Role of structural water for prediction of cation binding sites in apoproteins

Abstract

Structures of many metal-binding proteins are often obtained without structural cations in their apoprotein forms. Missing cation coordinates are usually updated from structural templates constructed from many holoprotein structures. Such templates usually do not include structural water, the important contributor to the ion binding energy. Structural templates are also inconvenient for taking into account structural modifications around the binding site at apo-/holo- transitions. An approach based upon statistical potentials readily takes into account structural modifications associated with binding as well as contribution of structural water molecules. Here, we construct a set of statistical potentials for Mg²⁺, Ca²⁺, and Zn²⁺ contacting with protein atoms of a different type or structural water oxygens. Each type of the cations tends to form tight contacts with protein atoms of specific types. Structural water contributes relatively more into the binding pseudo-energy of Mg²⁺ and Ca²⁺ than of Zn²⁺. We have developed PIONCA (Protein-Ion Calculator), a fast CUDA GPGPU-based algorithm that predicts ion-binding sites in apoproteins. Comparative tests demonstrate that PIONCA outperforms most of the tools based on structural templates or docking. Our software can be also used for locating bound cations in holoprotein structures with missing cation heteroatoms. PIONCA is equipped with an interactive web interface based upon JSmol.

Keywords:

• statistical potential
• structural water
• structural cations
• Mg²⁺
• Ca²⁺
• Zn²⁺
• PIONCA