内部氨基酸的距离矩阵

病树前头2024-08-25 22:25

我有1000个pdb, 每个pdb氨基酸数目为14，我需要写一个python程序实现计算1000个pdb各自内部氨基酸的距离矩阵。

使用Biopython库来解析PDB文件并计算氨基酸之间的距离矩阵。

python 复制代码

from Bio import PDB
import numpy as np

def calculate_distance(atom1, atom2):
    """Calculate the Euclidean distance between two atoms."""
    return np.linalg.norm(atom1.coord - atom2.coord)

def calculate_distance_matrix(structure):
    """Calculate the distance matrix for a given PDB structure."""
    atoms = list(structure.get_atoms())
    num_atoms = len(atoms)
    distance_matrix = np.zeros((num_atoms, num_atoms))

    for i in range(num_atoms):
        for j in range(i, num_atoms):
            distance = calculate_distance(atoms[i], atoms[j])
            distance_matrix[i, j] = distance
            distance_matrix[j, i] = distance

    return distance_matrix

def process_pdb_file(pdb_file_path):
    """Process a single PDB file."""
    parser = PDB.PDBParser(QUIET=True)
    structure = parser.get_structure("protein", pdb_file_path)
    distance_matrix = calculate_distance_matrix(structure)
    return distance_matrix

def main():
    pdb_file_paths = ["pdb1.pdb", "pdb2.pdb", "pdb3.pdb", ...]  # Replace with your PDB file paths
    distance_matrices = []

    for pdb_file_path in pdb_file_paths:
        distance_matrix = process_pdb_file(pdb_file_path)
        distance_matrices.append(distance_matrix)

    # distance_matrices now contains the distance matrices for each PDB file
    # You can further analyze or save the results as needed.

if __name__ == "__main__":
    main()

将pdb1.pdb, pdb2.pdb, pdb3.pdb, ... 替换为你实际的PDB文件路径。这个程序将计算每个PDB文件中氨基酸之间的距离矩阵，并将它们存储在distance_matrices 列表中。你可以根据实际需要进一步处理或保存这些距离矩阵。