AESOP: A Python Library for Investigating Electrostatics in Protein Interactions

Abstract

Electric fields often play a role in guiding the association of protein complexes. Such interactions can be further engineered to accelerate complex association, resulting in protein systems with increased productivity. This is especially true for enzymes where reaction rates are typically diffusion limited. To facilitate quantitative comparisons of electrostatics in protein families and to describe electrostatic contributions of individual amino acids, we previously developed a computational framework called AESOP. We now implement this computational tool in Python with increased usability and the capability of performing calculations in parallel. AESOP utilizes PDB2PQR and Adaptive Poisson-Boltzmann Solver to generate grid-based electrostatic potential files for protein structures provided by the end user. There are methods within AESOP for quantitatively comparing sets of grid-based electrostatic potentials in terms of similarity or generating ensembles of electrostatic potential files for a library of mutants to quantify the effects of perturbations in protein structure and protein-protein association.Electrostatics have been shown to play a pivotal role in guiding the association of a protein with its respective binding partner, forming the encounter complex (1-4). Additionally, electrostatic interactions can act to thermodynamically stabilize a protein complex (4). In attempts to improve protein activity, enhancing association rates is preferable to thermodynamic stabilization of the complex, as interactions are typically diffusion limited (1). To aid investigations into the electrostatics of protein interactions and to facilitate attempts to re-engineer protein behavior, our lab previously developed a computational tool for analysis of electrostatic structures of proteins (AESOP) (5-8). Here, we present an implementation of AESOP in Python (9) with increased functionality and the capability of parallel processing. This framework may be used to both compare electrostatic similarity of protein families and dissect the electrostatic contribution of individual amino acids to the free energy of association (5-8).Though several other computational tools have been developed for similar purposes, AESOP is the only platform, to our knowledge, that is focused on protein electrostatics and offers multiple computational methods for both family-based and single-structure-based analyses. In comparison, Surface Diver and PIPSA have been developed to compare electrostatic potentials across families of structurally homologous proteins. Surface Diver accomplishes this quantitative comparison without prior structural superpositioning through spherical harmonic decomposition (10), whereas PIPSA requires superpositioning and instead allows for comparisons between common structural regions that are functionally similar (11,12). Similar to PIPSA, AESOP requires superposed structures and quantitatively compares electrostatic potentials in a common grid space. PIPSA performs this comparison via calculation of a Hodgkin s...

Cross-Species Analysis of Glycosaminoglycan Binding Proteins Reveals Some Animal Models Are “More Equal” than Others

“…Electrostatic difference calculations were performed using the AESOP Python framework [ 71 ], based on previously published methods [ 22 ] at 298.15 K. In this step, a solvent dielectric constant of 78.0 was chosen. The protein dielectric was set to 2.0.…”

Molecular Mechanisms of Macular Degeneration Associated with the Complement Factor H Y402H Mutation

“…Electrostatic similarity for the 100 conformations of each FH SCR7 isoform used in BD simulations were compared using established methods in the Analysis of Electrostatic Structures of Proteins (AESOP) python library (38). All SCR7 conformers were superposed on backbone C a , and PDB2PQR (33,34) was used to assign partial charges and van der Waals radii to each atom at a pH of 7.4.…”

Immunophysical Evaluation of the Initiating Step in the Formation of the Membrane Attack Complex

“…We used the alanine scan method of our AESOP computational framework [44] to explore in detail the significance of the many pairwise charge-charge interactions in contributing to the stability of the C5b6 complex. We performed computational alanine scan by mutating every ionizable amino acid residue to alanine, one at a time, to generate families of single mutants for C5b and C6, and their C5b6 complex.…”

“…The Alanine scan method in the AESOP (Analysis of Electrostatic Structures Of Proteins) python package [44] was utilized to perform a computational alanine scan on ionizable residues at the C5b6 interface, and to evaluate their electrostatic contributions to binding. Alanine scans were performed for each of the six representative structures of the MD-derived conformational states.…”

“…Electrostatic free energies of binding were calculated according to a thermodynamic cycle that is similar to the one used for the MM-PBSA calculations, described above, except that binding at the reference state is evaluated using Coulomb's equation instead of the molecular mechanics method. The following equations are used, as described previously [44] and in recent applications of AESOP on C3d and its ligands [28][29][30]:…”