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Kazakova E, Lane TR, Jones T, Puhl AC, Riabova O, Makarov V, Ekins S. 1-Sulfonyl-3-amino-1 H-1,2,4-triazoles as Yellow Fever Virus Inhibitors: Synthesis and Structure-Activity Relationship. ACS OMEGA 2023; 8:42951-42965. [PMID: 38024733 PMCID: PMC10653066 DOI: 10.1021/acsomega.3c06106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 10/10/2023] [Accepted: 10/12/2023] [Indexed: 12/01/2023]
Abstract
Yellow fever virus (YFV) transmitted by infected mosquitoes causes an acute viral disease for which there are no approved small-molecule therapeutics. Our recently developed machine learning models for YFV inhibitors led to the selection of a new pyrazolesulfonamide derivative RCB16003 with acceptable in vitro activity. We report that the N-phenyl-1-(phenylsulfonyl)-1H-1,2,4-triazol-3-amine class, which was recently identified as active non-nucleoside reverse transcriptase inhibitors against HIV-1, can also be repositioned as inhibitors of yellow fever virus replication. As compared to other Flaviviridae or Togaviridae family viruses tested, both compounds RCB16003 and RCB16007 demonstrate selectivity for YFV over related viruses, with only RCB16007 showing some inhibition of the West Nile virus (EC50 7.9 μM, CC50 17 μM, SI 2.2). We also describe the absorption, distribution, metabolism, and excretion (ADME) in vitro and pharmacokinetics (PK) for RCB16007 in mice. This compound had previously been shown to not inhibit hERG, and we now describe that it has good metabolic stability in mouse and human liver microsomes, low levels of CYP inhibition, high protein binding, and no indication of efflux in Caco-2 cells. A single-dose oral PK study in mice has a T1/2 of 3.4 h and Cmax of 1190 ng/mL, suggesting good availability and stability. We now propose that the N-phenyl-1-(phenylsulfonyl)-1H-1,2,4-triazol-3-amine class may be prioritized for in vivo efficacy testing against YFV.
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Affiliation(s)
- Elena Kazakova
- Federal
Research Centre “Fundamentals of Biotechnology” of the
Russian Academy of Sciences (Research Centre of Biotechnology RAS), 33-2 Leninsky Prospect, 119071 Moscow, Russia
| | - Thomas R. Lane
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Thane Jones
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Ana C. Puhl
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Olga Riabova
- Federal
Research Centre “Fundamentals of Biotechnology” of the
Russian Academy of Sciences (Research Centre of Biotechnology RAS), 33-2 Leninsky Prospect, 119071 Moscow, Russia
| | - Vadim Makarov
- Federal
Research Centre “Fundamentals of Biotechnology” of the
Russian Academy of Sciences (Research Centre of Biotechnology RAS), 33-2 Leninsky Prospect, 119071 Moscow, Russia
| | - Sean Ekins
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
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2
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Feng H, Wang F, Li N, Xu Q, Zheng G, Sun X, Hu M, Xing G, Zhang G. A Random Forest Model for Peptide Classification Based on Virtual Docking Data. Int J Mol Sci 2023; 24:11409. [PMID: 37511165 PMCID: PMC10380188 DOI: 10.3390/ijms241411409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 06/25/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
The affinity of peptides is a crucial factor in studying peptide-protein interactions. Despite the development of various techniques to evaluate peptide-receptor affinity, the results may not always reflect the actual affinity of the peptides accurately. The current study provides a free tool to assess the actual peptide affinity based on virtual docking data. This study employed a dataset that combined actual peptide affinity information (active and inactive) and virtual peptide-receptor docking data, and different machine learning algorithms were utilized. Compared with the other algorithms, the random forest (RF) algorithm showed the best performance and was used in building three RF models using different numbers of significant features (four, three, and two). Further analysis revealed that the four-feature RF model achieved the highest Accuracy of 0.714 in classifying an independent unknown peptide dataset designed with the PEDV spike protein, and it also revealed overfitting problems in the other models. This four-feature RF model was used to evaluate peptide affinity by constructing the relationship between the actual affinity and the virtual docking scores of peptides to their receptors.
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Affiliation(s)
- Hua Feng
- Key Laboratory of Animal Immunology, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Fangyu Wang
- Key Laboratory of Animal Immunology, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Ning Li
- Key Laboratory of Animal Immunology, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Qian Xu
- Key Laboratory of Animal Immunology, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Guanming Zheng
- Public Health and Preventive Medicine Teaching and Research Center, Henan University of Chinese Medicine, Zhengzhou 450046, China
| | - Xuefeng Sun
- Key Laboratory of Animal Immunology, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Man Hu
- Key Laboratory of Animal Immunology, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Guangxu Xing
- Key Laboratory of Animal Immunology, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Gaiping Zhang
- Key Laboratory of Animal Immunology, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
- Longhu Modern Immunology Laboratory, Zhengzhou 450002, China
- School of Advanced Agricultural Sciences, Peking University, Beijing 100871, China
- Jiangsu Co-Innovation Center for the Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China
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3
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Rehman HM, Sajjad M, Ali MA, Gul R, Irfan M, Naveed M, Bhinder MA, Ghani MU, Hussain N, Said ASA, Al Haddad AHI, Saleem M. Identification of NS2B-NS3 Protease Inhibitors for Therapeutic Application in ZIKV Infection: A Pharmacophore-Based High-Throughput Virtual Screening and MD Simulations Approaches. Vaccines (Basel) 2023; 11:vaccines11010131. [PMID: 36679976 PMCID: PMC9862652 DOI: 10.3390/vaccines11010131] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 01/06/2023] Open
Abstract
Zika virus (ZIKV) pandemic and its implication in congenital malformations and severe neurological disorders had created serious threats to global health. ZIKV is a mosquito-borne flavivirus which spread rapidly and infect a large number of people in a shorter time-span. Due to the lack of effective therapeutics, this had become paramount urgency to discover effective drug molecules to encounter the viral infection. Various anti-ZIKV drug discovery efforts during the past several years had been unsuccessful to develop an effective cure. The NS2B-NS3 protein was reported as an attractive therapeutic target for inhibiting viral proliferation, due to its central role in viral replication and maturation of non-structural viral proteins. Therefore, the current in silico drug exploration aimed to identify the novel inhibitors of Zika NS2B-NS3 protease by implementing an e-pharmacophore-based high-throughput virtual screening. A 3D e-pharmacophore model was generated based on the five-featured (ADPRR) pharmacophore hypothesis. Subsequently, the predicted model is further subjected to the high-throughput virtual screening to reveal top hit molecules from the various small molecule databases. Initial hits were examined in terms of binding free energies and ADME properties to identify the candidate hit exhibiting a favourable pharmacokinetic profile. Eventually, molecular dynamic (MD) simulations studies were conducted to evaluate the binding stability of the hit molecule inside the receptor cavity. The findings of the in silico analysis manifested affirmative evidence for three hit molecules with -64.28, -55.15 and -50.16 kcal/mol binding free energies, as potent inhibitors of Zika NS2B-NS3 protease. Hence, these molecules holds the promising potential to serve as a prospective candidates to design effective drugs against ZIKV and related viral infections.
