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Designing of thiazolidinones against chicken pox, monkey pox, and hepatitis viruses: A computational approach. Comput Biol Chem 2023; 103:107827. [PMID: 36805155 PMCID: PMC9922439 DOI: 10.1016/j.compbiolchem.2023.107827] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 02/03/2023] [Accepted: 02/05/2023] [Indexed: 02/14/2023]
Abstract
Computational designing of four different series (D-G) of thiazolidinone was done starting from different amines which was further condensed with various aldehydes. These underwent in silico molecular investigations for density functional theory (DFT), molecular docking, and absorption, distribution metabolism, excretion, and toxicity (ADMET) studies. The different electrochemical parameters of the compounds are predicted using quantum mechanical modeling approach with Gaussian. The docking software was used to dock the compounds against choosing PDB file for chickenpox, human immunodeficiency, hepatitis, and monkeypox virus as 1OSN, 1VZV, 6VLK, 1RTD, 3I7H, 3TYV, 4JU3, and 4QWO, respectively. The molecular interactions were visualized with discovery studio and maximum binding affinity was observed with D8 compounds against 4QWO (-13.383 kcal/mol) while for compound D5 against 1VZV which was -12.713 kcal/mol. Swiss ADME web tool was used to assess the drug-likeness of the designed compounds under consideration, and it is concluded that these molecules had a drug-like structure with almost zero violations.
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Banerjee A, De P, Kumar V, Kar S, Roy K. Quick and efficient quantitative predictions of androgen receptor binding affinity for screening Endocrine Disruptor Chemicals using 2D-QSAR and Chemical Read-Across. CHEMOSPHERE 2022; 309:136579. [PMID: 36174732 DOI: 10.1016/j.chemosphere.2022.136579] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 09/18/2022] [Accepted: 09/20/2022] [Indexed: 06/16/2023]
Abstract
Endocrine Disruptor Chemicals are synthetic or natural molecules in the environment that promote adverse modifications of endogenous hormone regulation in humans and/or in animals. In the present research, we have applied two-dimensional quantitative structure-activity relationship (2D-QSAR) modeling to analyze the structural features of these chemicals responsible for binding to the androgen receptors (logRBA) in rats. We have collected the receptor binding data from the EDKB database (https://www.fda.gov/science-research/endocrine-disruptor-knowledge-base/accessing-edkb-database) and then employed the DTC-QSAR tool, available from https://dtclab.webs.com/software-tools, for dataset division, feature selection, and model development. The final partial least squares model was evaluated using various stringent validation criteria. From the model, we interpreted that hydrophobicity, steroidal nucleus, bulkiness and a hydrogen bond donor at an appropriate position contribute to the receptor binding affinity, while presence of electron rich features like aromaticity and polar groups decrease the receptor binding affinity. Additionally we have also performed chemical Read-Across predictions using Read-Across-v3.1 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home, and the results for the external validation metrics were found to be better than the QSAR-derived predictions. The best quality of external predictions emerged from the q-RASAR approach which combines both read-across and QSAR. To explore the essential features responsible for the receptor binding, pharmacophore mapping, molecular docking along with molecular dynamics simulation were also performed, and the results are in accordance with the QSAR/q-RASAR findings.
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Affiliation(s)
- Arkaprava Banerjee
- Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700032, India
| | - Priyanka De
- Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700032, India
| | - Vinay Kumar
- Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700032, India
| | - Supratik Kar
- Interdisciplinary Center for Nanotoxicity, Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, Jackson, MS 39217, United States
| | - Kunal Roy
- Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700032, India.
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Automated QSPR modeling and data curation of physicochemical properties using KNIME platform: Prediction of partition coefficients. J INDIAN CHEM SOC 2022. [DOI: 10.1016/j.jics.2022.100672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Pharmacological Mechanism of Zuojin Pill for Gastroesophageal Reflux Disease: A Network Pharmacology Study. J FOOD QUALITY 2022. [DOI: 10.1155/2022/5933348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Background. Although Zuojin Pill (ZJP) is widely used in China as a traditional prescription to treat gastroesophageal reflux disease (GERD), its exact mechanism of action is still unknown. Therefore, we employed network pharmacology (NP), molecular docking (MD), and molecular dynamics simulation (MDS) to investigate the pharmacological mechanisms of ZJP against GERD. Methods. Active compounds and target genes corresponding to ZJP and target genes related to GERD were identified through analysis of publicly available datasets. Subsequently, the obtained data were subjected to further network pharmacological analysis to explore the potential key active compounds, core target genes, and biological processes (BPs) associated with the effect of ZJP against GERD. Finally, the prediction results of NP were validated by MD, and MDS of the optimal core protein-ligand for each component obtained by MD were performed using Gromacs 2020 software. Results. Twelve active components of ZJP were identified to act on 82 target genes associated with GERD, and ZJP might exert an anti-GERD effect through the regulation of BPs such as reactive oxygen species (ROS) metabolism, response to oxidative stress (OS), and ROS, as well as the activation of signaling pathways such as apoptosis, p53 signaling, chemical carcinogenesis-ROS, and HIF-1 signaling pathways. Furthermore, quercetin, kaempferol, and coptisine, the three key components of ZJP were shown to stably bond with the 14 core target genes, including AKT1, MMP2, TP53, EGFR, JUN, CASP3, CXCL8, HIF1α, IL-1β, MYC, PPARG, MMP9, PTGS2, and FOS. Results from MDS showed that PPARG-quercetin and MMP2-quercetin bound more stably. Conclusions. The findings suggest that ZJP alleviates the symptoms of GERD and improves the prognosis by regulating ROS metabolism, thereby reducing the secretion of proinflammatory cytokines like IL-1β, COX-2, CXCL8, and MMPs, regulating the expression of oncogenes such as JUN and FOS, and maintaining the normal expression of tumor suppressor genes such as TP53 and MYC. However, whether the effect of this modulation of ROS metabolism is positive or negative needs to be further verified by pharmacological experiments.
