An ongoing debate concerns the role conformational motions, often termed dynamics, play in biomolceular
funtion. For enzymes, it so happens that the timescales for large-scale domain motions are similar to the
apparent "$$).
catalytic rate (!"# This observation is where the major point of contention has developed: do
"$$. In this context, the proposed studies
conformational motions directly impact the true rate of catalysis (!"#) or !"#
will further explore how the modulation of the conformational landscape can indeed fine-tune "$$ without
!"#
impacting !"# and the ground state structure. The genesis of this proposal arises from our work with human
guanylate kinase (hGMPK), a potential therapeutic target for treating cancer and perhaps even SARS-CoV-2,
which motivated us to solve the first structure of hGMPK with nuclear magnetic resonance (NMR) spectroscopy
(PDB: 6NUI). While solving the hGMPK structure, we expressed a series of seven functional site distant (FSD),
"$$ when compared to the wild-
non-synonymous single nucleotide variants (nsSNVs) of hGMPK that enhance !"#
type (wt). Intriguingly, the 2D [1H,15N]-HSQC NMR spectra of the wt hGMPK and its nsSNVs suggest that the
) for GMP binding to
FSD mutations minimally impact hGMPK’s backbone fold, yet the apparent off-rates (
wt and the FSD mutant V91M differ by ~3000 s-1. We hypothesize that hGMPK’s activity can be modulated with
FSD mutants by reshaping the conformational landscape. Utilizing NMR spectroscopy and isothermal
calorimetry, we will test this hypothesis in the following two Specific Aims. In Aim 1, we will quantify the impact
of the FSD mutations on the conformational landscape from kinetic and thermodynamic perspectives. The results
from this Aim will provide a comprehensive picture as to where within the hGMPK catalytic and binding schemes
the FSD mutations have the largest impact on function. For Aim 2, we will deconvolute the contribution transient
structures within the conformational landscape play in enzymatic catalysis through experimentally driven
ensemble generation. Our protocol will select hGMPK structures from unbiased molecular dynamics (MD)
simulations based on residual dipolar couplings and cross-correlated relaxation rates measured with NMR. The
ensembles will aid in the identification of the functionally important transient conformations and an assessment
of the impact the FSD mutations have on backbone dihedral correlated motions. To our knowledge, this proposal
provides the first examples 1.) of experimentally driven, ensemble generation for an enzyme spanning
physiologically relevant timescales and 2.) of determining thermodynamic and kinetic parameters with ligand
binding to the same exact site on a series of enzyme variants. The impact of this proposal is the direct linkage
of the conformational landscape to enzymatic function. Immediate applications for these results include drug
discovery, where targeting structures within the conformational landscape rather than the ground state structure
will lead to better outcomes, and biomolecular design, where FSD mutations can be implemented to adjust
function through manipulation of the conformational landscape.
