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Murthy, N. Sanjeeva

Publications and source records attributed to Murthy, N. Sanjeeva.

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Examining polymer‐protein biophysical interactions with small‐angle x‐ray scattering and quartz crystal microbalance with dissipation

Abstract Polymer‐protein hybrids can be deployed to improve protein solubility and stability in denaturing environments. While previous work used robotics and active machine learning to inform new designs, further biophysical information is required to ascertain structure–function behavior. Here, we show the value of tandem small‐angle x‐ray scattering (SAXS) and quartz crystal microbalance with dissipation (QCMD) experiments to reveal detailed polymer‐protein interactions with horseradish peroxidase (HRP) as a test case. Of particular interest was the process of polymer‐protein complex formation under thermal stress whereby SAXS monitors formation in solution while QCMD follows these dynamics at an interface. The radius of gyration ( R g ) of the protein as measured by SAXS does not change significantly in the presence of polymer under denaturing conditions, but thickness and dissipation changes were observed in QCMD data. SAXS data with and without thermal stress were utilized to create bead models of the potential complexes and denatured enzyme, and each model fit provided insight into the degree of interactions. Additionally, QCMD data demonstrated that HRP deforms by spreading upon surface adsorption at low concentration as shown by longer adsorption times and smaller frequency shifts. In contrast, thermally stressed and highly inactive HRP had faster adsorption kinetics. The combination of SAXS and QCMD serves as a framework for biophysical characterization of interactions between proteins and polymers which could be useful in designing polymer‐protein hybrids.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Iodination of PEGylated Polymers Counteracts the Inhibition of Fibrinogen Adsorption by PEG

Poly(ethylene glycol), PEG, known to inhibit protein adsorption, is widely used on the surfaces of biomedical devices when biofilm formation is undesirable. Poly(desaminotyrosyl-tyrosine ethyl ester carbonate), PDTEC, PC for short, has been a promising coating polymer for insertion devices, and it has been anticipated that PEG plays a similar role if it is copolymerized with PC. Earlier studies show that no fibrinogen (Fg) is adsorbed onto PC polymers with PEG beyond the threshold weight percentage. This is attributed to the phase separation of PEG. Further, iodination of the PC units in the PC polymer, (I 2 PC), has been found to counteract this Fg-repulsive effect by PEG. Here, in this study, we employ surface-sensitive X-ray techniques to demonstrate the surface affinity of Fg toward the air–water interface, particularly in the presence of self-assembled PC-based film, in which its constituent polymer units are assumed to be much more mobile as a free-standing film. Fg is found to form a Gibbs monolayer with its long axis parallel to the aqueous surface, thus maximizing its interactions with hydrophobic interfaces. It influences the amount of insoluble, surface-bound I 2 PC likely due to the desorption of the formed Fg–I 2 PC complex and/or the penetration of Fg onto the I 2 PC film. The results show that the phase behavior at the liquid–polymer interface shall be taken into account for the surface behavior of bulk polymers surrounded by tissue. The ability of PEG units rearranging into a protein-blocking layer, rather than its mere presence in the polymer, is the key to antifouling characteristics desired for polymeric coating on insertion devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine Learning on a Robotic Platform for the Design of Polymer–Protein Hybrids

Polymer–protein hybrids are intriguing materials that can bolster protein stability in non-native environments, thereby enhancing their utility in diverse medicinal, commercial, and industrial applications. One stabilization strategy involves designing synthetic random copolymers with compositions attuned to the protein surface, but rational design is complicated by the vast chemical and composition space. Here, a strategy is reported to design protein-stabilizing copolymers based on active machine learning, facilitated by automated material synthesis and characterization platforms. The versatility and robustness of the approach is demonstrated by the successful identification of copolymers that preserve, or even enhance, the activity of three chemically distinct enzymes following exposure to thermal denaturing conditions. Although systematic screening results in mixed success, active learning appropriately identifies unique and effective copolymer chemistries for the stabilization of each enzyme. Overall, this work broadens the capabilities to design fit-for-purpose synthetic copolymers that promote or otherwise manipulate protein activity, with extensions toward the design of robust polymer–protein hybrid materials.

36 MATERIALS SCIENCE↗