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Affiliation(s)
- Hafiz Muzzammel Rehman
- School of Biochemistry and Biotechnology, University of the Punjab, Lahore 54590, Punjab, Pakistan
- Department of Human Genetics and Molecular Biology, University of Health Sciences, Lahore 54590, Punjab, Pakistan
| | - Muhammad Sajjad
- School of Biological Sciences, University of the Punjab, Quaid e Azam Campus, Lahore 54590, Punjab, Pakistan
| | - Muhammad Akhtar Ali
- School of Biological Sciences, University of the Punjab, Quaid e Azam Campus, Lahore 54590, Punjab, Pakistan
| | - Roquyya Gul
- Faculty of Life Sciences, Gulab Devi Educational Complex, Lahore 54590, Punjab, Pakistan
| | - Muhammad Irfan
- Kauser Abdulla Malik School of Life Sciences, Forman Christian College (A Chartered University), Lahore 54600, Punjab, Pakistan
| | - Muhammad Naveed
- Department of Biotechnology, Faculty of Science and Technology, University of Central Punjab Lahore, Lahore 54590, Punjab, Pakistan
| | - Munir Ahmad Bhinder
- Department of Human Genetics and Molecular Biology, University of Health Sciences, Lahore 54590, Punjab, Pakistan
| | - Muhammad Usman Ghani
- Center for Applied Molecular Biology, University of the Punjab, Lahore 54590, Punjab, Pakistan
| | - Nadia Hussain
- Department of Pharmaceutical Sciences, College of Pharmacy, Al Ain University, Al Ain 64141, United Arab Emirates
- AAU Health and Biomedical Research Center, Al Ain University, Abu Dhabi 112612, United Arab Emirates
| | - Amira S. A. Said
- AAU Health and Biomedical Research Center, Al Ain University, Abu Dhabi 112612, United Arab Emirates
- Department of Clinical Pharmacy, College of Pharmacy, Al Ain University, Al Ain 64141, United Arab Emirates
- Clinical Pharmacy Department, Faculty of Pharmacy, Beni Suef University, Beni Suef 62521, Egypt
| | - Amal H. I. Al Haddad
- Chief Operations Office, Sheikh Shakhbout Medical City (SSMC) in Partnership with Mayo Clinic, Abu Dhabi 11001, United Arab Emirates
| | - Mahjabeen Saleem
- School of Biochemistry and Biotechnology, University of the Punjab, Lahore 54590, Punjab, Pakistan
- School of Medical Lab Technology, Minhaj University Lahore, Lahore 54770, Punjab, Pakistan
- Correspondence:
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4
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Edeh MO, Dalal S, Dhaou IB, Agubosim CC, Umoke CC, Richard-Nnabu NE, Dahiya N. Artificial Intelligence-Based Ensemble Learning Model for Prediction of Hepatitis C Disease. Front Public Health 2022; 10:892371. [PMID: 35570979 PMCID: PMC9092454 DOI: 10.3389/fpubh.2022.892371] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 03/17/2022] [Indexed: 12/15/2022] Open
Abstract
Machine learning algorithms are excellent techniques to develop prediction models to enhance response and efficiency in the health sector. It is the greatest approach to avoid the spread of hepatitis C, especially injecting drugs, is to avoid these behaviors. Treatments for hepatitis C can cure most patients within 8 to 12 weeks, so being tested is critical. After examining multiple types of machine learning approaches to construct the classification models, we built an AI-based ensemble model for predicting Hepatitis C disease in patients with the capacity to predict advanced fibrosis by integrating clinical data and blood biomarkers. The dataset included a variety of factors related to Hepatitis C disease. The training data set was subjected to three machine-learning approaches and the validated data was then used to evaluate the ensemble learning-based prediction model. The results demonstrated that the proposed ensemble learning model has been observed ad more accurate compared to the existing Machine learning algorithms. The Multi-layer perceptron (MLP) technique was the most precise learning approach (94.1% accuracy). The Bayesian network was the second-most accurate learning algorithm (94.47% accuracy). The accuracy improved to the level of 95.59%. Hepatitis C has a significant frequency globally, and the disease's development can result in irreparable damage to the liver, as well as death. As a result, utilizing AI-based ensemble learning model for its prediction is advantageous in curbing the risks and improving treatment outcome. The study demonstrated that the use of ensemble model presents more precision or accuracy in predicting Hepatitis C disease instead of using individual algorithms. It also shows how an AI-based ensemble model could be used to diagnose Hepatitis C disease with greater accuracy.
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Affiliation(s)
- Michael Onyema Edeh
- Department of Mathematics and Computer Science, Coal City University, Enugu, Nigeria
| | - Surjeet Dalal
- College of Computing Science & Information Technology, Teerthanker Mahaveer University, Moradabad, India
| | - Imed Ben Dhaou
- Department of Computer Science, Hekma School of Engineering, Computing and Informatics, Dar Al-Hekma University, Jeddah, Saudi Arabia
| | | | - Chukwudum Collins Umoke
- Department of Vocational and Technical Education, Alex Ekwueme Federal University Ndufu Alike Ikwo (AE- FUNAI), Abakaliki, Nigeria
| | - Nneka Ernestina Richard-Nnabu
- Department of Computer Science/Informatics, Alex Ekwueme Federal University Ndufu Alike Ikwo (AE-FUNAI), Abakaliki, Nigeria
| | - Neeraj Dahiya
- Department of Computer Science and Engineering, SRM University Delhi-NCR, Sonipat, India
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5
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Pathania S, Rawal RK, Singh PK. RdRp (RNA-dependent RNA polymerase): A key target providing anti-virals for the management of various viral diseases. J Mol Struct 2022; 1250:131756. [PMID: 34690363 PMCID: PMC8520695 DOI: 10.1016/j.molstruc.2021.131756] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 10/13/2021] [Accepted: 10/15/2021] [Indexed: 01/04/2023]
Abstract
With the arrival of the Covid-19 pandemic, anti-viral agents have regained center stage in the arena of medicine. Out of the various drug targets involved in managing RNA-viral infections, the one that dominates almost all RNA viruses is RdRp (RNA-dependent RNA polymerase). RdRp are proteins that are involved in the replication of RNA-based viruses. Inhibition of RdRps has been an integral approach for managing various viral infections such as dengue, influenza, HCV (Hepatitis), BVDV, etc. Inhibition of the coronavirus RdRp is currently rigorously explored for the treatment of Covid-19 related complications. So, keeping in view the importance and current relevance of this drug target, we have discussed the importance of RdRp in developing anti-viral agents against various viral diseases. Different reported inhibitors have also been discussed, and emphasis has been laid on highlighting the inhibitor's pharmacophoric features and SAR profile.
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Affiliation(s)
- Shelly Pathania
- Department of Pharmaceutical Chemistry, ISF College of Pharmacy, Moga-142001, Punjab, India
| | - Ravindra K. Rawal
- Department of Chemistry, Maharishi Markandeshwar (Deemed to be University), Mullana-133207, Haryana, India,CSIR-North East Institute of Science and Technology, Jorhat-785006, Assam, India,Corresponding authors
| | - Pankaj Kumar Singh
- Faculty of Medicine, Integrative Physiology and Pharmacology, Institute of Biomedicine, University of Turku, Turku, FI-20014, Finland,Corresponding authors
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6
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Ebenezer O, Damoyi N, Shapi M. Predicting New Anti-Norovirus Inhibitor With the Help of Machine Learning Algorithms and Molecular Dynamics Simulation-Based Model. Front Chem 2021; 9:753427. [PMID: 34869204 PMCID: PMC8636098 DOI: 10.3389/fchem.2021.753427] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 10/13/2021] [Indexed: 12/30/2022] Open
Abstract
Hepatitis C virus (HCV) inhibitors are essential in the treatment of human norovirus (HuNoV). This study aimed to map out HCV NS5B RNA-dependent RNA polymerase inhibitors that could potentially be responsible for the inhibitory activity of HuNoV RdRp. It is necessary to develop robust machine learning and in silico methods to predict HuNoV RdRp compounds. In this study, Naïve Bayesian and random forest models were built to categorize norovirus RdRp inhibitors from the non-inhibitors using their molecular descriptors and PubChem fingerprints. The best model observed had accuracy, specificity, and sensitivity values of 98.40%, 97.62%, and 97.62%, respectively. Meanwhile, an external test set was used to validate model performance before applicability to the screened HCV compounds database. As a result, 775 compounds were predicted as NoV RdRp inhibitors. The pharmacokinetics calculations were used to filter out the inhibitors that lack drug-likeness properties. Molecular docking and molecular dynamics simulation investigated the inhibitors' binding modes and residues critical for the HuNoV RdRp receptor. The most active compound, CHEMBL167790, closely binds to the binding pocket of the RdRp enzyme and depicted stable binding with RMSD 0.8-3.2 Å, and the RMSF profile peak was between 1.0-4.0 Å, and the conformational fluctuations were at 450-460 residues. Moreover, the dynamic residue cross-correlation plot also showed the pairwise correlation between the binding residues 300-510 of the HuNoV RdRp receptor and CHEMBL167790. The principal component analysis depicted the enhanced movement of protein atoms. Moreover, additional residues such as Glu510 and Asn505 interacted with CHEMBL167790 via water bridge and established H-bond interactions after the simulation. http://zinc15.docking.org/substances/ZINC000013589565.
