Design of novel isoxazole derivatives as tubulin inhibitors using computer-aided techniques: QSAR modeling, in silico ADMETox, molecular docking, molecular dynamics, biological efficacy, and retrosynthesis.

In the current work, computational methods were used to investigate new isoxazole derivatives that could be used as tubulin inhibitors. The study aims to develop a reliable quantitative structure-activity relationship (QSAR) model, following the criteria set by Golbraikh, Tropsha, and Roy. As a result, seven candidate compounds were developed, all having higher activity than the well-established anticancer agent Cisplatin (Cisp). According to the ADMETox in silico test, the candidates Pr4, Pr5, and P6 can be toxic. As a result, we have chosen to focus our study on compounds Pr1, Pr2, and Pr3. Molecular docking analysis revealed that drug candidate Pr2 exhibits the highest stability within the oxidized quinone reductase 2 (PDB ID: 4zvm), target receptor (ΔG(Pr2) = ΔG(Pr3) = -10.4 < ΔG(Pr1) = -10.0 < ΔG(Cisp) = -7.3 kcal/mol). This finding aligns with the activity predictions made by the QSAR model. Furthermore, molecular dynamics simulations of the Pr2-4zvm complex over 100 ns confirm the ligand's robust stability within the receptor's active site, supporting the results obtained from molecular docking and the QSAR model predictions. The CaverDock software was utilized to identify the tunnels likely to be followed by ligands moving from the active site to the receptor surface. This analysis also helped in determining the biological efficacy of the target compounds. The results indicated that the Pr2 compound is more effective than the others. Finally, the computer-assisted retrosynthesis process of two high confidence sequences was used to synthesize drug candidates.Communicated by Ramaswamy H. Sarma.

3D-QSAR methods were used to design eight new compounds and anti-tubulin agents.3D-QSAR models were validated by Golbraikh­Tropsha and Roy methods.The toxicity and pharmacokinetics of the proposed compounds were identified by the Lipinski rule of five, Veber rules, and ADMETox.Pr2 and Pr3 had a reasonable affinity to the receptor protein (ID PDB: 4zvm) based on molecular docking, reactivity indices, and molecular dynamics simulation.Metadynamics was used to study ligand transport in the receptor (ID PDB:3zvm).

The ethnopharmacological study of plant drugs used traditionally in Djibouti for malaria treatment.

ETHNOPHARMACOLOGICAL RELEVANCE: Djibouti was a country where malaria has been endemic for centuries. The local population use the plants as repellents or first aid for uncomplicated malaria. AIM OF THE STUDY: The aim was, for the first time, to collect and identify plants used by the local population to treat malaria and select the most interesting plants (those that are more commontly used, more available, and have fewer studies). These plants were evaluated for their antiplasmodial activity as well as their cytotoxicity on human cell lines for the most active ones. MATERIALS AND METHODS: A semi-structured questionnaire was developed for this study to collect information about the use and identity of botanical drugs used to treat malaria. The use-reports (percentage) of each plant were recorded to determine their use importance. Also, the availability status of the plants was assessed; and those in critical condition were discarded excluded from further study. Fifteen plants, out of the 41 listed, were extracted with hydro alcohol, ethyl acetate, and dichloromethane for biological testing. Chloroquine-resistant strain FcB-1 of P. falciparum and a human diploid embryonic lung cell line were used for the antiplasmodial test, and to assess the cytotoxicity for human cells respectively. Preliminary analysis of extract constituents was carried out using thin layer chromatography (TLC). RESULTS: This study identifies 41 plant taxa belonging to 32 families and records their use against malaria. Balanites rodunfolia, belonging to the Zygophyllaceae family, was the most commonly used plant, representing 44 % of use-reports. It was followed by Cadaba rodunfolia (15 %) from the Capparaceae family, and then the three species of Aloe: Aloe djiboutiensis (8.2 %), Aloe ericahenriettae (3.4 %), and Aloe rigens (3.4 %) from the Asphodelaceae family. The leaves are the most commonly used part of the plants to treat malaria, accounting for 76 % of usage. The preparation methods were decoction (52 %), maceration (29 %), and boiling (19 %). The administration routes were by oral (80 %), inhalation 19 %), and bathing (1 %). The best antiplasmodial activities were observed in the dichloromethane extracts of Cymbopogon commutatus and the ethyl acetate extracts of Aloe rigens and Terminalia brownii, with IC50 values of 9.8, 5, and 7.5 µg/mL, respectively. Their toxicity/activity levels were very favorable with selectivity indices of 5.6, 8.1, and 11.8 for C. commutatus, A. rigens, and T. Brownii, respectively. CONCLUSION: Forty-one species of botanical drugs were listed as being used to treat malaria in Djibouti. All fifteen selected species showed antiplasmodial activity (IC50 < 50 µg/mL). This work will help guide the valorization of botanical drugs used to treat malaria in Djibouti.