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Molecular Mechanism of the Effect of Zhizhu Pill on Gastroesophageal Reflux Disease Based on Network Pharmacology and Molecular Docking. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:2996865. [PMID: 35646148 PMCID: PMC9135531 DOI: 10.1155/2022/2996865] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 03/15/2022] [Accepted: 04/19/2022] [Indexed: 11/25/2022]
Abstract
Background To investigate the pharmacological mechanism of Zhizhu pill (ZZP) against gastroesophageal reflux disease (GERD), network pharmacology in combination with molecular docking was applied in this study. Methods Active compounds of ZZP and target genes related to GERD were identified through public databases. Subsequently, the obtained data were used as a basis for further network pharmacological analysis to explore the potential key active compounds, core targets, and biological processes involved in ZZP against GERD. Finally, the results predicted by network pharmacology were validated by molecular docking. Results Twenty active components of ZZP were identified to act on 59 targets related to GERD. Enrichment analysis revealed that multiple biological processes including response to oxygen levels, response to oxidative stress, and response to reactive oxygen species were involved in the GERD ZZP treatment with ZZP. ZZP had an impact on the prognosis of GERD mainly through the HIF-1 signaling pathway, PI3K-Akt signaling pathway, and pathways in cancer. Further analysis identified the key components and core targets of ZZP against GERD, of which nobiletin, didymin, luteolin, and naringenin were key components, and PPARG, MMP9, JUN, TP53, PTGS2, EGFR, MAPK3, CASP3, AKT1, and VEGFA were the core targets. Molecular docking verified the stable bonds formed between the key components and the core targets. Conclusions The results of this study predict that the therapeutic effects of ZZP in GERD are mediated at least in part via PPARG, MMP9, JUN, TP53, PTGS2, EGFR, MAPK3, CASP3, AKT1, and VEGFA. These results may be useful in providing an experimental basis and new ideas for further research on ZZP in GERD.
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Exploration of the Potential Mechanisms of Wumei Pill for the Treatment of Ulcerative Colitis by Network Pharmacology. Gastroenterol Res Pract 2022; 2021:4227668. [PMID: 34970312 PMCID: PMC8714398 DOI: 10.1155/2021/4227668] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Accepted: 11/09/2021] [Indexed: 12/17/2022] Open
Abstract
Background Wumei pill (WMP) has a long history of colitis treatment in China, but the protective mechanisms have not been elucidated. To uncover the potential mechanisms of WMP against ulcerative colitis (UC), the network pharmacology approach was utilized in this study. Methods Public databases were utilized to identify the potential targets of WMP and genes related to UC. Based on the identified overlapping common targets, drug-ingredient-target gene network, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and protein-protein interaction (PPI) analysis were conducted. Molecular docking was carried out to verify the selected key active ingredients and core targets. Results 129 active ingredients and 622 target genes were obtained. The drug-ingredient-target gene network revealed 52 active ingredients of WMP acting on 73 targets related to UC. GO analysis revealed that biological processes were mainly associated with oxidative stress, such as, reactive oxygen species metabolic processes, response to oxidative stress, cellular response to oxidative stress, response to reactive oxygen species, and regulation of reactive oxygen species metabolic processes. KEGG analysis revealed that the immune- and inflammation-related pathways, tumor-related signaling pathways, and microbial infection-related signaling pathways were the most significant. PPI network identified 13 core target genes. The molecular docking results indicated the formation of stable bonds between the active ingredients and core target genes. Conclusions The approach of network pharmacology reveals the key ingredients, potential core targets, and biological process of WMP in the treatment of UC. The mechanisms of action of WMP involve anti-inflammation, antioxidation, and modulation of immunity, which provides evidence for the therapeutic role of WMP in UC.
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Tam NM, Nguyen TH, Ngan VT, Tung NT, Ngo ST. Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations. ROYAL SOCIETY OPEN SCIENCE 2022; 9:211480. [PMID: 35116157 PMCID: PMC8790385 DOI: 10.1098/rsos.211480] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Accepted: 12/20/2021] [Indexed: 05/03/2023]
Abstract
The umbrella sampling (US) simulation is demonstrated to be an efficient approach for determining the unbinding pathway and binding affinity to the SARS-CoV-2 Mpro of small molecule inhibitors. The accuracy of US is in the same range as the linear interaction energy (LIE) and fast pulling of ligand (FPL) methods. In detail, the correlation coefficient between US and experiments does not differ from FPL and is slightly smaller than LIE. The root mean square error of US simulations is smaller than that of LIE. Moreover, US is better than FPL and poorer than LIE in classifying SARS-CoV-2 Mpro inhibitors owing to the reciever operating characteristic-area under the curve analysis. Furthermore, the US simulations also provide detailed insights on unbinding pathways of ligands from the binding cleft of SARS-CoV-2 Mpro. The residues Cys44, Thr45, Ser46, Leu141, Asn142, Gly143, Glu166, Leu167, Pro168, Ala191, Gln192 and Ala193 probably play an important role in the ligand dissociation. Therefore, substitutions at these points may change the mechanism of binding of inhibitors to SARS-CoV-2 Mpro.