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Affiliation(s)
- Oluwakemi Ebenezer
- Department of Chemistry, Faculty of Natural Science, Mangosuthu University of Technology, Durban, South Africa
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7
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A Novel Small Molecule Inhibits Hepatitis C Virus Propagation in Cell Culture. Microbiol Spectr 2021; 9:e0043921. [PMID: 34319169 PMCID: PMC8552720 DOI: 10.1128/spectrum.00439-21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Hepatitis C virus (HCV) can cause acute and chronic infection that is associated with considerable liver-related morbidity and mortality. In recent years, there has been a shift in the treatment paradigm with the discovery and approval of agents that target specific proteins vital for viral replication. We employed a cell culture-adapted strain of HCV and human hepatoma-derived cells lines to test the effects of our novel small-molecule compound (AO13) on HCV. Virus inhibition was tested by analyzing RNA replication, protein expression, and virus production in virus-infected cells treated with AO13. Treatment with AO13 inhibited virus spread in cell culture and showed a 100-fold reduction in the levels of infectious virus production. AO13 significantly reduced the level of viral RNA contained within cell culture fluids and reduced the cellular levels of HCV core protein, suggesting that the compound might act on a late step in the viral life cycle. Finally, we observed that AO13 did not affect the release of infectious virus from infected cells. Docking studies and molecular dynamics analyses suggested that AO13 might target the NS5B RNA polymerase, however, real-time RT-PCR analyses of cellular levels of HCV RNA showed only an ∼2-fold reduction in viral RNA levels in the presence of AO13. Taken together, this study revealed that AO13 showed consistent, but low-level antiviral effect against HCV, although the mechanism of action remains unclear. IMPORTANCE The discovery of curative antiviral drugs for a chronic disease such as HCV infection has encouraged drug discovery in the context of other viruses for which no curative drugs currently exist. Since we currently face a novel virus that has caused a pandemic, the need for new antiviral agents is more apparent than ever. We describe here a novel compound that shows a modest antiviral effect against HCV that could serve as a lead compound for future drug development against other important viruses such as SARS-CoV-2.
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8
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Gawriljuk VO, Foil DH, Puhl AC, Zorn KM, Lane TR, Riabova O, Makarov V, Godoy AS, Oliva G, Ekins S. Development of Machine Learning Models and the Discovery of a New Antiviral Compound against Yellow Fever Virus. J Chem Inf Model 2021; 61:3804-3813. [PMID: 34286575 DOI: 10.1021/acs.jcim.1c00460] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Yellow fever (YF) is an acute viral hemorrhagic disease transmitted by infected mosquitoes. Large epidemics of YF occur when the virus is introduced into heavily populated areas with high mosquito density and low vaccination coverage. The lack of a specific small molecule drug treatment against YF as well as for homologous infections, such as zika and dengue, highlights the importance of these flaviviruses as a public health concern. With the advancement in computer hardware and bioactivity data availability, new tools based on machine learning methods have been introduced into drug discovery, as a means to utilize the growing high throughput screening (HTS) data generated to reduce costs and increase the speed of drug development. The use of predictive machine learning models using previously published data from HTS campaigns or data available in public databases, can enable the selection of compounds with desirable bioactivity and absorption, distribution, metabolism, and excretion profiles. In this study, we have collated cell-based assay data for yellow fever virus from the literature and public databases. The data were used to build predictive models with several machine learning methods that could prioritize compounds for in vitro testing. Five molecules were prioritized and tested in vitro from which we have identified a new pyrazolesulfonamide derivative with EC50 3.2 μM and CC50 24 μM, which represents a new scaffold suitable for hit-to-lead optimization that can expand the available drug discovery candidates for YF.
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Affiliation(s)
- Victor O Gawriljuk
- São Carlos Institute of Physics, University of São Paulo, Av. João Dagnone, 1100 - Santa Angelina, São Carlos, São Paulo 13563-120, Brazil
| | - Daniel H Foil
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Ana C Puhl
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Kimberley M Zorn
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Thomas R Lane
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Olga Riabova
- Research Center of Biotechnology RAS, Leninsky Prospekt 33-2, 119071 Moscow, Russia
| | - Vadim Makarov
- Research Center of Biotechnology RAS, Leninsky Prospekt 33-2, 119071 Moscow, Russia
| | - Andre S Godoy
- São Carlos Institute of Physics, University of São Paulo, Av. João Dagnone, 1100 - Santa Angelina, São Carlos, São Paulo 13563-120, Brazil
| | - Glaucius Oliva
- São Carlos Institute of Physics, University of São Paulo, Av. João Dagnone, 1100 - Santa Angelina, São Carlos, São Paulo 13563-120, Brazil
| | - Sean Ekins
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
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9
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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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10
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Serafim MSM, Dos Santos Júnior VS, Gertrudes JC, Maltarollo VG, Honorio KM. Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade. Expert Opin Drug Discov 2021; 16:961-975. [PMID: 33957833 DOI: 10.1080/17460441.2021.1918098] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction: Drug design and discovery of new antivirals will always be extremely important in medicinal chemistry, taking into account known and new viral diseases that are yet to come. Although machine learning (ML) have shown to improve predictions on the biological potential of chemicals and accelerate the discovery of drugs over the past decade, new methods and their combinations have improved their performance and established promising perspectives regarding ML in the search for new antivirals.Areas covered: The authors consider some interesting areas that deal with different ML techniques applied to antivirals. Recent innovative studies on ML and antivirals were selected and analyzed in detail. Also, the authors provide a brief look at the past to the present to detect advances and bottlenecks in the area.Expert opinion: From classical ML techniques, it was possible to boost the searches for antivirals. However, from the emergence of new algorithms and the improvement in old approaches, promising results will be achieved every day, as we have observed in the case of SARS-CoV-2. Recent experience has shown that it is possible to use ML to discover new antiviral candidates from virtual screening and drug repurposing.
