A significant problem in molecular biology is our inability to accurately calculate, model and predict protein-ligand binding affinities, even when provided a high-resolution structure of the actual complex. This problem is made evident across a wide body of experimentation and literature, including (1) the poor performance of algorithms used to calculate binding affinities from structures, (2) disagreement on the physical basis for high affinity ligand binding for exceptionally well-studied proteins such as streptavidin, and (3) difficulties associated with engineering novel ligand-binding proteins. Attempts to understand the basis for tight, specific ligand binding by dissecting naturally evolved ligand binding protein, while informative, have not produced the ability to accurately predict binding affinities from structures, or to directly compute the structure of novel ligand binding proteins. Engineered proteins offer a possible advantage as alternative systems for the examination of ligand binding mechanisms. While the energetic and structural parameters that are used to create them may be inaccurate, those terms are nonetheless precisely defined during the engineering process and can be systematically altered during an iterative design project. In addition, protein engineering allows investigators to create large numbers of designed proteins against many precisely defined ligands, and then to identify the most interesting and informative constructs for detailed structural and physical analyses.
The Specific Aims of this project are: (1) To determine common structural and mechanistic features of successfully designed ligand binding proteins, and to compare those results against designs that display unexpected patterns of ligand binding affinities and specificities. (2) To assess whether constraints that are placed on the design of ligand binding proteins behave as intended. In particular, this study will examine whether two fundamental components of ligand- protein designs (shape complementarity, which attempts to enforce specificity, and structural 'pre-ordering' of the binding site, which attempts to reduce entropic penalties) actually impair ligand-binding function. We believe that completion of these aims will provide both an immediate impact (by improving protein design methods) and a longer-term impact (by further elucidating rules that govern the behavior of ligand binding proteins in general).

Public Health Relevance

The appropriate balance of ligand binding affinity and specificity is a fundamental feature of almost any biological process, including immune recognition, cellular metabolism, regulation of gene expression, and cell signaling. The ability to accurately predict and recapitulate the physical basis for ligand specificity and binding affinity s therefore a crucial part of understanding and manipulating such biological phenomena. It also represents a critical technical requirement in the reciprocal fields of drug design and protein.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM115545-04
Application #
9517920
Study Section
Macromolecular Structure and Function B Study Section (MSFB)
Program Officer
Lyster, Peter
Project Start
2015-09-01
Project End
2019-06-30
Budget Start
2018-07-01
Budget End
2019-06-30
Support Year
4
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Fred Hutchinson Cancer Research Center
Department
Type
DUNS #
078200995
City
Seattle
State
WA
Country
United States
Zip Code
98109
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Dou, Jiayi; Doyle, Lindsey; Jr Greisen, Per et al. (2017) Sampling and energy evaluation challenges in ligand binding protein design. Protein Sci 26:2426-2437
Berger, Stephanie; Procko, Erik; Margineantu, Daciana et al. (2016) Computationally designed high specificity inhibitors delineate the roles of BCL2 family proteins in cancer. Elife 5:
Doyle, Lindsey; Hallinan, Jazmine; Bolduc, Jill et al. (2015) Rational design of ?-helical tandem repeat proteins with closed architectures. Nature 528:585-8
King, Indigo Chris; Gleixner, James; Doyle, Lindsey et al. (2015) Precise assembly of complex beta sheet topologies from de novo designed building blocks. Elife 4: