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.

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.

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 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.

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.

Repositioning Cannabinoids and Terpenes as Novel EGFR-TKIs Candidates for Targeted Therapy Against Cancer: A virtual screening model using CADD and biophysical simulations.

This study examines the potential of Cannabis sativa L. plants to be repurposed as therapeutic agents for cancer treatment through designing of hybrid Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). A set of 50 phytochemicals was taken from Cannabinoids and Terpenes and subjected for screening using Semi-flexible and Flexible Molecular Docking methods, MM-GBSA free binding energy computations, and pharmacokinetic/pharmacodynamic (ADME-Tox) predictions. Nine promising phytochemicals, Cannabidiolic acid (CBDA), Cannabidiol (CBD), Tetrahydrocannabivarin (THCV), Dronabinol (Δ-9-THC), Delta-8-Tetrahydrocannabinol (Δ-8-THC), Cannabicyclol (CBL), Delta9-tetrahydrocannabinolic acid (THCA), Beta-Caryophyllene (BCP), and Gamma-Elemene (γ-Ele) were identified as potential EGFR-TKIs natural product candidates for cancer therapy. To further validate these findings, a set of Molecular Dynamics simulations were conducted over a 200 ns trajectory. This hybrid early drug discovery screening strategy has the potential to yield a new generation of EGFR-TKIs based on natural cannabis products, suitable for cancer therapy. In addition, the application of this computational strategy in the virtual screening of both natural and synthetic chemical libraries could support the discovery of a wide range of lead drug agents to address numerous diseases.

Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach.

The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer (NSCLC). In this context, the identification of new c-Met inhibitors based on heterocyclic small molecules could pave the way for the development of a new cancer therapeutic pathway. Using multiple linear regression (MLR)-quantitative structure-activity relationship (QSAR) and artificial neural network (ANN)-QSAR modeling techniques, we look at the quantitative relationship between the biological inhibitory activity of 40 small molecules derived from cyclohexane-1,3-dione and their topological, physicochemical, and electronic properties against NSCLC cells. In this regard, screening methods based on QSAR modeling with density-functional theory (DFT) computations, in silico pharmacokinetic/pharmacodynamic (ADME-Tox) modeling, and molecular docking with molecular electrostatic potential (MEP) and molecular mechanics-generalized Born surface area (MM-GBSA) computations were used. Using physicochemical (stretch-bend, hydrogen bond acceptor, Connolly molecular area, polar surface area, total connectivity) and electronic (total energy, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels) molecular descriptors, compound 6d is identified as the optimal scaffold for drug design based on in silico screening tests. The computer-aided modeling developed in this study allowed us to design, optimize, and screen a new class of 36 small molecules based on cyclohexane-1,3-dione as potential c-Met inhibitors against NSCLC cell growth. The in silico rational drug design approach used in this study led to the identification of nine lead compounds for NSCLC therapy via c-Met protein targeting. Finally, the findings are validated using a 100 ns series of molecular dynamics simulations in an aqueous environment on c-Met free and complexed with samples of the proposed lead compounds and Foretinib drug.

Synthesis, Characterization, 'ADMET-SAR' Prediction, DPPH Assay, and Anti-Mycobacterium Study of 4-[(substituted benzyl) amino]benzo hydrazides and its Hydrazones as the Acyl-CoA Carboxylase, AccD5 Inhibitors.

BACKGROUND: Hydrazide-hydrazone derivatives have shown diverse biological activities, such as antitubercular (anti-TB), antibacterial, antifungal, anticancer, anti-inflammatory, antiviral, and antiprotozoal actions. OBJECTIVES: Hydrazide-hydrazones contain azomethine (-NH-N=CH-) group connected with carbonyl group and are believed to be responsible for various pharmaceutical applications. They aid in the synthesis of different five-membered heterocyclic systems, such as oxadiazole, triazoles, etc. Methods: In the present study, various hydrazines/hydrazones were synthesized starting from 4- amino benzoic acid derivatives. Structures of all 9 newly synthesized compounds (6a-6d and 8a- 8e) were further characterized by using various spectroscopic methods, such as 1H-NMR (Nuclear Magnetic Resonance), FT-IR (Fourier-transform infrared spectroscopy), Gas chromatographymass spectrometry (GC-MS), etc. Furthermore, molecular docking analysis against the acyl-CoA carboxylase, AccD5 (PDB ID: 2A7S), was also carried out using the Glide module, which depicted good binding scores than standard drugs. The anti-tuberculosis activity of all the hydrazides and hydrazones (6a-6d and 8a-8e) were evaluated against the Mycobacterium tuberculosis H37 RV strain using the Alamar-Blue susceptibility (MABA) test. The activity was expressed as the minimum inhibitory concentration (MIC) in µg/mL values. The antioxidant activity was also carried out using a DPPH assay. RESULTS: Our findings demonstrated highly encouraging in-vitro results (MABA assay, MIC: 1.2 µg/mL) of hydrazones as depicted by good antimycobacterial activity. The antioxidant results showed a moderate to a good percentage of DPPH inhibition. Our in-silico ADMET analysis further suggested good pharmacokinetic and toxicity-free profiles of synthesized analogues (6a-6d and 8a-8e). CONCLUSION: Our results signify hydrazones/hydrazines as potential hit candidates against the future developments of potent and safer anti-TB agents.

