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Characterization of the role of Kunitz-type protease inhibitor domain in dimerization of amyloid precursor protein : Characterization of the role of KPI domain in the dimerization of amyloid precursor protein

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Byun, Jin Young; Vellampatti, Srivithya; Chatterjee, Prathit; Hwang, Sun Ha; Kim, Byoung Choul; Lee, Ju Yong

Issue Date
John Wiley & Sons Inc.
Journal of Computational Chemistry, Vol.44 No.15, pp.1437-1445
A major difference between amyloid precursor protein (APP) isoforms (APP695 and APP751) is the existence of a Kunitz type protease inhibitor (KPI) domain which has a significant impact on the homo- and hetero-dimerization of APP isoforms. However, the exact molecular mechanisms of dimer formation remain elusive. To characterize the role of the KPI domain in APP dimerization, we performed a single molecule pull down (SiMPull) assay where homo-dimerization between tethered APP molecules and soluble APP molecules was highly preferred regardless of the type of APP isoforms, while hetero-dimerization between tethered APP751 molecules and soluble APP695 molecules was limited. We further investigated the domain level APP-APP interactions using coarse-grained models with the Martini force field. Though the model initial ternary complexes (KPI-E1, KPI-KPI, KPI-E2, E1-E1, E2-E2, and E1-E2) generated using HADDOCK (HD) and AlphaFold2 (AF2), the binding free energy profiles and the binding affinities of the domain combinations were investigated via the umbrella sampling with Martini force field. Additionally, membrane-bound microenvironments at the domain level were modeled. As a result, it was revealed that the KPI domain has a stronger attractive interaction with itself than the E1 and E2 domains, as reported elsewhere. Thus, the KPI domain of APP751 may form additional attractive interactions with E1, E2 and the KPI domain itself, whereas it is absent in APP695. In conclusion, we found that the APP751 homo-dimer formation is predominant than the homodimerization in APP695, which is facilitated by the presence of the KPI domain.
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  • Graduate School of Convergence Science & Technology
  • Dept. of Molecular and Biopharmaceutical Sciences
Research Area AI models for drug discovery, Free energy calculation, Molecular dynamics, 분자동역학, 신약개발을 위한 AI 모델, 자유에너지 계산


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