Vol 20, No 5 (2024)
- Year: 2024
- Articles: 23
- URL: https://ruspoj.com/1573-4099/issue/view/9983
Chemistry
Docking, Synthesis, and In vitro Anti-depressant Activity of Certain Isatin Derivatives
Abstract
Background:In vitro, the molecular docking method has been suggested for estimating the biological affinity of the pharmacophores with physiologically active compounds. It is the latter stage in molecular docking, and the docking scores are examined using the AutoDock 4.2 tool program. The chosen compounds can be evaluated for in vitro activity based on the binding scores, and the IC50 values can be computed.
Objective:The purpose of this work was to create methyl isatin compounds as potential antidepressants, compute physicochemical characteristics, and carry out docking analysis.
Methods:The protein data bank of the RCSB (Research Collaboratory for Structural Bioinformatics) was used to download the PDB structures of monoamine oxidase (PDB ID: 2BXR) and indoleamine 2,3-dioxygenase (PDB ID: 6E35). Based on the literature, methyl isatin derivatives were chosen as the lead chemicals. By determining their IC50 values, the chosen compounds were tested for in vitro anti-depressant activity.
Results:The binding scores for the interactions of SDI 1 and SD 2 with indoleamine 2,3 dioxygenase were found to be -10.55 kcal/mol and -11.08 kcal/mol, respectively, while the scores for their interactions with monoamine oxidase were found to be -8.76 kcal/mol and -9.28 kcal/mol, respectively, using AutoDock 4.2. The relationship between biological affinity and pharmacophore electrical structure was examined using the docking technique. The chosen compounds were tested for their ability to inhibit MAO, and the IC50 values for each were found to be 51.20 and 56, respectively.
Conclusion:This investigation has identified many novel and effective MAO-A inhibitors from the family of chemicals known as methyl isatin derivatives. Lead optimization was applied to the SDI 1 and SDI 2 derivatives. The superior bioactivity, pharmacokinetic profile, BBB penetration, pre-ADMET profiles, such as HIA (human intestinal absorption) and MDCK (Madin-Darby canine kidney), plasma protein binding, toxicity assessment, and docking outcomes, have been obtained. According to the study, synthesised isatin 1 and SDI 2 derivatives exhibited a stronger MAO inhibitory activity and effective binding energy, which may help prevent stress-induced depression and other neurodegenerative disorders caused by a monoamine imbalance.
431-440
Assessment of Anticholinergic and Antidiabetic Properties of Some Natural and Synthetic Molecules: An In vitro and In silico Approach
Abstract
Introduction:This study aimed to determine the in vitro and in silico effects of some natural and synthetic molecules on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and α-glucosidase enzymes.
Background:Alzheimer's disease (AD) and Type II diabetes mellitus (T2DM) are considered the most important diseases of todays world. However, the side effects of therapeutic agents used in both diseases limit their use. Therefore, developing drugs with high therapeutic efficacy and better pharmacological profile is important.
Objective:This study sets out to determine the related enzyme inhibitors used in treating AD and T2DM, considered amongst the most important diseases of todays world.
Methods:In the current study, the in vitro and in silico effects of dienestrol, hesperetin, Lthyroxine, 3,3',5-Triiodo-L-thyronine (T3) and dobutamine molecules on AChE, BChE and α- glycosidase enzyme activities were investigated.
Results:All the molecules showed an inhibitory effect on the enzymes. The IC50 and Ki values of the L-Thyroxine molecule, which showed the strongest inhibition effect for the AChE enzyme, were determined as 1.71 µM and 0.83 ± 0.195 µM, respectively. In addition, dienestrol, T3, and dobutamine molecules showed a more substantial inhibition effect than tacrine. The dobutamine molecule showed the most substantial inhibition effect for the BChE enzyme, and IC50 and Ki values were determined as 1.83 µM and 0.845 ± 0.143 µM, respectively. The IC50 and Ki values for the hesperetin molecule, which showed the strongest inhibition for the α-glycosidase enzyme, were determined as 13.57 µM and 12.33 ± 2.57 µM, respectively.
Conclusion:According to the results obtained, the molecules used in the study may be considered potential inhibitor candidates for AChE, BChE and α-glycosidase.
441-451
In silico Identification of Potential Inhibitors against Staphylococcus aureus Tyrosyl-tRNA Synthetase
Abstract
Background:Drug-resistant Staphylococcus aureus (S. aureus) has spread from nosocomial to community-acquired infections. Novel antimicrobial drugs that are effective against resistant strains should be developed. S. aureus tyrosyl-tRNA synthetase (saTyrRS) is considered essential for bacterial survival and is an attractive target for drug screening.
Objective:The purpose of this study was to identify potential new inhibitors of saTyrRS by screening compounds in silico and evaluating them using molecular dynamics (MD) simulations.
Methods:A 3D structural library of 154,118 compounds was screened using the DOCK and GOLD docking simulations and short-time MD simulations. The selected compounds were subjected to MD simulations of a 75-ns time frame using GROMACS..