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Affiliation(s)
- Nguyen Minh Tam
- Computational Chemistry Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Trung Hai Nguyen
- Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Laboratory of Theoretical and Computational Biophysics, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Vu Thi Ngan
- Laboratory of Computational Chemistry and Modelling, Department of Chemistry, Quy Nhon University, Quy Nhon, Vietnam
| | - Nguyen Thanh Tung
- Institute of Materials Science, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Son Tung Ngo
- Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Laboratory of Theoretical and Computational Biophysics, Ton Duc Thang University, Ho Chi Minh City, Vietnam
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Hsu CW, Tsai SY, Wang LJ, Liang CS, Carvalho AF, Solmi M, Vieta E, Lin PY, Hu CA, Kao HY. Predicting Serum Levels of Lithium-Treated Patients: A Supervised Machine Learning Approach. Biomedicines 2021; 9:biomedicines9111558. [PMID: 34829787 PMCID: PMC8615637 DOI: 10.3390/biomedicines9111558] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/23/2021] [Accepted: 10/25/2021] [Indexed: 11/16/2022] Open
Abstract
Routine monitoring of lithium levels is common clinical practice. This is because the lithium prediction strategies available developed by previous studies are still limited due to insufficient prediction performance. Thus, we used machine learning approaches to predict lithium concentration in a large real-world dataset. Real-world data from multicenter electronic medical records were used in different machine learning algorithms to predict: (1) whether the serum level was 0.6–1.2 mmol/L or 0.0–0.6 mmol/L (binary prediction), and (2) its concentration value (continuous prediction). We developed models from 1505 samples through 5-fold cross-validation and used 204 independent samples to test their performance by evaluating their accuracy. Moreover, we ranked the most important clinical features in different models and reconstructed three reduced models with fewer clinical features. For binary and continuous predictions, the average accuracy of these models was 0.70–0.73 and 0.68–0.75, respectively. Seven features were listed as important features related to serum lithium levels of 0.6–1.2 mmol/L or higher lithium concentration, namely older age, lower systolic blood pressure, higher daily and last doses of lithium prescription, concomitant psychotropic drugs with valproic acid and -pine drugs, and comorbid substance-related disorders. After reducing the features in the three new predictive models, the binary or continuous models still had an average accuracy of 0.67–0.74. Machine learning processes complex clinical data and provides a potential tool for predicting lithium concentration. This may help in clinical decision-making and reduce the frequency of serum level monitoring.
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Affiliation(s)
- Chih-Wei Hsu
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (P.-Y.L.); (C.-A.H.)
- Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 70101, Taiwan
- Correspondence: (C.-W.H.); (H.-Y.K.)
| | - Shang-Ying Tsai
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110301, Taiwan;
- Department of Psychiatry and Psychiatric Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei 110301, Taiwan
| | - Liang-Jen Wang
- Department of Child and Adolescent Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan;
| | - Chih-Sung Liang
- National Defense Medical Center, Department of Psychiatry, Beitou Branch, Tri-Service General Hospital, Taipei 112003, Taiwan;
- National Defense Medical Center, Department of Psychiatry, Taipei 114201, Taiwan
| | - Andre F. Carvalho
- IMPACT (Innovation in Mental and Physical Health and Clinical Treatment) Strategic Research Centre, School of Medicine, Barwon Health, Deakin University, Geelong, VIC 3216, Australia;
| | - Marco Solmi
- Psychiatry Department, University of Ottawa, Ottawa, ON K1N 6N5, Canada;
- The Ottawa Hospital, University of Ottawa, Ottawa, ON K1H 8L6, Canada
- Clinical Epidemiology Program, Ottawa Hospital Research Institute (OHRI), University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Eduard Vieta
- Bipolar and Depressive Disorders Unit, Hospital Clinic, IDIBAPS, CIBERSAM, University of Barcelona, 08036 Barcelona, Catalonia, Spain;
| | - Pao-Yen Lin
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (P.-Y.L.); (C.-A.H.)
- Institute for Translational Research in Biomedical Sciences, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung 83301, Taiwan
| | - Chien-An Hu
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (P.-Y.L.); (C.-A.H.)
| | - Hung-Yu Kao
- Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 70101, Taiwan
- Correspondence: (C.-W.H.); (H.-Y.K.)
