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Velásquez PA, Hernandez JC, Galeano E, Hincapié-García J, Rugeles MT, Zapata-Builes W. Effectiveness of Drug Repurposing and Natural Products Against SARS-CoV-2: A Comprehensive Review. Clin Pharmacol 2024; 16:1-25. [PMID: 38197085 PMCID: PMC10773251 DOI: 10.2147/cpaa.s429064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Accepted: 11/14/2023] [Indexed: 01/11/2024] Open
Abstract
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a betacoronavirus responsible for the COVID-19 pandemic, causing respiratory disorders, and even death in some individuals, if not appropriately treated in time. To face the pandemic, preventive measures have been taken against contagions and the application of vaccines to prevent severe disease and death cases. For the COVID-19 treatment, antiviral, antiparasitic, anticoagulant and other drugs have been reused due to limited specific medicaments for the disease. Drug repurposing is an emerging strategy with therapies that have already tested safe in humans. One promising alternative for systematic experimental screening of a vast pool of compounds is computational drug repurposing (in silico assay). Using these tools, new uses for approved drugs such as chloroquine, hydroxychloroquine, ivermectin, zidovudine, ribavirin, lamivudine, remdesivir, lopinavir and tenofovir/emtricitabine have been conducted, showing effectiveness in vitro and in silico against SARS-CoV-2 and some of these, also in clinical trials. Additionally, therapeutic options have been sought in natural products (terpenoids, alkaloids, saponins and phenolics) with promising in vitro and in silico results for use in COVID-19 disease. Among these, the most studied are resveratrol, quercetin, hesperidin, curcumin, myricetin and betulinic acid, which were proposed as SARS-CoV-2 inhibitors. Among the drugs reused to control the SARS-CoV2, better results have been observed for remdesivir in hospitalized patients and outpatients. Regarding natural products, resveratrol, curcumin, and quercetin have demonstrated in vitro antiviral activity against SARS-CoV-2 and in vivo, a nebulized formulation has demonstrated to alleviate the respiratory symptoms of COVID-19. This review shows the evidence of drug repurposing efficacy and the potential use of natural products as a treatment for COVID-19. For this, a search was carried out in PubMed, SciELO and ScienceDirect databases for articles about drugs approved or under study and natural compounds recognized for their antiviral activity against SARS-CoV-2.
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Affiliation(s)
- Paula Andrea Velásquez
- Grupo Infettare, Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia
- Grupo Inmunovirología, Facultad de Medicina, Universidad de Antioquia UdeA, Medellín, Colombia
| | - Juan C Hernandez
- Grupo Infettare, Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia
- Grupo Inmunovirología, Facultad de Medicina, Universidad de Antioquia UdeA, Medellín, Colombia
| | - Elkin Galeano
- Grupo Productos Naturales Marinos, Departamento de Farmacia, Facultad de Ciencias Farmacéuticas y Alimentarias, Universidad de Antioquia UdeA, Medellín, Colombia
| | - Jaime Hincapié-García
- Grupo de investigación, Promoción y prevención farmacéutica, Facultad de Ciencias Farmacéuticas y Alimentarias, Universidad de Antioquia UdeA, Medellín, Colombia
| | - María Teresa Rugeles
- Grupo Inmunovirología, Facultad de Medicina, Universidad de Antioquia UdeA, Medellín, Colombia
| | - Wildeman Zapata-Builes
- Grupo Infettare, Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia
- Grupo Inmunovirología, Facultad de Medicina, Universidad de Antioquia UdeA, Medellín, Colombia
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Ali KM, Rashid PMA, Ali AM, Tofiq AM, Salih GF, Dana OI, Rostam HM. Clinical outcomes and phylogenetic analysis in reflection with three predominant clades of SARS-CoV-2 variants. Eur J Clin Invest 2023; 53:e14004. [PMID: 37036255 DOI: 10.1111/eci.14004] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 03/29/2023] [Accepted: 04/07/2023] [Indexed: 04/11/2023]
Abstract