Results:Thirty compounds were selected by hierarchical docking simulations. The binding of these compounds to saTyrRS was assessed by short-time MD simulations. Two compounds with an average value of less than 0.15 nm for the ligand RMSD were ultimately selected. The longtime (75 ns) MD simulation results demonstrated that two novel compounds bound stably to saTyrRS in silico.
Conclusion:Two novel potential saTyrRS inhibitors with different skeletons were identified by in silico drug screening using MD simulations. The in vitro validation of the inhibitory effect of these compounds on enzyme activity and their antibacterial effect on drug-resistant S. aureus would be useful for developing novel antibiotics.
452-462
Predicting the Mechanism of Tiannanxing-shengjiang Drug Pair in Treating Pain Using Network Pharmacology and Molecular Docking Technology
Abstract
Objective:This study aimed to analyze the potential targets and mechanism of the Tiannanxing-shengjiang drug pair in pain treatment using network pharmacology and molecular docking technology.
Methods:The active components and target proteins of Tiannanxing-Shengjiang were obtained from the TCMSP database. The pain-related genes were acquired from the DisGeNET database. The common target genes between Tiannanxing-Shengjiang and pain were identified and subjected to the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses on the DAVID website. AutoDockTools and molecular dynamics simulation analysis were used to assess the binding of the components with the target proteins.
Results:Ten active components were screened out, such as stigmasterol, β-sitosterol, and dihydrocapsaicin. A total of 63 common targets between the drug and pain were identified. GO analysis showed the targets to be mainly associated with biological processes, such as inflammatory response and forward regulation of the EKR1 and EKR2 cascade. KEGG analysis revealed 53 enriched pathways, including pain-related calcium signaling, cholinergic synaptic signaling, and serotonergic pathway. Five compounds and 7 target proteins showed good binding affinities. These data suggest that Tiannanxing-shengjiang may alleviate pain through specific targets and signaling pathways.
Conclusion:The active ingredients in Tiannanxing-shengjiang might alleviate pain by regulating genes, such as CNR1, ESR1, MAPK3, CYP3A4, JUN, and HDAC1 through the signaling pathways, including intracellular calcium ion conduction, cholinergic prominent signaling, and cancer signaling pathway.
463-473
Molecular Mechanism and Structure-activity Relationship of the Inhibition Effect between Monoamine Oxidase and Selegiline Analogues
Abstract
Introduction:To investigate the inhibition properties and structure-activity relationship between monoamine oxidase (MAO) and selected monoamine oxidase inhibitors (MAOIs, including selegiline, rasagiline and clorgiline).
Methods:The inhibition effect and molecular mechanism between MAO and MAOIs were identified via the half maximal inhibitory concentration (IC50) and molecular docking technology.
Results:It was indicated that selegiline and rasagiline were MAO B inhibitors, but clorgiline was MAO-A inhibitor based on the selectivity index (SI) of MAOIs (0.000264, 0.0197 and 14607.143 for selegiline, rasagiline and clorgiline, respectively). The high-frequency amino acid residues of the MAOIs and MAO were Ser24, Arg51, Tyr69 and Tyr407 for MAO-A and Arg42 and Tyr435 for MAO B. The MAOIs and MAO A/B pharmacophores included the aromatic core, hydrogen bond acceptor, hydrogen bond donor-acceptor and hydrophobic core.
Conclusion:This study shows the inhibition effect and molecular mechanism between MAO and MAOIs and provides valuable findings on the design and treatment of Alzheimer's and Parkinson's diseases.
474-485
Research on the Regulatory Mechanism of Ginseng on the Tumor Microenvironment of Colorectal Cancer based on Network Pharmacology and Bioinformatics Validation
Abstract
Background:A network pharmacology study on the biological action of ginseng in the treatment of colorectal cancer (CRC) by regulating the tumor microenvironment (TME).
Objective:To investigate the potential mechanism of action of ginseng in the treatment of CRC by regulating TME.
Methods:This research employed network pharmacology, molecular docking techniques, and bioinformatics validation. Firstly, the active ingredients and the corresponding targets of ginseng were retrieved using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the Traditional Chinese Medicine Integrated Database (TCMID), and the Traditional Chinese Medicine Database@Taiwan (TCM Database@Taiwan). Secondly, the targets related to CRC were retrieved using Genecards, Therapeutic Target Database (TTD), and Online Mendelian Inheritance in Man (OMIM). Tertiary, the targets related to TME were derived from screening the GeneCards and National Center for Biotechnology Information (NCBI)-Gene. Then the common targets of ginseng, CRC, and TME were obtained by Venn diagram. Afterward, the Protein-protein interaction (PPI) network was constructed in the STRING 11.5 database, intersecting targets identified by PPI analysis were introduced into Cytoscape 3.8.2 software cytoHubba plugin, and the final determination of core targets was based on degree value. The OmicShare Tools platform was used to analyze the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the core targets. Autodock and PyMOL were used for molecular docking verification and visual data analysis of docking results. Finally, we verified the core targets by Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases in bioinformatics.
