Malik Jonaid Ahmad, Wani Mushtaq Ahmad, Dar Mohammad Ovais, Garg Prabha, Agrewala Javed N
Immunology Laboratory, Department of Biomedical Engineering, Indian Institute of Technology Ropar, Rupnagar, 140001 India.
Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Sector 67, S.A.S. Nagar, Mohali, Punjab 160062 India.
In Silico Pharmacol. 2025 Apr 17;13(2):67. doi: 10.1007/s40203-025-00347-z. eCollection 2025.
Morphine and heroin dependence are growing concerns worldwide. Drug dependence is one of the greatest challenges, and developing alternative therapeutic strategies is essential. Due to few treatment options in pain management, morphine, a potent analgesic, is widely prescribed, but it carries a high risk of abuse. For the management of drug dependence, we have limited treatment options available, therefore, strategies should be developed to manage drug-seeking behaviors in clinical settings. We tried to find any FDA-approved drug targeting µ-opioid receptors through the approach. We screened around 186 FDA-approved drugs; we observed several drugs showing better docking scores with good affinity. We found vilazodone, indinavir, and lorazepam as potential drugs based on their affinity and mechanism of action. Later, these drugs were screened against human µ-opioid (PDB ID:8EF6) and other novel drug targets (5HT1 and TLR-4) that are associated with morphine dependence. Following docking, density functional theory (DFT), molecular dynamics (MD), molecular mechanics, and general born surface area (MM-GBSA) were performed to calculate the stability and ligand-protein binding free energies. Vilazodone, indinavir and lorazepam showed promising docking, MD, the energy gap between the HOMO and LUMO chemical reactivity, and MM-GBSA results compared to morphine and naloxone. We propose that these three drugs have huge potential to reverse the morphine and heroin dependence in diseased subjects near future.
The online version contains supplementary material available at 10.1007/s40203-025-00347-z.
吗啡和海洛因依赖在全球范围内日益引起关注。药物依赖是最大的挑战之一，制定替代治疗策略至关重要。由于疼痛管理的治疗选择有限，强效镇痛药吗啡被广泛处方，但它具有很高的滥用风险。对于药物依赖的管理，我们可用的治疗选择有限，因此，应制定策略来管理临床环境中的觅药行为。我们试图通过该方法找到任何美国食品药品监督管理局（FDA）批准的靶向μ-阿片受体的药物。我们筛选了约186种FDA批准的药物；我们观察到几种药物具有更好的对接分数和良好的亲和力。基于它们的亲和力和作用机制，我们发现维拉唑酮、茚地那韦和劳拉西泮为潜在药物。后来，针对与吗啡依赖相关的人μ-阿片（蛋白质数据银行ID：8EF6）和其他新的药物靶点（5HT1和TLR-4）对这些药物进行了筛选。对接后，进行密度泛函理论（DFT）、分子动力学（MD）、分子力学和广义玻恩表面积（MM-GBSA）计算以确定稳定性和配体-蛋白质结合自由能。与吗啡和纳洛酮相比，维拉唑酮、茚地那韦和劳拉西泮显示出有前景的对接、MD、最高已占分子轨道（HOMO）和最低未占分子轨道（LUMO）之间的能隙化学反应性以及MM-GBSA结果。我们提出，这三种药物在不久的将来有巨大潜力逆转患病受试者的吗啡和海洛因依赖。
在线版本包含可在10.1007/s40203-025-00347-z获取的补充材料。