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Affiliation(s)
- Mateus Sá Magalhães Serafim
- Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | | | - Jadson Castro Gertrudes
- Departamento de Computação, Instituto de Ciências Exatas e Biológicas, Universidade Federal de Ouro Preto (UFOP), Ouro Preto, Brazil
| | - Vinícius Gonçalves Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Kathia Maria Honorio
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo (USP), São Paulo, Brazil.,Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, Brazil
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11
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Immuno-Informatics Analysis of Pakistan-Based HCV Subtype-3a for Chimeric Polypeptide Vaccine Design. Vaccines (Basel) 2021; 9:vaccines9030293. [PMID: 33801143 PMCID: PMC8004085 DOI: 10.3390/vaccines9030293] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 03/17/2021] [Accepted: 03/18/2021] [Indexed: 12/12/2022] Open
Abstract
Hepatitis C virus (HCV) causes chronic and acute hepatitis infections. As there is extreme variability in the HCV genome, no approved HCV vaccine has been available so far. An effective polypeptide vaccine based on the functionally conserved epitopes will be greatly helpful in curing disease. For this purpose, an immuno-informatics study is performed based on the published HCV subtype-3a from Pakistan. First, the virus genome was translated to a polyprotein followed by a subsequent prediction of T-cell epitopes. Non-allergenic, IFN-γ producer, and antigenic epitopes were shortlisted, including 5 HTL epitopes and 4 CTL, which were linked to the final vaccine by GPGPG and AAY linkers, respectively. Beta defensin was included as an adjuvant through the EAAAK linker to improve the immunogenicity of the polypeptide. To ensure its safety and immunogenicity profile, antigenicity, allergenicity, and various physiochemical attributes of the polypeptide were evaluated. Molecular docking was conducted between TLR4 and vaccine to evaluate the binding affinity and molecular interactions. For stability assessment and binding of the vaccine-TLR4 docked complex, molecular dynamics (MD) simulation and MMGBSA binding free-energy analyses were conducted. Finally, the candidate vaccine was cloned in silico to ensure its effectiveness. The current vaccine requires future experimental confirmation to validate its effectiveness. The vaccine construct produced might be useful in providing immune protection against HCV-related infections.
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12
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El Hassab MA, Ibrahim TM, Al-Rashood ST, Alharbi A, Eskandrani RO, Eldehna WM. In silico identification of novel SARS-COV-2 2'-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches. J Enzyme Inhib Med Chem 2021; 36:727-736. [PMID: 33685335 PMCID: PMC7946047 DOI: 10.1080/14756366.2021.1885396] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The novel coronavirus disease COVID-19, caused by the virus SARS CoV-2, has exerted a significant unprecedented economic and medical crisis, in addition to its impact on the daily life and health care systems all over the world. Regrettably, no vaccines or drugs are currently available for this new critical emerging human disease. Joining the global fight against COVID-19, in this study we aim at identifying a potential novel inhibitor for SARS COV-2 2'-O-methyltransferase (nsp16) which is one of the most attractive targets in the virus life cycle, responsible for the viral RNA protection via a cap formation process. Firstly, nsp16 enzyme bound to Sinefungin was retrieved from the protein data bank (PDB ID: 6WKQ), then, a 3D pharmacophore model was constructed to be applied to screen 48 Million drug-like compounds of the Zinc database. This resulted in only 24 compounds which were subsequently docked into the enzyme. The best four score-ordered hits from the docking outcome exhibited better scores compared to Sinefungin. Finally, three molecular dynamics (MD) simulation experiments for 150 ns were carried out as a refinement step for our proposed approach. The MD and MM-PBSA outputs revealed compound 11 as the best potential nsp16 inhibitor herein identified, as it displayed a better stability and average binding free energy for the ligand-enzyme complex compared to Sinefungin.
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Affiliation(s)
- Mahmoud A El Hassab
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Badr University in Cairo (BUC), Badr City, Egypt
| | - Tamer M Ibrahim
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Kafrelsheikh University, Kafrelsheikh, Egypt
| | - Sara T Al-Rashood
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Amal Alharbi
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Razan O Eskandrani
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Wagdy M Eldehna
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Kafrelsheikh University, Kafrelsheikh, Egypt
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13
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Anwar MF, Khalid R, Hasanain A, Naeem S, Zarina S, Abidi SH, Ali S. Integrated Cheminformatics-Molecular Docking Approach to Drug Discovery Against Viruses. Infect Disord Drug Targets 2020; 20:150-159. [PMID: 30345931 DOI: 10.2174/1871526518666181019162359] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 08/03/2018] [Accepted: 10/11/2018] [Indexed: 11/22/2022]
Abstract
BACKGROUND In the current study, we present an integrated in silico cheminformaticsmolecular docking approach to screen and test potential therapeutic compounds against viruses. Fluoroquinolones have been shown to inhibit HCV replication by targeting HCV NS3-helicase. Based on this observation, we hypothesized that natural analogs of fluoroquinolones will have similar or superior inhibitory potential while having potentially fewer adverse effects. METHODS To screen for natural analogs of fluoroquinolones, we devised an integrated in silico Cheminformatics-Molecular Docking approach. We used 17 fluoroquinolones as bait reference, to screen large databases of natural analogs. 10399 natural compounds and their derivatives were retrieved from the databases. From these compounds, molecules bearing physicochemical similarities with fluoroquinolones were analyzed using a cheminformatics-docking approach. RESULTS From the 10399 compounds screened using our cheminformatics approach, only 20 compounds were found to share physicochemical similarities with fluoroquinolones, while the remaining 10379 compounds were physiochemically different from fluoroquinolones. Molecular docking analysis showed 32 amino acids in the HCV NS3 active site that were most frequently targeted by fluoroquinolones and their natural analogues, indicating a functional similarity between the two groups of compounds. CONCLUSION This study describes a speedy and inexpensive approach to complement drug discovery and design against viral agents. The in silico analyses we used here can be employed to shortlist promising compounds/putative drugs that can be further tested in wet-lab.
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Affiliation(s)
- Muhammad Faraz Anwar
- National Center for Proteomics, University of Karachi, Karachi, Pakistan.,Department of Biological and Biomedical Sciences, Aga Khan University, Karachi, Pakistan
| | - Ramsha Khalid
- Department of Biochemistry, University of Karachi, Karachi, Pakistan
| | | | - Sadaf Naeem
- Department of Biochemistry, University of Karachi, Karachi, Pakistan
| | - Shamshad Zarina
- National Center for Proteomics, University of Karachi, Karachi, Pakistan
| | - Syed Hani Abidi
- Department of Biological and Biomedical Sciences, Aga Khan University, Karachi, Pakistan.,Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Syed Ali
- Department of Biomedical Sciences, Nazarbayev University School of Medicine, Nazarbayev University, Astana, Kazakhstan
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14
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Asiri YI, Alsayari A, Muhsinah AB, Mabkhot YN, Hassan MZ. Benzothiazoles as potential antiviral agents. J Pharm Pharmacol 2020; 72:1459-1480. [PMID: 32705690 PMCID: PMC7405065 DOI: 10.1111/jphp.13331] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 06/03/2020] [Accepted: 06/13/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVES The recent viral pandemic poses a unique challenge for healthcare providers. Despite the remarkable progress, the number of novel antiviral agents in the pipeline is woefully inadequate against the evolving virulence and drug resistance of current viruses. This highlights the urgent need for new and improved vaccines, diagnostics and therapeutic agents to obviate the viral pandemic. KEY FINDINGS Benzothiazole plays a pivotal role in the design and development of antiviral drugs. This is evident from the fact that it comprises many clinically useful agents. The current review is aimed to provide an insight into the recent development of benzothiazole-based antiviral agents, with a special focus on their structure-activity relationships and lead optimisation. One hundred and five articles were initially identified, and from these studies, 64 potential novel lead molecules and main findings were highlighted in this review. SUMMARY We hope this review will provide a logical perspective on the importance of improving the future designs of novel broad-spectrum benzothiazole-based antiviral agents to be used against emerging viral diseases.