Results:A total of 22 active ingredients and 202 targets were identified to be closely related to the TME of CRC. PPI network mapping identified SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 as possible core targets. Go enrichment analysis showed that it was mainly involved in T cell co-stimulation, lymphocyte co-stimulation, growth hormone response, protein input, and other biological processes; KEGG pathway analysis found 123 related signal pathways, including EGFR tyrosine kinase inhibitor resistance, chemokine signaling pathway, VEGF signaling pathway, ErbB signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, etc. The molecular docking results showed that the main chemical components of ginseng have a stable binding activity to the core targets. The results of the GEPIA database showed that the mRNA levels of PIK3R1 were significantly lowly expressed and HSP90AA1 was significantly highly expressed in CRC tissues. Analysis of the relationship between core target mRNA levels and the pathological stage of CRC showed that the levels of SRC changed significantly with the pathological stage. The HPA database results showed that the expression levels of SRC were increased in CRC tissues, while the expression of STAT3, PIK3R1, HSP90AA1, and AKT1 were decreased in CRC tissues.
Conclusion:Ginseng may act on SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 to regulate T cell costimulation, lymphocyte costimulation, growth hormone response, protein input as a molecular mechanism regulating TME for CRC. It reflects the multi-target and multi-pathway role of ginseng in modulating TME for CRC, which provides new ideas to further reveal its pharmacological basis, mechanism of action and new drug design and development.
486-500
Exploring the Potential Molecular Mechanism of the Shugan Jieyu Capsule in the Treatment of Depression through Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation
Abstract
Background:Shugan Jieyu Capsule (SJC) is a pure Chinese medicine compound prepared with Hypericum perforatum and Acanthopanacis senticosi. SJC has been approved for the clinical treatment of depression, but the mechanism of action is still unclear.
Objective:Network pharmacology, molecular docking, and molecular dynamics simulation (MDS) were applied in the present study to explore the potential mechanism of SJC in the treatment of depression.
Methods:TCMSP, BATMAN-TCM, and HERB databases were used, and related literature was reviewed to screen the effective active ingredients of Hypericum perforatum and Acanthopanacis Senticosi. TCMSP, BATMAN-TCM, HERB, and STITCH databases were used to predict the potential targets of effective active ingredients. GeneCards database, DisGeNET database, and GEO data set were used to obtain depression targets and clarify the intersection targets of SJC and depression. STRING database and Cytoscape software were used to build a protein-protein interaction (PPI) network of intersection targets and screen the core targets. The enrichment analysis on the intersection targets was conducted. Then the receiver operator characteristic (ROC) curve was constructed to verify the core targets. The pharmacokinetic characteristics of core active ingredients were predicted by SwissADME and pkCSM. Molecular docking was performed to verify the docking activity of the core active ingredients and core targets, and molecular dynamics simulations were performed to evaluate the accuracy of the docking complex.
Results:We obtained 15 active ingredients and 308 potential drug targets with quercetin, kaempferol, luteolin, and hyperforin as the core active ingredients. We obtained 3598 targets of depression and 193 intersection targets of SJC and depression. A total of 9 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2) were screened with Cytoscape 3.8.2 software. A total of 442 GO entries and 165 KEGG pathways (p (<0.01) were obtained from the enrichment analysis of the intersection targets, mainly enriched in IL-17, TNF, and MAPK signaling pathways. The pharmacokinetic characteristics of the 4 core active ingredients indicated that they could play a role in SJC antidepressants with fewer side effects. Molecular docking showed that the 4 core active components could effectively bind to the 8 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2), which were related to depression by the ROC curve. MDS showed that the docking complex was stable.
Conclusion:SJC may treat depression by using active ingredients such as quercetin, kaempferol, luteolin, and hyperforin to regulate targets such as PTGS2 and CASP3 and signaling pathways such as IL-17, TNF, and MAPK, and participate in immune inflammation, oxidative stress, apoptosis, neurogenesis, etc.
501-517
Strychni Semen Combined with Atractylodes Macrocephala Koidz Attenuates Rheumatoid Arthritis by Regulating Apoptosis
Abstract
Background:Rheumatoid arthritis (RA) is a chronic autoimmune disease that can lead to joint pain and disability, and seriously impact patients' quality of life. Strychni Semen combined with Atractylodes Macrocephala koidz (SA) have pronounced curative effect on RA, and there is no poisoning of Strychni Semen (SS). However, its pharmacological mechanisms are still unclear.
Objective:In this study, we aimed to investigate the pharmacological mechanisms of Strychni Semen combined with Atractylodes Macrocephala Koidz (SA) for the treatment of RA.
Methods:We used network pharmacology to screen the active components of SA and predict the targets and pathways involved. Results originating from network pharmacology were then verified by animal experiments.
