Hi, I am a recent Bioengineering PhD graduate from the BioMoDeLab at University of California, Riverisde.
My dissertation research focused on mechanistic studies of protein interactions, peptide design, and virtual drug screening.
I currently work at BIOVIA Dassault Systèmes where I utilize my computational chemistry background for the development of modeling and simulation tools/methods for drug design and discovery.
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.
Electrostatic effects are ubiquitous in protein interactions and are found to be pervasive in the complement system as well. The interaction between complement fragment C3d and complement receptor 2 (CR2) has evolved to become a link between innate and adaptive immunity. Electrostatic interactions have been suggested to be the driving factor for the association of the C3d:CR2 complex. In this study, we investigate the effects of ionic strength and mutagenesis on the association of C3d:CR2 through Brownian dynamics simulations. We demonstrate that the formation of the C3d:CR2 complex is ionic strength-dependent, suggesting the presence of long-range electrostatic steering that accelerates the complex formation. Electrostatic steering occurs through the interaction of an acidic surface patch in C3d and the positively charged CR2 and is supported by the effects of mutations within the acidic patch of C3d that slow or diminish association. Our data are in agreement with previous experimental mutagenesis and binding studies and computational studies. Although the C3d acidic patch may be locally destabilizing because of unfavorable Coulombic interactions of like charges, it contributes to the acceleration of association. Therefore, acceleration of function through electrostatic steering takes precedence to stability. The site of interaction between C3d and CR2 has been the target for delivery of CR2-bound nanoparticle, antibody, and small molecule biomarkers, as well as potential therapeutics. A detailed knowledge of the physicochemical basis of C3d:CR2 association may be necessary to accelerate biomarker and drug discovery efforts.
Purpose: To redesign a complement-inhibiting peptide with the potential to become a therapeutic for dry and wet age-related macular degeneration (AMD).
Methods: We present a new potent peptide (Peptide 2) of the compstatin family. The peptide is developed by rational design, based on a mechanistic binding hypothesis, and structural and physicochemical properties derived from molecular dynamics (MD) simulation. The inhibitory activity, efficacy, and solubility of Peptide 2 are evaluated using a hemolytic assay, a human RPE cell–based assay, and ultraviolet (UV) absorption properties, respectively, and compared to the respective properties of its parent peptide (Peptide 1).
Results: The sequence of Peptide 2 contains an arginine-serine N-terminal extension (a characteristic of parent Peptide 1) and a novel 8-polyethylene glycol (PEG) block C-terminal extension. Peptide 2 has significantly improved aqueous solubility compared to Peptide 1 and comparable complement inhibitory activity. In addition, Peptide 2 is more efficacious in inhibiting complement activation in a cell-based model that mimics the pathobiology of dry AMD.
Conclusions: We have designed a new peptide analog of compstatin that combines N-terminal polar amino acid extensions and C-terminal PEGylation extensions. This peptide demonstrates significantly improved aqueous solubility and complement inhibitory efficacy, compared to the parent peptide. The new peptide overcomes the aggregation limitation for clinical translation of previous compstatin analogs and is a candidate to become a therapeutic for the treatment of AMD.