Integrated Exploration of Pyranocoumarin Derivatives as Synergistic Inhibitors of Dual-target for Mpro and PLpro Proteins of SARS-CoV-2 through Molecular Docking, ADMET Analysis, and Molecular Dynamics Simulation.

AIMS: This study aimed to explore the potential of natural anticoagulant compounds as synergistic inhibitors of the main protease (Mpro) and papain-like protease (PLpro) of SARS-CoV-2 and find effective therapies against SARS-CoV-2 by investigating the inhibitory effects of natural anticoagulant compounds on key viral proteases. OBJECTIVE: The objectives of this study were to conduct rigorous virtual screening and molecular docking analyses to evaluate the binding affinities and interactions of selected anticoagulant compounds with Mpro and PLpro, to assess the pharmacokinetic and pharmacodynamic profiles of the compounds to determine their viability for therapeutic use, and to employ molecular dynamics simulations to understand the stability of the identified compounds over time. METHODS: In this study, a curated collection of natural anticoagulant compounds was conducted. Virtual screening and molecular docking analyses were performed to assess binding affinities and interactions with Mpro and PLpro. Furthermore, pharmacokinetic and pharmacodynamic analyses were carried out to evaluate absorption, distribution, metabolism, and excretion profiles. Molecular dynamics simulations were performed to elucidate compound stability. RESULTS: Natural compounds exhibiting significant inhibitory activity against Mpro and PLpro were identified. A dual-target approach was established as a promising strategy for attenuating viral replication and addressing coagulopathic complications associated with SARS-CoV-2 infection. CONCLUSION: The study lays a solid foundation for experimental validation and optimization of identified compounds, potentially leading to the development of precise treatments for SARS-CoV-2.

Exploration of alpha-glucosidase inhibitors: A comprehensive in silico approach targeting a large set of triazole derivatives.

BACKGROUND: The increasing prevalence of diabetes and the side effects associated with current medications necessitate the development of novel candidate drugs targeting alpha-glucosidase as a potential treatment option. METHODS: This study employed computer-aided drug design techniques to identify potential alpha-glucosidase inhibitors from the PubChem database. Molecular docking was used to evaluate 81,197 compounds, narrowing the set for further analysis and providing insights into ligand-target interactions. An ADMET study assessed the pharmacokinetic properties of these compounds, including absorption, distribution, metabolism, excretion, and toxicity. Molecular dynamics simulations validated the docking results. RESULTS: 9 compounds were identified as potential candidate drugs based on their ability to form stable complexes with alpha-glucosidase and their favorable pharmacokinetic profiles, three of these compounds were subjected to the molecular dynamics, which showed stability throughout the entire 100 ns simulation. CONCLUSION: These findings suggest promising new alpha-glucosidase inhibitors for diabetes treatment. Further validation through in vitro and in vivo studies is recommended to confirm their efficacy and safety.

Targeting Fructosamine Oxidase (Amadoriase II) in Aspergillus fumigatus: Comprehensive Virtual Screening, ADMET Analysis, and Molecular Dynamics Simulation of Triazole Derivatives.

INTRODUCTION: Aspergillus fumigatus, a significant fungal pathogen, poses a threat to human health, especially in immunocompromised individuals. Addressing the need for novel antifungal strategies, this study employs virtual screening to identify potential inhibitors of Fructosamine oxidase, also known as Amadoriase II, a crucial enzyme in A. fumigatus (PDB ID: 3DJE). METHOD: Virtual screening of 81,197 triazole derivatives was subjected to computational analysis, aiming to pinpoint molecules with high binding affinity to the active site of Fructosamine oxidase. Subsequently, an in-depth ADMET analysis assessed the pharmacokinetic properties of lead compounds, ensuring their viability for further development. Molecular dynamics simulations were performed to evaluate the stability of top-ranked compounds over time. RESULTS: The results unveil a subset of triazole derivatives displaying promising interactions, suggesting their potential as inhibitors for further investigation. CONCLUSION: This approach contributes to the development of targeted antifungal agents, offering a rational starting point for experimental validation and drug development against Aspergillus fumigatus infections.

Advancements in Computational Approaches for Antidiabetic Drug Discovery: A Review.

