Abstract

Pyrethroids are a common class of pesticide which are used in crop and personal protection against insects. The insecticidal mechanism of pyrethroids is reliant on their excitotoxicity to axons, namely, they disrupt the voltage-gated sodium channels, leading to an influx of sodium ions and permanent depolarization of the nerve cell.¹ This is why their use draws concern surrounding their accumulation in the environment, threatening the health of humans and ecosystems alike. As such, biological interventions are in active development, seeking to minimize risk to the public through sequestering this class of compound from the environment.

Recently, Liu et. al. have explored ways to remove pyrethroid pollutants from the environment using an odorant binding protein (OBP), specifically, Spodoptera littoralis pheromone binding protein 1 (SlitPBP1). Through applying Cresset’s proprietary Electrostatic Complementary™ method as part of their workflow, Liu et al. have engineered SlitPBP1 mutants able to effectively sequester pyrethroids from different environmental media.²

In this article, we will showcase the power of Electrostatic Complementary (EC) for ligand and protein design, calling attention to the impactful application of EC in a real-world protein engineering use case.

Quantification of favorable protein-ligand electrostatics using Electrostatic Complementarity

Electrostatic interactions are a key contributor to the enthalpic component of the binding free energy and are, therefore, an important consideration when optimizing binding affinity. EC facilitates a swift quantification and assessment of the electrostatic match between the ligand and the binding pocket, thereby aiding in the optimization of the protein-ligand electrostatic interactions.³

EC is calculated by comparing the electrostatic potentials arising from both the protein and ligand at vertices marked out over the ligand or protein solvent accessible surface. These values are capped at a maximum absolute value, summed and normalized to a range from 1 to -1, where:

• Scores of 1 are points where the protein and ligand electrostatic potentials are of equal magnitude and opposite sign (perfect electrostatic complementarity)
• Scores of -1 are points of equal magnitude and same sign (perfect electrostatic clash)
• Scores of 0 are points where either the protein and/or the ligand potential is 0

EC also quantifies this interaction with several EC scores; EC, EC r and EC rho. The EC score is the normalized surface integral of the complementarity scores over the surface of the ligand. EC r and EC rho are the Pearson’s and Spearman’s correlation coefficient respectively, calculated on the ligand and protein electrostatic potential sampled on the surface vertices. These latter scores give a reliable estimate of electrostatic complementarity in cases where charge anisotropies exist within the target binding site. Notwithstanding, regardless of score type, EC scores closer to 1 indicate favorable protein-ligand electrostatics, translating to improved ligand binding stability and, thus, potency.

Given that an EC value between -1 and 1 is evaluated at each vertex, an EC isosurface can also be rendered over the ligand or protein solvent accessible surface, with green regions identifying areas of the ligand or protein that share complementary electrostatics (scores of 1), red regions identifying electrostatic clashes (scores of -1) and white areas are those where the complementarity is neither favorable nor unfavorable (scores of 0). This isosurface functions as a visual aid, guiding the researcher to sections of the ligand or protein that require re-engineering to improve potency (Figure 1).

Figure 1. Electrostatic complementarity assessment of RIPK1 inhibitors, 1_D and 3_D against RIPK1. Red circles highlight a region where the Electrostatic Complementarity changes between Ligand 1_D and Ligand 3_D in the binding site of RIPK1. Colour code: positive EC (green), 0 EC (white) and negative EC (red). Binding pocket residues as identified by Flare are also highlighted. Please note that this is a different example than the one used in the paper.

Electrostatic Complementarity used to optimize Pyrethroid sequestration by SlitPBP1

Reducing costs during the optimization process can be achieved by streamlining the costly and time-consuming wet lab validation stages. EC facilitates the identification of energetically unfavorable protein-ligand interactions in silico, identifying troublesome structural motifs that can be optimized to improve target binding on the basis of complementary electrostatics. As will be showcased herein, this is applicable to protein engineering as well as ligand engineering.

Indeed, Liu et. al. employed a multi-step computational approach that included homology modeling, molecular docking, and Molecular Dynamics (MD) simulations to obtain the complex structure of deltamethrin (DeltaM), pyrethroid ester insecticide, bound to SlitPBP1. Subsequent per-residue free-energy calculations revealed that the binding site glutamate residue Glu97 (E97) contributed an unfavorable free energy of 1.70 kcal/mol to the binding interaction, marking E97 as candidate residue for mutagenesis with the goal of improving affinity to DeltaM.

E97 was systematically mutated to each of the other 19 natural amino acids and the protein-ligand electrostatic favorability for each mutant was assessed using EC in Flare™. Mutating E97 to Asp (E97D), Phe (E97F), Asn (E97N) or His (E97H) all improved the EC, without introducing other unfavorable interactions, unlike the electrostatic clash observed between the RES97 and the terminal benzene ring of DeltaM, when mutating the E97 to Thr (E97T) or Trp (E97W). Guided by the EC calculation, in vitro binding assays were carried out on the SlitPBP1 E97N mutant. This confirmed the observation that mutating E97 to Asp mutation improved the binding affinity as the dissociation constant (Kd) went from 21.77 ± 1.41 μM between wild-type SlitPBP1 and DeltaM to 1.07 ± 0.36 μM between the SlitPBP1 E97N and DeltaM.

After establishing that the SlitPBP1 E97N mutant showed better binding affinity to DeltaM than wild-type SlitPBP1, Liu et. al. revisited the system and repeated their per-residue free energy calculations, maintaining the definition that any residue which contributed a total binding free energy above 1.00 kcal/mol as unfavorable. Despite Asp106 (D106) having an acceptable energy contribution in the SlitPBP1 WT, upon mutating E97 to Asn, the energy contribution of D106 exceeded their cap and became unfavorable, making it a target for mutagenesis and further optimization of the protein. As before, Liu et al. mutated D106 to the other 19 natural amino acids and evaluated the protein-ligand electrostatic favorability for each mutant using EC in Flare. Although the EC scores identified both D106W and D106E as viable mutations, the RMSD throughout the MD simulations showed that the D106E was more stable. In vitro assays showed that the expressed SlitPBP1B E97N D106E double mutant greatly improved the binding affinity compared to the single mutant and wild-type, with a K_d of 0.77 ± 0.17 μM.

Conclusion

This article has highlighted a recent use case of Cresset’s EC method for protein engineering. Liu et.al. have demonstrated how EC can be applied to gain a more comprehensive understanding of the electrostatic interactions between the OBP and DeltaM, identifying favorable protein mutations that improve the sequestration ability of SlitPBP1 to extract pyrethroids from environmental media.

References

1. Hołyńska-Iwan, I. & Szewczyk-Golec, K. Pyrethroids: How They Affect Human and Animal Health? Medicina (Mex.) 56, 582 (2020).
2. Liu, J., Li, Y., Wang, P., Zhang, Y. & Tian, Z. High-efficiency removal of pyrethroids using a redesigned odorant binding protein. J. Hazard. Mater. 463, (2024).
3. Bauer, M. R. & Mackey, M. D. Electrostatic complementarity as a fast and effective tool to optimize binding and selectivity of protein-ligand complexes. J. Med. Chem. (2019).