BACKGROUND The pandemic of coronavirus disease 2019 (COVID-19) has a broad spectrum of clinical manifestations. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) undergoes continuous evolution, resulting in the emergence of several variants. Each variant has a different severity and mortality rate. MATERIALS AND METHODS In this study, 1174 COVID-19 patients were studied for mortality and severity over three SARS-CoV-2 predominating variant periods in 2021 and 2022 in Sulaimani Province, Iraq. In each period, a representative, variant virus was subjected to phylogenetic and molecular and clinical analysis. RESULTS Phylogenetic analysis revealed three SARS-CoV-2 variants, belonging to: Delta B.1.617.2, Omicron BA.1.17.2, and Omicron BA.5.6. The Delta variants showed more severe symptoms and a lower PCR-Ct value than Omicron variants regardless of gender, and only 4.3% of the cases were asymptomatic. The mortality rate was lower with Omicron (.5% for BA.5.2 and 1.3% for BA.1.17.2) compared with Delta variants (2.5%). The higher mortality rate with Delta variants was in males (2.84%), while that with Omicron BA1.17.2 and BA.5.2 was in females, 1.05% and .0%, respectively. Age group (≥70) years had the highest mortality rate; however, it was (.0%) in the age group (30-49) years with Omicron variants, compared with (.96%) in Delta variants. CONCLUSIONS There has been a surge in COVID-19 infection in the city due to the predominant lineages of SARS-CoV-2, B.1.617, Omicron BA.1.17.2 and Omicron BA.5.6, respectively. A higher PCR-Ct value and severity of the Delta variant over Omicron BA.1.17.2 and/or BA.5.2 variants were significantly correlated with a higher death rate in the same order.
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Affiliation(s)
- Kameran M Ali
- Medical Laboratory Technology Department, Kalar Technical College, Sulaimani Polytechnic University, Kalar, Iraq
| | - Peshnyar M A Rashid
- Medical Laboratory Science Department, Komar University of Science and Technology, Sulaimania, Iraq
| | - Ayad M Ali
- Department of Chemistry, University of Garmian, Kalar, Iraq
| | - Ahmed M Tofiq
- Department of Biology, College of Education, University of Garmian, Head of International Academic Relations (IRO), Kalar, Iraq
| | - Gaza F Salih
- Biology Department, College of Science, University of Sulaimani, Sulaimania, Iraq
| | - Omer I Dana
- College of Veterinary Medicine, University of Sulaimani, Sulaimani, Iraq
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Tallapragada VS, Manga NA, Kumar GP. A novel COVID diagnosis and feature extraction based on discrete wavelet model and classification using X-ray and CT images. MULTIMEDIA TOOLS AND APPLICATIONS 2023; 82:1-42. [PMID: 36712955 PMCID: PMC9859748 DOI: 10.1007/s11042-023-14367-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/22/2022] [Accepted: 01/02/2023] [Indexed: 06/18/2023]
Abstract
Recently, the Covid-19 pandemic has affected several lives of people globally, and there is a need for a massive number of screening tests to diagnose the existence of coronavirus. For the medical specialist, detecting COVID-19 cases is a difficult task. There is a need for fast, cheap and accurate diagnostic tools. The chest X-ray and the computerized tomography (CT) play a significant role in the COVID-19 diagnosis. The advancement of deep learning (DL) approaches helps to introduce a COVID diagnosis system to achieve maximum detection rate with minimum time complexity. This research proposed a discrete wavelet optimized network model for COVID-19 diagnosis and feature extraction to overcome these problems. It consists of three stages pre-processing, feature extraction and classification. The raw images are filtered in the pre-processing phase to eliminate unnecessary noises and improve the image quality using the MMG hybrid filtering technique. The next phase is feature extraction, in this stage, the features are extracted, and the dimensionality of the features is diminished with the aid of a modified discrete wavelet based Mobile Net model. The third stage is the classification here, the convolutional Aquila COVID detection network model is developed to classify normal and COVID-19 positive cases from the collected images of the COVID-CT and chest X-ray dataset. Finally, the performance of the proposed model is compared with some of the existing models in terms of accuracy, specificity, sensitivity, precision, f-score, negative predictive value (NPV) and positive predictive value (PPV), respectively. The proposed model achieves the performance of 99%, 100%, 98.5%, and 99.5% for the CT dataset, and the accomplished accuracy, specificity, sensitivity, and precision values of the proposed model for the X-ray dataset are 98%, 99%, 98% and 97% respectively. In addition, the statistical and cross validation analysis is conducted to validate the effectiveness of the proposed model.