Diabetes mellitus (DM) manifests as a complex and chronic metabolic disorder, posing a significant threat to global public health and contributing substantially to mortality rates. It is characterized by elevated blood glucose levels or hyperglycemia and requires effective preventive and therapeutic strategies. One promising approach involves targeting the inhibition of α- glucosidase and α-amylase, key enzymes responsible for carbohydrate hydrolysis. Inhibiting these enzymes proves beneficial in reducing postprandial glucose levels and mitigating postprandial hyperglycemia. However, existing antidiabetic medications are associated with undesirable side effects, highlighting the need to develop new molecules with increased efficacy and reduced side effects. Traditional methods for designing such molecules are often lengthy and costly. To address this, computer-based molecular modeling tools offer a promising approach to evaluate the antidiabetic activities of chemical compounds. This review aims to compile information on chemical compounds assessed for their anti-diabetic activities through molecular modeling, with a particular focus on the period from 2020 to 2023.

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.

Unveiling Moroccan Nature's Arsenal: A Computational Molecular Docking, Density Functional Theory, and Molecular Dynamics Study of Natural Compounds against Drug-Resistant Fungal Infections.

Candida albicans and Aspergillus fumigatus are recognized as significant fungal pathogens, responsible for various human infections. The rapid emergence of drug-resistant strains among these fungi requires the identification and development of innovative antifungal therapies. We undertook a comprehensive screening of 297 naturally occurring compounds to address this challenge. Using computational docking techniques, we systematically analyzed the binding affinity of each compound to key proteins from Candida albicans (PDB ID: 1EAG) and Aspergillus fumigatus (PDB ID: 3DJE). This rigorous in silico examination aimed to unveil compounds that could potentially inhibit the activity of these fungal infections. This was followed by an ADMET analysis of the top-ranked compound, providing valuable insights into the pharmacokinetic properties and potential toxicological profiles. To further validate our findings, the molecular reactivity and stability were computed using the DFT calculation and molecular dynamics simulation, providing a deeper understanding of the stability and behavior of the top-ranking compounds in a biological environment. The outcomes of our study identified a subset of natural compounds that, based on our analysis, demonstrate notable potential as antifungal candidates. With further experimental validation, these compounds could pave the way for new therapeutic strategies against drug-resistant fungal pathogens.

Synthesis, Antimicrobial, Molecular Docking Against Bacterial and Fungal Proteins and In Silico Studies of Glucopyranoside Derivatives as Potent Antimicrobial Agents.

Carbohydrate derivatives play a crucial roles in biochemical and medicinal research, especially in the fields of chemistry and biochemistry. From this perspective, the present study was designed to explore the synthesis of methyl α-D-glucopyranoside derivatives (1-8), focusing on their efficacy against bacterial and fungal inhibition. The structure of the synthesized compounds was ascertained using FTIR, 1H-NMR, 13C-NMR, mass and elemental analyses. Antimicrobial screening revealed strong antifungal properties, with compound 7 exhibiting minimum inhibitory concentrations (MICs) ranging from 16-32 µg/L and minimum bactericidal concentrations (MBCs) ranging from 64-128 µg/L. Incorporating decanoyl acyl groups at C-2 and C-3 of (7) significantly improved the efficacy against bacteria and fungi. Structure-activity relationship (SAR) analysis indicated that adding nonanoyl and decanoyl groups to the ribose moiety enhanced potency against both bacterial and fungal strains. Computational methods, including molecular docking, density functional theory (DFT), Petra, Osiris, Molinspiration (POM) evaluation, and molecular dynamics (MD) simulations, were used to assess the efficacy of these derivatives. Compounds 6 and 7, which presented nonanoyl and decanoyl substituents, demonstrated greater efficacy. In addition, DFT studies identified compound 8 as possessing ideal electronic properties. Molecular docking revealed that compound 8 exhibits exceptional binding affinities to bacterial proteins, conferring potent antibacterial and antifungal activities. In addition, pharmacokinetic optimization via POM analysis highlighted compounds 1 and 2 as promising bioavailable drugs with minimal toxicity. Molecular dynamics simulations confirmed the stability of the 2-S. aureus complex, revealing the therapeutic potential of compounds 2 and 8. Future experiments are required to validate their efficacy for pharmaceutical development. The integration of in vitro and in silico methods, including DFT anchoring dynamics and molecular dynamics simulations, provides a solid framework for the advancement of effective anti-infective drugs.