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Prasher P, Sharma M. Medicinal chemistry of anthranilic acid derivatives: A mini review. Drug Dev Res 2021; 82:945-958. [PMID: 34117784 DOI: 10.1002/ddr.21842] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 06/01/2021] [Accepted: 06/03/2021] [Indexed: 01/04/2023]
Abstract
Anthranilic acid and its analogues present a privileged profile as pharmacophores for the rational development of pharmaceuticals deliberated for managing the pathophysiology and pathogenesis of various diseases. The substitution on anthranilic acid scaffold provides large compound libraries, which enable a comprehensive assessment of the structure activity relationship (SAR) analysis for the identification of hits and leads in a typical drug development paradigm. Besides, their widespread applications as anti-inflammatory fenamates, the amide and anilide derivatives of anthranilic acid analogues play a central role in the management of several metabolic disorders. In addition, these derivatives of anthranilic acid exhibit interesting antimicrobial, antiviral and insecticidal properties, whereas the derivatives based on anthranilic diamide scaffold present applications as P-glycoprotein inhibitors for managing the drug resistance in cancer cells. In addition, the anthranilic acid derivatives serve as the inducers of apoptosis, inhibitors of hedgehog signaling pathway, inhibitors of mitogen activated protein kinase pathway, and the inhibitors of aldo-keto reductase enzymes. The antiviral derivatives of anthranilic acid focus on the inhibition of hepatitis C virus NS5B polymerase to manifest considerable antiviral properties. The anthranilic acid derivatives reportedly present neuroprotective applications by downregulating the key pathways responsible for the manifestation of neuropathological features and neurodegeneration. Nevertheless, the transition metal complexes of anthranilic acid derivatives offer therapeutic applications in diabetes mellitus, and obesity by regulating the activity of α-glucosidase. The present review demonstrates a critical analysis of the therapeutic profile of the key derivatives of anthranilic acid and its analogues for the rational development of pharmaceuticals and therapeutic molecules.
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Affiliation(s)
- Parteek Prasher
- Department of Chemistry, UGC Sponsored Centre for Advanced Studies, Guru Nanak Dev University, Amritsar, Punjab, India.,Department of Chemistry, University of Petroleum & Energy Studies, Dehradun, Uttarakhand, India
| | - Mousmee Sharma
- Department of Chemistry, UGC Sponsored Centre for Advanced Studies, Guru Nanak Dev University, Amritsar, Punjab, India.,Department of Chemistry, Uttaranchal University, Dehradun, Uttarakhand, India
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Meftahi N, Walker ML, Smith BJ. Predicting aqueous solubility by QSPR modeling. J Mol Graph Model 2021; 106:107901. [PMID: 33857890 DOI: 10.1016/j.jmgm.2021.107901] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 03/09/2021] [Accepted: 03/09/2021] [Indexed: 12/26/2022]
Abstract
The aqueous solubility is predicted here using quantitative structure property relationship (QSPR) models. In this study, we examine whether descriptors that individually yield favorable models for the prediction of the Gibbs energy of solvation and sublimation can be used in combination with octanol-water partition coefficient to produce QSPR models for the prediction of aqueous solubility. Based on this strategy, applied to seven distinct datasets, all models exhibited an R2 greater than 0.7 and Q2 greater than 0.6 for the estimation of aqueous solubility. We also determined how uncoupling the descriptors used to create QSPR models in the prediction of Gibbs energy of sublimation yielded an improved model. Model refinement using an artificial neural network applying the same descriptors generated significantly better models with improved R2 and standard deviation.
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Affiliation(s)
- Nastaran Meftahi
- La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria, 3086, Australia
| | - Michael L Walker
- La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria, 3086, Australia
| | - Brian J Smith
- La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria, 3086, Australia.
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Network Pharmacology and Molecular Docking Analysis on Molecular Targets and Mechanisms of Buyang Huanwu Decoction in the Treatment of Ischemic Stroke. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2021; 2021:8815447. [PMID: 33727944 PMCID: PMC7937485 DOI: 10.1155/2021/8815447] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 02/01/2021] [Accepted: 02/09/2021] [Indexed: 02/07/2023]
Abstract
Methods The bioactive components and potential targets of BHD were screened by TCMSP, BATMAN-TCM, ETCM, and SymMap databases. Besides, compounds that failed to find the targets from the above databases were predicted through STITCH, SwissTargetPrediction, and SEA. Moreover, six databases were searched to mine targets of IS. The intersection targets were obtained and analyzed by GO and KEGG enrichment. Furthermore, BHD-IS PPI network, compound-target network, and herb-target-pathway network were constructed by Cytoscape 3.6.0. Finally, AutoDock was used for molecular docking verification. Results A total of 235 putative targets were obtained from 59 active compounds in BHD. Among them, 62 targets were related to IS. PPI network showed that the top ten key targets were IL6, TNF, VEGFA, AKT1, etc. The enrichment analysis demonstrated candidate BHD targets were more frequently involved in TNF, PI3K-Akt, and NF-kappa B signaling pathway. Network topology analysis showed that Radix Astragali was the main herb in BHD, and the key components were quercetin, beta-sitosterol, kaempferol, stigmasterol, etc. The results of molecular docking showed the active components in BHD had a good binding ability with the key targets. Conclusions Our study demonstrated that BHD exerted the effect of treating IS by regulating multitargets and multichannels with multicomponents through the method of network pharmacology and molecular docking.