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Affiliation(s)
- Yahya I Asiri
- Department of Pharmacology, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
| | - Abdulrhman Alsayari
- Department of Pharmacognosy, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
| | - Abdullatif B Muhsinah
- Department of Pharmacognosy, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
| | - Yahia N Mabkhot
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
| | - Mohd Z Hassan
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
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15
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Application of an integrated cheminformatics-molecular docking approach for discovery for physicochemically similar analogs of fluoroquinolones as putative HCV inhibitors. Comput Biol Chem 2019; 84:107167. [PMID: 31855781 DOI: 10.1016/j.compbiolchem.2019.107167] [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: 01/24/2018] [Revised: 10/02/2019] [Accepted: 11/16/2019] [Indexed: 01/13/2023]
Abstract
BACKGROUND Hepatitis C Virus (HCV) infection is a major public health concern across the globe. At present, direct-acting antivirals are the treatment of choice. However, the long-term effect of this therapy has yet to be ascertained. Previously, fluoroquinolones have been reported to inhibit HCV replication by targeting NS3 protein. Therefore, it is logical to hypothesize that the natural analogs of fluoroquinolones will exhibit NS3 inhibitory activity with substantially lesser side effects. METHOD In this study, we tested the application of a recently devised integrated in-silico Cheminformatics-Molecular Docking approach to identify physicochemically similar natural analogs of fluoroquinolones from the available databases (Ambinter, Analyticon, Indofines, Specs, and TimTec). Molecular docking and ROC curve analyses were performed, using PatchDock and Graphpad software, respectively, to compare and analyze drug-protein interactions between active natural analogs, Fluoroquinolones, and HCV NS3 protein. RESULT In our analysis, we were able to shortlist 18 active natural analogs, out of 10,399, that shared physicochemical properties with the template drugs (fluoroquinolones). These analogs showed comparable binding efficacy with fluoroquinolones in targeting 32 amino acids in the HCV NS3 active site that are crucial for NS3 activity. Our approach had around 80 % sensitivity and 70 % specificity in identifying physicochemically similar analogs of fluoroquinolones. CONCLUSION Our current data suggest that our approach can be efficiently applied to identify putative HCV drug inhibitors that can be taken for in vitro testing. This approach can be applied to discover physicochemically similar analogs of virtually any drug, thus providing a speedy and inexpensive approach to complement drug discovery and design, which can tremendously economize on time and money spent on the screening of putative drugs.
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16
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El-Hassab MAEM, El-Bastawissy EE, El-Moselhy TF. Identification of potential inhibitors for HCV NS5b of genotype 4a by combining dynamic simulation, protein-ligand interaction fingerprint, 3D pharmacophore, docking and 3D QSAR. J Biomol Struct Dyn 2019; 38:4521-4535. [PMID: 31647392 DOI: 10.1080/07391102.2019.1685005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
HCV NS5B polymerase has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting Hepatitis C Virus genotype 1 (HCV GT1). Hepatitis C virus genotype 4a (HCV GT4a) dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS5B polymerase of GT4a using homology modeling, protein-ligand interaction fingerprint (PLIF), docking, pharmacophore, and 3D CoMFA quantitative structure activity relationship (QSAR). Firstly, a high-quality 3D model of HCV NS5B polymerase of GT4a was constructed using crystal structure of HCV NS5B polymerase of GT1 (PDB ID: 3hkw) as a template. Then, both the model and the template were simulated to compare conformational stability. PLIF was generated using five crystal structures of HCV NS5B (PDB ID: 4mia, 4mib, 4mk9, 4mka, and 4mkb), which revealed the most important residues and their interactions with the co-crystalized ligands. After that, a 3D pharmacophore model was developed from the generated PLIF data and then used as a screening filter for 17000328 drug-like zinc database compounds. 900 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. Finally, a 3D CoMFA QSAR was developed using 42 compounds as a training and 19 compounds as a test set. The 3D CoMFA QSAR was used to design and screen some potential inhibitors, these compounds were further evaluated by the docking stage. The highest ranked five hits from docking result (compounds (p1-p4) and compound q1) were selected for further analysis.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
| | | | - Tarek Fathy El-Moselhy
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tanta University, Gharbia, Egypt
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17
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Akher FB, Farrokhzadeh A, Ramharack P, Shunmugam L, Van Heerden FR, Soliman MES. Discovery of novel natural flavonoids as potent antiviral candidates against hepatitis C virus NS5B polymerase. Med Hypotheses 2019; 132:109359. [PMID: 31466018 DOI: 10.1016/j.mehy.2019.109359] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Revised: 07/28/2019] [Accepted: 08/11/2019] [Indexed: 12/13/2022]
Abstract
The non-structural 5B (NS5B) polymerase of hepatitis C virus (HCV) is an attractive target for antiviral intervention. Quercetagetin (Que) is a natural flavonoid, which has been exhibited to have anti-HCV property through inhibition of RNA binding to NS5B. The last few decades have witnessed a growing interest in the extraction of natural flavonoids with a plethora of different biological activities. Considering the high therapeutic potential of Que, the aim of this study is to explore wide structure entities with potent activity using Que as a prototype. A virtual screen protocol involving docking and molecular dynamics has been performed to examine the potency of forty-three natural flavonoids which recently extracted from plants for inhibition of NS5B. During two screening stages, two compounds 24 and 41 were identified to have more favorable binding affinity to NS5B as compared to Que. The comparative analysis showed that there is a significant difference in the binding free energy of Que and 41 (ΔΔGbind = -11.17 kcal/mol). It was revealed that van der Waals (vdW) interaction drives the binding process of both 24 and 41 and plays an important role in increasing their activities relative to Que. PHE162 serves as a crucial residue in both the NS5B-24 and NS5B-41 systems, contributing the most vdW energy by π-π interaction, suggesting that aromatic interactions are critical for the binding of 24 and 41 to NS5B. Moreover, hydrogen bond analysis indicates that the hydrogen bonds formed by LYS98, THR137, ASP164 and ARG168, can play important roles in the increased binding affinity of 41 to NS5B relative to Que. The findings of this study will provide useful structure-activity relationship (SAR) guidelines for the design of novel inhibitors with improved/enhanced therapeutic activities in the treatment of hepatitis C.
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Affiliation(s)
- Farideh Badichi Akher
- Department of Computer Science, University of Cape Town, Cape Town 7701, South Africa; Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa.
| | - Abdolkarim Farrokhzadeh
- School of Chemistry and Physics, University of KwaZulu-Natal, Private Bag X01, Pietermaritzburg 3209, South Africa; Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
| | - Pritika Ramharack
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
| | - Letitia Shunmugam
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
| | - Fanie R Van Heerden
- School of Chemistry and Physics, University of KwaZulu-Natal, Private Bag X01, Pietermaritzburg 3209, South Africa
| | - Mahmoud E S Soliman
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa.
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18
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Qiu Y, Zhou L, Hu Y, Bao Y. Discovery of promising FtsZ inhibitors by E-pharmacophore, 3D-QSAR, molecular docking study, and molecular dynamics simulation. J Recept Signal Transduct Res 2019; 39:154-166. [PMID: 31355691 DOI: 10.1080/10799893.2019.1638404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Asbtract Filamentous temperature-sensitive protein Z (FtsZ), playing a key role in bacterial cell division, is regarded as a promising target for the design of antimicrobial agent. This study is looking for potential high-efficiency FtsZ inhibitors. Ligand-based pharmacophore and E-pharmacophore, virtual screening and molecular docking were used to detect promising FtsZ inhibitors, and molecular dynamics simulation was used to study the stability of protein-ligand complexes in this paper. Sixty-three inhibitors from published literatures with pIC50 ranging from 2.483 to 5.678 were collected to develop ligand-based pharmacophore model. 4DXD bound with 9PC was selected to develop the E-pharmacophore model. The pharmacophore models validated by test set method and decoy set were employed for virtual screening to exclude inactive compounds against ZINC database. After molecular docking, ADME analysis, IFD docking and MM-GBSA, 8 hits were identified as potent FtsZ inhibitors. A 50 ns molecular dynamics simulation was implemented on the compounds to assess the stability between potent inhibitors and FtsZ. The results indicated that the candidate compounds had a high docking score and were strongly combined with FtsZ by forming hydrogen bonding interactions with key amino acid residues, and van der Waals forces and hydrophobic interactions had significant contribution to the stability of the binding. Molecular dynamics simulation results showed that the protein-ligand compounds performed well in both the stability and flexibility of the simulation process.