Results:Network pharmacology identified 81 active ingredients and 141 targets of SA; 2640 disease- related genes were also identified. The core targets of SA for the treatment of RA included ALB, IL-6, TNF and IL-1β. A total of 354 gene ontology terms were identified by Gene ontology (GO) enrichment analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis results showed that SA was closely associated with TNF signaling pathways in the treatment of RA. Furthermore, according to the predicted results of network pharmacology, we established a rat model of Adjuvant Arthritis (AA) for in vivo experiments. Analysis showed that each treatment group led to an improvement in paw swelling, immune organ coefficient and synovial tissue morphology in AA rats to different degrees, inhibit the expression levels of IL-1β, TNF-α and IL-6, upregulated the levels of Fas, Bax and Caspase 3, down-regulated the expression levels of Fas-L, Bcl-2 and p53.
Conclusion:SA has an anti-RA effect, the mechanism underlying the therapeutic action of SA in AA rats was related to the regulation of apoptosis signaling pathways
518-533
Exploring the Mechanisms of Self-made Kuiyu Pingchang Recipe for the Treatment of Ulcerative Colitis and Irritable Bowel Syndrome using a Network Pharmacology-based Approach and Molecular Docking
Abstract
Background:Ulcerative colitis (UC) and irritable bowel syndrome (IBS) are common intestinal diseases. According to the clinical experience and curative effect, the authors formulated Kuiyu Pingchang Decoction (KYPCD) comprised of Paeoniae radix alba, Aurantii Fructus, Herba euphorbiae humifusae, Lasiosphaera seu Calvatia, Angelicae sinensis radix, Panax ginseng C.A. Mey., Platycodon grandiforus and Allium azureum Ledeb.
Objective:The aim of the present study was to explore the mechanisms of KYPCD in the treatment of UC and IBS following the Traditional Chinese Medicine (TCM) theory of "Treating different diseases with the same treatment".
Methods:The chemical ingredients and targets of KYPCD were obtained using the Traditional Chinese Medicine Systems Pharmacology database and analysis platform (TCMSP). The targets of UC and IBS were extracted using the DisGeNET, GeneCards, DrugBANK, OMIM and TTD databases. The "TCM-component-target" network and the "TCM-shared target-disease" network were imaged using Cytoscape software. The protein-protein interaction (PPI) network was built using the STRING database. The DAVID platform was used to analyze the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Using Autodock Tools software, the main active components of KYPCD were molecularly docked with their targets and visualized using PyMOL.
Results:A total of 46 active ingredients of KYPCD corresponding to 243 potential targets, 1,565 targets of UC and 1,062 targets of IBS, and 70 targets among active ingredients and two diseases were screened. Core targets in the PPI network included IL6, TNF, AKT1, IL1B, TP53, EGFR and VEGFA. GO and KEGG enrichment analysis demonstrated 563 biological processes, 48 cellular components, 82 molecular functions and 144 signaling pathways. KEGG enrichment results revealed that the regulated pathways were mainly related to the PI3K-AKT, MAPK, HIF-1 and IL-17 pathways. The results of molecular docking analysis indicated that the core active ingredients of KYPCD had optimal binding activity to their corresponding targets.
Conclusion:KYPCD may use IL6, TNF, AKT1, IL1B, TP53, EGFR and VEGFA as the key targets to achieve the treatment of UC and IBS through the PI3K-AKT, MAPK, HIF-1 and IL-17 pathways.
534-550
Synthesis, Docking Study of Some Novel Chromeno[4',3'-b]Pyrano [6,5-d]Pyrimidine Derivatives Against COVID-19 Main Protease (Mpro) (6LU7, 6M03)
Abstract
Aims:In this work, some new chromeno[4',3'-b]pyrano[6,5-d]pyrimidines,3-amino and 3-methyl-5-aryl-4-imino-5(H)-chromeno[4',3'-b]pyrano[6,5-d]pyrimidine-6-ones derivatives were synthesized.
Background:Chromenopyrimidines have attracted significant attention recently because of their activities, such as antiviral and cytotoxic activity.
Objective:All synthesized compounds were characterized using IR, 1H-NMR, Mass Spectroscopy, and elemental analysis data.
Method:Molecular docking studies were carried out to determine the inhibitory action of studied ligands against the Main Protease (6LU7, 6m03) of coronavirus (COVID-19). Moreover, the Lipinski Rule parameters were calculated for the synthesized compounds.
Result:The result of the docking studies showed a significant inhibitory action against the Main protease (Mpro) of SARS-CoV-2, and the binding energy (ΔG) values of the ligands against the protein (6LU7, 6M03) are -7.8 to -9.9 Kcal/mole.
Conclusion:It may conclude that some ligands were likely to be considered lead-like against the main protease of SARS-CoV-2.
551-563
Synthesis, Molecular Modeling and Biological Evaluation of Novel Trifluoromethyl Benzamides as Promising CETP Inhibitors
Abstract
Background:Hyperlipidemia is considered a major risk factor for the progress of atherosclerosis.
