Computational studies on the structural variations of MAO-A and MAO-B inhibitors - An in silico docking approach-Supplementary data

The neurological disorder is a concerning problem in the present social scenario. The malfunction of the monoamine oxidase (MAO) enzyme is the responsible factor behind this disorder because this enzyme regulates the metabolism of monoamine neurotransmitters. This work aimed to design and propose the best MAO inhibitors through extensive computational analysis so that the favourable drug-like molecules could be identified for future synthesis. The drugs selected in this study were three MAO-A inhibitors namely Moclobemide, Tolxatone and Brofaromine and two MAO-B inhibitors namely Selegiline and Rasagiline. By substituting hydrophilic and hydrophobic groups at the specified positions, structural variations were designed for each drug. The designed variations and their parent drugs were optimized (basis set is B3LYP/6-311G(d, p)) and the optimized structures were docked to the target using PyRx software. The binding energy of each variation was compared to that of parent drug. The drug-likeness, physicochemical properties (solubility, polarity, flexibility, gastrointestinal absorption, saturation etc.) and toxicity of the lower binding energy variations were analysed using the swissADME, Osiris property explorer and ProTox-II servers. The interacting residues of the enzymes were obtained from the LigPlot+ program. The safe and low binding energy variations with favourable drug properties are suggested for further drug research

Computational studies on the structural variations of MAO-A and MAO-B inhibitors - An in silico docking approach-Supplementary data

The neurological disorder is a concerning problem in the present social scenario. The malfunction of the monoamine oxidase (MAO) enzyme is the responsible factor behind this disorder because this enzyme regulates the metabolism of monoamine neurotransmitters. This work aimed to design and propose the best MAO inhibitors through extensive computational analysis so that the favourable drug-like molecules could be identified for future synthesis. The drugs selected in this study were three MAO-A inhibitors namely Moclobemide, Tolxatone and Brofaromine and two MAO-B inhibitors namely Selegiline and Rasagiline. By substituting hydrophilic and hydrophobic groups at the specified positions, structural variations were designed for each drug. The designed variations and their parent drugs were optimized (basis set is B3LYP/6-311G(d, p)) and the optimized structures were docked to the target using PyRx software. The binding energy of each variation was compared to that of parent drug. The drug-likeness, physicochemical properties (solubility, polarity, flexibility, gastrointestinal absorption, saturation etc.) and toxicity of the lower binding energy variations were analysed using the swissADME, Osiris property explorer and ProTox-II servers. The interacting residues of the enzymes were obtained from the LigPlot+ program. The safe and low binding energy variations with favourable drug properties are suggested for further drug research

Computational studies on the structural variations of MAO-A and MAO-B inhibitors - An in silico docking approach

The neurological disorder is a concerning problem in the present social scenario. The malfunction of the monoamine oxidase (MAO) enzyme is the responsible factor behind this disorder because this enzyme regulates the metabolism of monoamine neurotransmitters. This work aimed to design and propose the best MAO inhibitors through extensive computational analysis so that the favourable drug-like molecules could be identified for future synthesis. The drugs selected in this study were three MAO-A inhibitors namely Moclobemide, Tolxatone and Brofaromine and two MAO-B inhibitors namely Selegiline and Rasagiline. By substituting hydrophilic and hydrophobic groups at the specified positions, structural variations were designed for each drug. The designed variations and their parent drugs were optimized (basis set is B3LYP/6-311G(d, p)) and the optimized structures were docked to the target using PyRx software. The binding energy of each variation was compared to that of parent drug. The drug-likeness, physicochemical properties (solubility, polarity, flexibility, gastrointestinal absorption, saturation etc.) and toxicity of the lower binding energy variations were analysed using the swissADME, Osiris property explorer and ProTox-II servers. The interacting residues of the enzymes were obtained from the LigPlot+ program. The safe and low binding energy variations with favourable drug properties are suggested for further drug research

Computational evaluation of 2-arylbenzofurans for their potential use against SARS-CoV-2: A DFT, molecular docking, molecular dynamics simulation study