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Affiliation(s)
- Yaping Qiu
- a College of Chemical Engineering, Sichuan University , Chengdu , China
| | - Lu Zhou
- a College of Chemical Engineering, Sichuan University , Chengdu , China
| | - Yanqiu Hu
- a College of Chemical Engineering, Sichuan University , Chengdu , China
| | - Yinfeng Bao
- a College of Chemical Engineering, Sichuan University , Chengdu , China
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Caruso A, Ceramella J, Iacopetta D, Saturnino C, Mauro MV, Bruno R, Aquaro S, Sinicropi MS. Carbazole Derivatives as Antiviral Agents: An Overview. Molecules 2019; 24:E1912. [PMID: 31109016 PMCID: PMC6572111 DOI: 10.3390/molecules24101912] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 05/06/2019] [Accepted: 05/15/2019] [Indexed: 02/07/2023] Open
Abstract
Keywords: carbazole; tetrahydrocarbazole; antiviral agents.
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Affiliation(s)
- Anna Caruso
- Department of Pharmacy, Health & Nutritional Sciences, University of Calabria,87036 Arcavacata di Rende, Italy.
| | - Jessica Ceramella
- Department of Pharmacy, Health & Nutritional Sciences, University of Calabria,87036 Arcavacata di Rende, Italy.
| | - Domenico Iacopetta
- Department of Pharmacy, Health & Nutritional Sciences, University of Calabria,87036 Arcavacata di Rende, Italy.
| | - Carmela Saturnino
- Department of Science, University of Basilicata, Potenza 85100, Italy.
| | | | - Rosalinda Bruno
- Department of Pharmacy, Health & Nutritional Sciences, University of Calabria,87036 Arcavacata di Rende, Italy.
| | - Stefano Aquaro
- Department of Pharmacy, Health & Nutritional Sciences, University of Calabria,87036 Arcavacata di Rende, Italy.
| | - Maria Stefania Sinicropi
- Department of Pharmacy, Health & Nutritional Sciences, University of Calabria,87036 Arcavacata di Rende, Italy.
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20
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Venkatesan A, Prabhu Dass J F. Review on chemogenomic approaches towards hepatitis C viral targets. J Cell Biochem 2019; 120:12167-12181. [PMID: 30887580 DOI: 10.1002/jcb.28581] [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: 08/09/2018] [Revised: 01/09/2019] [Accepted: 01/14/2019] [Indexed: 12/18/2022]
Abstract
Hepatitis C virus (HCV) is the most prevalent viral pathogen that infects more than 185 million people worldwide. HCV infection leads to chronic liver diseases such as liver cirrhosis and hepatocellular carcinoma. Direct-acting antivirals (DAAs) are the recent combination therapy for HCV infection with reduced side effects than prior therapies. Sustained virological response (SVR) acts as a gold standard marker to monitor the success of antiviral treatment. Older treatment therapies attain 50-55% of SVR compared with DAAs which attain around 90-95%. The current review emphasizes the recent chemogenomic updates that have been unfolded through structure-based drug design of HCV drug target proteins (NS3/4A, NS5A, and NS5B) and ligand-based drug design of DAAs in achieving a stable HCV viral treatment strategies.
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Affiliation(s)
- Arthi Venkatesan
- Department of Integrative Biology, School of BioSciences and Technology (SBST), VIT, Vellore, Tamil Nadu, India
| | - Febin Prabhu Dass J
- Department of Integrative Biology, School of BioSciences and Technology (SBST), VIT, Vellore, Tamil Nadu, India
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21
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Shunmugam L, Soliman MES. Targeting HCV polymerase: a structural and dynamic perspective into the mechanism of selective covalent inhibition. RSC Adv 2018; 8:42210-42222. [PMID: 35558797 PMCID: PMC9092151 DOI: 10.1039/c8ra07346e] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 11/30/2018] [Indexed: 12/16/2022] Open
Abstract
Background: Concerns have been raised over the emerging pandemic status of hepatitis C virus (HCV). Current available drugs lack specificity, stability and potency. The HCV NS5B RNA-dependent RNA polymerase (RdRp) is a vital component in viral replication and is often targeted in antiviral therapies. Recent experimental procedures have led to the discovery of a novel covalent RdRp inhibitor, compound 47, which selectively targets cysteine 366 of the HCV RdRp and exhibits promising pharmacokinetic outcomes. Selective covalent inhibition of HCV is, however, a highly neglected subject in the literature, that is reinforced by the lack of efficient structure-based drug design protocols. In this paper, an atomistic insight into a novel selective approach to inhibit HCV RdRp is provided. Methodology/Results: Covalent molecular dynamic analyses revealed the inhibitory mechanism of compound 47 on the RdRp. Inhibitor binding induced distinctive internal movements resulting in the disruption of normal physiological interdomain interactions. Conclusion: Compound 47 stimulates reorganization of key protein elements required for RNA transcription, thus hampering viral replication as well as disrupting the overall conformation of HCV. This study will open new lines of approach for the design of novel selective inhibitors against HCV as well as other viral families.
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Affiliation(s)
- Letitia Shunmugam
- Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal Westville Campus Durban 4001 South Africa
| | - Mahmoud E S Soliman
- Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal Westville Campus Durban 4001 South Africa
- School of Health Sciences, University of KwaZulu-Natal Westville Campus Durban 4001 South Africa +27 (0) 31 260 7872 +27 (0) 31 260 8048
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22
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Ashraf MU, Iman K, Khalid MF, Salman HM, Shafi T, Rafi M, Javaid N, Hussain R, Ahmad F, Shahzad-Ul-Hussan S, Mirza S, Shafiq M, Afzal S, Hamera S, Anwar S, Qazi R, Idrees M, Qureshi SA, Chaudhary SU. Evolution of efficacious pangenotypic hepatitis C virus therapies. Med Res Rev 2018; 39:1091-1136. [PMID: 30506705 DOI: 10.1002/med.21554] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 10/11/2018] [Accepted: 10/11/2018] [Indexed: 12/12/2022]
Abstract
Hepatitis C compromises the quality of life of more than 350 million individuals worldwide. Over the last decade, therapeutic regimens for treating hepatitis C virus (HCV) infections have undergone rapid advancements. Initially, structure-based drug design was used to develop molecules that inhibit viral enzymes. Subsequently, establishment of cell-based replicon systems enabled investigations into various stages of HCV life cycle including its entry, replication, translation, and assembly, as well as role of host proteins. Collectively, these approaches have facilitated identification of important molecules that are deemed essential for HCV life cycle. The expanded set of putative virus and host-encoded targets has brought us one step closer to developing robust strategies for efficacious, pangenotypic, and well-tolerated medicines against HCV. Herein, we provide an overview of the development of various classes of virus and host-directed therapies that are currently in use along with others that are undergoing clinical evaluation.