Integrative Approach for Designing Novel Triazole Derivatives as α-Glucosidase Inhibitors: QSAR, Molecular Docking, ADMET, and Molecular Dynamics Investigations.

In response to the increasing prevalence of diabetes mellitus and the limitations associated with the current treatments, there is a growing need to develop novel medications for this disease. This study is focused on creating new compounds that exhibit a strong inhibition of alpha-glucosidase, which is a pivotal enzyme in diabetes control. A set of 33 triazole derivatives underwent an extensive QSAR analysis, aiming to identify the key factors influencing their inhibitory activity against α-glucosidase. Using the multiple linear regression (MLR) model, seven promising compounds were designed as potential drugs. Molecular docking and dynamics simulations were employed to shed light on the mode of interaction between the ligands and the target, and the stability of the obtained complexes. Furthermore, the pharmacokinetic properties of the designed compounds were assessed to predict their behavior in the human body. The binding free energy was also calculated using MMGBSA method and revealed favorable thermodynamic properties. The results highlighted three novel compounds with high biological activity, strong binding affinity to the target enzyme, and suitability for oral administration. These results offer interesting prospects for the development of effective and well-tolerated medications against diabetes mellitus.

Insights into the inhibitory potential of novel hydrazinyl thiazole-linked indenoquinoxaline against alpha-amylase: a comprehensive QSAR, pharmacokinetic, and molecular modeling study.

The rising prevalence of diabetes necessitates the development of novel drugs, especially given the side effects associated with current medications like Acarbose and Voglibose. A series of 36 Hydrazinyl thiazole-linked indenoquinoxaline derivatives with notable activity against alpha-amylase were studied. To create a molecular model predicting alpha-amylase activity, a QSAR study was performed on these compounds. Molecular descriptors were calculated using Chem3D and Gaussian software and then correlated with their IC50 biological activities to form a dataset. This model data was refined using PCA and modeled with MLR. The model's performance was statistically verified (R2 =0.800; Radj2 = 0.767; Rcv2 = 0.651) and its applicability domain was defined. It was predicted to possess high predictive power (Rtest2  = 0.872). Based on this, new compounds were proposed, and their activities were predicted using the developed model. Additionally, their binding ability to the biological target was studied through molecular docking and dynamics. Their pharmacokinetics were also evaluated using ADMET predictions. Two designed compounds named AE and AB emerged as particularly promising, displaying properties that suggest substantial therapeutic potential and they can form stable complexes into the binding pocket of alpha-amylase enzyme.Communicated by Ramaswamy H. Sarma.

Genotoxic effects and mitosis aberrations of chromium (VI) on root cells of Vicia faba and its molecular docking analysis.

Like other heavy metals, Cr (VI) is a powerful carcinogen and mutagen agent. Its toxic effects on plants are well considered. In order to elucidate its adverse effects, the present work aims to study the mitosis aberrations of Cr (VI) on the Vicia faba root-cells and its molecular docking analysis to understand the genotoxicity mechanisms. In-vivo, Vicia faba plants were exposed to 50 and 100 µM Cr (VI) for 48 h. In-silico, molecular docking and molecular dynamics simulation were used to study the interactions between dichromate and tubulin tyrosine ligase T2R-TTL (PDBID: 5XIW) with reference to Colchicine (microtubule inhibitor). According to our results, Cr (VI) affects growth and cell division and also induces many mitosis aberrations such as chromosome sticking, anaphase/telophase bridges, lagging chromosomes and fragmentation during all phases of mitosis. On the one hand, Cr (VI) reduces mitotic index and promotes micronuclei induction. The in-silico results showed that dichromate establishes very strong bonds at the binding site of the tubulin tyrosine ligase T2R-TTL, with a binding affinity of -5.17 Kcal/Mol and an inhibition constant of 163.59 µM. These interactions are similar to those of colchicine with this protein, so dichromate could be a very potent inhibitor of this protein's activity. TTL plays a fundamental role in the tyrosination/detyrosination of tubulin, which is crucial to the regulation of the microtubule cytoskeleton. Its inhibition leads to the appearance of many morphogenic abnormalities such as mitosis aberrations. In conclusion, our data confirm the highest genotoxicity effects of Cr (VI) on Vicia faba root-cells.

