A Discrete Geometry Method for Atom Depth Computation in Complex Molecular Systems

被引:0
|
作者
Marziali, Sara [1 ]
Nunziati, Giacomo [1 ,2 ]
Prete, Alessia Lucia [1 ,3 ]
Niccolai, Neri [4 ]
Brunetti, Sara [1 ]
Bianchini, Monica [1 ]
机构
[1] Univ Siena, Dept Informat Engn & Math DIISM, Via Roma 56, I-53100 Siena, Italy
[2] Univ Florence, Dept Informat Engn DINFO, Via S Marta 3, I-50139 Florence, Italy
[3] Toscana Life Sci Fdn, Mass Spectrometry Unit MSU, Via Fiorentina 1, I-53100 Siena, Italy
[4] Univ Siena, Dept Biotechnol Chem & Pharm, Via Aldo Moro 2, I-53100 Siena, Italy
关键词
Morphological Algorithms; Voxel Model; Structural biology; Atom depth; Molecular shape; Depth index; Discrete Geometry; PROTEIN-STRUCTURE;
D O I
10.1007/978-3-031-57793-2_34
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The field of structural biology is rapidly advancing thanks to significant improvements in X-ray crystallography, nuclear magnetic resonance (NMR), cryo-electron microscopy, and bioinformatics. The identification of structural descriptors allows for the correlation of functional properties with characteristics such as accessible molecular surfaces, volumes, and binding sites. Atom depth has been recognized as an additional structural feature that links protein structures to their folding and functional properties. In the case of proteins, the atom depth is typically defined as the distance between the atom and the nearest surface point or nearby water molecule. In this paper, we propose a discrete geometry method to calculate the depth index with an alternative approach that takes into account the local molecular shape of the protein. To compute atom depth indices, we measure the volume of the intersection between the molecule and a sphere with an appropriate reference radius, centered on the atom for which we want to quantify the depth. We validate our method on proteins of diverse shapes and sizes and compare it with metrics based on the distance to the nearest water molecule from bulk solvent to demonstrate its effectiveness.
引用
收藏
页码:443 / 455
页数:13
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