{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T03:09:52Z","timestamp":1770088192748,"version":"3.49.0"},"update-to":[{"DOI":"10.12688\/f1000research.162353.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T00:00:00Z","timestamp":1769990400000}},{"DOI":"10.12688\/f1000research.162353.2","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T00:00:00Z","timestamp":1769990400000}}],"reference-count":55,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T00:00:00Z","timestamp":1769990400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["f1000research.com"],"crossmark-restriction":false},"short-container-title":["F1000Res"],"abstract":"<ns3:p>Background As lung cancer treatment has progressed, there has been an increase in awareness of the short- and long-term adverse effects of targeted cancer therapies of tyrosine kinase inhibitors, particularly cardiovascular toxicities. Methods The current study assessed the potential drug-drug interactions using interaction checkers (IBM Micromedex and Drugs.com). Molecular docking was employed to further investigate the involvement of human ether-\u00e0-go-go-related gene (hERG) and pregnane X receptor (PXR) proteins to elucidate their potential interactions and their underlying mechanisms. Results A total of 74 pharmacokinetic and 105 pharmacodynamic interactions were detected between tyrosine kinase inhibitors and cardiovascular drugs, along with a report on the severity and level of documentation. A considerable fraction of molecular modelling outcomes concurred with information from drug-drug interaction checkers. The binding energies of tyrosine kinase inhibitors with hERG and PXR were high, indicating significant interactions. The cardiovascular drug class encompasses calcium channel blockers, antiarrhythmic medicines, and statins, which were observed to exhibit synergistic interactions. The identification of these potential drug-drug interactions involving CYP3A4, P-gp, and hERG proteins can be utilized in therapy optimization in clinical settings. Conclusion This study will aid clinicians in designing safe dosage regimens for patients with lung cancer. In cases where patients have multiple comorbidities, it is essential to study the clinical aspects to design efficient chemotherapy and manage adverse effects and toxicities.<\/ns3:p>","DOI":"10.12688\/f1000research.162353.3","type":"journal-article","created":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T14:14:08Z","timestamp":1770041648000},"page":"309","update-policy":"https:\/\/doi.org\/10.12688\/f1000research.crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimizing Cardiovascular Treatment in Non-Small Cell Lung Cancer: A Comprehensive Computational Approach for Assessment of Drug-Drug Interactions Between Tyrosine Kinase Inhibitors and Cardiovascular Drugs"],"prefix":"10.12688","volume":"14","author":[{"given":"Prajakta","family":"Patil","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mrunal","family":"Desai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gayathri","family":"Baburaj","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Levin","family":"Thomas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Viswam","family":"Subeesh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7129-5748","authenticated-orcid":false,"given":"Sumit","family":"Birangal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahadev","family":"Rao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gurupur Gautham","family":"Shenoy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5956-7499","authenticated-orcid":false,"given":"Jagadish","family":"P. 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C.<\/b>; \n<i>Posted: 14 Oct 2025<\/i>; \n<b>Dear Reviewer,<\/b> Thank you for your insightful suggestions regarding our published manuscript entitled \n<i>\u201cOptimizing Cardiovascular Treatment in Non-Small Cell Lung Cancer: A Comprehensive Computational Approach for Assessment of Drug-Drug Interactions between Tyrosine Kinase Inhibitors and Cardiovascular Drugs\u201d<\/i> in F1000 Research. We have carefully revised the manuscript in accordance with your recommendations and corrections. We are confident that these improvements enhance the overall quality of the research. Respective changes have been modified and included in the revised version of the manuscript:  \n<b><u>Response to comments <\/u><\/b> \n<b>1. <\/b>What is the rationale for choosing clinical DDI checkers (Micromedex &amp; Drugs.com)\n<b> <\/b> \n<b>Author Response: <\/b>Dear Reviewer, thank you for your comment regarding the rationale behind selecting Micromedex and Drugs.com as DDI checkers. IBM Micromedex is a peer-reviewed, evidence-based DDI checker widely used in hospital settings for generating official drug interaction risk reports, which is also a subscription-based platform. In contrast, Drugs.com is a freely accessible online interface that reports interactions based on literature and possible common real-world screening practices among clinicians. By integrating both platforms, we aimed to confirm clinically relevant drug\u2013drug interactions through evidence-based sources as well as those frequently encountered in routine practices. This approach also enabled us to contextualize our molecular docking findings against known clinical interactions and explore mechanistic insights for unreported DDIs. The details of the same are outlined in the methodology section of the manuscript. (Page no. : 06-08)  \n<b>2. <\/b>What is the rationale for choosing only PXR and hERG proteins?\n<b> <\/b> \n<b>Author Response: <\/b>Dear Reviewer, the selection of the Pregnane X Receptor (PXR) and the human Ether-&agrave;-go-go-Related Gene (hERG) channel as molecular docking targets was driven by their central roles in the two most clinically significant classes of DDIs in cardio-oncology, i.e., pharmacokinetic (PK) and pharmacodynamic (PD) interaction risks, respectively. While PXR governs key metabolic pathways influencing PK interactions, hERG is critical for assessing PD-related cardiotoxicity. This focused approach ensured that our computational predictions remain directly aligned with clinically actionable risk assessment in NSCLC patients with cardiovascular comorbidities. The details of the same are outlined in the methodology section of the manuscript. (Page no. : 06-08)  \n<b>3. <\/b>The method outlines MMGBSA binding energy calculations but does not define thresholds or benchmarks for classifying strong versus weak interactions, making interpretation potentially ambiguous.\n<b> <\/b> \n<b>Author Response: <\/b>Dear Reviewer, in the current study, the MMGBSA binding energy, reported as Net Binding Energy, serves as an indicator of the thermodynamic favorability of drug-target interactions. Where a more negative (i.e., lower) MMGBSA value reflects a stronger and more favorable interaction, which in turn suggests a higher potential for DDI risk. This principle forms the basis for interpreting all subsequent binding data presented in the manuscript.  \n<b>4. <\/b>The conclusion should be made more concise by directly linking the key findings of predicted DDIs with their clinical implications, while briefly acknowledging the need for clinical validation and multidisciplinary management. \n<b>Author Response: <\/b>Dear reviewer, thank you for the insightful suggestion. We have revised the conclusion section, acknowledging the need for clinical validation with a multidisciplinary patient care approach. (Page no: 17)","URL":"https:\/\/f1000research.com\/articles\/14-309\/v3#referee-comment-14785","order":2,"name":"referee-comment-14785","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.189728.r431630, Janmejay Pant, Chandigarh University, Sahibzada Ajit Singh Nagar, Punjab, 27 Dec 2025, version 2, indexed","URL":"https:\/\/f1000research.com\/articles\/14-309\/v2#referee-response-431630","order":3,"name":"referee-response-431630","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"The author(s) declared that no grants were involved in supporting this work","order":4,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}