Design, synthesis, In-vitro, In-silico and DFT studies of novel functionalized isoxazoles as antibacterial and antioxidant agents.

A series of new isoxazolederivatives incorporating the sulfonate ester function has been synthesized from 2-benzylidenebenzofuran-3(2 H)-one, known as aurone. The synthesis of the target compounds was carried out following an efficient methodology that allows access to the desired products in a reproducible way and with good yield. The structures of the synthesized compounds were established using NMR (1H and 13C) spectroscopy and mass spectrometry. A theoretical study was performed to optimize the geometrical structures and to calculate the structural and electronic parameters of the synthesized compounds. The calculations were also carried out to understand the influence and the effect of substitutions on the chemical reactivity of the studied compounds. The synthesized isoxazoles were screened for their antioxidant and antibacterial activities. The findings demonstrate that the studied compounds exhibit good to moderate antibacterial activity against the tested bacteria (Staphylococcus aureus, Bacillus subtilis, and Escherichia coli). Moreover, a number of the tested isoxazole derivatives exhibit high effectiveness against DPPH free radicals. Besides that, molecular docking studies were carried out to predict binding affinity and identify the most likely binding interactions between the active molecules and the target microorganisms' proteins. A 100 ns molecular dynamics study was then conducted to examine the dynamic behavior and stability of the highly potent isoxazole 4e in complex with the target bacterial proteins. Finally, the ADMET analyses suggest that all the synthesized isoxazoles have good pharmacokinetic profiles and non-toxicity and non-carcinogenicity in biological systems.

In vitro and in silico analysis for elucidation of antioxidant potential of Djiboutian Avicennia Marina (Forsk.) Vierh. phytochemicals.

The present work aims to study the phytochemical composition, the antioxidant capacity of the crude extracts, and the fraction of extract giving the best antioxidant activity of Avicennia marina. The leaves contain high TFC compared to other parts of the plant, whereas fruits have the highest amount of TPC. Fat-soluble pigments are strongly present in the leaves of Avicennia marina i.e. ß-carotene, lycopene, chlorophyll a, and chlorophyll b. The crude methanolic flower extracts showed strong DPPH and ABTS radical scavenging activity with IC50 values of 0.30 and 0.33 mg/mL respectively compared to the leaf and stem methanolic extracts for the DPPH and ABTS models with a value IC50 greater than 1 mg/mL. The crude fruit extract shows good activity with the ABTS model, unlike the DPPH model whose IC50 values are 0.95 and 0.38 mg/mL, respectively. Fractionation improved the antioxidant effect of crude flower extract. The ethyl acetate fraction exhibits the best antioxidant activity for both DPPH and ABTS methods with IC50 values of 0.125 and 0.16 mg/mL. The HR-LCMS/MS led to the identification of 13 compounds: 6 flavonoids and 7 iridoid glycoside compounds in the different parts of the plant. A bioinformatics study was performed to evaluate the antioxidant activity of the three major Iridoid glycosides towards the target protein Catalase compound II through free binding energy. Out of these three iridoid glycosides, compound C10 does not represent any toxicity, unlike C8 and C9 which showed an irritancy effect. Furthermore, molecular dynamics shows good stability of the C10-2CAG complex. HighlightsExtraction and fractionation of different part (leaf, stem, flower and fruit) of Avicennia marina.Botanical description and phytochemical analysis of crude extract methanolic. Investigation by HR-LCMS characterization of polyphenols and iridoid glycosides.Evaluation the antioxidant activity of crudes extracts methanolics by two methods in vitro DPPH and ABTS.Antioxidant activity of the fraction of the crude flower extracts presenting the best biological response.Evaluate the contribution of three major compounds 2'-Cinnamoylmussaenosidic acid, 10-O-[E-Cinnamoyl]-geniposidic acid and 10-O-[(E)-p-Coumaroyl]-geniposidic acid in the ethyl acetate fraction on the antioxidant activity through docking and dynamic molecular.Communicated by Ramaswamy H. Sarma.

Structure-based virtual screening, ADMET analysis, and molecular dynamics simulation of Moroccan natural compounds as candidates for the SARS-CoV-2 inhibitors.

