electrostatic surface potential (MESP) with high-quality data and visualization to find the most active site in these molecules. Reactivity descriptors, including the condensed Fukui function, chemical hardness (η), dual descriptors, chemical potential (μ), and electrophilicity (ω), were calculated for the chalcone derivatives.

In Silico Design and In Vitro Assessment of Bicyclic Trifluoromethylated Pyrroles as New Antibacterial and Antifungal Agents.

QSAR studies on the number of compounds tested as S. aureus inhibitors were performed using an interactive Online Chemical Database and Modeling Environment (OCHEM) web platform. The predictive ability of the developed consensus QSAR model was q2=0.79±0.02. The consensus prediction for the external evaluation set afforded high predictive power (q2=0.82±0.03). The models were applied to screen a virtual chemical library with anti-S. aureus activity. Six promising new bicyclic trifluoromethylated pyrroles were identified, synthesized and evaluated in vitro against S. aureus, E. coli, and A. baumannii for their antibacterial activity and against C. albicans, C. krusei and C. glabrata for their antifungal activity. The synthesized compounds were characterized by 1H, 19F, and 13C NMR and elemental analysis. The antimicrobial activity assessment indicated that trifluoromethylated pyrroles 9 and 11 demonstrated the greatest antibacterial and antifungal effects against all the tested pathogens, especially against multidrug-resistant strains. The acute toxicity of the compounds to Daphnia magna ranged from 1.21 to 33.39 mg/L (moderately and slightly toxic). Based on the docking results, it can be suggested that the antibacterial and antifungal effects of the compounds can be explained by the inhibition of bacterial wall component synthesis.

Synthesis, In Silico Study and Antimalarial Activity of Triazolo[1,5‐a]pyrimidine Derivatives

AbstractThe present study mainly focused on synthesizing novel triazolo[1,5‐a]pyrimidine‐6‐carboxamide derivatives using multicomponent reaction. Synthesized derivatives were duly characterized using spectroscopic methods of analysis FT‐IR and mass spectroscopy, and 1H NMR and 13C NMR confirmed the structure of compounds. Further, the potential of the synthesized compounds against Plasmodium falciparum dihydrofolate reductase (Pf‐DHFR) inhibitors was evaluated by in vitro antimalarial activity, and the results of the study showed moderate to good antimalarial profile of synthesized entities. In silico study of all the synthesized compounds was carried out using Schrödinger LLC‐2020‐3 Software to explain the binding mode and interactions between molecules and pf DHFR enzyme. To study the drug likeliness of molecules, 3D QSAR and Pharmacokinetic studies have been carried out, and the results obtained showed a good pharmacokinetics profile of two compounds, namely AMP‐24 and AMP‐28, having good IC50 values concerning standard drugs. Further, the in vitro enzyme inhibition assay results suggested that the synthesized compound interacts nicely with the enzyme and might be used as a potent antimalarial agent.

A SAR and QSAR study on 3CLpro inhibitors of SARS-CoV-2 using machine learning methods

ABSTRACT The 3C-like Proteinase (3CLpro) of novel coronaviruses is intricately linked to viral replication, making it a crucial target for antiviral agents. In this study, we employed two fingerprint descriptors (ECFP_4 and MACCS) to comprehensively characterize 889 compounds in our dataset. We constructed 24 classification models using machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), extreme Gradient Boosting (XGBoost), and Deep Neural Networks (DNN). Among these models, the DNN- and ECFP_4-based Model 1D_2 achieved the most promising results, with a remarkable Matthews correlation coefficient (MCC) value of 0.796 in the 5-fold cross-validation and 0.722 on the test set. The application domains of the models were analysed using dSTD-PRO calculations. The collected 889 compounds were clustered by K-means algorithm, and the relationships between structural fragments and inhibitory activities of the highly active compounds were analysed for the 10 obtained subsets. In addition, based on 464 3CLpro inhibitors, 27 QSAR models were constructed using three machine learning algorithms with a minimum root mean square error (RMSE) of 0.509 on the test set. The applicability domains of the models and the structure-activity relationships responded from the descriptors were also analysed.

Synthesis of thiazolidine-2,4-dione tethered 1,2,3-triazoles as α-amylase inhibitors: In vitro approach coupled with QSAR, molecular docking, molecular dynamics and ADMET studies

A new series of thiazolidine-2,4-dione tethered 1,2,3-triazole derivatives were designed, synthesized and screened for their α-amylase inhibitory potential employing in vitro and in silico approaches. The target compounds were synthesized with the help of Cu (I) catalyzed [3 + 2] cycloaddition of terminal alkyne with numerous azides, followed by unambiguously characterizing the structure by employing various spectroscopic approaches. The synthesized derivatives were assessed for their in vitro α-amylase inhibition and it was found that thiazolidine-2,4-dione derivatives 6e, 6j, 6o, 6u and 6x exhibited comparable inhibition with the standard drug acarbose. The compound 6e with a 7-chloroquinolinyl substituent on the triazole ring exhibited significant inhibition potential with IC50 value of 0.040 μmol mL−1 whereas compound 6c (IC50 = 0.099 μmol mL−1) and 6h (IC50 = 0.098 μmol mL−1) were poor inhibitors. QSAR studies revealed the positively correlating descriptors that aid in the design of novel compounds. Molecular docking was performed to investigate the binding interactions with the active site of the biological receptor and the stability of the complex over a period of 100 ns was examined using molecular dynamics studies. The physiochemical properties and drug-likeliness behavior of the potent derivatives were investigated by carrying out the ADMET studies.

An In Silico Study Based on QSAR and Molecular Docking and Molecular Dynamics Simulation for the Discovery of Novel Potent Inhibitor against AChE.

Acetylcholinesterase (AChE) is one of the main drug targets for treating Alzheimer's disease. This current study relies on multiple molecular modeling approaches to develop new potent inhibitors of AChE. We explored a 2D QSAR study using the statistical method of multiple linear regression based on a set of substituted 5-phenyl-1,3,4-oxadiazole and N-benzylpiperidine analogs, which were recently synthesized and proved their inhibitory activities against acetylcholinesterase (AChE). The molecular descriptors, polar surface area, dipole moment, and molecular weight are the key structural properties governing AChE inhibition activity. The MLR model was selected based on its statistical parameters: R2 = 0.701, R2test = 0.76, Q2CV = 0.638, and RMSE = 0.336, demonstrating its predictive reliability. Randomization tests, VIF tests, and applicability domain tests were adopted to verify the model's robustness. As a result, 11 new molecules were designed with higher anti-Alzheimer's activities than the model molecule. We demonstrated their improved pharmacokinetic properties through an in silico ADMET study. A molecular docking study was conducted to explore their AChE inhibition mechanisms and binding affinities in the active site. The binding scores of compounds M1, M2, and M6 were (-12.6 kcal/mol), (-13 kcal/mol), and (-12.4 kcal/mol), respectively, which are higher than the standard inhibitor Donepezil with a binding score of (-10.8 kcal/mol). Molecular dynamics simulations over 100 ns were used to validate the molecular docking results, indicating that compounds M1 and M2 remain stable in the active site, confirming their potential as promising anti-AChE inhibitors.