Objective:Cholesteryl ester transfer protein (CETP) facilitates the relocation of cholesterol esters from HDL to LDL. CETP inhibition produces higher HDL and lower LDL levels.
Methods:Synthesis of nine benzylamino benzamides 8a-8f and 9a-9c was performed.
Results:In vitro biological study displayed potential CETP inhibitory activity, where compound 9c had the best activity with an IC50 of 1.03 µM. Induced-fit docking demonstrated that 8a-8f and 9a-9c accommodated the CETP active site and hydrophobic interaction predominated ligand/ CETP complex formation.
Conclusion::Pharmacophore mapping showed that this scaffold endorsed CETP inhibitors features and consequently elaborated the high CETP binding affinity.
564-574
A Rationalized Approach to Design and Discover Novel Non-steroidal Derivatives through Computational Aid for the Treatment of Prostate Cancer
Abstract
Background:Prostate cancer is one of the most prevalent cancers in men, leading to the second most common cause of death in men. Despite the availability of multiple treatments, the prevalence of prostate cancer remains high. Steroidal antagonists are associated with poor bioavailability and side effects, while non-steroidal antagonists show serious side effects, such as gynecomastia. Therefore, there is a need for a potential candidate for the treatment of prostate cancer with better bioavailability, good therapeutic effects, and minimal side effects.
Objective:This current research work focused on identifying a novel non-steroidal androgen receptor antagonist through computational tools, such as docking and in silico ADMET analysis.
Methods:Molecules were designed based on a literature survey, followed by molecular docking of all designed compounds and ADMET analysis of the hit compounds.
Results:A library of 600 non-steroidal derivatives (cis and trans) was designed, and molecular docking was performed in the active site of the androgen receptor (PDBID: 1Z95) using Auto- Dock Vina 1.5.6. Docking studies resulted in 15 potent hits, which were then subjected to ADME analysis using SwissADME. ADME analysis predicted three compounds (SK-79, SK-109, and SK-169) with the best ADME profile and better bioavailability. Toxicity studies using Protox-II were performed on the three best compounds (SK-79, SK-109, and SK-169), which predicted ideal toxicity for these lead compounds.
Conclusion:This research work will provide ample opportunities to explore medicinal and computational research areas. It will facilitate the development of novel androgen receptor antagonists in future experimental studies.
575-589
To Explore the Mechanism of Maiwei Dihuang Decoction in the Treatment of Non-small Cell Lung Cancer based on Network Pharmacology Combined with LC-MS
Abstract
Objective:To explore the mechanism of Maiwei Dihuang decoction in the treatment of non-small cell lung cancer (NSCLC) by using network pharmacology and LC-MS technology.
Methods:The effective components in Maiwei Dihuang decoction were detected by liquid chromatography- mass spectrometry (LC-MS). Use the SuperPred database to collect the relevant targets of the active ingredients of Mai Wei Di Tang, and then collect the relevant targets of nonsmall cell lung cancer from GeneCards, DisgenNET and OMIM databases. On this basis, PPI network construction, GO enrichment analysis and KEGG pathway annotation analysis were carried out for target sites. Finally, AutoDock Vina is used for molecular docking.
Results:We further screened 16 effective Chinese herbal compounds through LC-MS combined with ADME level. On this basis, we obtained 77 core targets through protein interaction network analysis. Through GO, KEGG analysis and molecular docking results, we finally screened out the potential targets of Maiwei Dihuang Decoction for NSCLC: TP53, STAT3, MAPK3.
Conclusion:Maiwei Dihuang decoction may play a role in the treatment of NSCLC by coregulating TP53/STAT3/MAPK3 signal pathway.
590-597
Amalgamated Pharmacoinformatics Study to Investigate the Mechanism of Xiao Jianzhong Tang against Chronic Atrophic Gastritis
Abstract
Background:Traditional Chinese medicine (TCM) Xiaojianzhong Tang (XJZ) has a favorable efficacy in the treatment of chronic atrophic gastritis (CAG). However, its pharmacological mechanism has not been fully explained.
Objective:The purpose of this study was to find the potential mechanism of XJZ in the treatment of CAG using pharmacocoinformatics approaches.
Methods:Network pharmacology was used to screen out the key compounds and key targets, MODELLER and GNNRefine were used to repair and refine proteins, Autodock vina was employed to perform molecular docking, Δ Lin_F9XGB was used to score the docking results, and Gromacs was used to perform molecular dynamics simulations (MD).
Results:Kaempferol, licochalcone A, and naringenin, were obtained as key compounds, while AKT1, MAPK1, MAPK14, RELA, STAT1, and STAT3 were acquired as key targets. Among docking results, 12 complexes scored greater than five. They were run for 50ns MD. The free binding energy of AKT1-licochalcone A and MAPK1-licochalcone A was less than -15 kcal/mol and AKT1-naringenin and STAT3-licochalcone A was less than -9 kcal/mol. These complexes were crucial in XJZ treating CAG.