Molecular toxicity of nitrobenzene derivatives to tetrahymena pyriformis based on SMILES descriptors using Monte Carlo, docking, and MD simulations.

It is challenging to model the toxicity of nitroaromatic compounds due to limited experimental data. Nitrobenzene derivatives are commonly used in industry and can lead to environmental contamination. Extensive research, including several QSPR studies, has been conducted to understand their toxicity. Predictive QSPR models can help improve chemical safety, but their limitations must be considered, and the molecular factors affecting toxicity should be carefully investigated. The latest QSPR methods, molecular modeling techniques, machine learning algorithms, and computational chemistry tools are essential for developing accurate and robust models. In this work, we used these methods to study a series of fifty compounds derived from nitrobenzene. The Monte Carlo approach was used for QSPR modeling by applying the SMILES molecular structure representation and optimal molecular descriptors. The correlation ideality index (CII) and correlation contradiction index (CCI) were further introduced as validation parameters to estimate the developed models' predictive ability. The statistical quality of the CII models was better than those without CII. The best QSPR model with the following statistical parameters (Split-3): (R2 = 0.968, CCC = 0.984, IIC = 0.861, CII = 0.979, Q2 = 0.954, QF12 = 0.946, QF22 = 0.938, QF32 = 0.947, Rm2 = 0.878, RMSE = 0.187, MAE = 0.151, FTraining = 390, FInvisible = 218, FCalibration = 240, RTest2 = 0.905) was selected to generate the studied promoters with increasing and decreasing activity.

Computational evaluation of 1,2,3-triazole-based VEGFR-2 inhibitors: anti-angiogenesis potential and pharmacokinetic assessment.

The vascular endothelial growth factor (VEGF) and its cell surface receptor, as well as the human VEGFR-2 domain kinase, are some of the signaling pathways that have received the most attention in this field. This study aimed to identify novel molecules as VEGFR-2 inhibitors using 3D-QSAR modeling based on 1,2,3-triazole. Docking studies and dynamic simulations were performed to analyze novel interactions with the inhibitors and validate the molecular docking, dynamic simulations, and ADMET analyses. The optimized CoMSIA/SEH model showed good statistical results, and molecular docking and molecular dynamics simulations demonstrated stability of M3 ligand with the receptor and provided insight into ligand-receptor interactions. The newly developed compounds performed well in ADMET evaluations and showed promising results using Lipinski's rule of five, suggesting that the molecule M3 could be a useful anti-angiogenesis agent. In conclusion, this study provides insights into the structure-activity relationship of VEGFR-2 inhibitors and identifies M3 as a potential new anti-angiogenesis drug. The methodology used in this study can be applied to other similar drug targets to discover new and potent inhibitors.Communicated by Ramaswamy H. Sarma.

Exploring azomethine ylides reactivity with acrolein through cycloaddition reaction and computational antiviral activity assessment against hepatitis C virus.

CONTEXT: The regioselectivity and diastereoselectivity of the 1,3-dipolar cycloaddition reaction between azomethine ylides and acrolein were investigated. The DFT studies revealed that the favored pathway leads to the formation of cis-cycloadduct pyrrolidine and these computational findings align with experimental observations. The cis-cycloadduct pyrrolidine product serves as an advanced intermediate in the synthesis of a hepatitis C virus inhibitor. For this, the antiviral activity of cis-cycloadduct pyrrolidine against cyclophilin A, the co-factor responsible for hepatitis C virus, was also evaluated through molecular docking simulations which revealed intriguing interactions and a high C-score, which were further confirmed by molecular dynamics simulations, demonstrating stability over a 100-ns simulation period. Furthermore, the cis-cycloadduct pyrrolidine exhibits favorable drug-like properties and a better ADMET profile compared to hepatitis C virus inhibitor. METHODS: Chemical reactivity studies were performed using DFT method by the functional B3LYP at 6-31G (d, p) computational level by GAUSSIAN 16 program. Frontal molecular orbitals theory used to investigate HOMO/LUMO interactions between azomethine ylides and acrolein. Findings of this approach were confirmed by global reactivity indices and electron displacement was investigated based on Fukui functions. Furthermore, the activation energies were determined after frequency calculations using TS Berny algorithm and transition states were confirmed by the presence of a single imaginary frequency. Moreover, antiviral activity of cis-cycloadduct was explored through molecular docking using Surflex-Dock suite SYBYL X 2.0, and molecular dynamics simulation using GROMACS program. Finally, drug-like properties were investigated with SwissADME and ADMETlab 2.0.

