CADD Methods for Developing Novel Compounds Synthesized to Inhibit Tyrosine Kinase Receptors.

Growth factors and their receptor tyrosine kinases play a central role in regulating vital cellular processes such as proliferation, differentiation, division, and cell survival, and they are closely associated with the development of various types of cancer, particularly in the context of angiogenesis. Although several small chemical compounds targeting tyrosine kinase receptors have been approved by the FDA for cancer treatment by inhibiting angiogenesis, there is still a need for more effective medications. in silico studies are now crucial tools for the design of new drugs, offering considerable advantages such as cost and time reduction. In this review, we examined recent in silico research carried out between 2022 and 2024, focusing on new drug candidates synthesized to fight cancer, in particular by targeting tyrosine kinase receptors involved in the process of angiogenesis.

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.

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.

Design of New Aromatic Tertiary Amine-based as Butyrylcholinesterase Inhibitors Relying on Molecular Docking, ADME-Tox and Molecular Dynamics.

INTRODUCTION: Butyrylcholinesterase (BChE) plays a pivotal role in the progression of Alzheimer's disease. Empirical research demonstrated a fundamental alteration in the role of BChE concerning the reduction of cholinergic neurotransmission within the brains of individuals at advanced stages of Alzheimer's. METHOD: This study focuses on developing potent inhibitors for Butyrylcholinesterase (BChE) in the context of Alzheimer's disease (AD) treatment. Building upon previous research, a series of 44 aromatic tertiary amine-based compounds was investigated. Starting with ADME-Tox studies, the pharmacokinetic and pharmacodynamic properties of the compounds were analyzed to select promising candidates for BChE inhibition, which is a crucial factor in AD pathology. RESULTS: Molecular docking analyses identified compound M18 as the most promising candidate, and further compounds (X9 and X10) were proposed based on M18's chemical structure. These compounds displayed superior properties in terms of binding energies and hydrogen bonds in comparison to M18. CONCLUSION: The Molecular Dynamics (MD) simulations, which are over a 500 ns timeframe, confirmed the conformational stability of compounds X9 and X10, compared to M18. Overall, the stated results suggest that the proposed compounds, including X9 and X10 specifically, have a significant potential as candidates for BChE inhibition. This presents a promising avenue for therapeutic intervention in Alzheimer's disease.

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.

Rational Design of New Small Derivatives of 2,2'-Bithiophene as Hole Transport Material for Perovskite Solar Cells.

Using Density Functional Theory (DFT) and Time Dependent DFT (TD-DFT) methods, this inquiry theoretically examines seven novel hole-transport materials (HTMs) namely DFBT1, DFBT2, DFBT3, DFBT4, DFBT5, DFBT6, and DFBT7 based on the 2,2'bithiophene core for future use as HTMs for perovskite solar cells (PSCs). The model molecule has been modified through substituting the end groups situated on the diphenylamine moieties with a tow acceptor bridged by thiophene, this modification was performed to test the impact of the π-bridge and acceptor on the electronic, photophysical, and photovoltaic properties of the newly created molecules. DFBT1 - DFBT7 displayed a lower band gap (1.49 eV to 2.69 eV) than the model molecule (3.63 eV). Additionally, the newly engineered molecules presented a greater λmax ranging from 393.07 nm to 541.02 nm in dimethylformamide solvent, as compared to the model molecule (380.61 nm). The PCEs of all newly designed molecules (22.42% to 29.21%) were high compared with the reference molecule (19.62%). Thus, this study showed that all seven newly small molecules were excellent candidates for a novel PSC.

A comprehensive computational study to explore promising natural bioactive compounds targeting glycosyltransferase MurG in Escherichia coli for potential drug development.

Peptidoglycan is a carbohydrate with a cross-linked structure that protects the cytoplasmic membrane of bacterial cells from damage. The mechanism of peptidoglycan biosynthesis involves the main synthesizing enzyme glycosyltransferase MurG, which is known as a potential target for antibiotic therapy. Many MurG inhibitors have been recognized as MurG targets, but high toxicity and drug-resistant Escherichia coli strains remain the most important problems for further development. In addition, the discovery of selective MurG inhibitors has been limited to the synthesis of peptidoglycan-mimicking compounds. The present study employed drug discovery, such as virtual screening using molecular docking, drug likeness ADMET proprieties predictions, and molecular dynamics (MD) simulation, to identify potential natural products (NPs) for Escherichia coli. We conducted a screening of 30,926 NPs from the NPASS database. Subsequently, 20 of these compounds successfully passed the potency, pharmacokinetic, ADMET screening assays, and their validation was further confirmed through molecular docking. The best three hits and the standard were chosen for further MD simulations up to 400 ns and energy calculations to investigate the stability of the NPs-MurG complexes. The analyses of MD simulations and total binding energies suggested the higher stability of NPC272174. The potential compounds can be further explored in vivo and in vitro for promising novel antibacterial drug discovery.

