Optimizing Electrostatic Field Calculations with the Adaptive Poisson–Boltzmann Solver to Predict Electric Fields at Protein–Protein Interfaces. I. Sampling and Focusing

Probing the Electrostatic Effects of H-Ras Tyrosine 32 Mutations on Intrinsic GTP Hydrolysis Using Vibrational Stark Effect Spectroscopy of a Thiocyanate Probe

The wildtype H-Ras protein functions as a molecular switch in a variety of cell signaling pathways, and mutations to key residues result in a constitutively active oncoprotein. However, there is some debate regarding the mechanism of the intrinsic GTPase activity of H-Ras. It has been hypothesized that ordered water molecules are coordinated at the active site by Q61, a highly transforming amino acid site, and Y32, a position that has not previously been investigated. Here, we examine the electrostatic contribution of the Y32 position to GTP hydrolysis by comparing the rate of GTP hydrolysis of Y32X mutants to the vibrational energy shift of each mutation measured by a nearby thiocyanate vibrational probe to estimate changes in the electrostatic environment caused by changes at the Y32 position. We further compared vibrational energy shifts for each mutation to the hydration potential of the respective side chain and demonstrated that Y32 is less critical for recruiting water molecules into the active site to promote hydrolysis than Q61. Our results show a clear interplay between a steric contribution from Y32 and an electrostatic contribution from Q61 that are both critical for intrinsic GTP hydrolysis.

Electrostatic Impact of Brefeldin A on Thiocyanate Probes Surrounding the Interface of Arf1-BFA-ARNO4M, a Protein-Drug-Protein Complex

Protein-protein interactions regulate many cellular processes, making them ideal drug candidates. Design of such drugs, however, is hindered by a lack of understanding of the factors that contribute to the interaction specificity. Specific protein-protein complexes possess both structural and electrostatic complementarity, and while structural complementarity of protein complexes has been extensively investigated, fundamental understanding of the complicated networks of electrostatic interactions at these interfaces is lacking, thus hindering the rational design of orthosterically binding small molecules. To better understand the electrostatic interactions at protein interfaces and how a small molecule could contribute to and fit within that environment, we used a model protein-drug-protein system, Arf1-BFA-ARNO4M, to investigate how small molecule brefeldin A (BFA) perturbs the Arf1-ARNO4M interface. By using nitrile probe labeled Arf1 sites and measuring vibrational Stark effects as well as temperature dependent infrared shifts, we measured changes in the electric field and hydrogen bonding at this interface upon BFA binding. At all five probe locations of Arf1, we found that the vibrational shifts resulting from BFA binding corroborate trends found in Poisson-Boltzmann calculations of surface potentials of Arf1-ARNO4M and Arf1-BFA-ARNO4M, where BFA contributes negative electrostatic potential to the protein interface. The data also corroborate previous hypotheses about the mechanism of interfacial binding and confirm that alternating patches of hydrophobic and polar interactions lead to BFA binding specificity. These findings demonstrate the impact of BFA on this protein-protein interface and have implications for the design of other interfacial drug candidates.

Vibrational Lifetime of the SCN Protein Label in H2O and D2O Reports Site-Specific Solvation and Structure Changes During PYP's Photocycle

The application of vibrational labels such as thiocyanate  (-S-C≡N) for studying protein structure and dynamics is thriving. Absorption spectroscopy is usually employed to obtain wavenumber and line shape of the label. An observable of great significance might be the vibrational lifetime, which can be obtained by pump probe or 2D-IR spectroscopy. Due to the insulating effect of the heavy sulfur atom in the case of the SCN label, the lifetime of the C≡N oscillator is expected to be particularly sensitive to its surrounding as it is not dominated by through-bond relaxation. We therefore investigate the vibrational lifetime of the SCN label at various positions in the blue light sensor protein Photoactive Yellow Protein (PYP) in the ground state and signaling state of the photoreceptor. We find that the vibrational lifetime of the C≡N stretching mode is strongly affected both by its protein environment and by the degree of exposure to the solvent. Even for label positions where the line shape and wavenumber observed by FTIR are barely changing upon activation of the photoreceptor, we find that the lifetime can change considerably. To obtain an unambiguous measure for the solvent exposure of the labeled site, we show that it is imperative to compare the lifetimes in H₂O and D₂O. Importantly, the lifetimes shorten in H₂O as compared to D₂O for water exposed labels, while they stay largely the same for buried labels. We quantify this effect by defining a solvent exclusion coefficient (SEC). The response of the label's vibrational lifetime to its solvent exposure renders it a suitable universal probe for protein investigations. This applies even to systems that are otherwise hard to address, such as transient or short-lived states, which could be created during a protein's working cycle (as here in PYP) or during protein folding. It is also applicable to flexible systems (intrinsically disordered proteins), protein-protein and protein-membrane interactions.

