PyCPET - Computing Heterogeneous 3D Protein Electric Fields and Their Dynamics

Electrostatic preorganization is an exciting mode to understand the catalytic function of enzymes, yet limited tools exist to computationally analyze it. In particular, no methods exist to interpret the geometry, dynamics, and fundamental components of 3-D electric fields, E(r), in protein active sites. Here we present PyCPET (Python Computation of Electric Field Topologies), a comprehensive, open-source toolbox to analyze E(r), in enzymes. We designed it to be computationally efficient and user friendly with both CPU and GPU accelerated codes. Our aim is to provide a set of functions for rich, descriptive analysis of enzyme systems including dynamics, benchmarking, distribution of streamlines analysis in 3-D E(r), computation of point E(r), principal component analysis, and 3-D field visualization. Finally, we demonstrate its versatility by exploring the nature of electrostatic preorganization and dynamics in three cases: Cytchrome C, Co-substituted Liver Alcohol Dehydrogenase, and HIV Protease. These test systems, along with previous work, establish PyCPET as an essential toolkit for the in-depth analysis and visualization of electric fields in enzymatic systems, unlocking new avenues for understanding electrostatic contributions to enzyme catalysis.