Natural compounds obtained from various sources have been used in the treatment of many diseases for many years and are very important compounds for drug development studies. They can also be an option to treat COVID-19, which is affecting the whole world and not curable with medication, yet. In this study, two 2-arylbenzofuran derivatives from Sesbania cannabina which are newly entered the literature were investigated computationally with the assistance of computational techniques including DFT calculations, molecular docking calculation and molecular dynamics simulations. The study consists of four parts, in the first part of the study DFT calculations were performed on the 2-arylbenzofurans, and geometry optimizations, vibrational analyses, molecular electrostatic potential (MEP) map calculations, frontier molecular orbital (FMO) calculations and Mulliken charge analyses were carried out.In the second part, molecular docking calculations were performed to investigate the interactions between the molecules and two potential target, SARS-CoV-2 main protease (SARS-CoV-2 Mpro) and SARS-CoV-2 spike receptor binding domain – human angiotensin converting enzyme 2 complex (SARS-CoV-2 SRBD – hACE2). In the third part, MD simulations were performed on the top-scoring ligand – receptor complexes to investigate the stability of the complex and the interactions between ligands and receptors in more detail. Finally, drug-likeness analyses and ADME (adsorption, desorption, metabolism, excretion) predictions were performed on the investigated compounds. Results showed that investigated natural compounds effectively interacted with the target receptors and gave comparable results to the reference drug molecules.

New benzimidazole derivatives as inhibitors of Pteridine reductase 1: Design, molecular docking study and ADMET prediction

Pteridine reductase 1 (PTR1) is a unique enzyme required for survival of Leishmania species, a causative organism forthe disease leishmaniasis. We herein report the design, docking, and Absorption, Distribution, Metabolism, Excretion,Toxicity (ADMET) prediction studies of 2-substituted-5-[(6-substituted-1H-benzimidazol-2yl)methyl]azole derivatives(B1–B14) as PTR1 inhibitors. Molecular docking studies showed good binding interaction of the compounds withthe active site of pteridine reductase from Leishmania Major, with compounds B5 and B12 showing docking scoresof −61.5232 and −62.5897, respectively, which were comparable with the original ligand, dihydrobiopterin. Largesubstituents on the azole ring, as well as substitutions on sixth position of the benzimidazole ring, were found to befavorable for interaction with PTR1 active site. Physicochemical properties, bioactivity prediction, and toxicity profilesof the compounds were studied using the Molinspiration and admetSAR web servers. All compounds followed Lipinski’srule of five and can be considered as good oral candidates. Bioactivity prediction indicated that the compounds wereenzyme inhibitor, thus the rationale for designing PTR1 inhibitors was met. Most of the compounds were predicted tohave good ADMET properties in terms of Gastrointestinal (GI) absorption, absence of P-glycoprotein interaction, andLD50 values in rats. The designed molecules can be further explored for their antileishmanial activity

In vitro antimicrobial and α-glucosidase inhibitory potential of enantiopure cycloalkylglycine derivatives: Insights into their in silico pharmacokinetic, druglikeness, and medicinal chemistry properties

The present investigation deals with the evaluation for the first time of the in vitro antimicrobial and α-glucosidaseinhibitory potential of a series of 15 enantiopure cycloalkylglycines using agar well diffusion and spectrophotometricmethods, respectively. The obtained results were compared to the positive controls. The antimicrobial results revealedthat all compounds exerted strongly inhibitory activity, especially against Gram-positive bacterial strains with the mostpotent activity was ascribed to α-γ-hydroxy-α-amino acids 11–14 [minimum inhibitory concentration (MIC) = 1.58–12.50 mg/ml, minimum bactericidal concentration (MBC) = 3.17–100 mg/ml, and minimum fungicidal concentration(MFC) = 6.25–50 mg/ml], followed by both isoxazolidine 5–9 (MIC = 1.58–12.50 mg/ml, MBC = 6.25–100 mg/ml,and MFC = 25–100 mg/ml) and isoxazine 10 (MIC = 3.17–12.50 mg/ml, MBC = 3.17–50 mg/ml, and MFC = 25–50mg/ml) compounds, and slightly inhibitory effect with α-amino-γ-lactones series 1–4 (MIC = 3.17–25 mg/ml, MBC =6.25–100 mg/ml, and MFC = 25–100 mg/ml). All the derivatives exhibited a potent α-glucosidase inhibitory activitywith compound 10 (IC50 = 30.1 ± 0.6 μM) was found to be the most active. The druglikeness and pharmacokineticprofiles have been also predicted. The in silico results indicate that all derivatives showed a resemblance with severalparameters of the antimicrobial standards, especially in terms of molecular property, bioavailability, lipophilicity,medicinal chemistry, and enzymatic inhibitory effects as well as they agree with the different drug discovery rules suchas Lipinski (Pfizer), Ghose (Amgen), Veber (GlaxoSmithKline), Egan (Pharmacia), and Muegge (Bayer) displaying ahigher druglikeness behavior.