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Affiliation(s)
| | | | - G.V. Pradeep Kumar
- Department of ECE, Chaitanya Bharathi Institute of Technology, Hyderabad, India
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4
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Devi MB, Devi A, Gupta PK, Tripathi D. Response of vaccination on community transmission of COVID-19: a dynamical approach. THE EUROPEAN PHYSICAL JOURNAL. SPECIAL TOPICS 2022; 231:3749-3765. [PMID: 35991944 PMCID: PMC9380690 DOI: 10.1140/epjs/s11734-022-00652-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 07/26/2022] [Indexed: 06/15/2023]
Abstract
Due to the severity of COVID-19, vaccination campaigns have been or are underway in most parts of the world. In the current circumstances, it is obligatory to examine the response of vaccination on transmission of the SARS-CoV-2 virus when there are many vaccines available. Considering the importance of vaccination, a dynamic model has been proposed to provide an insight in the same direction. A mathematical model has been developed where six population compartments viz. susceptible, infected, vaccinated, home-isolated, hospitalized and recovered population are considered. Moreover, two novel parameters are included in the model to ascertain the effectiveness and speed of the vaccination campaign. Reproduction number and local stability of both the disease-free and endemic equilibrium points are studied to examine the nature of population dynamics. Graphical results for the community stage of COVID-19 infection are simulated and compared with real data to ascertain the validity of our model. The data is then studied to understand the impact of vaccination. These numerical results evidently demonstrate that home isolation and hospitalization should continue for the infected people until the transmission of the virus from person to person reduces sufficiently after completely vaccinating every nation. This model also recommends that all type of prevention measures should still be taken to avoid any type of critical situation due to infection and also reduce the death rate.
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Affiliation(s)
| | - Arpita Devi
- Department of Mathematics, National Institute of Technology Silchar, Cachar, 788010 Assam India
| | - Praveen Kumar Gupta
- Department of Mathematics, National Institute of Technology Silchar, Cachar, 788010 Assam India
| | - Dharmendra Tripathi
- Department of Mathematics, National Institute of Technology Uttarakhand, Srinagar, 246174 Uttarakhand India
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Hudák A, Morgan G, Bacovsky J, Patai R, Polgár TF, Letoha A, Pettko-Szandtner A, Vizler C, Szilák L, Letoha T. Biodistribution and Cellular Internalization of Inactivated SARS-CoV-2 in Wild-Type Mice. Int J Mol Sci 2022; 23:ijms23147609. [PMID: 35886958 PMCID: PMC9316427 DOI: 10.3390/ijms23147609] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/04/2022] [Accepted: 07/07/2022] [Indexed: 02/04/2023] Open
Abstract
Despite the growing list of identified SARS-CoV-2 receptors, the human angiotensin-converting enzyme 2 (ACE2) is still viewed as the main cell entry receptor mediating SARS-CoV-2 internalization. It has been reported that wild-type mice, like other rodent species of the Muridae family, cannot be infected with SARS-CoV-2 due to differences in their ACE2 receptors. On the other hand, the consensus heparin-binding motif of SARS-CoV-2’s spike protein, PRRAR, enables the attachment to rodent heparan sulfate proteoglycans (HSPGs), including syndecans, a transmembrane HSPG family with a well-established role in clathrin- and caveolin-independent endocytosis. As mammalian syndecans possess a relatively conserved structure, we analyzed the cellular uptake of inactivated SARS-CoV-2 particles in in vitro and in vivo mice models. Cellular studies revealed efficient uptake into murine cell lines with established syndecan-4 expression. After intravenous administration, inactivated SARS-CoV-2 was taken up by several organs in vivo and could also be detected in the brain. Internalized by various tissues, inactivated SARS-CoV-2 raised tissue TNF-α levels, especially in the heart, reflecting the onset of inflammation. Our studies on in vitro and in vivo mice models thus shed light on unknown details of SARS-CoV-2 internalization and help broaden the understanding of the molecular interactions of SARS-CoV-2.
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Affiliation(s)
- Anett Hudák
- Pharmacoidea Ltd., H-6726 Szeged, Hungary; (A.H.); (L.S.)
| | | | | | - Roland Patai
- Institute of Biophysics, Biological Research Centre, H-6726 Szeged, Hungary; (R.P.); (T.F.P.)
| | - Tamás F. Polgár
- Institute of Biophysics, Biological Research Centre, H-6726 Szeged, Hungary; (R.P.); (T.F.P.)
