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

Modeling pH-Dependent Biomolecular Photochemistry

The tuning mechanism of pH can be extremely challenging to model computationally in complex biological systems, especially with respect to the photochemical properties. This article reports a protocol aimed at modeling pH-dependent photodynamics using a combination of constant-pH molecular dynamics and semiclassical nonadiabatic molecular dynamics simulations. With retinal photoisomerization in Anabaena sensory rhodopsin (ASR) as a testbed, we show that our protocol produces pH-dependent photochemical properties, such as the isomerization quantum yield or decay rates. We decompose our results into single-titrated residue contributions, identifying some key tuning amino acids. Additionally, we assess the validity of the single protonation state picture to represent the system at a given pH and propose the most populated protein charge state as a compromise between cost and accuracy.

Different pKa Shifts of Internal GLU8 in Human β-Endorphin Amyloid Revealing a Coupling of Internal Ionization and Stepwise Fibril Disassembly

As a functional amyloid, human β-endorphin amyloid fibril features a β-solenoid conformation and store peptide hormones within acidic secretory granules, which would be released into the blood through fibril disassembly when the cellular milieu pH increases from acidic to neutral level on exocytosis. To gain detailed atomic mechanism of β-endorphin amyloid fibrils' pH-responsive disassembly, we conduct constant pH molecular dynamics simulations to investigate the structural and dynamical properties of β-endorphin amyloid fibrils in experiencing the environmental pH changes. Our results demonstrate a clear pK_a shift of the internal ionizable residue of GLU8, and this shift becomes even more pronounced when it is buried more deeply in the amyloid fibrils. The unusual pK_a of GLU8 reveals that its protonation state changes from the protonated state in the acidic secretory granule to the deprotonated state in the neutral pH conditions in the blood, where the deprotonation of GLU8 leads to unfavorable interactions within the hydrophobic core of the amyloid and subsequent fibril disassembly. The different pK_a shifts of GLU8 relative to its positions in the amyloid fibril indicate that the β-endorphin amyloid fibril disassembly is a stepwise process, accounting for the experimental observation that the disassembly always initiates from the outermost layer. This study reveals the critical role of the protonation state of GLU8 in amyloid fibrils' pH-responsive disassembly, and provides clear insights for understanding the structural transitions of amyloids in hormone secretion. This study also provides theoretical basis for designing pH-sensitive biological tools for specific use with precise positioning of ionizable residues into the hydrophobic interior of proteins.

Ionization of D571 Is Coupled with SARS-CoV-2 Spike Up/Down Equilibrium Revealing the pH-Dependent Allosteric Mechanism of Receptor-Binding Domains

As a type I viral fusion protein, SARS-CoV-2 spike undergoes a pH-dependent switch to mediate the endosomal positioning of the receptor-binding domain to facilitate viral entry into cells and immune evasion. Gaps in our knowledge concerning the conformational transitions and key intramolecular motivations have hampered the development of effective therapeutics against the virus. To clarify the pH-sensitive elements on spike-gating the receptor-binding domain (RBD) opening and understand the details of the RBD opening transition, we performed microsecond-time scale constant pH molecular dynamics simulations in this study. We identified the deeply buried D571 with a clear pKa shift, suggesting a potential pH sensor, and showed the coupling of ionization of D571 with spike RBD-up/down equilibrium. We also computed the free-energy landscape for RBD opening and identified the crucial interactions that influence RBD dynamics. The atomic-level characterization of the pH-dependent spike activation mechanism provided herein offers new insights for a better understanding of the fundamental mechanisms of SARS-CoV-2 viral entry and infection and hence supports the discovery of novel therapeutics for COVID-19.

Protein pKa Prediction by Tree-Based Machine Learning

Protonation states of ionizable protein residues modulate many essential biological processes. For correct modeling and understanding of these processes, it is crucial to accurately determine their pKa values. Here, we present four tree-based machine learning models for protein pKa prediction. The four models, Random Forest, Extra Trees, eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), were trained on three experimental PDB and pKa datasets, two of which included a notable portion of internal residues. We observed similar performance among the four machine learning algorithms. The best model trained on the largest dataset performs 37% better than the widely used empirical pKa prediction tool PROPKA and 15% better than the published result from the pKa prediction method DelPhiPKa. The overall root-mean-square error (RMSE) for this model is 0.69, with surface and buried RMSE values being 0.56 and 0.78, respectively, considering six residue types (Asp, Glu, His, Lys, Cys, and Tyr), and 0.63 when considering Asp, Glu, His, and Lys only. We provide pKa predictions for proteins in human proteome from the AlphaFold Protein Structure Database and observed that 1% of Asp/Glu/Lys residues have highly shifted pKa values close to the physiological pH.

