The dense, heterogeneous cellular environment is known to affect protein stability through interactions with other biomacromolecules. The effect of excluded volume due to these biomolecules, also known as crowding agents, on a protein of interest, or test protein, has long been known to increase the stability of a test protein. Recently, it has been recognized that attractive protein-crowder interactions play an important role. These interactions affect protein stability and can destabilize the test protein. However, most computational work investigating the role of attractive interactions has used spherical crowding agents and has neglected the specific roles of crowding agent hydrophobicity and hydrogen bonding. Here we use multicanonical molecular dynamics and a coarse-grained protein model to study the folding thermodynamics of a small helical test protein in the presence of crowding agents that are themselves proteins. Our results show that the stability of the test protein depends on the hydrophobicity of the crowding agents. For low values of crowding agent hydrophobicity, the excluded volume effect is dominant, and the test protein is stabilized relative to the dilute solution. For intermediate values of the crowding agent hydrophobicity, the test protein is destabilized by favorable side chain-side chain interactions stabilizing the unfolded states. For high values of the crowding agent hydrophobicity, the native state is stabilized by the strong intermolecular attractions, causing the formation of a packed structure that increases the stability of the test protein through favorable side chain-side chain interactions. In addition, increasing crowding agent hydrophobicity increases the "foldability" of the test protein and alters the potential energy landscape by simultaneously deepening the basins corresponding to the folded and unfolded states and increasing the energy barrier between them.

The dense, heterogeneous cellular environment is known to affect protein stability. It is now recognized that attractive "quinary" interactions with other biomacromolecules in the cell, referred to as the crowding agents, play a significant role in determining the stability of the protein of interest or test protein. These attractive interactions can reduce or overcome the stabilizing effect of the excluded volume of the crowding agents. However, the roles of specific interactions, such as hydrogen bonding and side chain-side chain hydrophobic interactions, are still unclear. Here, we use molecular simulation to investigate the roles played by hydrophobic interactions and hydrogen bonding between a small helical test protein and equally sized crowding agent proteins in a fixed β-hairpin configuration. The test protein and crowding agents are represented by a coarse-grained protein model, and we use multicanonical molecular dynamics to study the folding thermodynamics of the test protein. Our results confirm that the stability of the test protein depends on the hydrophobicity of the crowding agents and that the stability of the test protein is reduced through favorable side chain-side chain interactions that preferentially stabilize the unfolded states. In addition, we show that when the intermolecular hydrophobic interactions are more favorable than the intramolecular hydrophobic interactions, the β-rich crowding agents can completely destabilize the test protein, causing it to adopt configurations with increased β-content and preventing it from forming its native helical state. Similarities between our results and those seen in the formation of amyloid fibrils are also discussed.

while the entropic change can even be unfavorable. To elucidate the molecular basis of these depletion interactions, we use simulations and analytic theory. Monte-Carlo simulations follow the association of two rod ''macromolecules'' in binary Lennard-Jones solutions. By dissecting the association free energy change into the respective thermodynamic components, we find different cosolutes induce stabilization through different thermodynamic driving mechanisms. Even for these simple liquids, considering intermolecular interactions beyond hard-cores can result in depletion forces that are completely enthalpic. We discuss how this newly resolved mechanism originates from intermolecular interactions and solvent restructuring. Finally, a mean-field theoretical model based on regular solution theories complements the simulation analysis. The dense, heterogeneous cellular environment is known to affect protein stability through interactions with other biomacromolecules. The effect of excluded volume due to these biomolecules, also known as crowding agents, on a protein of interest, or test protein, has long been known to increase the stability of a test protein. Recently, it has been recognized that attractive proteincrowder interactions play an important role. These interactions affect protein stability and can destabilize the test protein. However, most computational work investigating the role of attractive interactions has used spherical crowding agents and has neglected the specific roles of crowding agent hydrophobicity and hydrogen bonding. Here, we use multicanonical molecular dynamics and a coarse-grained protein model to study the folding thermodynamics of a small helical test protein in the presence of crowding agents that are themselves proteins. Our results show that the stability of the test protein depends on the hydrophobicity of the crowding agents. For low values of crowding agent hydrophobicity, the excluded volume effect is dominant and the test protein is stabilized relative to the dilute solution. For intermediate values of the crowding agent hydrophobicity, the test protein is destabilized by favorable side chainside chain interactions stabilizing the unfolded states. For high values of the crowding agent hydrophobicity, the native state is stabilized by the strong intermolecular attractions causing the formation of a packed structure that increases the stability of the test protein through favorable side chain-side chain interactions. In addition, increasing crowding agent hydrophobicity increases the ''foldability'' of the test protein and alters the potential energy landscape by simultaneously deepening the basins corresponding to the folded and unfolded states and increasing the energy barrier between them. Molecular chaperones are commonly identified by their ability to suppress heat induced protein aggregation. The muscle specific molecular chaperone UNC-45B is known to be critical in folding myosin and is trafficked to the sarcomeres A-band during thermal stress. Here, we identify thermally...

This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR04) of the Conference Proceedings. Citation Format: Haichuan Hu, Lecia Sequist, Zofia Piotrowska, Hillary Mulvey, Sundus Noeen, Patricia Hare, David Kodack, Aaron Hata, Matt Niederst, Cyril Benes, Jeff Engelman. Decoding tumor microenvironment to enhance NSCLC targeted therapy [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr B25.

Background: Tyrosine kinase inhibitors (TKI) have yielded great responses in non-small-cell lung cancer (NSCLC) with EGFR mutations and ALK translocations, however these and other targeted therapies are limited by intrinsic and acquired drug resistance. Previous study from our group was looking into tumor autonomous resistance mechanisms by developing patient-derived cancer models (PDCs). In this study, we aimed to decipher the non-autonomous resistance mechanisms via tumor microenvironment by developing patient-derived fibroblast (PDF) cell lines. Method: Cancer-associated fibroblast cells are isolated directly from EGFR mutant and ALK translocated NSCLC biopsies. Over 30 PDFs models have been established, which represent different clinical features and response profiles. Result: By co-culturing the PDCs with PDFs, we found that there is considerable variability in both models for their magnitude and mechanism by which the TKI treatment is desensitized. Both HGF dependent and HGF independent resistance mechanisms can be overcome by specific therapeutic combinations. Conclusion: Together, our results indicate that PDFs are clinically relevant models for deciphering non-autonomous resistance mechanisms, that they are heterogeneous in protecting cancer cells from TKI treatment, and that the resistance mediated by PDFs can be overcome by specific therapeutic combinations. Citation Format: Haichuan Hu, Hillary Mulvey, Sundus Noeen, Kodack David, Aaron Hata, Matthew Niederst, Cyril Benes, Jeffrey Engelman. Patient-derived tumor microenvironment models uncover nonautonomous TKI resistance mechanisms in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1012. doi:10.1158/1538-7445.AM2017-1012