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Ngo ST. Estimating the ligand-binding affinity via λ-dependent umbrella sampling simulations. J Comput Chem 2020; 42:117-123. [PMID: 33078419 DOI: 10.1002/jcc.26439] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 08/21/2020] [Accepted: 09/24/2020] [Indexed: 12/16/2022]
Abstract
The umbrella sampling (US) approach has been demonstrated to be a very efficient method for estimating the ligand-binding affinity. However, most of the calculated values overestimate experimental ones that are probably caused by the inaccurate representation of the interaction between the ligand and the surrounding molecules. The issue can be resolved via the implementation aspects of λ-alteration simulation into the US approach, which we call the λ-dependent umbrella sampling (λUS) scheme. In particular, the electrostatic and van der Waals interactions were simultaneously changed by using the coupling parameter λ during λUS simulations. The mean value of obtained results, ∆ G US λ = 0.20 = - 11.59 ± 1.51 kcal mol-1 , is in good fitting to the mean value of respective experiments, ∆GEXP = - 11.26 ± 0.89 kcal mol-1 . Moreover, the correlation between the proposed approach and experiment is quite good with a value of R US λ = 0.20 = 0.82 ± 0.10 . The λUS scheme significantly enhances the calculated accuracy since the RMSE of the proposed scheme is smaller than traditional US simulations, RMSE US λ = 0.20 = 2.99 ± 0.82 kcal mol-1 versus RMSE US λ = 0.00 = 5.48 ± 0.81 kcal mol-1 . Furthermore, the precision is increased since the computed error via λUS approach, δ US λ = 0.20 = 1.51 kcal mol-1 , was smaller than those of the US simulation, δ US λ = 0.00 = 1.78 kcal mol-1 . Overall, the proposed approach perhaps provides an efficient way to accurately and precisely estimate the ligand-binding free energy.
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Affiliation(s)
- Son Tung Ngo
- Laboratory of Theoretical and Computational Biophysics, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Applied Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam
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Synthetic Analogues of Aminoadamantane as Influenza Viral Inhibitors-In Vitro, In Silico and QSAR Studies. Molecules 2020; 25:molecules25173989. [PMID: 32883012 PMCID: PMC7504818 DOI: 10.3390/molecules25173989] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 08/29/2020] [Accepted: 08/31/2020] [Indexed: 11/29/2022] Open
Abstract
A series of nineteen amino acid analogues of amantadine (Amt) and rimantadine (Rim) were synthesized and their antiviral activity was evaluated against influenza virus A (H3N2). Among these analogues, the conjugation of rimantadine with glycine illustrated high antiviral activity combined with low cytotoxicity. Moreover, this compound presented a profoundly high stability after in vitro incubation in human plasma for 24 h. Its thermal stability was established using differential and gravimetric thermal analysis. The crystal structure of glycyl-rimantadine revealed that it crystallizes in the orthorhombic Pbca space group. The structure–activity relationship for this class of compounds was established, with CoMFA (Comparative Molecular Field Analysis) 3D-Quantitative Structure Activity Relationships (3D-QSAR) studies predicting the activities of synthetic molecules. In addition, molecular docking studies were conducted, revealing the structural requirements for the activity of the synthetic molecules.
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Silva S, Shimizu JF, Oliveira DMD, Assis LRD, Bittar C, Mottin M, Sousa BKDP, Mesquita NCDMR, Regasini LO, Rahal P, Oliva G, Perryman AL, Ekins S, Andrade CH, Goulart LR, Sabino-Silva R, Merits A, Harris M, Jardim ACG. A diarylamine derived from anthranilic acid inhibits ZIKV replication. Sci Rep 2019; 9:17703. [PMID: 31776405 PMCID: PMC6881388 DOI: 10.1038/s41598-019-54169-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 10/29/2019] [Indexed: 12/13/2022] Open
Abstract
Zika virus (ZIKV) is a mosquito-transmitted Flavivirus, originally identified in Uganda in 1947 and recently associated with a large outbreak in South America. Despite extensive efforts there are currently no approved antiviral compounds for treatment of ZIKV infection. Here we describe the antiviral activity of diarylamines derived from anthranilic acid (FAMs) against ZIKV. A synthetic FAM (E3) demonstrated anti-ZIKV potential by reducing viral replication up to 86%. We analyzed the possible mechanisms of action of FAM E3 by evaluating the intercalation of this compound into the viral dsRNA and its interaction with the RNA polymerase of bacteriophage SP6. However, FAM E3 did not act by these mechanisms. In silico results predicted that FAM E3 might bind to the ZIKV NS3 helicase suggesting that this protein could be one possible target of this compound. To test this, the thermal stability and the ATPase activity of the ZIKV NS3 helicase domain (NS3Hel) were investigated in vitro and we demonstrated that FAM E3 could indeed bind to and stabilize NS3Hel.
