Garrett B. Goh

Characterizing the Protonation State of Cytosine in Transient G•C Hoogsteen Base Pairs in Duplex DNA

G·C Hoogsteen base pairs can form transiently in duplex DNA and play important roles in DNA recognition, replication, and repair. G·C Hoogsteen base pairs are thought to be stabilized by protonation of cytosine N3, which affords a second key hydrogen bond, but experimental evidence for this is sparse because the proton cannot be directly visualized by X-ray crystallography and nuclear magnetic resonance spectroscopy. Here, we combine NMR and constant pH molecular dynamics simulations to directly investigate the pKa of cytosine N3 in a chemically trapped N1-methyl-G·C Hoogsteen base pair within duplex DNA. Analysis of NMR chemical shift perturbations and NOESY data as a function of pH revealed that cytosine deprotonation is coupled to a syn-to-anti transition in N1-methyl-G, which results in a distorted Watson-Crick geometry at pH >9. A four-state analysis of the pH titration profiles yields a lower bound pKa estimate of 7.2 ± 0.1 for the G·C Hoogsteen base pair, which is in good agreement with the pKa value (7.1 ± 0.1) calculated independently using constant pH MD simulations. Based on these results and pH-dependent NMR relaxation dispersion measurements, we estimate that under physiological pH (pH 7-8), G·C Hoogsteen base pairs in naked DNA have a population of 0.02-0.002%, as compared to 0.4% for A·T Hoogsteen base pairs, and likely exist primarily as protonated species.

Constant pH molecular dynamics of proteins in explicit solvent with proton tautomerism

pH is a ubiquitous regulator of biological activity, including protein‐folding, protein‐protein interactions, and enzymatic activity. Existing constant pH molecular dynamics (CPHMD) models that were developed to address questions related to the pH‐dependent properties of proteins are largely based on implicit solvent models. However, implicit solvent models are known to underestimate the desolvation energy of buried charged residues, increasing the error associated with predictions that involve internal ionizable residue that are important in processes like hydrogen transport and electron transfer. Furthermore, discrete water and ions cannot be modeled in implicit solvent, which are important in systems like membrane proteins and ion channels. We report on an explicit solvent constant pH molecular dynamics framework based on multi‐site λ‐dynamics (CPHMDMSλD). In the CPHMDMSλD framework, we performed seamless alchemical transitions between protonation and tautomeric states using multi‐site λ‐dynamics, and designed novel biasing potentials to ensure that the physical end‐states are predominantly sampled. We show that explicit solvent CPHMDMSλD simulations model realistic pH‐dependent properties of proteins such as the Hen‐Egg White Lysozyme (HEWL), binding domain of 2‐oxoglutarate dehydrogenase (BBL) and N‐terminal domain of ribosomal protein L9 (NTL9), and the pKa predictions are in excellent agreement with experimental values, with a RMSE ranging from 0.72 to 0.84 pKa units. With the recent development of the explicit solvent CPHMDMSλD framework for nucleic acids, accurate modeling of pH‐dependent properties of both major class of biomolecules—proteins and nucleic acids is now possible. Proteins 2014; 82:1319–1331.

Uncovering pH-dependent transient states of proteins with buried ionizable residues.

The role of pH in regulating biological activity is ubiquitous, and understanding pH-mediated activity has traditionally relied on analyzing static biomolecular structures of highly populated ground states solved near physiological pH. However, recent advances have shown the increasing importance of transiently populated states, the characterization of which is extremely challenging but made plausible with the development of techniques such as relaxation dispersion NMR spectroscopy. To unlock the pH dependence of these transient states with atomistic-level details, we applied the recently developed explicit solvent constant pH molecular dynamics (CPHMDMSλD) framework to a series of staphylococcal nuclease (SNase) mutants with buried ionizable residues and probed their dynamics in different pH environments. Among our key findings is the existence of open states in all SNase mutants containing “buried” residues with highly shifted pKa’s, where local solvation around the protonation site was observed. The calculated pKa demonstrated good agreement with experimental pKa’s, with a low average unsigned error of 1.3 pKa units and correlation coefficient R2 = 0.78. Sampling both open and closed states in their respective pH range, where they are expected to be dominant, was necessary to reproduce experimental pKa’s, and in the most extreme examples of pKa shifts measured, it can be interpreted that the open-state structures are transient at physiological pH, contributing a small population of 1–2%. This suggests that buried ionizable residues can trigger conformational fluctuations that may be observed as transient-state structures at physiological pH. Furthermore, the coupled relationship of both open and closed states and their role in recapitulating macroscopic experimental observables suggest that structural analysis of buried residues may benefit from looking at structural pairs, as opposed to the conventional approach of looking at a single static ground-state conformation.

pH-dependent transient conformational states control optical properties in cyan fluorescent protein.

