Protein association in membranes is a process of major physiological and technological significance. Association of individual helices in a membrane environment is a critical step towards the assembly of a functional integral protein. Regulation of this process provides a path to modulate signal transduction mechanisms and cell proliferation. Association of proteins is also a required step for the successful formation of stable artificial pores and membrane redox proteins. Current state of knowledge on the factors that control protein association is significantly limited. While several studies have provided a qualitative view of the underlying thermodynamics, there is a clear need of quantitative predictive tools that will offer estimates of structural and thermodynamic properties for a specific amino-acid sequence in a lipid membrane. The hypothesis is that computational methods can serve this purpose if both amino-acid detail and membrane composition are accounted for. These factors control the function and phase behavior of transmembrane proteins. To test the hypothesis, the investigators will design and perform extensive parallel Monte Carlo simulations with the transmembrane sequence of Glycophorin A and the transmembrane domains of the epidermal growth factor receptor family in lipid membranes composed by cholesterol and phospholipids. Results from the first system will be directly compared to available experimental data while predictions for the second will increase our knowledge on contributions of transmembrane sequences to the association of an important family of receptors.
Intellectual merit: In this interfacial-related and health-related project, the investigators will provide a fundamental understanding on the factors controlling aggregation of small transmembrane helices in lipid membranes. Molecular simulations will examine the effect of amino-acid sequence, quantify local concentrations not accessible to experimental techniques and provide estimates of the association thermodynamics. The project will develop parallel Monte Carlo algorithms that reach beyond current techniques examining sequence-specific association in explicit multicomponent membranes. Furthermore, it will produce new knowledge on the behavior of transmembrane domains of the family of epidermal growth factor receptors in different microenvironments ranging from single-component fluid lipid bilayers to ordered membranes reminiscent of lipid rafts.
Broader impacts: Research results will have a broader societal impact by developing predictive computational tools to study protein association without the need to resort to the current limited knowledge of membrane protein structures. The development of such tools will advance our ability to design new functional proteins with applications in biotechnology. Additionally, the extracted estimates on the association affinity of transmembrane sequences of receptor proteins in membranes will assist the design of peptides acting as inhibitors.
Finally, the successful implementation of advanced modeling techniques represents a multidisciplinary problem-solving activity through computational tools. The PI aims to inspire students from underrepresented groups to learn about modeling and engage them into research activities with simulation methods within the scope of the proposed research. Using existing opportunities at the University of Houston, the PI will work with high-school teachers and undergraduate students on short-term projects aiming to extract atomistic details of protein complexes with the resulting structures made available to the community.
Protein association in membranes, a process where several individual protein molecules form a single complex unit, is of major physiological and technological significance. Regulating this process can provide a path to treat health-related problems and devise several technological applications. However, it is challenging to study association phenomena through experimental characterization, particularly when employing quantitative measures. The main aim of the project was to develop computational methods and predictive tools to quantitatively characterize the formation of protein aggregates within the membranes. The developed methods incorporated molecular detail, such as the chemistry of the protein molecules as well as the membrane environment enabling discovery for specific systems. The large-scale computer simulations performed within the course of the project were able to explicitly identify and quantify the factors that contribute to formation of stable dimers for several prototype systems. Furthermore, simulations revealed the need to extend characterization beyond thermodynamic stability, incorporating concepts of chemical kinetics into studying such phenomena. We found that cholesterol, a common constituent in lipid membranes, appears to control both stability and rates of association. These results support an active role of membrane composition into regulating protein aggregation, significantly extending our current knowledge on these processes. The project supported the development of tools that had a broader societal impact by being employed in close collaboration with experimental teams. An investigation of the association of two distinct transmembrane parts of the Growth Hormone Receptor into a single unit, lead to significant contributions into formulating a new mechanism for the activation of this important protein molecule. This mechanism will serve as the basis for further investigation and potential development of techniques to regulate the process. The successful application of the software developed and the new insight offered provides a statement of the progress performed in characterizing quantitatively interfacial phenomena at the molecular level within the scope of the supported project. .