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Affiliation(s)
- Suely Silva
- Laboratory of Virology, Institute of Biomedical Science, ICBIM, Federal University of Uberlandia, Uberlândia, MG, Brazil
- São Paulo State University, IBILCE, S. José do Rio Preto, SP, Brazil
| | - Jacqueline Farinha Shimizu
- Laboratory of Virology, Institute of Biomedical Science, ICBIM, Federal University of Uberlandia, Uberlândia, MG, Brazil
- São Paulo State University, IBILCE, S. José do Rio Preto, SP, Brazil
| | - Débora Moraes de Oliveira
- Laboratory of Virology, Institute of Biomedical Science, ICBIM, Federal University of Uberlandia, Uberlândia, MG, Brazil
| | - Leticia Ribeiro de Assis
- Laboratory of Antibiotics and Chemotherapeutics, São Paulo State University, IBILCE, S. José do Rio Preto, SP, Brazil
| | - Cintia Bittar
- São Paulo State University, IBILCE, S. José do Rio Preto, SP, Brazil
| | - Melina Mottin
- LabMol - Laboratory of Molecular Modeling and Drug Design, Faculdade de Farmácia, Universidade Federal de Goias, Goiânia, GO, 74605- 170, Brazil
| | - Bruna Katiele de Paula Sousa
- LabMol - Laboratory of Molecular Modeling and Drug Design, Faculdade de Farmácia, Universidade Federal de Goias, Goiânia, GO, 74605- 170, Brazil
| | | | - Luis Octávio Regasini
- Laboratory of Antibiotics and Chemotherapeutics, São Paulo State University, IBILCE, S. José do Rio Preto, SP, Brazil
| | - Paula Rahal
- São Paulo State University, IBILCE, S. José do Rio Preto, SP, Brazil
| | - Glaucius Oliva
- Institute of Physics of São Carlos, University of São Paulo, São Carlos, Brazil
| | - Alexander Luke Perryman
- Department of Pharmacology, Physiology and Neuroscience, Rutgers University-New Jersey Medical School, Newark, NJ 07103, United States
- Repare Therapeutics, 7210 Rue Frederick-Banting, Suite 100, Montreal, QC, H4S 2A1, Canada
| | - Sean Ekins
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, NC, 27606, United States
| | - Carolina Horta Andrade
- LabMol - Laboratory of Molecular Modeling and Drug Design, Faculdade de Farmácia, Universidade Federal de Goias, Goiânia, GO, 74605- 170, Brazil
| | - Luiz Ricardo Goulart
- Laboratory of Nanobiotechnology, Federal University of Uberlandia, Uberlândia, MG, Brasil
| | - Robinson Sabino-Silva
- Integrative Physiology and Salivary Nanobiotechnology Group, Federal University of Uberlandia, Uberlândia, MG, Brasil
| | - Andres Merits
- Institute of Technology, University of Tartu, Nooruse 1, 50411, Tartu, Estonia
| | - Mark Harris
- School of Molecular and Cellular Biology, Faculty of Biological Sciences and Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, LS2 9JT, United Kingdom
| | - Ana Carolina Gomes Jardim
- Laboratory of Virology, Institute of Biomedical Science, ICBIM, Federal University of Uberlandia, Uberlândia, MG, Brazil.
- São Paulo State University, IBILCE, S. José do Rio Preto, SP, Brazil.
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15
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Wang Y, Guo H, Tang G, He Q, Zhang Y, Hu Y, Wang Y, Lin Z. A selectivity study of benzenesulfonamide derivatives on human carbonic anhydrase II/IX by 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation. Comput Biol Chem 2019; 80:234-243. [DOI: 10.1016/j.compbiolchem.2019.03.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Revised: 02/14/2019] [Accepted: 03/12/2019] [Indexed: 10/27/2022]
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16
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Khan MF, Verma G, Alam P, Akhter M, Bakht MA, Hasan SM, Shaquiquzzaman M, Alam MM. Dibenzepinones, dibenzoxepines and benzosuberones based p38α MAP kinase inhibitors: Their pharmacophore modelling, 3D-QSAR and docking studies. Comput Biol Med 2019; 110:175-185. [PMID: 31173941 DOI: 10.1016/j.compbiomed.2019.05.023] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 05/30/2019] [Accepted: 05/30/2019] [Indexed: 01/24/2023]
Abstract
In the present study, a series of dibenzepinones, dibenzoxepines, and benzosuberones targeting p38α MAP kinase were subjected to pharmacophore modelling, 3D-QSAR and molecular docking studies. The IC50 values for these 67 compounds ranged between 0.003 and 6.80 μM. A five-point model (DDHHR.8) was generated using these compounds. This model was found to be statistically significant and was found to have high correlation (R2 = 0.98), cross-validation coefficient (Q2 = 0.95) and F (330) values at six component PLS factor. Tests were performed to ascertain the efficacy of the generated model. These tests included external validation, Tropsha's test for predictive ability, Y-randomisation test and domain of applicability (APD). In order to check the restrictivity of the model, enrichment studies were performed with inactive compounds by using decoy set molecules. To evaluate the effectiveness of the docking protocol, the co-crystallised ligand was extracted from the ligand-binding domain of the protein and was re-docked into the same position. Both the conformers were then superimposed, suggesting satisfactory docking parameters with an RMSD value of less than 1.0 Å (0.853 Å). A 10 ns molecular dynamics simulation confirmed the docking results of the 3UVP-ligand complex and the presumed active conformation. The outcome of the present study provides insight into the molecular features that promote bioactivity and can be exploited for the prediction of novel potent p38α MAP kinase inhibitors before carrying out their synthesis and anticancer evaluation.
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Affiliation(s)
- Mohemmed Faraz Khan
- Drug Design and Medicinal Chemistry Lab, Department of Pharmaceutical Chemistry, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India
| | - Garima Verma
- Drug Design and Medicinal Chemistry Lab, Department of Pharmaceutical Chemistry, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India
| | - Perwez Alam
- Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Mymoona Akhter
- Drug Design and Medicinal Chemistry Lab, Department of Pharmaceutical Chemistry, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India
| | - Md Afroz Bakht
- Department of Chemistry, College of Science and Humanities, Prince Sattam Bin Abdulaziz University, P.O. Box- 173, Al-Kharj, Saudi Arabia
| | - Syed Misbahul Hasan
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Integral University, Lucknow, 226026, India
| | - Mohammad Shaquiquzzaman
- Drug Design and Medicinal Chemistry Lab, Department of Pharmaceutical Chemistry, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India
| | - Mohammad Mumtaz Alam
- Drug Design and Medicinal Chemistry Lab, Department of Pharmaceutical Chemistry, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India.