Analysis and prediction pathways of natural products and their cytotoxicity against HeLa cell line protein using docking, molecular dynamics and ADMET.

Natural product such as flavonoids and their derivatives have a discernible capability to inhibit tumor formation and the growth of cancer cell, which have a vital link between diet and chronic disease prevention. Several plants and spices that contain flavonoid derivatives have been used in traditional medicine as disease preventative and therapeutic agents. Therefore, flavonoids could be used as chemotherapeutic drugs, indicating their potential clinical utility in cancer treatment. The purpose of this research was to discover and produce innovative pharmaceuticals from natural sources by introducing structural changes into flavonoids' backbones and changing their structures to improve biological activity and anticancer effects. In the current study, it was expected that the percent unbound values for the 15 compounds in human plasma would be low, ranging between 0.188 and 0.391. However, all compounds have a safe range and are not toxic to the brain. Compounds 2, 10, and 13 were shown to be permeable to the CNS (log PS > -3), but all other compounds had difficulty penetrating the CNS. Furthermore, all compounds had a low total clearance, ranging from 0.038 to 1.216 ml/min/kg, indicating that these compounds have a long half-life. None of the compounds caused skin sensitization (SS), and only compounds 1, 11, and 12 are expected to be AMES-positive, suggesting that the other compounds are not mutagenic. The result of the study showed based on the Drug-likeness and ADMET studies, only 3 compounds, including 3, 4, and 15, have a good pharmacokinetics propriety, the lowest toxicity, and good binding affinity towards Caspase 3 V266APDB (ID: 5I9B) as potential inhibitor candidates for the HeLa cell line, they have a low total clearance property and no AMES mutagenicity or hERG inhibition properties. These compounds (3,4,15) were examined to act as new cytotoxic drug candidates and would have an interest as starting point for designing compounds against the HeLa cell line.Communicated by Ramaswamy H. Sarma.

Pharmacophore-based virtual screening, molecular docking, and molecular dynamics studies for the discovery of novel FLT3 inhibitors.

FLT3 is considered a potential target of acute myeloid leukemia therapy. In this study, we applied a computer-aided methodology unifying molecular docking and pharmacophore screening to identify potent inhibitors against FLT3. To investigate the pharmacophore area and binding mechanism of FLT3, the reported co-crystallized Gilteritinib ligand was docked into the active site using Glide XP. Based on the docking results, we identified structure-based pharmacophore characteristics resistant to potent FLT3 inhibitors. The best hypothesis was corroborated using test and decoy sets, and the verified hypo was utilized to screen the chemical database. The hits from the pharmacophore-based screening were then screened again using a structure-based method that included molecular docking at various precisions; the selected molecules were further examined and refined using drug-like filters and ADMET analysis. Finally, two hits were picked out for molecular dynamic simulation. The results showed two hits were expected to have potent inhibitory activity and excellent ADMET characteristics, and they might be used as new leads in the development of FLT3 inhibitors.Communicated by Ramaswamy H. Sarma.

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.

Design of novel quinoline derivatives as antibreast cancer using 3D-QSAR, molecular docking and pharmacokinetic investigation.

Breast cancer has been one of the most challenging women's cancers and leading cause of mortality for decades. There are several studies being conducted all the time to find a cure for breast cancer. Quinoline derivatives have shown their potential as antitumor agents in breast cancer therapy. In this work, three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking with aromatase enzyme (Protein Data Bank: 3S7S) studies were performed to suggest the current scenario of quinoline derivatives as antitumor agents and to refine the path of these derivatives to discover and develop new drugs against breast cancer. For developing the 3D-QSAR model, comparative molecular similarity indices analysis (CoMSIA) and comparative molecular field analysis (CoMFA) were included. To attain the high level of predictability, the best CoMSIA model was applied. External validation utilizing a test set has been used in order to validate the predictive capabilities of the built model. According to the findings, electrostatic, hydrophobic and hydrogen bond donor, and acceptor fields had a significant impact on antibreast cancer activity. Thus, we generated a variety of novel effective aromatase inhibitors based on prior findings and we predicted their inhibitory activity using the built model. In addition, absorption, distribution, metabolism, elimination and toxicity properties were employed to explore the effectiveness of new drug candidates.