The lack of treatments and vaccines effective against SARS-CoV-2 has forced us to explore natural compounds that could potentially inhibit this virus. Additionally, Morocco is renowned for its rich plant diversity and traditional medicinal uses, which inspires us to leverage our cultural heritage and the abundance of natural resources in our country for therapeutic purposes. In this study, an extensive investigation was conducted to gather a collection of phytoconstituents extracted from Moroccan plants, aiming to evaluate their ability to inhibit the proliferation of the SARS-CoV-2 virus. Molecular docking of the studied compounds was performed at the active sites of the main protease (6lu7) and spike (6m0j) proteins to assess their binding affinity to these target proteins. Compounds exhibiting high affinity to the proteins underwent further evaluation based on Lipinski's rule and ADME-Tox analysis to gain insights into their oral bioavailability and safety. The results revealed that the two compounds demonstrated strong binding affinity to the target proteins, making them potential candidates for oral antiviral drugs against SARS-CoV-2. The molecular dynamics results from this computational analysis supported the overall stability of the resulting complex.

Synthesis, biological evaluation and molecular modelling of 3-Formyl-6-isopropylchromone derived thiosemicarbazones as α-glucosidase inhibitors.

Type-2 Diabetes Mellitus (T2DM) is one of the most common metabolic disorders in the world and over the past three decades its incidence has increased drastically. α-Glucosidase inhibitors are used to control the hyperglycemic affect of T2DM. Herein, we report the synthesis, α-glucosidase inhibition, structure activity relationship, pharmacokinetics and docking analysis of various novel chromone based thiosemicarbazones 3(a-r). The derivatives displayed potent activity against α-glucosidase with IC50 in range of 0.11 ± 0.01-79.37 ± 0.71 µM. Among all the synthesized compounds, 3a (IC50 = 0.17 ± 0.026 µM), 3 g (IC50 = 0.11 ± 0.01 µM), 3n (IC50 = 0.55 ± 0.02 µM), and 3p (IC50 = 0.43 ± 0.025 µM) displayed higher inhibitory activity as compared to the standard, acarbose. Moreover, we have developed a statistically significant 2D-QSAR model (R2tr:0.9693; F: 50.4647 and Q2LOO:0.9190), which can be used in future to further design potent thiosemicarbazones as inhibitors of α-glucosidase.

The anti-SARS-CoV-2 activity of novel 9, 10-dihydrophenanthrene derivatives: an insight into molecular docking, ADMET analysis, and molecular dynamics simulation.

Originating in Wuhan, the COVID-19 pandemic wave has had a profound impact on the global healthcare system. In this study, we used a 2D QSAR technique, ADMET analysis, molecular docking, and dynamic simulations to sort and evaluate the performance of thirty-nine bioactive analogues of 9,10-dihydrophenanthrene. The primary goal of the study is to use computational approaches to create a greater variety of structural references for the creation of more potent SARS-CoV-2 3Clpro inhibitors. This strategy is to speed up the process of finding active chemicals. Molecular descriptors were calculated using 'PaDEL' and 'ChemDes' software, and then redundant and non-significant descriptors were eliminated by a module in 'QSARINS ver. 2.2.2'. Subsequently, two statistically robust QSAR models were developed by applying multiple linear regression (MLR) methods. The correlation coefficients obtained by the two models are 0.89 and 0.82, respectively. These models were then subjected to internal and external validation tests, Y-randomization, and applicability domain analysis. The best model developed is applied to designate new molecules with good inhibitory activity values against severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). We also examined various pharmacokinetic properties using ADMET analysis. Then, through molecular docking simulations, we used the crystal structure of the main protease of SARS-CoV-2 (3CLpro/Mpro) in a complex with the covalent inhibitor "Narlaprevir" (PDB ID: 7JYC). We also supported our molecular docking predictions with an extended molecular dynamics simulation of a docked ligand-protein complex. We hope that the results obtained in this study can be used as good anti-SARS-CoV-2 inhibitors.

A computer-aided drug design approach to explore novel type II inhibitors of c-Met receptor tyrosine kinase for cancer therapy: QSAR, molecular docking, ADMET and molecular dynamics simulations.