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17
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Zhou W, Lu S, Zhang Y, Yin L, Zhu L, Zhao J, Lu T, Chen Y, Liu H. In Silico Design of New B-Raf Kinase Type-II Inhibitors Through Combined Molecular Modeling Studies. LETT DRUG DES DISCOV 2019. [DOI: 10.2174/1570180815666180816121628] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Background:B-Raf has become an important and exciting therapeutic cancer target.Methods:In the present work, molecular modeling protocols like molecular docking, MM/GBSA calculations, 3D-QSAR and binding site detection were performed on a dataset of 41 Type II inhibitors. Molecular docking was applied to explore the detailed binding process between the inhibitors and B-Raf kinase. Furthermore, the good linear relationships between G-Scores and MM/GBSA calculated and the experimental activity were shown. The satisfactory CoMFA and CoMSIA were constructed based on the conformations obtained by molecular docking.Results:The key structural requirements for increasing biological activity were verified by analyzing 3D contour maps of the 3D-QSAR models. FTMap and SiteMap were also used to detect the more efficient active binding site.Conclusion:New inhibitors were synthesized and the biological activities were evaluated, the results further validated our design strategy.
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Affiliation(s)
- Weineng Zhou
- School of Basic Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Shuai Lu
- School of Basic Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Yanmin Zhang
- School of Basic Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Lingfeng Yin
- School of Basic Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Lu Zhu
- School of Basic Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Junnan Zhao
- School of Basic Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Tao Lu
- School of Basic Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Yadong Chen
- School of Basic Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Haichun Liu
- School of Basic Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
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18
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Toropov AA, Raška I, Toropova AP, Raškova M, Veselinović AM, Veselinović JB. The study of the index of ideality of correlation as a new criterion of predictive potential of QSPR/QSAR-models. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 659:1387-1394. [PMID: 31096349 DOI: 10.1016/j.scitotenv.2018.12.439] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 12/14/2018] [Accepted: 12/28/2018] [Indexed: 06/09/2023]
Abstract
Acetylcholinesterase (AChE) inhibitors, dihydrofolate reductase inhibitors (DHFR), Toxicity in Tetrahymena pyriformis (TP), Acute Toxicity in fathead minnow (TFat), Water solubility (WS), and Acute Aquatic Toxicity in Daphnia magna (DM) are examined as endpoints to establish quantitative structure - property/activity relationships (QSPRs/QSARs). The Index of Ideality of Correlation (IIC) is a measure of predictive potential. The IIC has been studied in a few recent works. The comparison of models for the six endpoints above confirms that the index can be a useful tool for building up and validation of QSPR/QSAR models. All examined endpoints are important from an ecologic point of view. The diversity of examined endpoints confirms that the IIC is real criterion of the predictive potential of a model.
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Affiliation(s)
- Andrey A Toropov
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Ivan Raška
- 3rd Medical Department, 1st Faculty of Medicine, Charles University in Prague, U Nemocnice 1, 12808 Prague 2, Czech Republic
| | - Alla P Toropova
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy.
| | - Maria Raškova
- 3rd Medical Department, 1st Faculty of Medicine, Charles University in Prague, U Nemocnice 1, 12808 Prague 2, Czech Republic
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19
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Li X, Zhou H, Mo X, Zhang L, Li J. In silico study of febuxostat analogs as inhibitors of xanthine oxidoreductase: A combined 3D-QSAR and molecular docking study. J Mol Struct 2019. [DOI: 10.1016/j.molstruc.2019.01.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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20
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Meng L, Feng K, Ren Y. Molecular modelling studies of tricyclic triazinone analogues as potential PKC-θ inhibitors through combined QSAR, molecular docking and molecular dynamics simulations techniques. J Taiwan Inst Chem Eng 2018. [DOI: 10.1016/j.jtice.2018.06.017] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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21
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A 3D-QSAR assisted activity prediction strategy for expanding substrate spectra of an aldehyde ketone reductase. MOLECULAR CATALYSIS 2018. [DOI: 10.1016/j.mcat.2018.06.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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22
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Balasubramanian K, Patil VM. Quantum molecular modeling of hepatitis C virus inhibition through non-structural protein 5B polymerase receptor binding of C 5-arylidene rhodanines. Comput Biol Chem 2018; 73:147-158. [PMID: 29486389 DOI: 10.1016/j.compbiolchem.2018.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 01/09/2018] [Accepted: 01/23/2018] [Indexed: 11/25/2022]
Abstract
We have carried out high-level quantum chemical computations followed by molecular docking studies on a set of 17C5-arylidene rhodanine isomers to provide insights into the binding modes with different reported binding pockets of the nonstructural protein 5B (NS5B) polymerase that contribute to the hepatitis C virus (HCV) inhibition. We optimized the multi-target profile of the selected rhodanine analogs to investigate potential non-nucleotide inhibitors (NNIs) by quantum chemical optimization of the 18 isomers followed by docking with quantum chemically optimized structures of each isomer with NS5B polymerase at multiple binding pockets. The binding affinities of the PP-I, PP-II and TP-II pockets of NS5B polymerase were analyzed for all the 17 isomers of 2-[(5Z)-5-(2,4-dichlorobenzylidene)-4-oxo-2-thioxo-1,3-thiazolidin-3-yl]-3-phenylpropanoic acid. On the basis of binding propensity at the different pockets and inhibitor constants, we ranked these isomers as potential candidates for the HCV inhibition. We have identified four isomers as promising NNIs of NS5B polymerase with comparable binding and inhibition to the standard (1,3) dichloro substituted isomer that exhibits in vitro activity and several other isomers as candidates in a "multi-targeted drug" approach.
