4.7 Article

Finding the Ion in the RNA-Stack: Can Computational Models Accurately Predict Key Functional Elements in Large Macromolecular Complexes?

期刊

JOURNAL OF CHEMICAL INFORMATION AND MODELING
卷 61, 期 6, 页码 2511-2515

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.1c00572

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资金

  1. Agence Nationale de la Recherche [ANR-15-CE11-0003-01]
  2. Agence Nationale de Recherche sur le Sida et les hepatites virales (ANRS) [ECTZ18552]
  3. ITMO Cancer [18CN04700]
  4. Fondation ARC pour la recherche sur le cancer [PJA-20191209284]
  5. Grenoble Instruct Center [ISBG: UMS 3518 CNRS-CEAUJF-EMBL]
  6. FRISBI [ANR-10-INSB-0502]
  7. GRAL within the Grenoble Partnership for Structural Biology (PSB) [ANR-10-LABX-49-01]
  8. Italian Association for Cancer Research (AIRC) [IG 23679]

向作者/读者索取更多资源

This viewpoint discusses the importance of computational analyses and simulations in gaining mechanistic insights into complex biological systems. Two newly resolved cryoEM structures have confirmed previous predictions of key catalytic ions, highlighting the synergy of computational and experimental methods in exploring large multicomponent biosystems.
This viewpoint discusses the predictive power and impact of computational analyses and simulations to gain prospective, experimentally supported mechanistic insights into complex biological systems. Remarkably, two newly resolved cryoEM structures have confirmed the previous, and independent, prediction of the precise localization and dynamics of key catalytic ions in megadalton-large spliceosomal complexes. This outstanding outcome endorses a prominent synergy of computational and experimental methods in the prospective exploration of such large multicomponent biosystems.

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