In vitro cytotoxicity and druglikeness of pyrazolines and pyridines bearing benzofuran moiety

A series of pyrazolines and pyridines bearing benzofuran moiety (M1–M10) were synthesized for evaluation of theirin vitro cytotoxicity against MCF-7 and HepG2 cell lines. Furthermore, in silico drug-likeness study was carried out.The result of the cytotoxicity of M1–M10 showed that some compounds displayed cytotoxic activity against MCF-7and HepG2 cells. An assessment of in silico drug-likeness study of M1–M10 illustrates that some compounds showedan agreement to the Lipinski, Ghose, Veber, Egan, and Muegge rules with orally bioavailable.

Antimicrobial evaluation and molecular properties prediction of pyrazolines incorporating benzofuran and pyrazole moieties

A series of chalcones 3–5, 1H-pyrazolines 6–8, N-phenylpyrazolines 9–11, and N-acetylpyrazolines 12–14incorporating benzofuran and pyrazole moieties were synthesized and screened for their in vitro antimicrobial activityagainst some of pathogenic microorganisms. Among the screened compounds, 7 and 13 showed the most promisingantibacterial activity against Escherichia coli (G-). Compound 11 displayed broad spectrum antibacterial activityagainst Bacillus subtilis (G+). Moreover, compounds 10 and 4 were found to be the most potent antifungal agentagainst Candida albicans and Aspergillus niger, respectively. Also, the molecular properties prediction and druglikeness model score (DLS) of all the synthesized compounds were calculated by SwissADME and MolSoft websites,respectively. The two compounds 7 and 13 were found to be maximum DLS of 0.75 and 0.83, respectively.

Integrating drug-likeness and network target to analyze the potential molecular mechanism of Danggui Buxue Jiawei decoction in the prevention and treatment of diabetic retinopathy / 国际药学研究杂志

Objective: Integrating drug-likeness and network targets to preliminarily predict and explore the targets and pathways of Danggui Buxue Jiawei decoction(DBJD)in the prevention and treatment of diabetic retinopathy(DR). Methods: The chemical constituents of DBJD were identified by UPLC-Q-TOF/HRMS E analytical techniques. The related websites were used to esti mate the drug-likeness for all identified constituents. Then, for the selected drug-like constituents, targets-predicting was carried out on PharmMapper, and the targets for DR were searched by CTD, TTD and GeneCards. The component-target and disease-target net works were integrated to establish a large network, and core targets were searched on the basis of the DC, CC and BC values of the large network. Moreover, indirect targets were further searched on the basis of the core targets. Then, an all potential targets-related network was constructed and related key targets were searched by the constructed network. The key targets were verified by docking with the related components. Gene ontology(GO)biological analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis and Reactome pathway analysis were carried out on all potential targets. Eventually, a large Prescription-Medicinal material-Component-Direct target-Indirect target-Pathway integrated network was established for the DBJD studies. Results: A total of 55 chemical constituents were identified by UPLC-Q-TOF/HRMS E. Among them, 33 components were selected by the drug-likeness esti mation. The core targets consisted of 36 targets, and 20 indirect targets were obtained by relating with the core targets. By comparing de gree values, 6 key targets were established: AKT1, MAPK3, VEGFA, INS, MAPK1 and CASP3. In molecular docking tests, these key targets showed good binding activities with tanshinone, salvianolic acid B, ginsenoside Rg 1, notoginsenoside R 1, tanshinone Ⅱ A and other quality control components. Pathway analysis suggested that DBJD could likely interfere with the diabetic retinopathy by regulating oxidative stress, inflammatory factors and sugar metabolism. Conclusion: Accurate prediction of the action mechanism of complex Chinese medicinal ingredients based on the drug-likeness and network targets may be helpful to improve the blindness in relat ed research and accelerate the research process in modernization of traditional Chinese medicine. In this study, the molecular mecha nism of DBJD for the prevention and treatment of DR is preliminarily investigated and discussed, which could provide a valuable refer ence for future in-depth study.

