We are using a range of computational and theoretical methods to study problems of specificity in protein–protein interactions. We are interested in understanding underlying chemical and physical principles and in developing novel methods, with our primary focus of study being various components of the heterotrimeric G-protein signal transduction pathway, a system of signficant medical and biotechnological relevance.
The chemistry of biology takes place within an incredibly complex, heterogenous environment, including a rich diversity of many classes of molecules. However, the proper function of biological systems requires the specific association of individual molecules from this vast array of molecules into functional complexes. Understanding the basic principles behind this specificity of interaction has important consequences, not only for understanding the natural complexity of biology, but also for the design of novel biomolecular complexes. Beginning with the heterotrimeric G-proteins themselves, we are studying the basic biophysical principles behind both promiscuous and highly specific binding. The network of "allowed" and "disallowed" interactions between the three components of this system are being explored using techniques from the field of computational protein design. This analysis will be extended to both upstream and downstream components of the signalling network, with a focus on developing an understanding suitable for application to the design of specifically interacting molecules.
Proteins can be chemically modified in numerous ways that may change the properties of the affected protein, and may have profound effects on molecular association. These effects may be due to gross physical changes (e.g. large scale conformational change, blocking of a binding site, or significant change in charge at the binding interface) or may be due to more subtle changes (e.g. local conformational change, altered dynamics of the molecule or binding site, or long-range electrostatic effects). Understanding how the chemical modification of proteins affects their association properties will help in furthering our understanding of regulation of cellular processes. While known to be an essential component in modulating essential biomedical characteristics such as immune system recognition and viral entry into cells, the effects of glycosylation on protein structure, dynamics, and function are particularly poorly understood. We are extending traditional methods for the study of protein systems to investigate the effects of glycosylation on protein–protein interactions, using the interactions made by the HIV-1 envelope glycoproteins (gp41 and gp120) as part of the cell-entry process as an initial case study. Future work will extend the methods and understanding gained in this system to the effects of glycosylation on the function of G-protein-coupled receptors.
To date, most molecular design work in biology has been done in the context of a reductionist approach — the system is considered in isolation from the biological context, and a single property (e.g. maximal stability or highest binding affinity) is targeted for design. While a great deal of progress has been made using this approach, it is clear that there are important limitations to this design paradigm; biology is an inherently complex and highly non-linear system of interacting molecular components, and thus perturbing a single component may have highly variable effects depending on the state of the system. An important goal in the field of biomolecular design must be methods which target more sophisticated properties, and we are interested in the development of such techniques. Hierarchical, multi-scale models will likely play a key role, and thus we are investigating this approach. Our studies of molecular level interactions in the G-protein signalling pathway will be combined with higher-level models of the system as an initial system in which to study information transfer from the molecular to the systems level.
This page is maintained by David F. Green <dfgreen@ams.sunysb.edu>. Last updated: Tue Apr 17 12:32:39 2007Copyright © 2003–2006 David F. Green. All rights reserved.