Theoretical investigation of the effect of changing the auxiliary acceptor on the performance of organic D-A'-A dyes used as sensitizers in DSSCs.

CONTEXT: Dye-sensitized solar cells (DSSCs) have displayed huge potential in inexpensive, efficient, and clean solar energy technology. In this work, seven new dyes with the structure D-A'-A were designed in which the thiophene in the reference dye was replaced by auxiliary acceptors (A'). These dyes consist mainly of a pyranylidene-based electron donor D and the cyanoacrylic acid moiety as acceptor A. A computational investigation was carried out on the effect of various auxiliary acceptors A' on the efficiency of D-A'-A dyes in isolation and after binding to the semiconductor TiO2. Optimized structures, geometrical, optoelectronic, and photovoltaic parameters were calculated to predict promising dyes for potential use as solar cell sensitizers, including band gap (Egap), natural bond orbital (NBO) analysis, nonlinear optical properties (NLO), UV-Vis absorption spectra, maximum absorption wavelength (λmax), reorganization energy (λtotal), light-harvesting efficiency (LHE), electron injection driving force (ΔGinject) and open-circuit photovoltage (VOC). The results of this study revealed that all designed dyes, compared to the reference dye, are characterized by small Egap and λtotal values as well as large λmax, in addition to significant NLO properties and large adsorption energy (Eads). Therefore, all studied dyes can be used as sensitizers in DSSC. METHODS: Using Density Functional Theory (DFT) approaches with the B3LYP functional and the 6-31G(d,p) basis set, all ground state geometries of the isolated dyes were fully optimized. Time-Dependent Density Functional Theory (TD-DFT) method using the CAM-B3LYP/6-31G(d,p)/IEF-PCM level was applied to simulate the UV-visible absorption properties. All isolated dye calculations were performed using the Gaussian 09 software package. DFT calculations have been carried out with the DMol3 package included in Materials Studio for simulating the adsorption of the investigated dyestuff on the TiO2 surface of anatase (101), using the generalized gradient corrected approximation (GGA) approach of the Perdew-Burke-Ernzerhof (PBE) functional with the basic set of digital double polarisation (DNP). To study the optical performance of dye@TiO2 the PBE/DNP method present in DMol3 was applied.

Identification of novel curcumin derivatives against pancreatic cancer: a comprehensive approach integrating 3D-QSAR pharmacophore modeling, virtual screening, and molecular dynamics simulations.

Pancreatic cancer, known as the "silent killer," poses a daunting challenge in cancer therapy. The dysregulation of the PI3Kα signaling pathway in pancreatic cancer has attracted considerable interest as a promising target for therapeutic intervention. In this regard, the use of curcumin derivatives as inhibitors of PI3Kα has emerged, providing a novel and promising avenue for developing effective treatments for this devastating disease. Computational approaches were employed to explore this potential and investigate 58 curcumin derivatives with cytotoxic activity against the Panc-1 cell line. Our approach involved ligand-based pharmacophore modeling and atom-based 3D-QSAR analysis. The resulting QSAR model derived from the best-fitted pharmacophore hypothesis (AAHRR_1) demonstrated remarkable performance with high correlation coefficients (R2) of 0.990 for the training set and 0.977 for the test set. The cross-validation coefficient (Q2) of 0.971 also validated the model's predictive power. Tropsha's recommended criteria, including the Y-randomization test, were employed to ensure its reliability. Furthermore, an enrichment study was conducted to evaluate the model's performance in identifying active compounds. AAHRR_1 was used to screen a curated PubChem database of curcumin-related compounds. Two molecules (CID156189304 and CID154728220) exhibited promising pharmacokinetic properties and higher docking scores than Alpelisib, warranting further investigation. Extensive molecular dynamics simulations provided crucial insights into the conformational dynamics within the binding site, validating their stability and behavior. These findings contribute to our understanding of the potential therapeutic effectiveness of these compounds as PI3Kα inhibitors in pancreatic cancer.Communicated by Ramaswamy H. Sarma.