Conclusion:Our findings suggest that licochalcone A could act on AKT1, MAPK1, and STAT3, and naringenin could act on AKT1 to play the potential therapeutic effect on CAG. The work also provides a powerful approach to interpreting the complex mechanism of TCM through the amalgamation of network pharmacology, deep learning-based protein refinement, molecular docking, machine learning-based binding affinity estimation, MD simulations, and MM-PBSA-based estimation of binding free energy.
598-615
Virtual Screening of Flavonoids against Plasmodium vivax Duffy Binding Protein Utilizing Molecular Docking and Molecular Dynamic Simulation
Abstract
Background:Plasmodium vivax (P. vivax) is one of the highly prevalent human malaria parasites. Due to the presence of extravascular reservoirs, P. vivax is extremely challenging to manage and eradicate. Traditionally, flavonoids have been widely used to combat various diseases. Recently, biflavonoids were discovered to be effective against Plasmodium falciparum.
Methods:In this study, in silico approaches were utilized to inhibit Duffy binding protein (DBP), responsible for Plasmodium invasion into red blood cells (RBC). The interaction of flavonoid molecules with the Duffy antigen receptor for chemokines (DARC) binding site of DBP was investigated using a molecular docking approach. Furthermore, molecular dynamic simulation studies were carried out to study the stability of top-docked complexes.
Results:The results showed the effectiveness of flavonoids, such as daidzein, genistein, kaempferol, and quercetin, in the DBP binding site. These flavonoids were found to bind in the active region of DBP. Furthermore, the stability of these four ligands was maintained throughout the 50 ns simulation, maintaining stable hydrogen bond formation with the active site residues of DBP.
Conclusion:The present study suggests that flavonoids might be good candidates and novel agents against DBP-mediated RBC invasion of P. vivax and can be further analyzed in in vitro studies.
616-627
Chemical Composition, In vitro and In silico Evaluation of Essential Oil from Ocimum tenuiflorum and Coriandrum sativum Linn for Lung Cancer
Abstract
Background:Medicinal plants play an essential role in everyday life; plants highly contain therapeutic phytoconstituents commonly used to treat various diseases. This paper discusses the Chemical composition, In vitro antiproliferative activity and In silico study of essential oil extracted from Ocimum tenuiflorum (family Lamiaceae) and Coriandrum sativum (family Apiaceae).
Objective:In present study GC-MS was used to identify the chemical constituents from O. tenuiflorum and C. sativum. In vitro antiproliferative activity was performed on A549 cancer cell lines. In silico study was performed by Schrodingers maestro software to identify chemical constituents in both plants as potential EGFR inhibitors for the treatment of lung cancer
Methods:The essential oil was extracted by hydro distillation from aerial parts of O. tenuiflorum and C. sativum. The volatile oil sample was analyzed by (GC-MS) Gas Chromatography- Mass Spectrometry. Different chemical constituents were identified based on the retention index and compared with the NIST library. The oil samples from O. tenuiflorum and C. sativum was also evaluated for antiproliferative activity against human lung cancer A549 cell lines. In silico study was performed by Schrodinger maestro software against EGFR (PDB ID 5HG8).
Resuls:O. tenuiflorum essential oil contains Eugenol (42.90%), 2-β-Elemene (25.98%), β- Caryophyllene (19.12%) are the major constituents. On the other side, C. sativum contains nnonadecanol- 1 (16.37%), decanal (12.37%), dodecanal (12.27%), 2-Dodecanal (9.67%), Phytol (8.81%) as the major constituents. Both the oils have shown in vitro antiproliferative activity against human lung cancer cell lines A549 having IC50 values of 38.281 µg/ml (O. tenuiflorum) and 74.536 µg/ml (C. sativum). Molecular interactions of constituents hydro distilled from two oils was analysed by schrodinger maestro software against EGFR (PDB ID 5HG8).
Conclusion:The oil sample extracted from O. tenuiflorum showed more antiproliferative activity than C. sativum. In silico study showed that two chemical constituents, namely di-isobutyl phthalate (-7.542 kcal/mol) and dibutyl phthalate (-7.181 kcal/mol) from O. tenuiflorum and one diethyl phthalate (-7.224 kcal/mol) from C. sativum having more docking score than standard Osimertinib which indicates the effectiveness of oils for lung cancer.
628-639
Synthesis, and In-silico Studies of Indole-chalcone Derivatives Targeting Estrogen Receptor Alpha (ER-α) for Breast Cancer
Abstract
Background:Breast cancer is the prominent reason of death in women worldwide, and the cases are increasing day by day. There are many FDA-approved drugs for treating breast cancer. Due to drug resistance, and problems in selectivity, there is a need to develop more effective agents with few side effects. Indole derivatives have demonstrated significant pharmacological potential as anti-breast cancer agents. Further, chalcone derivatives incorporating heterocyclic scaffolds play a significant role in medicine. Indole-chalcone-based compounds offer the potential for improved biological activity and enhanced drug-like properties. It prompted us to explore the synthesis of Indole-Chalcone derivatives targeting estrogen receptor alpha (ER-α) to discover potent anti-breast cancer agents.
