Prediction of potential drug interactions between repurposed COVID-19 and antitubercular drugs: an integrational approach of drug information software and computational techniques data.

IF 3.4 3区 医学 Q2 PHARMACOLOGY & PHARMACY Therapeutic Advances in Drug Safety Pub Date : 2021-08-26 eCollection Date: 2021-01-01 DOI:10.1177/20420986211041277
Levin Thomas, Sumit Raosaheb Birangal, Rajdeep Ray, Sonal Sekhar Miraj, Murali Munisamy, Muralidhar Varma, Chidananda Sanju S V, Mithu Banerjee, Gautham G Shenoy, Mahadev Rao
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With a larger population of tuberculosis patients anticipated to be co-infected with COVID-19 infection, an ongoing pandemic, identifying, preventing and managing drug-drug interactions is inevitable for maximizing patient benefits for the current repurposed COVID-19 and antitubercular drugs.</p><p><strong>Methods: </strong>We assessed the potential drug-drug interactions between repurposed COVID-19 drugs and antitubercular drugs using the drug interaction checker of IBM Micromedex®. Extensive computational studies were performed at a molecular level to validate and understand the drug-drug interactions found from the Micromedex drug interaction checker database at a molecular level. 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The results suggest antitubercular drugs, particularly rifampin and second-line agents, warrant high alert and monitoring while prescribing with the repurposed COVID-19 drugs.</p><p><strong>Conclusion: </strong>Predicting these potential drug-drug interactions, particularly related to CYP3A4, P-gp and the human Ether-à-go-go-Related Gene proteins, could be used in clinical settings for screening and management of drug-drug interactions for delivering safer chemotherapeutic tuberculosis and COVID-19 care. The current study provides an initial propulsion for further well-designed pharmacokinetic-pharmacodynamic-based drug-drug interaction studies.</p><p><strong>Plain language summary: </strong><b>Introduction::</b> Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. 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Molecular docking is a method that predicts the preferred orientation of one medicine molecule to a second molecule, when bound to each other to form a stable complex. Knowledge of the preferred orientation may be used to determine the strength of association or binding affinity between two medicines using scoring functions to determine the extent of the interactions between medicines. The combined knowledge from Micromedex and molecular modelling data was used to properly predict the potential medicine interactions between currently used COVID-19 and antitubercular medicines.<b>Results::</b> We found a total of 91 medication interactions from Micromedex. Majority of our molecular modelling findings matched with the interaction information obtained from the drug information software. QT prolongation, an abnormal heartbeat, was identified as one of the most common interactions. 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引用次数: 3

Abstract

Introduction: Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. With a larger population of tuberculosis patients anticipated to be co-infected with COVID-19 infection, an ongoing pandemic, identifying, preventing and managing drug-drug interactions is inevitable for maximizing patient benefits for the current repurposed COVID-19 and antitubercular drugs.

Methods: We assessed the potential drug-drug interactions between repurposed COVID-19 drugs and antitubercular drugs using the drug interaction checker of IBM Micromedex®. Extensive computational studies were performed at a molecular level to validate and understand the drug-drug interactions found from the Micromedex drug interaction checker database at a molecular level. The integrated knowledge derived from Micromedex and computational data was collated and curated for predicting potential drug-drug interactions between repurposed COVID-19 and antitubercular drugs.

Results: A total of 91 potential drug-drug interactions along with their severity and level of documentation were identified from Micromedex between repurposed COVID-19 drugs and antitubercular drugs. We identified 47 pharmacodynamic, 42 pharmacokinetic and 2 unknown DDIs. The majority of our molecular modelling results were in line with drug-drug interaction data obtained from the drug information software. QT prolongation was identified as the most common type of pharmacodynamic drug-drug interaction, whereas drug-drug interactions associated with cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp) inhibition and induction were identified as the frequent pharmacokinetic drug-drug interactions. The results suggest antitubercular drugs, particularly rifampin and second-line agents, warrant high alert and monitoring while prescribing with the repurposed COVID-19 drugs.

Conclusion: Predicting these potential drug-drug interactions, particularly related to CYP3A4, P-gp and the human Ether-à-go-go-Related Gene proteins, could be used in clinical settings for screening and management of drug-drug interactions for delivering safer chemotherapeutic tuberculosis and COVID-19 care. The current study provides an initial propulsion for further well-designed pharmacokinetic-pharmacodynamic-based drug-drug interaction studies.