Discovery of Phenylcarbamoylazinane-1,2,4-Triazole Amides Derivatives as the Potential Inhibitors of Aldo-Keto Reductases (AKR1B1 & AKRB10): Potential Lead Molecules for Treatment of Colon Cancer.

Both members of the aldo-keto reductases (AKRs) family, AKR1B1 and AKR1B10, are over-expressed in various type of cancer, making them potential targets for inflammation-mediated cancers such as colon, lung, breast, and prostate cancers. This is the first comprehensive study which focused on the identification of phenylcarbamoylazinane-1, 2,4-triazole amides (7a−o) as the inhibitors of aldo-keto reductases (AKR1B1, AKR1B10) via detailed computational analysis. Firstly, the stability and reactivity of compounds were determined by using the Guassian09 programme in which the density functional theory (DFT) calculations were performed by using the B3LYP/SVP level. Among all the derivatives, the 7d, 7e, 7f, 7h, 7j, 7k, and 7m were found chemically reactive. Then the binding interactions of the optimized compounds within the active pocket of the selected targets were carried out by using molecular docking software: AutoDock tools and Molecular operation environment (MOE) software, and during analysis, the Autodock (academic software) results were found to be reproducible, suggesting this software is best over the MOE (commercial software). The results were found in correlation with the DFT results, suggesting 7d as the best inhibitor of AKR1B1 with the energy value of −49.40 kJ/mol and 7f as the best inhibitor of AKR1B10 with the energy value of −52.84 kJ/mol. The other potent compounds also showed comparable binding energies. The best inhibitors of both targets were validated by the molecular dynamics simulation studies where the root mean square value of <2 along with the other physicochemical properties, hydrogen bond interactions, and binding energies were observed. Furthermore, the anticancer potential of the potent compounds was confirmed by cell viability (MTT) assay. The studied compounds fall into the category of drug-like properties and also supported by physicochemical and pharmacological ADMET properties. It can be suggested that the further synthesis of derivatives of 7d and 7f may lead to the potential drug-like molecules for the treatment of colon cancer associated with the aberrant expression of either AKR1B1 or AKR1B10 and other associated malignancies.

Unsymmetrical aromatic disulfides as SARS-CoV-2 Mpro inhibitors: Molecular docking, molecular dynamics, and ADME scoring investigations.

COVID-19 pandemic caused by very severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) agent is an ongoing major global health concern. The disease has caused more than 452 million affected cases and more than 6 million death worldwide. Hence, there is an urgency to search for possible medications and drug treatments. There are no approved drugs available to treat COVID-19 yet, although several vaccine candidates are already available and some of them are listed for emergency use by the world health organization (WHO). Identifying a potential drug candidate may make a significant contribution to control the expansion of COVID-19. The in vitro biological activity of asymmetric disulfides against coronavirus through the inhibition of SARS-CoV-2 main protease (Mpro) protein was reported. Due to the lack of convincing evidence those asymmetric disulfides have favorable pharmacological properties for the clinical treatment of Coronavirus, in silico evaluation should be performed to assess the potential of these compounds to inhibit the SARS-CoV-2 Mpro. In this context, we report herein the molecular docking for a series of 40 unsymmetrical aromatic disulfides as SARS-CoV-2 Mpro inhibitor. The optimal binding features of disulfides within the binding pocket of SARS-CoV-2 endoribonuclease protein (Protein Data Bank [PDB]: 6LU7) was described. Studied compounds were ranked for potential effectiveness, and those have shown high molecular docking scores were proposed as novel drug candidates against SARS-CoV-2. Moreover, the outcomes of drug similarity and ADME (Absorption, Distribution, Metabolism, and Excretion) analyses have may have the effectiveness of acting as medicines, and would be of interest as promising starting point for designing compounds against SARS-CoV-2. Finally, the stability of these three compounds in the complex with Mpro was validated through molecular dynamics (MD) simulation, in which they displayed stable trajectory and molecular properties with a consistent interaction profile.

Identification of potent inhibitors of NEK7 protein using a comprehensive computational approach.

