The unparalleled specificity and activity of therapeutic proteins has reshaped many aspects of modern clinical practice, and aggressive development of new protein drugs promises a continued revolution in disease therapy. As a result of their biological origins, however, therapeutic proteins present unique design challenges for the biomolecular engineer. For example, protein drugs are subject to immune surveillance within the patient's body; this anti-drug immune response can compromise therapeutic efficacy and even threaten patient safety. Thus, there is a growing demand for broadly applicable protein deimmunization strategies. We have recently developed optimization algorithms that integrate computational prediction of T-cell epitopes and bioinformatics-based assessment of the structural and functional consequences of epitope-deleting mutations. Here, we describe the first experimental validation of our deimmunization algorithms using Enterobacter cloacae P99 β-lactamase, a component of antibody-directed enzyme prodrug cancer therapies. Compared with wild-type or a previously deimmunized variant, our computationally optimized sequences exhibited significantly less in vitro binding to human type II major histocompatibility complex immune molecules. At the same time, our globally optimal design exhibited wild-type catalytic proficiency. We conclude that our deimmunization algorithms guide the protein engineer towards promising immunoevasive candidates and thereby have the potential to streamline biotherapeutic development.
Despite intense efforts by the medical and pharmaceutical communities, Staphylococcus aureus continues to be a pervasive pathogen that causes a myriad of diseases and a high level of morbidity and mortality among infected patients. Thus, discovering or designing novel therapeutics able to kill both drug-resistant and drug-sensitive S. aureus remains a top priority. Bacteriolytic enzymes, mostly from phage, have shown great promise in preclinical studies, but little consideration has been given to cis-acting autolytic enzymes derived from the pathogen itself. Here, we use the S. aureus autolysin LytM as a proof-of-principal to demonstrate the antibacterial potential of endogenous peptidoglycan degrading enzymes. While native LytM is only marginally bactericidal, fusion of LytM to the lysostaphin cell wall binding domain enhances its anti-staphylococcal activity approximately 540-fold, placing it on par with many phage lysins currently in preclinical development. The potential to therapeutically co-opt a pathogen’s endogenous peptidoglycan recycling machinery opens the door to a previously untapped reservoir of antibacterial drug candidates.
Human lysozyme is a key component of the innate immune system, and recombinant forms of the enzyme represent promising leads in the search for therapeutic agents able to treat drug-resistant infections. The wild type protein, however, fails to participate effectively in clearance of certain infections due to inherent functional limitations. For example, wild type lysozymes are subject to electrostatic sequestration and inactivation by anionic biopolymers in the infected airway. A charge engineered variant of human lysozyme has recently been shown to possess improved antibacterial activity in the presence of disease associated inhibitory molecules. Here, the 2.04 Å crystal structure of this variant is presented along with an analysis that provides molecular level insights into the origins of the protein's enhanced performance. The charge engineered variant's two mutated amino acids exhibit stabilizing interactions with adjacent native residues, and from a global perspective, the mutations cause no gross structural perturbations or loss of stability. Importantly, the two substitutions dramatically expand the negative electrostatic potential that, in the wild type enzyme, is restricted to a small region near the catalytic residues. The net result is a reduction in the overall strength of the engineered enzyme's electrostatic potential field, and it appears that the specific nature of this remodeled field underlies the variant's reduced susceptibility to inhibition by anionic biopolymers.
Staphylococcus aureus is a dangerous bacterial pathogen whose clinical impact has been amplified by the emergence and rapid spread of antibiotic resistance. In the search for more effective therapeutic strategies, great effort has been placed on the study and development of staphylolytic enzymes, which benefit from high potency, activity towards drug-resistant strains, and a low inherent susceptibility to emergence of new resistance phenotypes. To date, the majority of therapeutic candidates have derived from either bacteriophage or environmental competitors of S. aureus. Little to no consideration has been given to cis-acting autolysins that represent key elements in the bacterium's endogenous cell wall maintenance and recycling machinery. In this study, five putative autolysins were cloned from the S. aureus genome, and their activities were evaluated. Four of these novel enzymes, or component domains thereof, demonstrated lytic activity towards live S. aureus cells, but their potencies were 10s to 1000s of times lower than that of the well-characterized therapeutic candidate lysostaphin. We hypothesized that their poor activities were due in part to suboptimal cell wall targeting associated with their native cell wall binding domains, and we sought to enhance their antibacterial potential via chimeragenesis with the peptidoglycan binding domain of lysostaphin. The most potent chimera exhibited a 140-fold increase in lytic rate, bringing it within 8-fold of lysostaphin. While this enzyme was sensitive to certain biologically relevant environmental factors and failed to exhibit a measurable minimal inhibitory concentration, it was able to kill lysostaphin-resistant S. aureus and ultimately proved active in lung surfactant. We conclude that the S. aureus proteome represents a rich and untapped reservoir of novel antibacterial enzymes, and we demonstrate enhanced bacteriolytic activity via improved cell wall targeting of autolysin catalytic domains.
A mathematical concept known as Parrondo's paradox motivated the development of several novel computational models of chemical systems in which thermal cycling was explored. In these kinetics systems we compared the rates of formation of product under cycling temperature and steady-sate conditions. We found that a greater concentration of product was predicted under oscillating temperature conditions. Our computational models of thermal cycling suggest new applications in chemical and chemical engineering systems.
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