Objectives:To synthesize indole-chalcone derivatives and study their binding interactions for ER-α protein by molecular docking for breast cancer treatment.
Methods:In this study, indole-chalcone derivatives have been synthesized using conventional heating. With the help of Schrodinger software, molecular interaction as well as ADME (Adsorption, Distribution, Metabolism, and Excretion) studies of the compounds were conducted.
Results:Among all the synthesized compounds, four compounds (1, 2, 3, and 4) showed better docking scores (-10.24 kcal/mol, -10.15 kcal/mol, -9.40 kcal/mol, -9.29 kcal/mol, respectively) than the standard tamoxifen (-8.43 kcal/mol).
Conclusion:From In-silico studies, we can conclude that four compounds from the synthesized series fit into the active site of ER-α. ADME properties of synthesized derivatives were found in the acceptable range. In the future, these compounds can be further explored for biological activity.
640-652
Optimizing the Extraction of Polyphenols from the Bark of Terminalia arjuna and an In-silico Investigation on its Activity in Colorectal Cancer
Abstract
Background::The interconnection between different fields of research has gained interest due to its cutting-edge perspectives in solving scientific problems. Terminalia arjuna is indigenously used in India for curing several diseases, and its pharmacological activities are being revisited in recent drug-repurposing research.
Objective:Efficient ultrasound-assisted extraction of phytochemicals from the bark of Terminalia arjuna is highlighted in this study. Following the optimization of the extraction process, the crude hydroethanolic extract is subjected to phytochemical profiling and an in-silico investigation of its anti-cancer properties.
Materials and Methods:A three-level four-factor Box-Behnken design is exploited to optimize four operational parameters, namely extraction time, ultrasonic power, ethanol concentration (as the extracting solvent) and solute (in g): solvent (in mL) ratio. At the optimum parametric condition, the crude extract is obtained, and its GC-MS analysis is carried out. An analysis of network pharmacology (by constructing and visualizing biological networks using Cytoscape) combined with molecular docking reveals the potential antineoplastic targets of the crude extract.
Results:The ANOVA table exhibits the significance, adequacy and reliability of the proposed second-order polynomial model with the R² value of 0.917 and adjusted R² of 0.865. Experimental results portray the significant antioxidant potential of the prepared extract in its crude form. The GC-MS analysis of the crude extract predicts the extracted phytochemicals, while the constructed biological networks highlight its multi-targeted activity in colorectal cancer
Conclusion:The study identifies three phytochemicals viz. luteolin, β-sitosterol and arjunic acid as potent anti-cancer agents and can be extended with in-vitro and in-vivo experiments to validate the in-silico results, thus establishing lead phytochemicals in multi-targeted colorectal cancer therapies.
653-665
A Novel Deep Learning Model for Drug-drug Interactions
Abstract
Introduction:Drug-drug interactions (DDIs) can lead to adverse events and compromised treatment efficacy that emphasize the need for accurate prediction and understanding of these interactions.
Methods:in this paper, we propose a novel approach for DDI prediction using two separate message-passing neural network (MPNN) models, each focused on one drug in a pair. By capturing the unique characteristics of each drug and their interactions, the proposed method aims to improve the accuracy of DDI prediction. The outputs of the individual MPNN models combine to integrate the information from both drugs and their molecular features. Evaluating the proposed method on a comprehensive dataset, we demonstrate its superior performance with an accuracy of 0.90, an area under the curve (AUC) of 0.99, and an F1-score of 0.80. These results highlight the effectiveness of the proposed approach in accurately identifying potential drugdrug interactions.
Results:The use of two separate MPNN models offers a flexible framework for capturing drug characteristics and interactions, contributing to our understanding of DDIs. The findings of this study have significant implications for patient safety and personalized medicine, with the potential to optimize treatment outcomes by preventing adverse events. Conclusion: Further research and validation on larger datasets and
Conclusion:Further research and validation on larger datasets and real-world scenarios are necessary to explore the generalizability and practicality of this approach.
666-672
In-silico Assessment of Polyherbal Oils as Anti-diabetic Therapeutics
Abstract
Background:Diabetes mellitus (DM) is characterized by elevated blood glucose levels either due to insufficient insulin production, defective insulin action, or both. It affects nearly 537 million individuals worldwide. Pharmacological treatment involves the use of oral antidiabetic agents as mono or combination therapy that effectively aids in controlling hyperglycemia. Despite providing therapeutic benefits, these medications limit their use owing to adverse side effects. Certain natural products, including essential oils, have promising anti-diabetic properties.
Objective:The present study explores the effectiveness of two polyherbal oils and their compound towards the treatment of DM based on an In-silico approach to drug investigations.
