Experimental data-guided parameterization and validation of an AMBER protein force field
Folded or globular proteins adopt well-defined three-dimensional structures that correlate directly with function, forming the classical structure-function paradigm. Intrinsically Disordered Proteins (IDPs) and Regions (IDRs), encoded by roughly one-third of the eukaryotic genome, lack this fixed structure; their structural plasticity and major roles in diverse biological phenomena instead challenge this paradigm, making them a critical class of biomolecules studied through both experimental and computational approaches. Molecular dynamics (MD) simulations provide an atomistic understanding of IDP structure and dynamics, but their accuracy is limited by methodological assumptions and by the precision of the force field--the potential-energy function that approximates atomic interactions and governs how faithfully a simulation reflects real conformational behavior. Previous studies show that contemporary force fields fail to adequately capture amino acid residue specificity, limiting their applicability to IDPs. The central focus of this dissertation is therefore the development of an improved force field, Amber ff24EXP-GA, derived from its parent, Amber ff14SB, and its evaluation against Amber ff14SB and other contemporary force fields, such as CHARMM36m, in capturing the empirically determined conformational properties of unfolded systems: short peptides that serve as model systems for IDPs, and longer unfolded proteins. Chapter 3 addresses this gap by reporting a new force field, Amber ff24EXP-GA, derived from Amber ff14SB by optimizing backbone dihedral potentials for guest glycine and alanine residues in cationic GGG and GAG peptides, respectively, to best match guest-residue-specific spectroscopic data. Amber ff24EXP-GA outperforms Amber ff14SB for conformational ensembles of all 14 guest residues x (G, A, L, V, I, F, Y, D^p, E^p, R, C, N, S, T) in GxG peptides in water--the full set for which spectroscopic data exist--and outperforms CHARMM36m for at least 7 of them (G, A, V, F, C, T, E^p), showing greater amino acid specificity than both Amber ff14SB and CHARMM36m. It also reproduces experimental data on three-folded proteins and three longer IDPs well, while still outperforming Amber ff14SB on short unfolded peptides. Chapter 4 examines the effect of nearest-neighbor (NN) residues on conformational dynamics: extensive experimental evidence shows that the Flory hypothesis--which assumes neighboring residues behave independently--does not hold, as NN residues instead alter the conformational landscape of a given residue. Here, we evaluate CHARMM36m, Amber ff14SB, and Amber ff24EXP-GA for their ability to capture these NN effects on conformational dynamics of amino acid residues in short unfolded peptides in water. Amber ff24EXP-GA, whose reproduction of intrinsic conformational ensembles is significantly better than its parent's, also captures the NN effects better than Amber ff14SB. Despite lacking residue specificity in its intrinsic conformational ensembles, CHARMM36m--calibrated on global IDP properties--reproduces the NN effects on par with Amber ff24EXP-GA. These findings matter for the development of next-generation force fields that capture both residue-specific dynamics and global IDP properties. Chapter 5 examines the current scope, achievements, and limitations of various MD force-field parametrization strategies for modeling proteins, with particular emphasis on intrinsically disordered proteins.