Determinants of conductance of a bacterial voltage-gated sodium channel

Through molecular dynamics (MD) and free energy simulations in electric fields, we examine the factors influencing conductance of bacterial voltage-gated sodium channel Na_vMs. The channel utilizes four glutamic acid residues in the selectivity filter (SF). Previously, we have shown, through constant pH and free energy calculations of pKa values, that fully deprotonated, singly protonated, and doubly protonated states are all feasible at physiological pH, depending on how many ions are bound in the SF. With 173 MD simulations of 450 or 500 ns and additional free energy simulations, we determine that the conductance is highest for the deprotonated state and decreases with each additional proton bound. We also determine that the pKa value of the four glutamic residues for the transition between deprotonated and singly protonated states is close to the physiological pH and that there is a small voltage dependence. The pKa value and conductance trends are in agreement with experimental work on bacterial Na_v channels, which show a decrease in maximal conductance with lowering of pH, with pKa in the physiological range. We examine binding sites for Na⁺ in the SF, compare with previous work, and note a dependence on starting structures. We find that narrowing of the gate backbone to values lower than the crystal structure's backbone radius reduces the conductance, whereas increasing the gate radius further does not affect the conductance. Simulations with some amount of negatively charged lipids as opposed to purely neutral lipids increases the conductance, as do simulations at higher voltages.

Mapping the Ligand Binding Landscape

The interaction between a ligand and a protein involves a multitude of conformational states. To achieve a particular deeply bound pose, the ligand must search across a rough free-energy landscape with many metastable minima. Creating maps of the ligand binding landscape is a great challenge, as binding and release events typically occur on timescales that are beyond the reach of molecular simulation. The WExplore enhanced sampling method is well suited to build these maps because it is designed to broadly explore free-energy landscapes and is capable of simulating ligand release pathways that occur on timescales as long as minutes. WExplore also uses only unbiased trajectory segments, allowing for the construction of Markov state models (MSMs) and conformation space networks that combine the results of multiple simulations. Here, we use WExplore to study two bromodomain-inhibitor systems using multiple docked starting poses (Brd4-MS436 and Baz2B-ICR7) and synthesize our results using a series of MSMs using time-lagged independent component analysis. Ranking the starting poses by exit rate agrees with the crystal structure pose in both cases. We also predict the most stable pose using the equilibrium populations from the MSM but find that the prediction is not robust as a function of MSM parameters. The simulated trajectories are synthesized into network models that visualize the entire binding landscape for each system, and we examine transition paths between deeply bound stable states. We find that, on average, transitions between deeply bound states convert through the unbound state 81% of the time, implying a trial-and-error approach to ligand binding. We conclude with a discussion of the implications of this result for both kinetics-based drug discovery and virtual screening pipelines that incorporate molecular dynamics.

Reservoir pH replica exchange

We present the reservoir pH replica exchange (R-pH-REM) method for constant pH simulations. The R-pH-REM method consists of a two-step procedure; the first step involves generation of one or more reservoirs of conformations. Each reservoir is obtained from a standard or enhanced molecular dynamics simulation with a constrained (fixed) protonation state. In the second step, fixed charge constraints are relaxed, as the structures from one or more reservoirs are periodically injected into a constant pH or a pH-replica exchange (pH-REM) simulation. The benefit of this two-step process is that the computationally intensive part of conformational search can be decoupled from constant pH simulations, and various techniques for enhanced conformational sampling can be applied without the need to integrate such techniques into the pH-REM framework. Simulations on blocked Lys, KK, and KAAE peptides were used to demonstrate an agreement between pH-REM and R-pH-REM simulations. While the reservoir simulations are not needed for these small test systems, the real need arises in cases when ionizable molecules can sample two or more conformations separated by a large energy barrier, such that adequate sampling is not achieved on a time scale of standard constant pH simulations. Such problems might be encountered in protein systems that exploit conformational transitions for function. A hypothetical case is studied, a small molecule with a large torsional barrier; while results of pH-REM simulations depend on the starting structure, R-pH-REM calculations on this model system are in excellent agreement with a theoretical model.

A Coupled Ionization-Conformational Equilibrium Is Required To Understand the Properties of Ionizable Residues in the Hydrophobic Interior of Staphylococcal Nuclease

Ionizable residues in the interior of proteins play essential roles, especially in biological energy transduction, but are relatively rare and seem incompatible with the complex and polar environment. We perform a comprehensive study of the internal ionizable residues on 21 variants of staphylococcal nuclease with internal Lys, Glu, or Asp residues. Using pH replica exchange molecular dynamics simulations, we find that, in most cases, the pK_a values of these internal ionizable residues are shifted significantly from their values in solution. Our calculated results are in excellent agreement with the experimental observations of the Garcia-Moreno group. We show that the interpretation of the experimental pK_a values requires the study of not only protonation changes but also conformational changes. The coupling between the protonation and conformational equilibria suggests a mechanism for efficient pH-sensing and regulation in proteins. This study provides new physical insights into how internal ionizable residues behave in the hydrophobic interior of proteins.