Computational Prediction of 3,5-Diaryl-1H-Pyrazole and spiropyrazolines derivatives as potential acetylcholinesterase inhibitors for alzheimer disease treatment by 3D-QSAR, molecular docking, molecular dynamics simulation, and ADME-Tox.

The efficacy of 40 synthesized variants of 3,5-diaryl-1H-pyrazole and spiropyrazoline' derivatives as acetylcholinesterase inhibitors is verified using a quantitative three-dimensional structure-activity relationship (3D-QSAR) by comparative molecular field analysis (CoMFA) and molecular similarity index analysis (CoMSIA) models. In this research, different field models proved that CoMSIA/SE model is the best model with high predictive power compared to several models (Qved2 = O.65; R2 = 0.980; R2test = 0.727). Also, contour maps produced by CoMSIA/SE model have been employed to prove the key structural needs of the activity. Consequently, six new compounds have been generated. Among these compounds, M4 and M5 were the most active but remained toxic and had poor absorption capacities. While the M1, M2, M3 and M6 remained highly active while respecting ADMET's characteristics. Molecular docking results showed compound M2 better with acetylcholinesterase than compound 22. The interactions are classical hydrogen bonding with residues TYR:124, TYR:72, and SER:293, which play a critical role in the biological activity as AChE inhibitors. MD results confirmed the docking results and showed that compound M2 had satisfactory stability with (ΔGbinding = -151.225 KJ/mol) in the active site of AChE receptor compared with compound 22 (ΔGbinding = -133.375 KJ/mol). In addition, both compounds had good stability regarding RMSD, Rg, and RMSF. The previous results show that the newly designed compound M2 is more active in the active site of AChE receptor than compound 22.Communicated by Ramaswamy H. Sarma.

In silico research on new sulfonamide derivatives as BRD4 inhibitors targeting acute myeloid leukemia using various computational techniques including 3D-QSAR, HQSAR, molecular docking, ADME/Tox, and molecular dynamics.

Acute myeloid leukemia, a serious condition affecting stem cells, drives uncontrollable myeloblast proliferation, leading to accumulation. Extensive research seeks rapid, effective chemotherapeutics. A potential option is a BRD4 inhibitor, known for suppressing cell proliferation. Sulfonamide derivatives probed essential structural elements for potent BRD4 inhibitors. To achieve this goal, we employed 3D-QSAR molecular modeling techniques, including CoMFA, CoMSIA, and HQSAR models, along with molecular docking and molecular dynamics simulations. The validation of the 2D/3D QSAR models, both internally and externally, underscores their robustness and reliability. The contour plots derived from CoMFA, CoMSIA, and HQSAR analyses played a pivotal role in shaping the design of effective BRD4 inhibitors. Importantly, our findings highlight the advantageous impact of incorporating bulkier substituents on the pyridinone ring and hydrophobic/electrostatic substituents on the methoxy-substituted phenyl ring, enhancing interactions with the BRD4 target. The interaction mode of the new compounds with the BRD4 receptor (PDB ID: 4BJX) was investigated using molecular docking simulations, revealing favorable binding energies, supported by the formation of hydrogen and hydrophobic bonds with key protein residues. Moreover, these novel inhibitors exhibited good oral bioavailability and demonstrated non-toxic properties based on ADMET analysis. Furthermore, the newly designed compounds along with the most active one from series 58, underwent a molecular dynamics simulation to analyze their behavior. The simulation provided additional evidence to support the molecular docking results, confirming the sustained stability of the analyzed molecules over the trajectory. This outcome could serve as a valuable reference for designing and developing novel and effective BRD4 inhibitors.Communicated by Ramaswamy H. Sarma.

Analysis molecular design of novel D-A-Di-A-D conjugated compounds for high-efficiency organic solar cells.

