Kırboğa Kevser Kübra, Karim Aman, Küçüksille Ecir Uğur, Rudrapal Mithun, Khan Johra, Achar Raghu Ram, Silina Ekaterina, Manturova Natalia, Stupin Victor
Faculty of Engineering, Department of Bioengineering, Bilecik Şeyh Edebali University, Bilecik, Türkiye.
Faculty of Multidisciplinary Studies, Department of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan.
Front Chem. 2025 Jan 6;12:1515424. doi: 10.3389/fchem.2024.1515424. eCollection 2024.
Cannabinoid and stilbenoid compounds derived from were screened against eight specific fungal protein targets to identify potential antifungal agents. The proteins investigated included Glycosylphosphatidylinositol (GPI), Enolase, Mannitol-2-dehydrogenase, GMP synthase, Dihydroorotate dehydrogenase (DHODH), Heat shock protein 90 homolog (Hsp90), Chitin Synthase 2 (CaChs2), and Mannitol-1-phosphate 5-dehydrogenase (M1P5DH), all of which play crucial roles in fungal survival and pathogenicity. This research evaluates the binding affinities and interaction profiles of selected cannabinoids and stilbenoids with these eight proteins using molecular docking and molecular dynamics simulations. The ligands with the highest binding affinities were identified, and their pharmacokinetic profiles were analyzed using ADMET analysis. The results indicate that GMP synthase exhibited the highest binding affinity with Cannabistilbene I (-9.1 kcal/mol), suggesting hydrophobic solid interactions and multiple hydrogen bonds. Similarly, Chitin Synthase 2 demonstrated significant binding with Cannabistilbene I (-9.1 kcal/mol). In contrast, ligands such as Cannabinolic acid and 8-hydroxycannabinolic acid exhibited moderate binding affinities, underscoring the variability in interaction strengths among different proteins. Despite promising results, experimental validation is necessary to confirm therapeutic potential. This research lays a crucial foundation for future studies, emphasizing the importance of evaluating binding affinities, pharmacokinetic properties, and multi-target interactions to identify promising antifungal agents.
对源自[具体来源未提及]的大麻素和芪类化合物针对八个特定的真菌蛋白靶点进行了筛选，以鉴定潜在的抗真菌剂。所研究的蛋白质包括糖基磷脂酰肌醇（GPI）、烯醇化酶、甘露醇-2-脱氢酶、鸟苷酸合酶、二氢乳清酸脱氢酶（DHODH）、热休克蛋白90同源物（Hsp90）、几丁质合酶2（CaChs2）和甘露醇-1-磷酸5-脱氢酶（M1P5DH），所有这些蛋白在真菌的存活和致病性中都起着关键作用。本研究使用分子对接和分子动力学模拟评估了所选大麻素和芪类化合物与这八种蛋白质的结合亲和力和相互作用谱。确定了具有最高结合亲和力的配体，并使用ADMET分析对其药代动力学特征进行了分析。结果表明，鸟苷酸合酶与大麻二苯乙烯I表现出最高的结合亲和力（-9.1千卡/摩尔），表明存在疏水固体相互作用和多个氢键。同样，几丁质合酶2与大麻二苯乙烯I也表现出显著的结合（-9.1千卡/摩尔）。相比之下，大麻酚酸和8-羟基大麻酚酸等配体表现出中等的结合亲和力，突出了不同蛋白质之间相互作用强度的变异性。尽管结果很有前景，但仍需要进行实验验证以确认其治疗潜力。本研究为未来的研究奠定了关键基础，强调了评估结合亲和力、药代动力学性质和多靶点相互作用以鉴定有前景的抗真菌剂的重要性。