Identification of Potent Acetylcholinesterase Inhibitors as New Candidates for Alzheimer Disease via Virtual Screening, Molecular Docking, Dynamic Simulation, and Molecular Mechanics-Poisson-Boltzmann Surface Area Calculations.

Huperzine A (HUP) plays a crucial role in Alzheimer's therapy by enhancing cognitive function through increased cholinergic activity as a reversible acetylcholinesterase (AChE) inhibitor. Despite some limitations being seen in AChE inhibitors, ongoing research remains dedicated to finding innovative and more effective treatments for Alzheimer's disease. To achieve the goal of the discovery of potential HUP analogues with improved physicochemical properties, less toxic properties, and high biological activity, many in silico methods were applied. Based on the acetylcholinesterase-ligand complex, an e-pharmacophore model was developed. Subsequently, a virtual screening involving a collection of 1762 natural compounds, sourced from the PubChem database, was performed. This screening yielded 131 compounds that exhibited compatibility with the established pharmacophoric hypothesis. These selected ligands were then subjected to molecular docking within the active site of the 4EY5 receptor. As a result, we identified four compounds that displayed remarkable docking scores and exhibited low free binding energy to the target. These top four compounds, CID_162895946, CID_44461278, CID_44285285, and CID_81108419, were submitted to ADMET prediction and molecular dynamic simulations, yielding encouraging findings in terms of their pharmacokinetic characteristics and stability. Finally, the molecular dynamic simulation, cross-dynamic correlation matrix, free energy landscape, and MM-PBSA calculations demonstrated that two ligands from the selected ligands formed very resilient complexes with the enzyme acetylcholinesterase, with significant binding affinity. Therefore, these two compounds are recommended for further experimental research as possible (AChE) inhibitors.

Computer-Aided Strategy on 5-(Substituted benzylidene) Thiazolidine-2,4-Diones to Develop New and Potent PTP1B Inhibitors: QSAR Modeling, Molecular Docking, Molecular Dynamics, PASS Predictions, and DFT Investigations.

A set of 5-(substituted benzylidene) thiazolidine-2,4-dione derivatives was explored to study the main structural requirement for the design of protein tyrosine phosphatase 1B (PTP1B) inhibitors. Utilizing multiple linear regression (MLR) analysis, we constructed a robust quantitative structure-activity relationship (QSAR) model to predict inhibitory activity, resulting in a noteworthy correlation coefficient (R2) of 0.942. Rigorous cross-validation using the leave-one-out (LOO) technique and statistical parameter calculations affirmed the model's reliability, with the QSAR analysis revealing 10 distinct structural patterns influencing PTP1B inhibitory activity. Compound 7e(ref) emerged as the optimal scaffold for drug design. Seven new PTP1B inhibitors were designed based on the QSAR model, followed by molecular docking studies to predict interactions and identify structural features. Pharmacokinetics properties were assessed through drug-likeness and ADMET studies. After that density functional theory (DFT) was conducted to assess the stability and reactivity of potential diabetes mellitus drug candidates. The subsequent dynamic simulation phase provided additional insights into stability and interactions dynamics of the top-ranked compound 11c. This comprehensive approach enhances our understanding of potential drug candidates for treating diabetes mellitus.

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.

Design of new molecules against cervical cancer using DFT, theoretical spectroscopy, 2D/3D-QSAR, molecular docking, pharmacophore and ADMET investigations.

Cervical cancer is a major health problem of women. Hormone therapy, via aromatase inhibition, has been proposed as a promising way of blocking estrogen production as well as treating the progression of estrogen-dependent cancer. To overcome the challenging complexities of costly drug design, in-silico strategy, integrating Structure-Based Drug Design (SBDD) and Ligand-Based Drug Design (LBDD), was applied to large representative databases of 39 quinazoline and thioquinazolinone compound derivatives. Quantum chemical and physicochemical descriptors have been investigated using density functional theory (DFT) and MM2 force fields, respectively, to develop 2D-QSAR models, while CoMSIA and CoMFA descriptors were used to build 3D-QSAR models. The robustness and predictive power of the reliable models were verified, via several validation methods, leading to the design of 6 new drug-candidates. Afterwards, 2 ligands were carefully selected using virtual screening methods, taking into account the applicability domain, synthetic accessibility, and Lipinski's criteria. Molecular docking and pharmacophore modelling studies were performed to examine potential interactions with aromatase (PDB ID: 3EQM). Finally, the ADMET properties were investigated in order to select potential drug-candidates against cervical cancer for experimental in vitro and in vivo testing.