NIMA related Kinases (NEK7) plays an important role in spindle assembly and mitotic division of the cell. Over expression of NEK7 leads to the progression of different cancers and associated malignancies. It is becoming the next wave of targets for the development of selective and potent anti-cancerous agents. The current study is the first comprehensive computational approach to identify potent inhibitors of NEK7 protein. For this purpose, previously identified anti-inflammatory compound i.e., Phenylcarbamoylpiperidine-1,2,4-triazole amide derivatives by our own group were selected for their anti-cancer potential via detailed Computational studies. Initially, the density functional theory (DFT) calculations were carried out using Gaussian 09 software which provided information about the compounds' stability and reactivity. Furthermore, Autodock suite and Molecular Operating Environment (MOE) software's were used to dock the ligand database into the active pocket of the NEK7 protein. Both software performances were compared in terms of sampling power and scoring power. During the analysis, Autodock results were found to be more reproducible, implying that this software outperforms the MOE. The majority of the compounds, including M7, and M12 showed excellent binding energies and formed stable protein-ligand complexes with docking scores of - 29.66 kJ/mol and - 31.38 kJ/mol, respectively. The results were validated by molecular dynamics simulation studies where the stability and conformational transformation of the best protein-ligand complex were justified on the basis of RMSD and RMSF trajectory analysis. The drug likeness properties and toxicity profile of all compounds were determined by ADMETlab 2.0. Furthermore, the anticancer potential of the potent compounds were confirmed by cell viability (MTT) assay. This study suggested that selected compounds can be further investigated at molecular level and evaluated for cancer treatment and associated malignancies.

QSAR, molecular docking and ADMET properties in silico studies of novel 4,5,6,7-tetrahydrobenzo[D]-thiazol-2-Yl derivatives derived from dimedone as potent anti-tumor agents through inhibition of C-Met receptor tyrosine kinase.

A quantitative structure-activity relationship (QSAR) study is performed on 48 novel 4,5,6,7-tetrahydrobenzo[D]-thiazol-2 derivatives as anticancer agents capable of inhibiting c-Met receptor tyrosine kinase. The present study is conducted using multiple linear regression, multiple nonlinear regression and artificial neural networks. Three QSAR models are developed after partitioning the database into two sets (training and test) via the k-means method. The obtained values of the correlation coefficients by the three developed QSAR models are 0.90, 0.91 and 0.92, respectively. The resulting models are validated by using the external validation, leave-one-out cross-validation, Y-randomization test, and applicability domain methods. Moreover, we evaluated the drug-likeness properties of seven selected molecules based on their observed high activity to inhibit the c-Met receptor. The results of the evaluation showed that three of the seven compounds present drug-like characteristics. In order to identify the important active sites for the inhibition of the c-Met receptor responsible for the development of cancer cell lines, the crystallized form of the Crizotinib-c-Met complex (PDB code: 2WGJ) is used. These sites are used as references in the molecular docking test of the three selected molecules to identify the most suitable molecule for use as a new c-Met inhibitor. A comparative study is conducted based on the evaluation of the predicted properties of ADMET in silico between the candidate molecule and the Crizotinib inhibitor. The comparison results show that the selected molecule can be used as new anticancer drug candidates.

Computer aided drug design based on 3D-QSAR and molecular docking studies of 5-(1H-indol-5-yl)-1,3,4-thiadiazol-2-amine derivatives as PIM2 inhibitors: a proposal to chemists.

PIM2 kinase plays a crucial role in the cell cycle events including survival, proliferation, and differentiation in normal and neoplastic neuronal cells. Thus, it is regarded as an essential target for cancer pharmaceutical. Design of novel 5-(1H-indol-5-yl)-1,3,4-thiadiazol-2-amine derivatives with enhanced PIM2 inhibitory activity. A series of twenty-five PIM2 inhibitors reported in the literature containing 5-(1H-indol-5-yl)-1,3,4-thiadiazol-2-amines scaffold was studied by using two computational techniques, namely, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indexes analysis (CoMSIA) studies were developed using nineteen molecules having pIC50 ranging from 8.222 to 4.157. The best generated CoMFA and CoMSIA models exhibit conventional determination coefficients R2 of 0.91 and 0.90 as well as the Leave One Out cross-validation determination coefficients Q2 of 0.68 and 0.62, respectively. Moreover, the predictive ability of those models was evaluated by the external validation using a test set of six compounds with predicted determination coefficients Rtest 2 of 0.96 and 0.96, respectively. Besides, y-randomization test was also performed to validate our 3D-QSAR models. The most and the least active compounds were docked into the active site of the protein (PDB ID: 4 × 7q) to confirm those obtained results from 3D-QSAR models and elucidate the binding mode between this kind of compounds and the PIM2 enzyme. These satisfactory results are not offered help only to understand the binding mode of 5-(1H-indol-5-yl)-1,3,4-thiadiazol series compounds into this kind of targets, but provide information to design new potent PIM2 inhibitors.