CONTEXT: The work described in this section uses DFT/TD-DFT/B3LYP/6-31G (d,p) (density functional theory and time-dependent density functional theory) to study and simulate the structural, optoelectronic, and optical properties of a series of conjugated compounds based on a modular D-A-Di-A-D architecture. These compounds integrate the D donor unit (carbazole), the A acceptor unit (benzothiadiazole) and various Di donor units. Using AMPS-1D (analysis of micronic structure and photonics), work has been carried out to evaluate the photovoltaic performance of these conjugated compounds in the context of organic solar cells. The compounds show variable performance in terms of energy conversion efficiency, ranging from 7.11 to 11.70%. The addition of a PEDOT layer between the active layer and the anode results in a significant improvement in photovoltaic performance, with energy conversion efficiencies of up to 15.31%, the highest value achieved. The use of ZnO as an intermediate layer remarkably improves photovoltaic performance for all compounds, with notable energy conversion efficiencies reaching 17.13%, 17.20%, and 18%. All in all, the compounds studied present promising prospects as viable candidates for organic block heterojunction (BHJ) solar cell applications. METHODS: DFT/TD-DFT/B3LYP/6-31G (d,p), these acronyms stand for the computational methods used to study the properties of compounds. DFT, for "Density Functional Theory", is a quantum computation method used to describe the electronic and structural properties of molecular systems. TD-DFT, for "Time-Dependent Density Functional Theory", is an extension of DFT that allows the treatment of optical and excitation properties. B3LYP is a density functional frequently used in DFT to calculate molecular properties. In addition, 6-31G (d,p) refers to a basic wave function used to approximate the distribution of electrons in molecules. AMPS-1D, or "Analysis of Micro and Photonic Structure", is a modeling tool for studying the photovoltaic properties of multilayer structures, particularly in the context of organic solar cells.

Computational investigation of imidazo[2,1-b]oxazole derivatives as potential mutant BRAF kinase inhibitors: 3D-QSAR, molecular docking, molecular dynamics simulation, and ADMETox studies.

BRAF inhibitors are known to be an effective therapeutic target for treating melanoma and other types of cancer. Using 3D-QSAR, molecular docking, and MD simulations, this study evaluated various imidazo[2,1-b]oxazole derivatives that function as mutant BRAF kinase inhibitors. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were used to create the 3D-QSAR models. CoMSIA/SEHA model has solid predictive power across several models (Q2 = 0.578; R2 = 0.828; R2pred = 0.74) and is the best model according to the numerous field models generated. The created model's predictive power was evaluated through external validation using a test set. CoMSIA/SEHA contour maps collect information that can be used to identify critical regions with solid anticancer activity. We developed four inhibitors with high predicted activity due to these observations. ADMET prediction was used to assess the toxicity of the proposed imidazo[2,1-b]oxazole compounds. The predictive molecules (T1-T4) demonstrated good ADMET properties, excluding the toxic active compounds 11r from the database. Molecular docking was also used to determine the patterns and modes of interactions between imidazo[2,1-b]oxazole ligands and receptors, which revealed that the proposed imidazo[2,1-b]oxazole scaffold was stable in the receptor's active site (PDB code: 4G9C). The suggested compounds (T1-T4) were subjected to molecular dynamics simulations lasting 100 ns to determine their binding free energies. The results showed that T2 had a more favorable binding free energy (-149.552 kJ/mol) than T1 (-112.556 kJ/mol), T3 (-115.503 kJ/mol), and T4 (-102.553 kJ/mol). The results suggest that the imidazo[2,1-b]oxazole compounds investigated in this study have potential as inhibitors of BRAF kinase and could be further developed as anticancer drugs. Highlights22 imidazo[2,1-b]oxazole compounds were subjected to research on three-dimensional quantitative conformational relationships.Using contour maps from 3D-QSAR models as a guide was used to figure out the areas and strategies for structural optimization.Combined molecular docking, molecular dynamics simulations, and binding free energy calculations to verify the inhibitor activity of the proposed 22 imidazo[2,1-b]oxazole compounds.Four potential B-RAF Kinase inhibitors were discovered, providing theoretical clues for developing a highly anticancer agent.Communicated by Ramaswamy H. Sarma.

3D-QSAR, molecular docking, simulation dynamic and ADMET studies on new quinolines derivatives against colorectal carcinoma activity.