An in silico investigation of phytochemicals as potential inhibitors against non-structural protein 1 from dengue virus 4

Dengue fever has emerged as a big threat to human health since the last decade owing to high morbidity with considerable mortalities. The proposed study aims at the in silico investigation of the inhibitory action against DENV4-NS1 of phytochemicals from two local medicinal plants of Pakistan. Non-Structural Protein 1 of Dengue Virus 4 (DENV4-NS1) is known to be involved in the replication and maturation of viron in the host cells. A total of 129 phytochemicals (50 from Tanacetum parthenium and 79 from Silybum marianum) were selected for this study. The tertiary structure of DENV4-NS1 was predicted based on homology modelling using Modeller 9.18 and the structural stability was evaluated using molecular dynamics simulations. Absorption, distribution, metabolism, excretion and toxicity (ADMET) along with the drug-likeness was also predicted for these phytochemicals using SwissADME and PreADMET servers. The results of ADMET and drug-likeness predictions exhibited that 54 phytochemicals i.e. 25 from Tanacetum parthenium and 29 from Silybum marianum showed effective druglikeness. These phytochemicals were docked against DENV4-NS1 using AutoDock Vina and 18 most suitable phytochemicals with binding affinities ≤ -6.0 kcal/mol were selected as potential inhibitors for DENV4-NS1. Proposed study also exploits the novel inhibitory action of Jaceidin, Centaureidin, Artecanin, Secotanaparthenolide, Artematin, Schizolaenone B, Isopomiferin, 6, 8-Diprenyleriodictyol, and Anthraxin against dengue virus. It is concluded that the screened 18 phytochemicals have strong inhibition potential against Dengue Virus 4.

Molecular descriptors for drugs: A discriminant analysis

Background@#The biological activity of a compound is assumed to be encoded in its chemical composition and geometric structure, from which physico-chemical, electrotopological, and graph theory-derived properties can be determined.@*Objective@#This study aimed to identify the molecular descriptors derived from Dragon® 6 software that can discriminate compounds as drug or nondrug@*Methodology@#Over 4000 molecular properties were obtained for approximately 2000 known drugs and 2000 nondrugs on which Linear Discriminant Analysis was performed. @*Results@#Compounds can be discriminated between drug and nondrug with 81% accuracy using only two molecular descriptors, the information index HVcpx and the topological index MDDD. @*Conclusion@#A “Rule of Three” (HVcpx ≤ 3 and MDDD ≥ 30) seems to confer druglikeness in compounds. This rule can be used as additional filter in high throughput screening of compounds in any drug discovery research.

Network pharmacology study of effective constituents of traditional Chinese medicine for Alzheimer's disease treatment / 药学学报

This study aims to investigate the network pharmacology of Chinese medicinal formulae for treatment of Alzheimer's disease. Machine learning algorithms were applied to construct classifiers in predicting the active molecules against 25 key targets toward Alzheimer's disease (AD). By extensive data profiling, we compiled 13 classical traditional Chinese medicine (TCM) formulas with clinical efficacy for AD. There were 7 Chinese herbs with a frequency of 5 or higher in our study. Based on the predicted results, we built constituent-target, and further construct target-target interaction network by STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) and target-disease network by DAVID (Database for Annotation, Visualization and Integrated Discovery) and gene disease database to study the synergistic mechanism of the herbal constituents in the Chinese traditional patent medicine. By prediction of blood-brain penetration and validation by TCMsp (traditional Chinese medicine systems pharmacology) and Drugbank, we found 7 typical multi-target constituents which have diverse structure. The mechanism uncovered by this study may offer a deep insight into the action mechanism of TCMs for AD. The predicted inhibitors for the AD-related targets may provide a good source of new lead constituents against AD.

Drug-like properties of potential anti-cancer compounds from Cameroonian flora: A virtual studies.

Assessment of the ‘drug-like’ using a set of calculated molecular descriptors, of a collection of 195compounds from plants in Cameroon exhibiting in vitro or/and in vivo activities against various cancer cell lines was made. Lipinski’s ‘Rule of Five’ (Ro5) was used to evaluate drug-likeness/oral availability of the compounds by making use of popular parameters like Molecular Weight (MW), predicted lipophilicity (log P), number of Hydrogen Bond Donors/Acceptors (HBD and HBA) and Number of Rotatable Bonds (NRB). The drug-like properties of the studied compounds were compared to that of the Dictionary of Natural Products (DNP). Our results revealed that79.50%, 43.60% and 12.30% of our dataset fall within the recommended range for ‘drug-like’, ‘lead-like’ and ‘fragment-like’ respectively with significant enhancement of some oral availability parameters over DNP and this paints the significant of our dataset in search for lead-like anti-cancer molecules with desirable ‘drug-like’ properties.