Multiple Ligand Unbinding Pathways and Ligand-Induced Destabilization Revealed by WExplore

We report simulations of full ligand exit pathways for the trypsin-benzamidine system, generated using the sampling technique WExplore. WExplore is able to observe millisecond-scale unbinding events using many nanosecond-scale trajectories that are run without introducing biasing forces. The algorithm generates rare events by dividing the coordinate space into regions, on-the-fly, and balancing computational effort between regions through cloning and merging steps, as in the weighted ensemble method. The averaged exit flux yields a ligand exit rate of 180 μs, which is within an order of magnitude of the experimental value. We obtain broad sampling of ligand exit pathways, and visualize our findings using conformation space networks. The analysis shows three distinct exit channels, two of which are formed through large, rare motions of the loop regions in trypsin. This broad set of ligand-bound poses is then used to investigate general properties of ligand binding: we observe both a direct stabilizing effect of ligand-protein interactions and an indirect destabilizing effect on intraprotein interactions that is induced by the ligand. Significantly, the crystallographic binding poses are distinguished not only because their ligands induce large stabilizing effects, but also because they induce relatively low indirect destabilizations.

Proton-coupled charge-transfer reactions and photoacidity of N,N-dimethyl-3-arylpropan-1-ammonium chloride salts

Excited-state, intermolecular proton-transfers of aromatics tethered to ammonium groups are solvent mediated and coupled to either the formation of an exciplex or a solvent-separated ion pair.

Characterizing the Structures, Spectra, and Energy Landscapes Involved in the Excited-State Proton Transfer Process of Red Fluorescent Protein LSSmKate1

By applying molecular dynamics (MD) simulations and quantum chemical calculations, we have characterized the states and processes involved in the excited-state proton transfer (ESPT) of LSSmKate1. MD simulations identify two stable structures in the electronic ground state of LSSmKate1, one with a protonated chromophore and the other with a deprotonated chromophore, thus leading to two separate low-energy absorption maxima with a large energy spacing, as observed in the calculated and experimentally measured absorption spectra. Proton transfer is induced by electronic excitation. When LSSmKate1 is excited, the electrons in the chromophore are transferred from the phenol ring to the N-acylimine moiety; the acidity of a phenolic hydroxyl group is thus enhanced. The calculated potential energy curves (PECs) exhibit energetic feasibility in the generation of the fluorescent species in LSSmKate1, and the exact agreement between the calculated and experimentally measured values of the large Stokes shift further provides solid theoretical evidence for the ESPT process taking place in photoexcited LSSmKate1. The molecular environments play a significant role in the geometries and absorption/emission energies of the chromophores. Overall, TD-ωB97X-D/molecular mechanics (MM) provides a better description of the optical properties of LSSmKate1 than TD-B3LYP/MM, although it always overestimates the excitation energies.

PCl3-mediated synthesis of green/cyan fluorescent protein chromophores using amino acids

An efficient synthesis of green and cyan fluorescent protein chromophores from l-tyrosine and l-tryptophan using PCl₃ has been successfully developed.

Stable DNA Nanomachine Based on Duplex-Triplex Transition for Ratiometric Imaging Instantaneous pH Changes in Living Cells

DNA nanomachines are becoming useful tools for molecular recognition, imaging, and diagnostics and have drawn gradual attention. Unfortunately, the present application of most DNA nanomachines is limited in vitro, so expanding their application in organism has become a primary focus. Hence, a novel DNA nanomachine named t-switch, based on the DNA duplex-triplex transition, is developed for monitoring the intracellular pH gradient. Our strategy is based on the DNA triplex structure containing C(+)-G-C triplets and pH-dependent Förster resonance energy transfer (FRET). Our results indicate that the t-switch is an efficient reporter of pH from pH 5.3 to 6.0 with a fast response of a few seconds. Also the uptake of the t-switch is speedy. In order to protect the t-switch from enzymatic degradation, PEI is used for modification of our DNA nanomachine. At the same time, the dynamic range could be extended to pH 4.6-7.8. The successful application of this pH-depended DNA nanomachine and motoring spatiotemporal pH changes associated with endocytosis is strong evidence of the possibility of self-assembly DNA nanomachine for imaging, targeted therapies, and controllable drug delivery.