인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Background Polycystic ovary syndrome (PCOS) is a prevalent endocrinopathy characterized by excess androgen production and associated metabolic disturbances. Although several synthetic drugs, such as hypoglycemic and ovulation-inducing agents, are used in PCOS management, their clinical outcomes remain limited due to adverse side effects. Therefore, natural compounds offer promising alternatives or adjunct drugs with improved safety and efficacy. Objective and methods This study evaluated phytochemicals from Anethum graveolens (dill) for potential therapeutic activity against PCOS using an integrative computational strategy. PCOS-related targets were identified through DiseaseNet and GeneCards, followed by protein–protein interaction (PPI) analysis via STRING and hub gene selection with CytoHubba. Lead compounds were assessed through molecular docking, density functional theory (DFT) calculations, and to confirm the stability of the compound–target interactions, we performed molecular dynamics (MD) simulations (100 ns). Results The selected phytochemicals demonstrated favorable drug-likeness properties. DFT analysis revealed strong reactivity of carvacrol, eugenol, geraniol, and thymol, indicated by low energy gaps. Docking studies showed that these compounds exhibited stronger binding affinities with key PCOS targets compared to the control drug metformin. MD simulations further confirmed the stable interaction of these compounds with PCOS-associated proteins, including MMP9, AR, ALB, and PPAR-α. Conclusion Carvacrol, eugenol, geraniol, and thymol exhibited strong binding affinities, favorable drug-likeness profiles, and stable interactions with PCOS-associated receptors, highlighting their potential as multi-target therapeutic candidates for PCOS management.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.