Cancer is the uncontrolled spread of abnormal cells that results in abnormal tissue growth in the affected organ. One of the most important organs is exposed to the growth of colon cancer cells, which start in the large intestine (colon) or the rectum. Several therapeutic protocols were used to treat different kinds of cancer. Recently, several studies have targeted tubulin and microtubules due to their remarkable prefoliation. Also, recent research shows that quinoline compounds have significant efficacy against human colorectal cancer. So, the present work investigated the potential of thirty quinoline compounds as tubulin inhibitors using computational methods. A 3D-QSAR approach using two contours (CoMFA and CoMSIA), molecular docking simulation to determine the binding type of the complexes (ligand-receptor), molecular dynamics simulation and identifying pharmacokinetic characteristics were used to design molecules. For all compounds designed (T1-5), molecular docking was used to compare the stability by type of binding. The ADMET has been utilized for molecules with good stability in molecular docking (T1-3); these compounds have good medicinal characteristics. Furthermore, a molecular dynamics simulation (MD) at 100 ns was performed to confirm the stability of the T1-3 compounds; the molecules (T1-3) remained the most stable throughout the simulation. The compounds T1, T2 and T3 are the best-designed drugs for colorectal carcinoma treatments.Communicated by Ramaswamy H. Sarma.

Profiling the structural determinants of pyrrolidine derivative as gelatinases (MMP-2 and MMP-9) inhibitors using in silico approaches.

Quantitative structure activity relationship (QSAR) studies on pyrrolidine derivatives have been established using CoMFA, CoMSIA, and Hologram QSAR analysis to estimate the values (pIC50) of gelatinase inhibitors. When the CoMFA cross-validation value, Q², was 0.625, the training set coefficient of determination, R² was 0.981. In CoMSIA, Q² was 0.749 and R² was 0.988. In the HQSAR, Q² was 0.84 and R² was 0.946. Visualization of these models was performed by contour maps showing favorable and unfavorable regions for activity, while visualization of HQSAR model was performed by a colored atomic contribution graph. Based on the results obtained of external validation, the CoMSIA model was statistically more significant and robust and was selected as the best model to predict new, more active inhibitors. To study the modes of interactions of the predicted compounds in the active site of MMP-2 and MMP-9, a simulation of molecular docking was realized. A combined study of MD simulations and calculation of free binding energy, were also carried out to validate the results obtained on the best predicted and most active compound in dataset and the compound NNGH as control compound. The results confirm the molecular docking results and indicate that the predicted ligands were stable in the binding site of MMP-2 and MMP-9.

Design new organic material based on triphenylamine (TPA) with D-π-A-π-D structure used as an electron donor for organic solar cells: A DFT approach.

Because of the increasing scarcity of fossil fuels and the growing need for energy, it has become necessary to research new renewable energy resources. In this study, five new high-performance materials (TP-FA1F-TP - TP-FA5F-TP) of the D-π-A-π-D configuration based on triphenylamine (TPA) were theoretically investigated by applying DFT and TD-DFT methods for future application as heterojunction organic solar cells (BHJ). The influence of the modification of the acceptor (A) of the parent molecule TP-FTzF-TP on the structural, electronic, photovoltaic and optical properties of the TP-FA1F-TP - TP-FA5F-TP organic molecules was investigated in detail. TP-FA1F-TP - TP-FA5F-TP showed Egap in the interval of 1.44-2.01 eV with λabs in the range of 536-774 nm, open-circuit voltage (Voc) values varied between 0.3 and 0.56 V and power conversion efficiencies (PCE) ranging from (3-6) %. Our results also show that the donor molecules suggested in this research exhibit an improved performance compared to the recently synthesized TP-FTzF-TP, such as a lowest HOMO energy, a smaller Egap, and a greater absorption spectrum, and can lead to higher performance. Indeed, this theoretical research could lead to the future synthesis of better compounds as active substances used in BHJ.

Structure-based virtual screening of novel natural products as chalcone derivatives against SARS-CoV-2 Mpro.

