Fu Ruijiang, Su Wu-Pei, He Hongxing
Department of Physics, School of Physical Science and Technology, Ningbo University, Ningbo 315211, China.
Department of Physics and Texas Center for Superconductivity, University of Houston, Houston, TX 77204, USA.
Molecules. 2025 Jan 13;30(2):288. doi: 10.3390/molecules30020288.
Direct methods based on iterative projection algorithms can determine protein crystal structures directly from X-ray diffraction data without prior structural information. However, traditional direct methods often converge to local minima during electron density iteration, leading to reconstruction failure. Here, we present an enhanced direct method incorporating genetic algorithms for electron density modification in real space. The method features customized selection, crossover, and mutation strategies; premature convergence prevention; and efficient message passing interface (MPI) parallelization. We systematically tested the method on 15 protein structures from different space groups with diffraction resolutions of 1.35∼2.5 Å. The test cases included high-solvent-content structures, high-resolution structures with medium solvent content, and structures with low solvent content and non-crystallographic symmetry (NCS). Results showed that the enhanced method significantly improved success rates from below 30% to nearly 100%, with average phase errors reduced below 40°. The reconstructed electron density maps were of sufficient quality for automated model building. This method provides an effective alternative for solving structures that are difficult to predict accurately by AlphaFold3 or challenging to solve by molecular replacement and experimental phasing methods. The implementation is available on Github.
基于迭代投影算法的直接方法可以直接从X射线衍射数据确定蛋白质晶体结构，而无需先验结构信息。然而，传统的直接方法在电子密度迭代过程中常常收敛到局部最小值，导致重建失败。在此，我们提出一种增强的直接方法，该方法在实空间中结合遗传算法进行电子密度修正。该方法具有定制的选择、交叉和变异策略；防止早熟收敛；以及高效的消息传递接口（MPI）并行化。我们用衍射分辨率为1.35至2.5 Å的来自不同空间群的15个蛋白质结构系统地测试了该方法。测试案例包括高溶剂含量结构、中等溶剂含量的高分辨率结构以及低溶剂含量和非晶体学对称性（NCS）的结构。结果表明，增强后的方法显著提高了成功率，从低于30%提高到近100%，平均相位误差降低到40°以下。重建的电子密度图质量足以用于自动模型构建。该方法为解决难以通过AlphaFold3准确预测或通过分子置换和实验相位方法难以解决的结构提供了一种有效的替代方法。其实现可在Github上获取。