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.

Ligand-Based Design of Novel Quinoline Derivatives as Potential Anticancer Agents: An In-Silico Virtual Screening Approach.

In this study, using the Comparative Molecular Field Analysis (CoMFA) approach, the structure-activity relationship of 33 small quinoline-based compounds with biological anti-gastric cancer activity in vitro was analyzed in 3D space. Once the 3D geometric and energy structure of the target chemical library has been optimized and their steric and electrostatic molecular field descriptions computed, the ideal 3D-QSAR model is generated and matched using the Partial Least Squares regression (PLS) algorithm. The accuracy, statistical precision, and predictive power of the developed 3D-QSAR model were confirmed by a range of internal and external validations, which were interpreted by robust correlation coefficients (RTrain2=0.931; Qcv2=0.625; RTest2=0.875). After carefully analyzing the contour maps produced by the trained 3D-QSAR model, it was discovered that certain structural characteristics are beneficial for enhancing the anti-gastric cancer properties of Quinoline derivatives. Based on this information, a total of five new quinoline compounds were developed, with their biological activity improved and their drug-like bioavailability measured using POM calculations. To further explore the potential of these compounds, molecular docking and molecular dynamics simulations were performed in an aqueous environment for 100 nanoseconds, specifically targeting serine/threonine protein kinase. Overall, the new findings of this study can serve as a starting point for further experiments with a view to the identification and design of a potential next-generation drug for target therapy against cancer.

Design of new small molecules derived from indolin-2-one as potent TRKs inhibitors using a computer-aided drug design approach.

Tropomyosin receptor kinase (TRKs) enzymes are responsible for cancers associated with the neurotrophic tyrosine kinase receptor gene fusion and are identified as effective targets for anticancer drug discovery. A series of small-molecule indolin-2-one derivatives showed remarkable biological activity against TRKs enzymatic activity. These small molecules could have an excellent profile for pharmaceutical application in the treatment of cancers caused by TRKs activity. The aim of this study is to modify the structure of these molecules to obtain new molecules with improved TRK inhibitory activity and pharmacokinetic properties favorable to the design of new drugs. Based on these series, we carried out a 3D-QSAR study. As a result, robust and reliable CoMFA and CoMSIA models are developed and applied to the design of 11 new molecules. These new molecules have a biological activity superior to the most active molecule in the starting series. The eleven designed molecules are screened using drug-likeness, ADMET proprieties, molecular docking, and MM-GBSA filters. The results of this screening identified the T1, T3, and T4 molecules as the best candidates for strong inhibition of TRKs enzymatic activity. In addition, molecular dynamics simulations are performed for TRK free and complexed with ligands T1, T3, and T4 to evaluate the stability of ligand-protein complexes over the simulation time. On the other hand, we proposed experimental synthesis routes for these newly designed molecules. Finally, the designed molecules T1, T2, and T3 have great potential to become reliable candidates for the conception of new drug inhibitors of TRKs.Communicated by Ramaswamy H. Sarma.

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.

Molecular docking, drug-likeness and DFT study of some modified tetrahydrocurcumins as potential anticancer agents.

The present study utilized molecular docking and density functional theory (DFT) approaches, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties to investigate the binding interactions, reactivity, stability, and drug-likeness of curcumin (1), tetrahydrocurcumin (2), and tetrahydrocurcumin derivatives (3-6) as potential anti-cancer agents. MGL (Molecular Graphic Laboratory) and Discovery Studio Visualizer (DSV) software employed for docking studies. Pharmacokinetic and pharmacodynamic (ADME-Tox) analyses were conducted using SwissADME and pKCSM web servers. Total Electron Density (TED) measurements identified molecular adsorption sites, considering various factors, including quantum chemical characteristics, to assess compound effectiveness using DFT method implanted in the Gaussian software. The binding energy (Eb) from docking simulations was used to evaluate inhibitory potential. ADMET analysis suggested favorable oral bioavailability and pharmacokinetics for all studied substances, excluding compound 4. DFT and docking investigations highlighted compounds 1, 2, and 6 as optimal scaffolds for drug design based on in silico screening tests.

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.