From Distinct to Differential Conformational Dynamics to Map Allosteric Communication Pathways in Proteins

Illuminating Protein Allostery by Chemically Accurate Contact Response Analysis (ChACRA)

Decoding allostery at the atomic level is essential for understanding the relationship between a protein's sequence, structure, and dynamics. Recently, we have shown that decomposing temperature responses of inter-residue contacts can reveal allosteric couplings and provide useful insight into the functional dynamics of proteins. The details of this Chemically Accurate Contact Response Analysis (ChACRA) are presented here along with its application to two well-known allosteric proteins. The first protein, IGPS, is a model of ensemble allostery that lacks clear structural differences between the active and inactive states. We show that the application of ChACRA reveals the experimentally identified allosteric coupling between effector and active sites of IGPS. The second protein, ATCase, is a classic example of allostery with distinct active and inactive structural states. Using ChACRA, we directly identify the most significant residue level interactions underlying the enzyme's cooperative behavior. Both test cases demonstrate the utility of ChACRA's unsupervised machine learning approach for dissecting allostery at the residue level.

Probing allosteric communication with combined molecular dynamics simulations and network analysis

Understanding the allosteric mechanisms within biomolecules involved in diseases is of paramount importance for drug discovery. Indeed, characterizing communication pathways and critical hotspots in signal transduction can guide a rational approach to leverage allosteric modulation for therapeutic purposes. While the atomistic signatures of allosteric processes are difficult to determine experimentally, computational methods can be a remarkable resource. Network analysis built on Molecular Dynamics simulation data is particularly suited in this respect and is gradually becoming of routine use. Herein, we collect the recent literature in the field, discussing different aspects and available options for network construction and analysis. We further highlight interesting refinements and extensions, eventually providing our perspective on this topic.

Dissecting the Allosteric Fine-Tuning of Enzyme Catalysis

Fully understanding the mechanism of allosteric regulation in biomolecules requires separating and examining all of the involved factors. In enzyme catalysis, allosteric effector binding shifts the structure and dynamics of the active site, leading to modified energetic (e.g., energy barrier) and dynamical (e.g., diffusion coefficient) factors underlying the catalyzed reaction rate. Such modifications can be subtle and dependent on the type of allosteric effector, representing a fine-tuning of protein function. The microscopic description of allosteric regulation at the level of function-dictating factors has prospective applications in fundamental and pharmaceutical sciences, which is, however, largely missing so far. Here, we characterize the allosteric fine-tuning of enzyme catalysis, using human Pin1 as an example, by performing more than half-millisecond all-atom molecular dynamics simulations. Changes of reaction kinetics and the dictating factors, including the free energy surface along the reaction coordinate and the diffusion coefficient of the reaction dynamics, under various enzyme and allosteric effector binding conditions are examined. Our results suggest equal importance of the energetic and dynamical factors, both of which can be modulated allosterically, and the combined effect determines the final allosteric output. We also reveal the potential dynamic basis for allosteric modulation using an advanced statistical technique to detect function-related conformational dynamics. Methods developed in this work can be applied to other allosteric systems.

Single-molecule visualization determines conformational substate ensembles in β-sheet-rich peptide fibrils

An understanding of protein conformational ensembles is essential for revealing the underlying mechanisms of interpeptide recognition and association. However, experimentally resolving multiple simultaneously existing conformational substates remains challenging. Here, we report the use of scanning tunneling microscopy (STM) to analyze the conformational substate ensembles of β sheet peptides with a submolecular resolution (in-plane <2.6 Å). We observed ensembles of more than 10 conformational substates (with free energy fluctuations between several k_BTs) in peptide homoassemblies of keratin (KRT) and amyloidal peptides (-5Aβ42 and TDP-43 341-357). Furthermore, STM reveals a change in the conformational ensemble of peptide mutants, which is correlated with the macroscopic properties of peptide assemblies. Our results demonstrate that the STM-based single-molecule imaging can capture a thorough picture of the conformational substates with which to build an energetic landscape of interconformational interactions and can rapidly screen conformational ensembles, which can complement conventional characterization techniques.

The Importance of Charge Transfer and Solvent Screening in the Interactions of Backbones and Functional Groups in Amino Acid Residues and Nucleotides

Quantum mechanical (QM) calculations at the level of density-functional tight-binding are applied to a protein–DNA complex (PDB: 2o8b) consisting of 3763 atoms, averaging 100 snapshots from molecular dynamics simulations. A detailed comparison of QM and force field (Amber) results is presented. It is shown that, when solvent screening is taken into account, the contributions of the backbones are small, and the binding of nucleotides in the double helix is governed by the base–base interactions. On the other hand, the backbones can make a substantial contribution to the binding of amino acid residues to nucleotides and other residues. The effect of charge transfer on the interactions is also analyzed, revealing that the actual charge of nucleotides and amino acid residues can differ by as much as 6 and 8% from the formal integer charge, respectively. The effect of interactions on topological models (protein -residue networks) is elucidated.

Kinetic solvent viscosity effects uncover an internal isomerization of the enzyme-substrate complex in Pseudomonas aeruginosa PAO1 NADH:Quinone oxidoreductase

NAD(P)H:quinone oxidoreductases (NQOs) play an essential protective role as antioxidants in the detoxification of quinones in both Prokaryotes and Eukaryotes. NQO from Pseudomonas aeruginosa PAO1 uses FMN to catalyze the two-electron reduction of various quinones with NADH. In this study, steady-state kinetics, kinetic solvent viscosity effects, and rapid reaction kinetics were used to determine which kinetic steps control the overall turnover of the enzyme with benzoquinone or juglone. The rate constant for flavin reduction (k_red) at pH 6.0 was 12.9 ± 0.3 s^-1, and the K_d for NADH was at least an order of magnitude lower than 90 μM. With benzoquinone, the k_cat value was 11.7 ± 0.3 s^-1, consistent with flavin reduction being almost entirely rate-limiting for overall turnover. With juglone, a k_cat value of 10.0 ± 0.5 s^-1 was recorded. The normalized plot of the relative solvent viscosity effects on the k_cat values established that hydride transfer from NADH to the FMN and quinol product release, with a calculated rate constant (k_P-rel) of 52 s^-1, are partially rate-limiting for the overall turnover of NQO. Kinetic solvent viscosity effects with glucose or sucrose revealed a hyperbolic dependence on the k_cat and k_cat/K_m values with benzoquinone or juglone, respectively, consistent with the presence of a solvent-sensitive internal isomerization of the enzyme-substrate complex (ES). The data demonstrate opposing effects of benzoquinone and juglone on the equilibrium of the NQO ES isomerization with glucose or sucrose. Thus, our study demonstrates how quinol substrate properties alter the equilibrium of NQO ES isomerization.