Combining the polarizable Drude force field with a continuum electrostatic Poisson-Boltzmann implicit solvation model

In this work, we have combined the polarizable force field based on the classical Drude oscillator with a continuum Poisson-Boltzmann/solvent-accessible surface area (PB/SASA) model. In practice, the positions of the Drude particles experiencing the solvent reaction field arising from the fixed charges and induced polarization of the solute must be optimized in a self-consistent manner. Here, we parameterized the model to reproduce experimental solvation free energies of a set of small molecules. The model reproduces well-experimental solvation free energies of 70 molecules, yielding a root mean square difference of 0.8 kcal/mol versus 2.5 kcal/mol for the CHARMM36 additive force field. The polarization work associated with the solute transfer from the gas-phase to the polar solvent, a term neglected in the framework of additive force fields, was found to make a large contribution to the total solvation free energy, comparable to the polar solute-solvent solvation contribution. The Drude PB/SASA also reproduces well the electronic polarization from the explicit solvent simulations of a small protein, BPTI. Model validation was based on comparisons with the experimental relative binding free energies of 371 single alanine mutations. With the Drude PB/SASA model the root mean square deviation between the predicted and experimental relative binding free energies is 3.35 kcal/mol, lower than 5.11 kcal/mol computed with the CHARMM36 additive force field. Overall, the results indicate that the main limitation of the Drude PB/SASA model is the inability of the SASA term to accurately capture non-polar solvation effects. © 2018 Wiley Periodicals, Inc.

Heparin Binds Lamprey Angiotensinogen and Promotes Thrombin Inhibition through a Template Mechanism

Lamprey angiotensinogen (l-ANT) is a hormone carrier in the regulation of blood pressure, but it is also a heparin-dependent thrombin inhibitor in lamprey blood coagulation system. The detailed mechanisms on how angiotensin is carried by l-ANT and how heparin binds l-ANT and mediates thrombin inhibition are unclear. Here we have solved the crystal structure of cleaved l-ANT at 2.7 Å resolution and characterized its properties in heparin binding and protease inhibition. The structure reveals that l-ANT has a conserved serpin fold with a labile N-terminal angiotensin peptide and undergoes a typical stressed-to-relaxed conformational change when the reactive center loop is cleaved. Heparin binds l-ANT tightly with a dissociation constant of ∼10 nm involving ∼8 monosaccharides and ∼6 ionic interactions. The heparin binding site is located in an extensive positively charged surface area around helix D involving residues Lys-148, Lys-151, Arg-155, and Arg-380. Although l-ANT by itself is a poor thrombin inhibitor with a second order rate constant of 500 m^-1 s^-1, its interaction with thrombin is accelerated 90-fold by high molecular weight heparin following a bell-shaped dose-dependent curve. Short heparin chains of 6-20 monosaccharide units are insufficient to promote thrombin inhibition. Furthermore, an l-ANT mutant with the P1 Ile mutated to Arg inhibits thrombin nearly 1500-fold faster than the wild type, which is further accelerated by high molecular weight heparin. Taken together, these results suggest that heparin binds l-ANT at a conserved heparin binding site around helix D and promotes the interaction between l-ANT and thrombin through a template mechanism conserved in vertebrates.

Vibrational solvatochromism of nitrile infrared probes: beyond the vibrational Stark dipole approach

Systematic probing of local environments around biopolymers is important for understanding their functions.

Understanding and Manipulating Electrostatic Fields at the Protein-Protein Interface Using Vibrational Spectroscopy and Continuum Electrostatics Calculations

Biological function emerges in large part from the interactions of biomacromolecules in the complex and dynamic environment of the living cell. For this reason, macromolecular interactions in biological systems are now a major focus of interest throughout the biochemical and biophysical communities. The affinity and specificity of macromolecular interactions are the result of both structural and electrostatic factors. Significant advances have been made in characterizing structural features of stable protein-protein interfaces through the techniques of modern structural biology, but much less is understood about how electrostatic factors promote and stabilize specific functional macromolecular interactions over all possible choices presented to a given molecule in a crowded environment. In this Feature Article, we describe how vibrational Stark effect (VSE) spectroscopy is being applied to measure electrostatic fields at protein-protein interfaces, focusing on measurements of guanosine triphosphate (GTP)-binding proteins of the Ras superfamily binding with structurally related but functionally distinct downstream effector proteins. In VSE spectroscopy, spectral shifts of a probe oscillator's energy are related directly to that probe's local electrostatic environment. By performing this experiment repeatedly throughout a protein-protein interface, an experimental map of measured electrostatic fields generated at that interface is determined. These data can be used to rationalize selective binding of similarly structured proteins in both in vitro and in vivo environments. Furthermore, these data can be used to compare to computational predictions of electrostatic fields to explore the level of simulation detail that is necessary to accurately predict our experimental findings.

On the possible role of protein vibrations in information processing in the brain: three Russian dolls

Until recently it was held that the neurocomputations conducted by the brain involved only whole neurons as the operating units. This may however represent only a part of the mechanism. This theoretical and academic position article reviews the considerable evidence that allosteric interactions between proteins (as extensively described by Fuxe et al., 2014), and in particular protein vibrations in neurons, form small scale codes that are involved as parts of the complex information processing systems of the brain. The argument is then developed to suggest that the protein allosteric and vibration codes (that operate at the molecular level) are nested within a medium scale coding system whose computational units are organelles (such as microtubules). This medium scale code is nested in turn inside a large scale coding system, whose computational units are individual neurons. The hypothesis suggests that these three levels interact vertically in both directions thus materially increasing the computational capacity of the brain. The whole hierarchy is thus similar to three nested Russian dolls. This theoretical development may be of use in the design of experiments to test it.