Plain language summary: Introduction:: Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. With a larger population of tuberculosis patients predicted to be infected with COVID-19 during this period, there is a higher risk for the occurrence of medication interactions between the medicines used for COVID-19 and tuberculosis. Hence, identifying and managing these interactions is vital to ensure the safety of patients undergoing COVID-19 and tuberculosis treatment simultaneously.Methods:: We studied the major medication interactions that could likely happen between the various medicines that are currently given for COVID-19 and tuberculosis treatment using the medication interaction checker of a drug information software (Micromedex®). In addition, thorough molecular modelling was done to confirm and understand the interactions found from the medication interaction checker database using specific docking software. Molecular docking is a method that predicts the preferred orientation of one medicine molecule to a second molecule, when bound to each other to form a stable complex. Knowledge of the preferred orientation may be used to determine the strength of association or binding affinity between two medicines using scoring functions to determine the extent of the interactions between medicines. The combined knowledge from Micromedex and molecular modelling data was used to properly predict the potential medicine interactions between currently used COVID-19 and antitubercular medicines.Results:: We found a total of 91 medication interactions from Micromedex. Majority of our molecular modelling findings matched with the interaction information obtained from the drug information software. QT prolongation, an abnormal heartbeat, was identified as one of the most common interactions. Our findings suggest that antitubercular medicines, mainly rifampin and second-line agents, suggest high alert and scrutiny while prescribing with the repurposed COVID-19 medicines.Conclusion:: Our current study highlights the need for further well-designed studies confirming the current information for recommending safe prescribing in patients with both infections.

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预测重组COVID-19与抗结核药物之间潜在的药物相互作用:药物信息软件和计算技术数据的集成方法
结核病是一种全球性的主要呼吸道疾病,亚洲和非洲国家的患病率高于世界其他地区。随着更多的结核病患者预计将同时感染COVID-19感染,一场持续的大流行,识别、预防和管理药物-药物相互作用是不可避免的,以最大限度地提高当前重新使用的COVID-19和抗结核药物的患者效益。方法:采用IBM Micromedex®药物相互作用检测仪评估新冠病毒药物与抗结核药物之间潜在的药物相互作用。在分子水平上进行了广泛的计算研究,以验证和理解从Micromedex药物相互作用检查数据库中发现的药物-药物相互作用在分子水平上。对来自Micromedex的综合知识和计算数据进行整理和整理,以预测重新利用的COVID-19与抗结核药物之间潜在的药物-药物相互作用。结果:从Micromedex中共鉴定出91种潜在的药物-药物相互作用,以及它们的严重程度和记录水平。我们确定了47种药物动力学,42种药代动力学和2种未知的ddi。我们的大多数分子模型结果与药物信息软件获得的药物-药物相互作用数据一致。QT间期延长被认为是最常见的药物-药物相互作用类型,而与细胞色素P450 3A4 (CYP3A4)和p -糖蛋白(P-gp)抑制和诱导相关的药物-药物相互作用被认为是常见的药物-药物相互作用。结果表明,抗结核药物,特别是利福平和二线药物,在处方重新使用的COVID-19药物时需要高度警惕和监测。结论:预测这些潜在的药物-药物相互作用,特别是与CYP3A4、P-gp和人Ether-à-go-go-Related基因蛋白相关的药物-药物相互作用,可用于临床环境中筛选和管理药物-药物相互作用,以提供更安全的化疗结核病和COVID-19护理。目前的研究为进一步设计良好的基于药代动力学-药效学的药物-药物相互作用研究提供了初步的推动力。前言:结核病是全球一种主要的呼吸道疾病,亚洲和非洲国家的患病率高于世界其他地区。在此期间,预计将有更多的结核病患者感染COVID-19,因此用于COVID-19和结核病的药物之间发生药物相互作用的风险更高。因此,识别和管理这些相互作用对于确保同时接受COVID-19和结核病治疗的患者的安全至关重要。方法:利用药物信息软件(Micromedex®)的药物相互作用检查器,研究目前用于治疗COVID-19的各种药物与结核病治疗之间可能发生的主要药物相互作用。此外,利用特定的对接软件,进行了彻底的分子建模,以确认和理解从药物相互作用检查器数据库中发现的相互作用。分子对接是一种预测一个药物分子与另一个药物分子结合形成稳定复合物时的首选取向的方法。优选取向的知识可用于确定两种药物之间的关联强度或结合亲和力,使用评分函数来确定药物之间相互作用的程度。结合Micromedex的知识和分子建模数据,正确预测当前使用的COVID-19与抗结核药物之间潜在的药物相互作用。结果:从Micromedex中共发现91种药物相互作用。我们的大多数分子模型发现与从药物信息软件获得的相互作用信息相匹配。QT延长,一种异常心跳,被认为是最常见的相互作用之一。我们的研究结果表明,抗结核药物,主要是利福平和二线药物,在处方重新使用的COVID-19药物时应高度警惕和仔细检查。结论:我们目前的研究强调需要进一步精心设计的研究来证实目前的信息,为两种感染的患者推荐安全的处方。
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来源期刊
Therapeutic Advances in Drug Safety
Therapeutic Advances in Drug Safety Medicine-Pharmacology (medical)
CiteScore
6.70
自引率
4.50%
发文量
31
审稿时长
9 weeks
期刊介绍: Therapeutic Advances in Drug Safety delivers the highest quality peer-reviewed articles, reviews, and scholarly comment on pioneering efforts and innovative studies pertaining to the safe use of drugs in patients. The journal has a strong clinical and pharmacological focus and is aimed at clinicians and researchers in drug safety, providing a forum in print and online for publishing the highest quality articles in this area. The editors welcome articles of current interest on research across all areas of drug safety, including therapeutic drug monitoring, pharmacoepidemiology, adverse drug reactions, drug interactions, pharmacokinetics, pharmacovigilance, medication/prescribing errors, risk management, ethics and regulation.
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