인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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
Streptococcus pneumoniae (S. pneumoniae) has developed resistance to β-lactam antibiotics, largely due to mutations in penicillin-binding protein 2x (PBP2x), particularly within conserved motifs such as STMK and KSG. PBP2x mutations are frequently reported in multidrug-resistant pneumococcal strains associated with pneumonia, meningitis, and septicaemia. especially in serotypes 19A, 19F, and 23F, showing reduced susceptibility to β-lactam antibiotics. These mutations in the PBP2x disrupt antibiotic binding and enzymatic functions, highlighting the need for alternative therapeutic strategies. This study focused on five clinically relevant PBP2x mutations (T338A/G/P and K547G/T) within its active site. A library of phytocompounds was screened using a machine learning model trained to identify antibacterial compounds. Top candidates were filtered based on ADMET properties, and their electronic characteristics were assessed using HOMO-LUMO analysis and electrostatic potential mapping, through density functional theory (DFT). Glucozaluzanin C, a phytochemical derived from Elephantopus scaber, emerged as a potential candidate. Molecular docking and dynamics simulations revealed strong binding affinity and structural integrity with all PBP2x mutants, over a 100-ns timescale. RMSD, RMSF, and hydrogen bonding analysis confirmed stable interactions, suggesting Glucozaluzanin C may effectively interact with PBP2x mutants. Overall, the study highlights an effective strategy for identifying plant-derived inhibitors against β-lactam-resistant S. pneumoniae.
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.
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