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Affiliation(s)
| | - Vaishali M Patil
- Department of Pharmaceutical Chemistry, KIET School of Pharmacy, KIET Group of Institutions, Ghaziabad, Uttar Pradesh, India.
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23
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Speck-Planche A, Dias Soeiro Cordeiro MN. Speeding up Early Drug Discovery in Antiviral Research: A Fragment-Based in Silico Approach for the Design of Virtual Anti-Hepatitis C Leads. ACS COMBINATORIAL SCIENCE 2017; 19:501-512. [PMID: 28437091 DOI: 10.1021/acscombsci.7b00039] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Hepatitis C constitutes an unresolved global health problem. This infectious disease is caused by the hepatotropic hepatitis C virus (HCV), and it can lead to the occurrence of life-threatening medical conditions, such as cirrhosis and liver cancer. Nowadays, major clinical concerns have arisen because of the appearance of multidrug resistance (MDR) and the side effects especially associated with long-term treatments. In this work, we report the first multitasking model for quantitative structure-biological effect relationships (mtk-QSBER), focused on the simultaneous exploration of anti-HCV activity and in vitro safety profiles related to the absorption, distribution, metabolism, elimination, and toxicity (ADMET). The mtk-QSBER model was created from a data set formed by 40 158 cases, displaying accuracy higher than 95% in both training and prediction (test) sets. Several molecular fragments were selected, and their quantitative contributions to anti-HCV activity and ADMET profiles were calculated. By combining the analysis of the fragments with positive contributions and the physicochemical meanings of the different molecular descriptors in the mtk-QSBER, six new molecules were designed. These new molecules were predicted to exhibit potent anti-HCV activity and desirable in vitro ADMET properties. In addition, the designed molecules have good druglikeness according to the Lipinski's rule of five and its variants.
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Affiliation(s)
- Alejandro Speck-Planche
- LAQV@REQUIMTE/Department
of Chemistry and Biochemistry, University of Porto, 4169-007 Porto, Portugal
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24
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Fast and accurate determination of the relative binding affinities of small compounds to HIV-1 protease using non-equilibrium work. J Comput Chem 2016; 37:2734-2742. [DOI: 10.1002/jcc.24502] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2016] [Revised: 08/29/2016] [Accepted: 09/06/2016] [Indexed: 02/06/2023]
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25
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Li W, Si H, Li Y, Ge C, Song F, Ma X, Duan Y, Zhai H. 3D-QSAR and molecular docking studies on designing inhibitors of the hepatitis C virus NS5B polymerase. J Mol Struct 2016. [DOI: 10.1016/j.molstruc.2016.03.073] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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26
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Ul-Haq Z, Ashraf S, Al-Majid AM, Barakat A. 3D-QSAR Studies on Barbituric Acid Derivatives as Urease Inhibitors and the Effect of Charges on the Quality of a Model. Int J Mol Sci 2016; 17:ijms17050657. [PMID: 27144563 PMCID: PMC4881483 DOI: 10.3390/ijms17050657] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Revised: 04/05/2016] [Accepted: 04/26/2016] [Indexed: 01/02/2023] Open
Abstract
Urease enzyme (EC 3.5.1.5) has been determined as a virulence factor in pathogenic microorganisms that are accountable for the development of different diseases in humans and animals. In continuance of our earlier study on the helicobacter pylori urease inhibition by barbituric acid derivatives, 3D-QSAR (three dimensional quantitative structural activity relationship) advance studies were performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods. Different partial charges were calculated to examine their consequences on the predictive ability of the developed models. The finest developed model for CoMFA and CoMSIA were achieved by using MMFF94 charges. The developed CoMFA model gives significant results with cross-validation (q²) value of 0.597 and correlation coefficients (r²) of 0.897. Moreover, five different fields i.e., steric, electrostatic, and hydrophobic, H-bond acceptor and H-bond donors were used to produce a CoMSIA model, with q² and r² of 0.602 and 0.98, respectively. The generated models were further validated by using an external test set. Both models display good predictive power with r²pred ≥ 0.8. The analysis of obtained CoMFA and CoMSIA contour maps provided detailed insight for the promising modification of the barbituric acid derivatives with an enhanced biological activity.
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Affiliation(s)
- Zaheer Ul-Haq
- Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical & Biological Sciences, University of Karachi, Karachi 75210, Pakistan.
| | - Sajda Ashraf
- Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical & Biological Sciences, University of Karachi, Karachi 75210, Pakistan.
| | - Abdullah Mohammed Al-Majid
- Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia.
| | - Assem Barakat
- Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia.
- Department of Chemistry, Faculty of Science, Alexandria University, P.O. Box 426-Ibrahimia, Alexandria 21321, Egypt.
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