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, has spread quickly around the world, causing a global pandemic. It has infected more than 500 million people as of April 28, 2022. Much research has been reported to stop the virus from spreading, but there are currently no approved medicines to treat COVID-19. In this work, a dataset of 142 natural products collected from various medicinal plants was used to perform structure-based virtual screening (SBVS) through the combined application of molecular docking and molecular dynamics (MD) simulation methods. First, the dataset of compounds was optimized using the density functional theory (DFT) approach. The optimized compounds were then submitted to the first screening, which was done by the pKCM web server to look for drug-likeness and the PyRx to look for binding affinity. Among the 142 natural substances, 10 compounds were selected for docking validation. Compounds that interact with CYS145 and LEU141, the essential catalytic residues, as well as compounds with binding affinities less than -8.0 kcal/mol, are considered promising anti-SARS-CoV-2 drug candidates. The top-ranked compounds were then evaluated by MD simulations and MM-GBSA method. These results could help researchers come up with new natural compounds that could be used to treat SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Molecular modeling study of pyrrolidine derivatives as novel myeloid cell leukemia-1 inhibitors through combined 3D-QSAR, molecular docking, ADME/Tox and MD simulation techniques.

A series of pyrrolidine derivatives have been used to study the main structural requirements for designing novel Mcl-1 inhibitors. For this purpose, three models CoMSIA, CoMFA and HQSAR were generated using QSAR molecular modeling techniques. The statistical results of the CoMFA (Q2 = 0.689; R = 0.999; R2pred = 0.986), CoMSIA (Q2 = 0.614; R2 = 0.923; R2pred = 0.815) and HQSAR (Q2= 0.603; R2 = 0.662; R2pred = 0.743) models showed good stability and predictability. The results of the models were presented as contours and colored fragments indicating the favorable and unfavorable contribution to the inhibitory activity of Mcl-1. Based on the obtained results, four new compounds were designed with more potent predicted pIC50 inhibitory activity. The ADME/Tox results and the pharmacokinetic properties revealed that these four compounds are orally bioavailable and show good permeability. In addition the four compounds showing non-inhibitors of CYP3A4 and CYP2D6 with the exception of Pred03. At the level of toxicity profile, the compounds Pred01, Pred02 and Pred03 showed interesting results and showed no AMES toxicity, no hERG inhibition and no skin sensitization. Molecular docking results were used to uncover the mode of interaction between the ligand and key residues of protein binding site. Molecular docking results were supported by molecular simulation and binding free energy estimation (MMPBSA). These results demonstrate the stability of the analyzed compounds in the target protein binding site during a 100 ns trajectory. Finally, all these results create a strong lead to develop promising new Pyrrolidine-based inhibitors against Mcl-1.Communicated by Ramaswamy H. Sarma.

3D-QSAR modeling and molecular docking studies on a series of 2, 4, 5-trisubstituted imidazole derivatives as CK2 inhibitors.

Protein case in kinase II alpha subunit (CK2) plays an imperative function in treating cancer disease. Herein, we have performed a three-dimensional quantitative structure activity relationship (3D-QSAR), and molecular docking analysis on a novel series of 2, 4, 5-trisubstituted imidazole derivatives in order to design potent kinase II alpha subunit (CK2) inhibitors. The 3D-QSAR methods such as comparative molecular similarity indexes analysis (COMSIA), and the comparative molecular field analysis (COMFA) were investigate using twenty-four molecules of 2, 4, 5-trisubstituted imidazole derivatives as anticancer agent. The best COMFA and COMSIA models exhibit excellent Q2 values of 0.66 and 0.75 and R2 values of 0.98 and 0.99 respectively. To check the validity of the selected COMFA and COMSIA models, a variety of validation tests were utilized: Internal validation analyses, and externally validation beside Y-randomization according to the principles of the Organization for Economic Co-operation and Development (OECD), and the Golbraikh and Tropsha's criteria for the validation of 3D-QSAR models. The proposed models for COMFA and COMSIA analysis have been successful. The developed models, indicating that they were reliable for activity prediction. Based on the preceding results, we designed several new potent molecules. Such outcome can proffer helpful theoretical references for future experimental studies.Communicated by Ramaswamy H. Sarma.

Development of novel monoamine oxidase B (MAO-B) inhibitors by combined application of docking-based alignment, 3D-QSAR, ADMET prediction, molecular dynamics simulation, and MM_GBSA binding free energy.