- Theoretical Medicine Doctoral School, Faculty of Medicine, University of Szeged, H-6720 Szeged, Hungary
| | - Annamária Letoha
- Department of Medicine, Albert Szent-Györgyi Clinical Center, Faculty of Medicine, University of Szeged, H-6720 Szeged, Hungary;
| | | | - Csaba Vizler
- Institute of Biochemistry, Biological Research Centre, H-6726 Szeged, Hungary;
| | - László Szilák
- Pharmacoidea Ltd., H-6726 Szeged, Hungary; (A.H.); (L.S.)
| | - Tamás Letoha
- Pharmacoidea Ltd., H-6726 Szeged, Hungary; (A.H.); (L.S.)
- Correspondence: ; Tel.: +36-30-2577393
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Choi MH, Lee J, Seo YJ. Dual-site ligation-assisted loop-mediated isothermal amplification (dLig-LAMP) for colorimetric and point-of-care determination of real SARS-CoV-2. Mikrochim Acta 2022; 189:176. [PMID: 35381892 PMCID: PMC8982663 DOI: 10.1007/s00604-022-05293-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 03/21/2022] [Indexed: 12/24/2022]
Abstract
A probing system has been developed based on dual-site ligation-assisted loop-mediated isothermal amplification (dLig-LAMP) for the selective colorimetric detection of SARS-CoV-2. This approach can induce false-positive and -negative detection in real clinical samples; dLig-LAMP operates with improved selectivity. Unlike RT-LAMP, the selectivity of dLig-LAMP is determined in both the ligation and primer binding steps, not in the reverse transcription step. With this selective system in hand, we developed a colorimetric signaling system for point-of-care detection. We also developed a colorimetric probe for sensing pyrophosphate, which arises as a side product during the LAMP DNA amplification. Thus, dLig-LAMP appears to be an alternative method for improving the selectivity problems associated with reverse transcription. In addition, combining dLig-LAMP with colorimetric pyrophosphate probing allows point-of-care detection of SARS-CoV-2 within 1 h with high selectivity.
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Affiliation(s)
- Moon Hyeok Choi
- Department of Chemistry, Jeonbuk National University, Jeonju, 54896, South Korea
| | - Jaehyeon Lee
- Department of Laboratory Medicine, Jeonbuk National University Medical School and Hospital, Jeonju, 54896, South Korea
| | - Young Jun Seo
- Department of Chemistry, Jeonbuk National University, Jeonju, 54896, South Korea.
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Cheng XW, Li J, Zhang L, Hu WJ, Zong L, Xu X, Qiao JP, Zheng MJ, Jiang XW, Liang ZK, Zhou YF, Zhang N, Zhu HQ, Xu YH. Identification of SARS-CoV-2 Variants and Their Clinical Significance in Hefei, China. Front Med (Lausanne) 2022; 8:784632. [PMID: 35083244 PMCID: PMC8784789 DOI: 10.3389/fmed.2021.784632] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 12/13/2021] [Indexed: 11/13/2022] Open
Abstract
The ongoing coronavirus disease 2019 (COVID-19) pandemic represents one of the most exigent threats of our lifetime to global public health and economy. As part of the pandemic, from January 10 to March 10, 2020, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) began to spread in Hefei (Anhui Province, China) with a total of 174 confirmed cases of COVID-19. During this period, we were able to gather critical information on the transmission and evolution of pathogens through genomic surveillance. Particularly, the objective of our study was to track putative variants of SARS-CoV-2 circulating in Hefei for the first time and contribute to the global effort toward elucidating the molecular epidemic profile of the virus. Patients who showed symptoms of COVID-19 were routinely tested for SARS-CoV-2 infections via RT-PCR at the First Affiliated Hospital of Anhui Medical University. Whole-genome sequencing was performed on 97 clinical samples collected from 29 confirmed COVID-19 patients. As a result, we identified a local novel single-nucleotide polymorphism site (10,380) harboring a G → T mutation (Gly → Val) in Hefei. Further phylogenetic network analysis with all the sequences of SARS-CoV-2 deposited in GenBank collected in East and Southeast Asia revealed a local subtype of S-type SARS-CoV-2 (a1) harboring a C → T synonymous mutation (Leu) at position 18,060 of ORF1b, likely representing a local SARS-CoV-2 mutation site that is obviously concentrated in Hefei and the Yangtze River Delta region. Moreover, clinical investigation on the inflammatory cytokine profile of the patients suggested that mutations at positions 18,060 (the shared variable site of subtype a1) and 28,253(harboring a C → T synonymous mutation, Phe) were associated with milder immune responses in the patients.