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Affiliation(s)
- Muhammad Usman Ashraf
- Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan.,Virology Laboratory, Center of Excellence in Molecular Biology, University of the Punjab, Lahore, Pakistan
| | - Kanzal Iman
- Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan
| | - Muhammad Farhan Khalid
- Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan.,Department of Biomedical Engineering, University of Engineering and Technology, Lahore, Pakistan
| | - Hafiz Muhammad Salman
- Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan.,Plant Biotechnology Laboratory, Institute of Agricultural Sciences, University of the Punjab, Lahore, Pakistan
| | - Talha Shafi
- Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan
| | - Momal Rafi
- Department of Statistics, University of Gujrat, Gujrat, Pakistan
| | - Nida Javaid
- Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan
| | - Rashid Hussain
- Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan
| | - Fayyaz Ahmad
- Department of Statistics, University of Gujrat, Gujrat, Pakistan
| | | | - Shaper Mirza
- Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan
| | - Muhammad Shafiq
- Plant Biotechnology Laboratory, Institute of Agricultural Sciences, University of the Punjab, Lahore, Pakistan
| | - Samia Afzal
- Virology Laboratory, Center of Excellence in Molecular Biology, University of the Punjab, Lahore, Pakistan
| | - Sadia Hamera
- Department of Plant Genetics, Institute of Life Sciences, University of Rostock, Germany
| | - Saima Anwar
- Department of Biomedical Engineering, University of Engineering and Technology, Lahore, Pakistan
| | - Romena Qazi
- Department of Pathology, Shaukat Khanum Memorial Cancer Hospital & Research Centre, Lahore, Pakistan
| | - Muhammad Idrees
- Virology Laboratory, Center of Excellence in Molecular Biology, University of the Punjab, Lahore, Pakistan.,Hazara University, Mansehra, Pakistan
| | - Sohail A Qureshi
- Institute of Integrative Biosciences, CECOS-University of Information Technology and Emerging Sciences, Peshawar, Pakistan
| | - Safee Ullah Chaudhary
- Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan
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23
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Zhao D, He HS, Wang WJ, Liu J, Du H, Wu M, Tan X. Distribution and Driving Factors of Forest Swamp Conversions in a Cold Temperate Region. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15102103. [PMID: 30257466 PMCID: PMC6210808 DOI: 10.3390/ijerph15102103] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 09/14/2018] [Accepted: 09/20/2018] [Indexed: 11/16/2022]
Abstract
Forest swamps are widely distributed in cold temperate regions, with important landscape and ecological functions. They are prone to conversion caused by complex factors. Forest swamp conversions involve forest swamping, meadow swamping, water body swamping, and conversion to farmland. An understanding of the landscape characteristics and primary environmental factors driving forest swamp conversions is imperative for exploring the mechanism of forest swamp conversions. We investigated the landscape characteristics of forest swamp conversions and quantified the relative importance of environmental factors driving these conversions for the period from 1990 to 2015 in the Great Xing’an Mountains of China. We found that forest swamping displayed high patch numbers (34,916) and density (8.51/100 ha), commonly occurring at the edge of large areas of forests. Meadow swamping was localized with low patch numbers (3613) and density (0.88/100 ha) due to lack of water recharge from ground water. Water body swamping had complex shapes (perimeter area ratio mean = 348.32) because of water table fluctuations and helophyte growth during this conversion process. Conversions to farmland presented fairly regular (perimeter area ratio mean = 289.91) and aggregated (aggregation index = 67.82) characteristics affected by agricultural irrigation and management. We found that climatic and geomorphic factors were relatively important compared to topographic factors for forest swamp conversions. Negative geomorphic conditions provided the waterlogging environment as a precondition of swamp formation. Sufficient precipitation was an important source of water recharge due to the existence of permafrost regions and long-term low temperature reduced the evaporation of swamps water and the decomposition rate of organisms. These wet and cold climatic conditions promoted forest swamp development in cold temperate regions. Humans exerted a relatively important role in forest swamping and conversions to farmland. Fire disturbance and logging accelerated the conversion from forest to swamp. This study provides scientific information necessary for the management and conservation of forest swamp resources in cold temperate regions.
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Affiliation(s)
- Dandan Zhao
- School of Geographical Sciences, Northeast Normal University, Changchun 130024, China.
| | - Hong S He
- School of Geographical Sciences, Northeast Normal University, Changchun 130024, China.
- School of Natural Resources, University of Missouri, Columbia, MO 65211, USA.
| | - Wen J Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
| | - Jiping Liu
- School of Tourism and Geography Science, Jilin Normal University, Siping 136000, China.
| | - Haibo Du
- School of Geographical Sciences, Northeast Normal University, Changchun 130024, China.
| | - Miaomiao Wu
- School of Geographical Sciences, Northeast Normal University, Changchun 130024, China.
| | - Xinyuan Tan
- School of Geographical Sciences, Northeast Normal University, Changchun 130024, China.
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24
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Rohini K, Agarwal P, Preethi B, Shanthi V, Ramanathan K. Exploring the Lead Compounds for Zika Virus NS2B-NS3 Protein: an e-Pharmacophore-Based Approach. Appl Biochem Biotechnol 2018; 187:194-210. [PMID: 29911269 DOI: 10.1007/s12010-018-2814-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Accepted: 06/05/2018] [Indexed: 12/19/2022]
Abstract
The rapid spread of the Zika virus and its association with the abnormal brain development constitute a global health emergency. With a continuing spread of the mosquito vector, the exposure is expected to accelerate in the coming years. Despite number of efforts, there is still no proper vaccine or medicine to combat this virus. Of note, the NS2B-NS3 protein is proven to be the potential target for the Zika virus therapeutics. Hence, e-pharmacophore-based drug design strategy was employed to identify potent inhibitors of NS2B-NS3 protein from ASINEX database consisting of 467,802 molecules. A 3D e-pharmacophore model was generated using PHASE module of Schrödinger Suite. The generated model consists of one hydrogen bond acceptor (A), two hydrogen bond donors (D), and two aromatic rings (R), ADDRR. The model was further evaluated for its ability to screen actives using enrichment analysis. Subsequently, high-throughput virtual screening protocol was employed, and the resultant hit molecules were also examined for its binding free energies and ADME properties using Prime MM-GBSA and Qikprop module of Schrodinger packages, respectively. Finally, the screened hit molecule was subjected to molecular dynamics simulation to examine its stability. Overall, the results from our analysis suggest that compound BAS 19192837 could be a potent inhibitor for the NS2B-NS3 protein of the Zika virus. It is also noteworthy to mention that our results are in good agreement with literature evidences. We hope that this result is of immense importance in designing potential drug molecules to combat the spread of Zika virus in the near future.
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Affiliation(s)
- K Rohini
- Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, 632014, India
| | - Pratika Agarwal
- Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, 632014, India
| | - B Preethi
- Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, 632014, India
| | - V Shanthi
- Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, 632014, India
| | - K Ramanathan
- Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, 632014, India.
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25
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Elaziz MA, Moemen YS, Hassanien AE, Xiong S. Quantitative Structure-Activity Relationship Model for HCVNS5B inhibitors based on an Antlion Optimizer-Adaptive Neuro-Fuzzy Inference System. Sci Rep 2018; 8:1506. [PMID: 29367667 PMCID: PMC5784174 DOI: 10.1038/s41598-017-19122-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Accepted: 12/15/2017] [Indexed: 11/23/2022] Open
Abstract
The global prevalence of hepatitis C Virus (HCV) is approximately 3% and one-fifth of all HCV carriers live in the Middle East, where Egypt has the highest global incidence of HCV infection. Quantitative structure-activity relationship (QSAR) models were used in many applications for predicting the potential effects of chemicals on human health and environment. The adaptive neuro-fuzzy inference system (ANFIS) is one of the most popular regression methods for building a nonlinear QSAR model. However, the quality of ANFIS is influenced by the size of the descriptors, so descriptor selection methods have been proposed, although these methods are affected by slow convergence and high time complexity. To avoid these limitations, the antlion optimizer was used to select relevant descriptors, before constructing a nonlinear QSAR model based on the PIC50 and these descriptors using ANFIS. In our experiments, 1029 compounds were used, which comprised 579 HCVNS5B inhibitors (PIC50 < ~14) and 450 non-HCVNS5B inhibitors (PIC50 > ~14). The experimental results showed that the proposed QSAR model obtained acceptable accuracy according to different measures, where [Formula: see text] was 0.952 and 0.923 for the training and testing sets, respectively, using cross-validation, while [Formula: see text] was 0.8822 using leave-one-out (LOO).
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Affiliation(s)
- Mohamed Abd Elaziz
- School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China.
- Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, Egypt.
| | - Yasmine S Moemen
- Clinical Pathology Department, National Liver Institute, Menoufia University, Menofia, Egypt
| | | | - Shengwu Xiong
- School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China.
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26
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Simon L, Abdul Salam AA, Madan Kumar S, Shilpa T, Srinivasan KK, Byrappa K. Synthesis, anticancer, structural, and computational docking studies of 3-benzylchroman-4-one derivatives. Bioorg Med Chem Lett 2017; 27:5284-5290. [PMID: 29074256 DOI: 10.1016/j.bmcl.2017.10.026] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 10/12/2017] [Accepted: 10/13/2017] [Indexed: 12/28/2022]
Abstract
A series of 3-Benzylchroman-4-ones were synthesized and screened for anticancer activity by MTT assay. The compounds were evaluated against two cancerous cell lines BT549 (human breast carcinoma), HeLa (human cervical carcinoma), and one noncancerous cell line vero (normal kidney epithelial cells). 3b was found to be the most active molecule against BT549 cells (IC50 = 20.1 µM) and 3h against HeLa cells (IC50 = 20.45 µM). 3b also exhibited moderate activity against HeLa cells (IC50 = 42.8 µM). The molecular structures of 3h and 3i were solved by single crystal X-ray crystallographic technique. Additionally, the molecular docking studies between the tumour suppressor protein p53 with the lead compound 3h, which exhibited better anticancer activity against HeLa cells was examined.
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Affiliation(s)
- Lalitha Simon
- Department of Chemistry, Manipal Institute of Technology, Manipal University, Manipal 576 104, India
| | - Abdul Ajees Abdul Salam
- Department of Atomic and Molecular Physics, Manipal Institute of Technology, Manipal University, Manipal 576 104, India.
| | - S Madan Kumar
- PURSE Lab, Mangalagangotri, Mangalore University, Mangalore 574 199, India
| | - T Shilpa
- Department of Atomic and Molecular Physics, Manipal Institute of Technology, Manipal University, Manipal 576 104, India
| | - K K Srinivasan
- Department of Chemistry, Shri Madhwa Vadiraja Institute of Technology and Management, Vishwothama Nagar, Bantakal, Udupi 576 115, India
| | - K Byrappa
- Department of Material Science, Mangalagangotri, Mangalore University, Mangalore 574 199, India
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27
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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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28
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El-Hasab MAEM, El-Bastawissy EE, El-Moselhy TF. Identification of potential inhibitors for HCV NS3 genotype 4a by combining protein–ligand interaction fingerprint, 3D pharmacophore, docking, and dynamic simulation. J Biomol Struct Dyn 2017; 36:1713-1727. [DOI: 10.1080/07391102.2017.1332689] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
| | | | - Tarek Faathy El-Moselhy
- Faculty of Pharmacy, Department of Pharmaceutical Chemistry, Tanta University , Tanta, Egypt
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29
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Ganesan A, Barakat K. Applications of computer-aided approaches in the development of hepatitis C antiviral agents. Expert Opin Drug Discov 2017; 12:407-425. [PMID: 28164720 DOI: 10.1080/17460441.2017.1291628] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
INTRODUCTION Hepatitis C virus (HCV) is a global health problem that causes several chronic life-threatening liver diseases. The numbers of people affected by HCV are rising annually. Since 2011, the FDA has approved several anti-HCV drugs; while many other promising HCV drugs are currently in late clinical trials. Areas covered: This review discusses the applications of different computational approaches in HCV drug design. Expert opinion: Molecular docking and virtual screening approaches have emerged as a low-cost tool to screen large databases and identify potential small-molecule hits against HCV targets. Ligand-based approaches are useful for filtering-out compounds with rich physicochemical properties to inhibit HCV targets. Molecular dynamics (MD) remains a useful tool in optimizing the ligand-protein complexes and understand the ligand binding modes and drug resistance mechanisms in HCV. Despite their varied roles, the application of in-silico approaches in HCV drug design is still in its infancy. A more mature application should aim at modelling the whole HCV replicon in its active form and help to identify new effective druggable sites within the replicon system. With more technological advancements, the roles of computer-aided methods are only going to increase several folds in the development of next-generation HCV drugs.
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Affiliation(s)
- Aravindhan Ganesan
- a Faculty of Pharmacy and Pharmaceutical Sciences , University of Alberta , Edmonton , Canada
| | - Khaled Barakat
- a Faculty of Pharmacy and Pharmaceutical Sciences , University of Alberta , Edmonton , Canada
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30
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Sesmero E, Brown JA, Thorpe IF. Molecular simulations to delineate functional conformational transitions in the HCV polymerase. J Comput Chem 2016; 38:1125-1137. [PMID: 27859387 DOI: 10.1002/jcc.24662] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2016] [Revised: 09/29/2016] [Accepted: 10/18/2016] [Indexed: 01/08/2023]
Abstract
Hepatitis C virus (HCV) is a global health concern for which there is no vaccine available. The HCV polymerase is responsible for the critical function of replicating the RNA genome of the virus. Transitions between at least two conformations (open and closed) are necessary to allow the enzyme to replicate RNA. In this study, molecular dynamic simulations were initiated from multiple crystal structures to understand the free energy landscape (FEL) explored by the enzyme as it interconverts between these conformations. Our studies reveal the location of distinct states within the FEL as well as the molecular interactions associated with these states. Specific hydrogen bonds appear to play a key role in modulating conformational transitions. This knowledge is essential to elucidate the role of these conformations in replication and may also be valuable in understanding the basis by which this enzyme is inhibited by small molecules. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Ester Sesmero
- Department of Chemistry and Biochemistry, University of Maryland Baltimore County, Baltimore, Maryland, 21250
| | - Jodian A Brown
- Department of Chemistry and Biochemistry, University of Maryland Baltimore County, Baltimore, Maryland, 21250
| | - Ian F Thorpe
- Department of Chemistry and Biochemistry, University of Maryland Baltimore County, Baltimore, Maryland, 21250
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31
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Saigo K, Ozaki S, Ueda K, Ryo R, Tatsumi E, Yamaguchi N. [An aged patient with acute myelogenous leukemia complicated with liver cirrhosis: successful treatment with low-dose cytosine arabinoside]. Gan To Kagaku Ryoho 1989; 83:881-891. [PMID: 2751321 DOI: 10.1016/j.biopha.2016.08.002] [Citation(s) in RCA: 28] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Revised: 07/30/2016] [Accepted: 08/01/2016] [Indexed: 12/29/2022]
Abstract
A 76-year-old woman, who had suffered from liver cirrhosis, was referred to our hospital because of pancytopenia. Her peripheral leukocyte count was 2,500/microliters with 43% myeloblasts, hemoglobin at 9.0 g/dl and platelet count of 0.9 x 10(4)/microliters. Aspirate from bone marrow showed hypercellular marrow with 52% myeloblasts. No chromosomal abnormality was detected. She was diagnosed as acute myelogenous leukemia (AML, M2). The diagnosis of liver cirrhosis was confirmed by laboratory data and findings of abdominal sonography. Moreover, she had valvular aortic stenosis. These complications made it difficult to treat her with combined chemotherapy containing anthracycline antibiotics, so she was given a small dose of cytosine arabinoside (Ara-C, 10 mg/body/12 hr) for 18 days. After severe myelosuppression, complete remission was achieved. The highest serum concentration of Ara-C was obtained at 15 min after subcutaneous injection of Ara-C; thereafter the Ara-C concentration decreased immediately within 60 min in a pattern similar to that observed in patients without liver cirrhosis. Thus, low-dose Ara-C regimen might be a useful treatment for aged patients with AML, even complicated with liver cirrhosis.
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Affiliation(s)
- K Saigo
- Section of Internal Medicine, Kobe Kyodo Hospital
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