Small molecules such as 4-phenoxypyridine derivatives have remarkable inhibitory activity against c-Met enzymatic activity and proliferation of cancer cell lines. Since there is a relationship between structure and biological activity of these molecules, these little compounds may have great potential for clinical pharmaceutical use against various types of cancer caused by c-Met activity. The purpose of this study was to remodel the structures of 4-phenoxypyridine derivatives to achieve strong inhibitory activity against c-Met and provide favorable pharmacokinetic properties for drug design and discovery. Therefore, this paper describes the structure-activity relationship and the rationalization of appropriate pharmacophore sites to improve the biological activity of the investigated molecules, based on bioinformatics techniques represented by a computer-aided drug design approach. Accordingly, robust and reliable 3D-QSAR models were developed based on CoMFA and CoMSIA techniques. As a result, 46 lead molecules were designed and their biological and pharmacokinetic activities were predicted in silico. Screening filters by 3D-QSAR, Molecular Docking, drug-like and ADME-Tox identified the computer-designed compounds P54 and P55 as the best candidates to achieve high inhibition of c-Met enzymatic activity compared to the synthesized template compound T14. Finally, through molecular dynamics simulations, the structural properties and dynamics of c-Met free and complex (PDB code: 3LQ8) in the presence of 4-phenoxypyridine-derived compounds in an aqueous environment are discussed. Overall, the rectosynthesis of the designed drug inhibitors (P54 and P55) and their in vitro and in vivo bioactivity evaluation may be attractive for design and discovery of novel drug effective to inhibit c-Met enzymatic activity.Communicated by Ramaswamy H. Sarma.

Combined computational approaches for developing new anti-Alzheimer drug candidates: 3D-QSAR, molecular docking and molecular dynamics studies of liquiritigenin derivatives.

Butyrylcholinesterase is an acetylcholine-degrading enzyme involved in the memorization process, which is becoming an interesting target for the symptomatic treatment of Alzheimer's disease. In the present investigation, the structure-activity relationship of a set of Liquiritigenin derivatives recently revealed to be Butyrylcholinesterase inhibitors was studied basing on comparative field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMISA). As a result, performant models with high predictive capability have been developed (CoMFA model: R2 = 0.91, Q2 = 0.62, R2 pred = 0.85; CoMISA model: R2 = 0.92, Q2 = 0.59, R2 pred = 0.83) and implemented to design new Liquiritigenin derivatives with improved activity. Besides, the affinity of the designed derivatives towards the active site of Butyrylcholinesterase, was confirmed by molecular docking and molecular dynamics studies. Moreover, they exhibited good pharmacokinetics properties. Accordingly, the outcomes of the present investigations can provide important direction for the development of new anti-Alzheimer's drug candidates.

Design of novel benzimidazole derivatives as potential α-amylase inhibitors using QSAR, pharmacokinetics, molecular docking, and molecular dynamics simulation studies.

In the present study, a quantitative relationship between the biological inhibitory activity of alpha-amylase and molecular structures of novel benzimidazole derivatives is analyzed in silico. The best QSAR model screened via MLR technique indicated that the exact mass, topological diameter and numerical rotational bonding structural properties of benzimidazole derivatives highly affect the bioactivity of these compounds against α-amylase. Based on the structural properties identified via linear QSAR model favorable for improving pIC50 of benzimidazole derivatives, fourteen new molecules bearing benzimidazole radicals were designed and their biological inhibitory activity against α-amylase was improved. QSAR model predictions showed that the designed molecules exhibited a higher potential biological level activity IC50 than acarbose used in positive control (IC50= 1.46 µM). Screening of drug-like properties, pharmacokinetics and toxicity of the proposed molecules led to select three molecules as candidates for use as drug aid to ingest starch and glycogen. As a result, using molecular docking simulations, the docking poses of the three molecules inside the α-amylase receptor pocket (PDB code: 1HNY) were predicted. Also, the most important potential interactions between the active amino acid sites in α-amylase protein pocket and the proposed drug molecules were described. The obtained hypotheses regarding the stability of the proposed molecules inside α-amylase pocket were validated by carrying out molecular dynamic simulations in aqueous background similar to the ones of proteins. The DM results confirmed the optimal stability of the α-amylase backbone with the drug molecules proposed in this computational investigation.