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Affiliation(s)
- Xiao-Wen Cheng
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Laboratory of Molecular Biology, Department of Biochemistry, Anhui Medical University, Hefei, China
| | - Jie Li
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Lu Zhang
- College of Life Sciences, Anhui Medical University, Hefei, China
| | - Wen-Jun Hu
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Lu Zong
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiang Xu
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jin-Ping Qiao
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Mei-Juan Zheng
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xi-Wen Jiang
- Da An Gene Co., Ltd., Sun Yat-sen University, Guangzhou, China.,The Medicine and Biological Engineering Technology Research Center of the Ministry of Health, Guangzhou, China
| | - Zhi-Kun Liang
- Clinical Laboratory Center, Guangzhou Darui Biotechnology, Co., Ltd., Guangzhou, China
| | - Yi-Fan Zhou
- Division of Life Sciences and Medicine, Department of Pathology, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, China
| | - Ning Zhang
- Wellcome Centre for Anti-Infectives Research, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Hua-Qing Zhu
- Laboratory of Molecular Biology, Department of Biochemistry, Anhui Medical University, Hefei, China
| | - Yuan-Hong Xu
- Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China
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Wu C, Duan Y, Gong S, Osterhoff G, Kallendrusch S, Schopow N. Identification of Tumor Antigens and Immune Subtypes for the Development of mRNA Vaccines and Individualized Immunotherapy in Soft Tissue Sarcoma. Cancers (Basel) 2022; 14:448. [PMID: 35053609 PMCID: PMC8774220 DOI: 10.3390/cancers14020448] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/10/2022] [Accepted: 01/14/2022] [Indexed: 02/01/2023] Open
Abstract
Soft tissue sarcomas (STS) are a rare disease with high recurrence rates and poor prognosis. Missing therapy options together with the high heterogeneity of this tumor type gives impetus to the development of individualized treatment approaches. This study identifies potential tumor antigens for the development of mRNA tumor vaccines for STS and explores potential immune subtypes, stratifying patients for immunotherapy. RNA-sequencing data and clinical information were extracted from 189 STS samples from The Cancer Genome Atlas (TCGA) and microarray data were extracted from 103 STS samples from the Gene Expression Omnibus (GEO). Potential tumor antigens were identified using cBioportal, the Oncomine database, and prognostic analyses. Consensus clustering was used to define immune subtypes and immune gene modules, and graph learning-based dimensionality reduction analysis was used to depict the immune landscape. Finally, four potential tumor antigens were identified, each related to prognosis and antigen-presenting cell infiltration in STS: HLTF, ITGA10, PLCG1, and TTC3. Six immune subtypes and six gene modules were defined and validated in an independent cohort. The different immune subtypes have different molecular, cellular, and clinical characteristics. The immune landscape of STS reveals the immunity-related distribution of patients and intra-cluster heterogeneity of immune subtypes. This study provides a theoretical framework for STS mRNA vaccine development and the selection of patients for vaccination, and provides a reference for promoting individualized immunotherapy.
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Affiliation(s)
- Changwu Wu
- Institute of Anatomy, University of Leipzig, 04103 Leipzig, Germany; (C.W.); (S.K.); (N.S.)
| | - Yingjuan Duan
- Faculty of Chemistry and Mineralogy, University of Leipzig, 04103 Leipzig, Germany;
| | - Siming Gong
- Institute of Anatomy, University of Leipzig, 04103 Leipzig, Germany; (C.W.); (S.K.); (N.S.)
| | - Georg Osterhoff
- Sarcoma Center, Department of Orthopedics, Trauma and Plastic Surgery, University Hospital Leipzig, 04103 Leipzig, Germany;
| | - Sonja Kallendrusch
- Institute of Anatomy, University of Leipzig, 04103 Leipzig, Germany; (C.W.); (S.K.); (N.S.)