Unsaturated ketone derivatives are known as inhibitors of monoamine oxidase B (MAO-B), a potential drug target of Parkinson's disease. Here, docking-based alignment, 3 D-QSAR (three-dimensional quantitative structure-activity relationship) studies, ADMET (absorption, distribution, metabolism, excretion, and toxicity) prediction, molecular dynamics (MD) simulation, and MM_GBSA binding free energy were performed on a novel series of MAO-B inhibitors. The objective is to predict new MAO-B inhibitors with high potency activity. The 3 D-QSAR models were created using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). Molecular docking findings indicated that compounds with strong inhibitory efficacy also had a high binding affinity. 3 D-QSAR studies showed the importance of steric, electrostatic, and H-bond acceptor fields on the inhibitory activity of MAO-B. Based on the appropriate 3 D-QSAR model, a new series of MAO-B inhibitors were predicted and their pharmacokinetic characteristics were evaluated using in silico ADMET prediction. All screened compounds show good oral bioavailability without any side effects. Moreover, the dynamic behavior and stability of the most active compounds were evaluated using MD simulations. The results showed that unsaturated ketone derivatives are stable and compact during the 100 ns of MD simulation. Finally, the binding free energy of complexes was determined using the MM_GBSA method; the findings indicated that the T1 compound is more stable (ΔGbinding = -409.506 KJ/mol) than the data set's highest active compound (ΔGbinding = -31.883 KJ/mol).Communicated by Ramaswamy H. Sarma.

Novel Eubacterium rectale inhibitor from Coriandrum sativum L. for possible prevention of colorectal cancer: a computational approach.

This research aims to screen out the effective bioactive compounds from Coriander (Coriandrum sativum L.), which may be novel potential inhibitors of Eubacterium rectale for the prevention of colorectal cancer (CRC). A series of 8 coriander-derived chemical compounds previously assessed for their anti-inflammatory, antioxidant, and antidiabetic activities were tested against Carbohydrate ABC transporter substrate-binding protein and compared to the standard inhibitor Acarbose, to support their use as novel Eubacterium rectale inhibitors. Herein, these derivatives were submitted to a thorough analysis of docking studies, in which detailed interactions of the selected phytocompounds with carbohydrate ABC transporter substrate-binding protein were revealed. Molecular docking analysis recommends Rutin, Gallocatechin, and Epigallocatechin as the most potential Eubacterium rectale inhibitors among the eight selected phytochemical compounds. Subsequently, the stability of the three selected phytochemical complexes was checked using molecular dynamics (MD) simulation at 100 ns and Molecular Mechanics combined with Poisson-Boltzmann Surface Area (MM-PBSA). The results show quite good stability for Rutin and Gallocatechin. In silico ADMET prediction was performed on the selected compounds, and the findings revealed a reasonably good ADMET profile for both Rutin and Gallocatechin. The current findings predict that Gallocatechin could be a better CRC preventive natural compound, and, further in vitro, in vivo and clinical studies may confirm its therapeutic potential.Communicated by Ramaswamy H. Sarma.

In silico identification of 1,2,4-triazoles as potential Candida Albicans inhibitors using 3D-QSAR, molecular docking, molecular dynamics simulations, and ADMET profiling.

Fluconazole and Voriconazole are individual antifungal inhibitors broadly adopted for treating fungal infections, including Candida Albicans. Unfortunately, these medicines clinically used have significant side effects. Consequently, the improvement of safer and better therapy became more indispensable. In this study, a set of 27 1,2,4-triazole compounds have been tested as potential Candida Albicans inhibitors by using different theoretical methods. The created comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) contour maps significantly impacted the development of novel Candida Albicans inhibitors with valuable activities. The mode of interactions between the 1,2,4-triazole inhibitors and the targeted receptor was studied by molecular docking simulation. The proposed new molecule P1 showed satisfied stability in the active pocket of the targeted receptor compared to the more active molecule in the dataset compared to Fluconazole medication. Meanwhile, the binding energy obtained by molecular docking for molecule P1 is - 9.3 kcal/mol compared with - 6.7 kcal/mol for Fluconazole medication. Also, MM/GBSA value obtained by molecular dynamics simulations at 100 ns for molecule P1 is - 33.34 kcal/mol compared with - 15.85 kcal/mol for Fluconazole medication. In addition, molecule P1 showed good oral bioavailability and was non-toxic according to ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties. Therefore, the results indicated compound P1 might be a future inhibitor of Candida Albicans infection.