FLEXR: automated multi-conformer model building using electron-density map sampling.
FLEXR: automated multi-conformer model building using electron-density map sampling.
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DOI：
10.1107/s2059798323002498
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发表时间：
2023-05-01
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由于手动检测、构建和检查多个构象的困难，在当前的PDB模型中替代构象的代表性不足。为了克服这一缺点，FLEXR开发了一种自动化的多构象建模程序，该程序使用基于林格的电子密度采样来明确地构建多构象模型以进行改进。在高分辨率电子密度图中，可能为生物学提供信息的蛋白质构象动力学常常处于休眠状态。虽然高分辨率模型中估计约18%的侧链包含替代构象，但由于人工检测、构建和检查替代构象的困难，这些在当前的PDB模型中代表性不足。为了克服这一挑战，我们开发了一个自动化的多形像建模程序FLEXR。使用基于林格的电子密度采样，FLEXR建立了明确的多构象模型进行细化。因此，它弥补了在电子密度图中检测隐藏的交替状态并将其包括在结构模型中以进行细化，检查和沉积的差距。使用一系列高质量的晶体结构（0.8-1.85 Å分辨率），我们表明FLEXR生成的多构象模型揭示了手动或使用当前工具构建模型所缺少的新见解。具体来说，FLEXR模型揭示了配体结合位点的隐藏侧链和主链构象，这可能重新定义蛋白质-配体结合机制。最终，该工具使晶体学家有机会在其高分辨率晶体学模型中包含显式的多构象状态。一个关键的优势是，这样的模型可以更好地反映电子密度图中有趣的高能量特征，这些特征很少被整个社区参考，然后可以有效地用于下游的配体发现。FLEXR是开源的，可以在GitHub上找到https://github.com/TheFischerLab/FLEXR。
Alternative conformations are underrepresented in current PDB models due to difficulties in manually detecting, building and inspecting multiple conformers. To overcome this shortcoming, an automated multi-conformer modeling program, FLEXR, has been developed that uses Ringer-based electron-density sampling to explicitly build multi-conformer models for refinement. Protein conformational dynamics that may inform biology often lie dormant in high-resolution electron-density maps. While an estimated ∼18% of side chains in high-resolution models contain alternative conformations, these are underrepresented in current PDB models due to difficulties in manually detecting, building and inspecting alternative conformers. To overcome this challenge, we developed an automated multi-conformer modeling program, FLEXR. Using Ringer-based electron-density sampling, FLEXR builds explicit multi-conformer models for refinement. Thereby, it bridges the gap of detecting hidden alternate states in electron-density maps and including them in structural models for refinement, inspection and deposition. Using a series of high-quality crystal structures (0.8–1.85 Å resolution), we show that the multi-conformer models produced by FLEXR uncover new insights that are missing in models built either manually or using current tools. Specifically, FLEXR models revealed hidden side chains and backbone conformations in ligand-binding sites that may redefine protein–ligand binding mechanisms. Ultimately, the tool facilitates crystallographers with opportunities to include explicit multi-conformer states in their high-resolution crystallographic models. One key advantage is that such models may better reflect interesting higher energy features in electron-density maps that are rarely consulted by the community at large, which can then be productively used for ligand discovery downstream. FLEXR is open source and publicly available on GitHub at https://github.com/TheFischerLab/FLEXR.