- Faculty of Medicine, Health and Medical University Potsdam, 14471 Potsdam, Germany
| | - Nikolas Schopow
- Institute of Anatomy, University of Leipzig, 04103 Leipzig, Germany; (C.W.); (S.K.); (N.S.)
- Sarcoma Center, Department of Orthopedics, Trauma and Plastic Surgery, University Hospital Leipzig, 04103 Leipzig, Germany;
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Astakhov AV, Chernenko AY, Kutyrev VV, Ranny GS, Minyaev ME, Chernyshev VM, Ananikov VP. Selective Buchwald–Hartwig arylation of C-amino-1,2,4-triazoles and other coordinating aminoheterocycles enabled by bulky NHC ligands and TPEDO activator. Inorg Chem Front 2022. [DOI: 10.1039/d2qi01832b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
A facile method for selective N-(hetero)arylation of coordinating 3(5)-amino-1,2,4-triazoles under Pd/NHC catalysis using TPEDO as a new efficient Pd(ii) to Pd(0) reductant has been developed.
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Affiliation(s)
- Alexander V. Astakhov
- Platov South-Russian State Polytechnic University, (NPI), Prosvescheniya st., 132, Novocherkassk, 346428, Russia
| | - Andrey Yu. Chernenko
- Platov South-Russian State Polytechnic University, (NPI), Prosvescheniya st., 132, Novocherkassk, 346428, Russia
| | - Vadim V. Kutyrev
- Platov South-Russian State Polytechnic University, (NPI), Prosvescheniya st., 132, Novocherkassk, 346428, Russia
| | - Gleb S. Ranny
- Platov South-Russian State Polytechnic University, (NPI), Prosvescheniya st., 132, Novocherkassk, 346428, Russia
| | - Mikhail E. Minyaev
- Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospect 47, Moscow, 119991, Russia
| | - Victor M. Chernyshev
- Platov South-Russian State Polytechnic University, (NPI), Prosvescheniya st., 132, Novocherkassk, 346428, Russia
| | - Valentine P. Ananikov
- Platov South-Russian State Polytechnic University, (NPI), Prosvescheniya st., 132, Novocherkassk, 346428, Russia
- Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospect 47, Moscow, 119991, Russia
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10
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Databases, Knowledgebases, and Software Tools for Virus Informatics. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1368:1-19. [DOI: 10.1007/978-981-16-8969-7_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Alam R, Imon RR, Kabir Talukder ME, Akhter S, Hossain MA, Ahammad F, Rahman MM. GC-MS analysis of phytoconstituents from Ruellia prostrata and Senna tora and identification of potential anti-viral activity against SARS-CoV-2. RSC Adv 2021; 11:40120-40135. [PMID: 35494115 PMCID: PMC9044520 DOI: 10.1039/d1ra06842c] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 12/07/2021] [Indexed: 12/15/2022] Open
Abstract
SARS-CoV-2 is an etiologic agent responsible for the coronavirus disease 2019 (COVID-19) pandemic. The virus has rapidly extended globally and taken millions of lives due to the unavailability of therapeutics candidates against the virus. Till now, no specific drug candidates have been developed that can prevent or treat infections caused by the pathogen. The main protease (Mpro) of the SARS-CoV-2 plays a pivotal role in mediating viral replication and mechanistically inhibition of the protein can hinder the replication and infection process of the virus. Therefore, the study aimed to identify the natural bioactive compounds against the virus that can block the activity of the Mpro and subsequently block viral infections. Initially, a total of 96 phytochemicals from Ruellia prostrata Poir. and Senna tora (L.) Roxb. plants were identified through the gas chromatography-mass spectrometry (GC-MS) analytical method. Subsequently, the compounds were screened through molecular docking, absorption, distribution, metabolism, excretion (ADME), toxicity (T), and molecular dynamics (MD) simulation approach. The molecular docking method initially identified four molecules having a PubChem CID: 70825, CID: 25247358, CID: 54685836 and, CID: 1983 with a binding affinity ranging between −6.067 to −6.53 kcal mol−1 to the active site of the target protein. All the selected compounds exhibit good pharmacokinetics and toxicity properties. Finally, the four compounds were further evaluated based on the MD simulation methods that confirmed the binding stability of the compounds to the targeted protein. The computational approaches identified the best four compounds CID: 70825, CID: 25247358, CID: 54685836 and, CID: 1983 that can be developed as a treatment option of SARS-CoV-2 disease-related complications. Although, experimental validation is suggested for further evaluation of the work. Protease (Mpro) of SARS-CoV-2 has been identified as being able to hinder the replication process of the virus. Using GC-MS analytical methods, phytochemicals were identified from different medicinal plants that resulted in inhibitory activity of the molecules against Mpro.![]()
