Treponema pallidum表面タンパク質に対する人工知能生成DNAアプタマーの評価

DNA aptamer sequences were selected in silico with assistance from artificial intelligence (AI) using the new Xelari.com platform against three known immunogenic surface proteins of Treponema pallidum designated Tpp17, Tpp47 and Tp0751. The in silico aptamers were synthesized with 5' Alexa Fluor 647 labels and shown to bind live Treponema pallidum by fluorescence microscopy and spectrofluorometry. While AI-predicted K_d values differed somewhat from measured K_d values, it is clear that the aptamers bound the T. pallidum surface which is consistent with the molecular docking models for each aptamer with each cognate target protein all of which are thought to be largely accessible for binding (i.e., not predominately embedded in the outer membrane or cell wall). All three aptamers also demonstrated good specificity in cross-reactivity binding studies.