A recently engineered mutant of cyan fluorescent protein (WasCFP) that exhibits pH-dependent absorption suggests that its tryptophan-based chromophore switches between neutral (protonated) and charged (deprotonated) states depending on external pH. At pH 8.1, the latter gives rise to green fluorescence as opposed to the cyan color of emission that is characteristic for the neutral form at low pH. Given the high energy cost of deprotonating the tryptophan at the indole nitrogen, this behavior is puzzling, even if the stabilizing effect of the V61K mutation in proximity to the protonation/deprotonation site is considered. Because of its potential to open new avenues for the development of optical sensors and photoconvertible fluorescent proteins, a mechanistic understanding of how the charged state in WasCFP can possibly be stabilized is thus important. Attributed to the dynamic nature of proteins, such understanding often requires knowledge of the various conformations adopted, including transiently populated conformational states. Transient conformational states triggered by pH are of emerging interest and have been shown to be important whenever ionizable groups interact with hydrophobic environments. Using a combination of the weighted-ensemble sampling method and explicit-solvent constant pH molecular dynamics (CPHMD(MSλD)) simulations, we have identified a solvated transient state, characterized by a partially open β-barrel where the chromophore pKa of 6.8 is shifted by over 20 units from that of the closed form (6.8 and 31.7, respectively). This state contributes a small population at low pH (12% at pH 6.1) but becomes dominant at mildly basic conditions, contributing as much as 53% at pH 8.1. This pH-dependent population shift between neutral (at pH 6.1) and charged (at pH 8.1) forms is thus responsible for the observed absorption behavior of WasCFP. Our findings demonstrate the conditions necessary to stabilize the charged state of the WasCFP chromophore (namely, local solvation at the deprotonation site and a partial flexibility of the protein β-barrel structure) and provide the first evidence that transient conformational states can control optical properties of fluorescent proteins.

Accurate modeling of ionic surfactants at high concentration.

Molecular dynamics (MD) simulation is a useful tool for simulating formulations of surfactant mixtures from first-principles, which can be used to predict surfactant morphology and other industrially relevant thermodynamic properties. However, the surfactant structure is sensitive to the parameters used in MD simulations, and in the absence of extensive validation against experimental data, it is often not obvious a priori which range of parameter sets to choose. In this work, we compare the performance of ion parameters implemented in nonpolarizable classical MD simulations, and its effect on simulations of an idealized solution of sodium dodecyl sulfate (SDS). We find that previous artifacts reported in simulations of larger SDS constructs are a direct consequence of using parameters that poorly model ionic interactions at high concentration. Using osmotic pressure and/or other thermodynamic properties measured at finite concentration, such as Kirkwood-Buff integrals, is shown to be the most cost-effective means to validate and parametrize existing force fields. Our findings highlight the importance of optimizing intermolecular parameters for simulations of systems with a high local concentration, which may be applicable in other contexts, such as in molecular crowding, hotspot mapping, protein folding, and modeling pH effects.

Predicting Binding Free Energies in a Large Combinatorial Chemical Space Using Multisite λ Dynamics

In this study, we demonstrate the extensive scalability of the biasing potential replica exchange multisite λ dynamics (BP-REX MSλD) free energy method by calculating binding affinities for 512 inhibitors to HIV Reverse Transcriptase (HIV-RT). This is the largest exploration of chemical space using free energy methods known to date, requires only a few simulations, and identifies 55 new inhibitor designs against HIV-RT predicted to be at least as potent as a tight binding reference compound (i.e., as potent as 56 nM). We highlight that BP-REX MSλD requires an order of magnitude less computational resources than conventional free energy methods while maintaining a similar level of precision, overcomes the inherent poor scalability of conventional free energy methods, and enables the exploration of combinatorially large chemical spaces in the context of in silico drug discovery.