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Affiliation(s)
- Rahat Alam
- Molecular and Cellular Biology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology Jashore-7408 Bangladesh .,Laboratory of Computational Biology, Biological Solution Centre (BioSol Centre) Jashore-7408 Bangladesh
| | - Raihan Rahman Imon
- Molecular and Cellular Biology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology Jashore-7408 Bangladesh .,Laboratory of Computational Biology, Biological Solution Centre (BioSol Centre) Jashore-7408 Bangladesh
| | - Md Enamul Kabir Talukder
- Molecular and Cellular Biology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology Jashore-7408 Bangladesh .,Laboratory of Computational Biology, Biological Solution Centre (BioSol Centre) Jashore-7408 Bangladesh
| | - Shahina Akhter
- Laboratory of Computational Biology, Biological Solution Centre (BioSol Centre) Jashore-7408 Bangladesh .,Department of Biochemistry and Biotechnology, University of Science and Technology Chittagong (USTC) Foy's Lake, Khulshi Chittagong-4202 Bangladesh
| | - Md Alam Hossain
- Department of Computer Science and Engineering, Jashore University of Science and Technology Jashore-7408 Bangladesh
| | - Foysal Ahammad
- Laboratory of Computational Biology, Biological Solution Centre (BioSol Centre) Jashore-7408 Bangladesh .,Department of Biology, Faculty of Science, King Abdul-Aziz University Jeddah-21589 Saudi Arabia
| | - Md Mashiar Rahman
- Molecular and Cellular Biology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology Jashore-7408 Bangladesh
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Tiwari V, Kumar M, Tiwari A, Sahoo BM, Singh S, Kumar S, Saharan R. Current trends in diagnosis and treatment strategies of COVID-19 infection. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:64987-65013. [PMID: 34601675 PMCID: PMC8487330 DOI: 10.1007/s11356-021-16715-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 09/21/2021] [Indexed: 04/15/2023]
Abstract
Coronaviruses are terrifically precise and adapted towards specialized respiratory epithelial cells, observed in organ culture and human volunteers both. This virus is found to possess an unpredictable anti-viral T-cell response which in turn results in T-cell activation and finally apoptosis, leading to cytokine storm and collapse of the whole immune system. The present review provides comprehensive information regarding SARS-CoV-2 infection, mutant strains, and the impact of SARS-COV-2 on vital organs, the pathophysiology of the disease, diagnostic tests available, and possible treatments. It also includes all the vaccines developed so far throughout the world to control this pandemic. Until now, 18 vaccines have been approved by the WHO and further 22 vaccines are in the third trial. This study also provides up-to-date information regarding the drugs repurposed in clinical trials and the recent status of allopathic drugs along with its result. Although vaccines are available, specific treatment is not available for the disease. Furthermore, the effect of vaccines on new variants is a new area of research at this time. Therefore, a preventive attitude is the best approach to fight against this virus.
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Affiliation(s)
- Varsha Tiwari
- Department of Pharmacy, Devsthali Vidyapeeth College of Pharmacy, Lalpur (U.S. Nagar), Uttrakhand, Rudrapur, 236148, India
| | - Manish Kumar
- M.M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Ambala, Haryana, 133207, India
| | - Abhishek Tiwari
- Department of Pharmacy, Devsthali Vidyapeeth College of Pharmacy, Lalpur (U.S. Nagar), Uttrakhand, Rudrapur, 236148, India.
| | - Biswa Mohan Sahoo
- Roland Institute of Pharmaceutical Sciences, Odisha, ha-760010, Berhampur, India
| | - Sunil Singh
- Department of Pharmaceutical Chemistry, Shri Sai College of Pharmacy, Handia, Prayagraj, Uttar Pradesh, 221503, India
| | - Suresh Kumar
- Bharat Institute of Pharmacy, Pehladpur, Babain, Kurukshetra, Haryana, 136156, India
| | - Renu Saharan
- M.M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Ambala, Haryana, 133207, India
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