Methods:Compounds present in the polyherbal oil formulation were identified using GCMS/ MS analysis. Selected compounds undergo molecular docking with the receptor, and proteins play an important role in DM. The potential compounds showing higher interactions than the known inhibitors or inducers were evaluated using molecular dynamic simulations RMSD values.
Results:The compounds identified through GC-MS analysis possess anti-diabetic and antiinflammatory properties. With the aid of in silico prediction methods, compounds such as geraniol, cinnamaldehyde, anethole, caryophyllene, terpinyl acetate, cymene, linalool, menthol, Phenol,2-methoxy-3-(2-propenyl), and 2,6- octadienal,3,7-dimethyl were identified as strong binders of GLUT4 and insulin receptor proteins. Geraniol and Phenol,2-methoxy-3-(2-propenyl) interaction with GLUT4 were of particular importance owing to their conformational stability.
Conclusion:Our data suggest an agonistic effect of compounds on target proteins aiding in enhanced insulin activity and could serve as a potential anti-diabetic agent.
673-684
Hybrid Analogues of Hydrazone and Phthalimide: Design, Synthesis, In vivo, In vitro, and In silico Evaluation as Analgesic Agents
Abstract
Background:Based on the anti-inflammatory and analgesic activity of hydrazone and phthalimide, a new series of hybrid hydrazone and phthalimide pharmacophores was prepared and evaluated as analgesic agents.
Methods:The designed ligands were synthesized by reaction of the appropriate aldehydes and 2- aminophthalimide. Analgesic, cyclooxygenase inhibitory, and cytostatic activity of prepared compounds were measured.
Results:All the tested ligands demonstrated significant analgesic activity. Moreover, compounds 3i and 3h were the most potent ligands in the formalin and writhing tests, respectively. Compounds 3g, 3j, and 3l were the most COX-2 selective ligands and ligand 3e was the most potent COX inhibitor with a 0.79 of COX-2 selectivity ratio. The presence of electron-withdrawing moieties with hydrogen bonding ability at the meta position was found to affect the selectivity efficiently, in which compounds 3g, 3l, and 3k showed high COX-2 selectivity, and compound 3k was the most potent one. The cytostatic activity of selected ligands demonstrated that compounds 3e, 3f, 3h, 3k, and 3m showed good analgesic and COX inhibitory activity and were less toxic than the reference drug.
Conclusion:High therapeutic index of these ligands is one of the valuable advantages of these compounds.
685-696
Advances in Drug Discovery and Design using Computer-aided Molecular Modeling
Abstract
Computer-aided molecular modeling is a rapidly emerging technology that is being used to accelerate the discovery and design of new drug therapies. It involves the use of computer algorithms and 3D structures of molecules to predict interactions between molecules and their behavior in the body. This has drastically improved the speed and accuracy of drug discovery and design. Additionally, computer-aided molecular modeling has the potential to reduce costs, increase the quality of data, and identify promising targets for drug development. Through the use of sophisticated methods, such as virtual screening, molecular docking, pharmacophore modeling, and quantitative structure-activity relationships, scientists can achieve higher levels of efficacy and safety for new drugs. Moreover, it can be used to understand the activity of known drugs and simplify the process of formulating, optimizing, and predicting the pharmacokinetics of new and existing drugs. In conclusion, computer-aided molecular modeling is an effective tool to rapidly progress drug discovery and design by predicting the interactions between molecules and anticipating the behavior of new drugs in the body.
697-710
In-silico Investigation of Ginseng Phytoconstituents as Novel Therapeutics Against MAO-A
Abstract
Background:Ginseng (Panax ginseng) is a herb of medicinal and nutritional importance. Ginseng has been used since ancient times for the treatment of numerous ailments as it has many therapeutic properties. Several phytoconstituents are present in Panax ginseng that possess a variety of beneficial pharmacological properties.
Objective:To explore the potential of phytoconstituents of Panax ginseng in the treatment of depression, a molecular modeling technique was utilized targeting monoamine oxidase-A (MAO-A).
Methods:A total of sixty-one phytoconstituents of ginseng were drawn with the help of ChemBioDraw Ultra 12.0 software and PDBs for MAO-A enzyme were retrieved from the RCSB PDB database. The prepared ligands were screened for MAO-A properties using the software Molegro Virtual Docker (MVD 2010.4.1.0). All the prepared ligands were evaluated for drug-likeliness properties using Swiss ADME.
Result:Among the docking studies of 60 Ginseng phytochemicals including one standard, 15 phytoconstituents with the highest dock score and better binding interactions were selected further for absorption, distribution, metabolism and excretion (ADME) studies. Stachyose (-227.287, 17 interactions), Raffinose (-222.157, 14 interactions), and Ginsenoside Rg1 (-216.593, 10 interactions) were found to possess better interactions as compared to Clorgyline taken as a standard drug.
Conclusion:Stachyose was found to be the most potent inhibitor of MAO-A enzyme under investigation and can be a potential lead molecule for the development of newer phytochemical-based treatment of depression.
711-722