Interpretation of pH-activity profiles for acid-base catalysis from molecular simulations

An active site mutation induces oxygen reactivity in D-arginine dehydrogenase: A case of superoxide diverting protons

Enzymes are potent catalysts that increase biochemical reaction rates by several orders of magnitude. Flavoproteins are a class of enzymes whose classification relies on their ability to react with molecular oxygen (O2) during catalysis using ionizable active site residues. Pseudomonas aeruginosa D-arginine dehydrogenase (PaDADH) is a flavoprotein that oxidizes D-arginine for P. aeruginosa survival and biofilm formation. The crystal structure of PaDADH reveals the interaction of the glutamate 246 (E246) side chain with the substrate and at least three other active site residues, establishing a hydrogen bond network in the active site. Additionally, E246 likely ionizes to facilitate substrate binding during PaDADH catalysis. This study aimed to investigate how replacing the E246 residue with leucine affects PaDADH catalysis and its ability to react with O2 using steady-state kinetics coupled with pH profile studies. The data reveal a gain of O2 reactivity in the E246L variant, resulting in a reduced flavin semiquinone species and superoxide (O2•-) during substrate oxidation. The O2•- reacts with active site protons, resulting in an observed nonstoichiometric slope of 1.5 in the enzyme's log (kcat/Km) pH profile with D-arginine. Adding superoxide dismutase results in an observed correction of the slope to 1.0. This study demonstrates how O2•- can alter the slopes of limbs in the pH profiles of flavin-dependent enzymes and serves as a model for correcting nonstoichiometric slopes in elucidating reaction mechanisms of flavoproteins.

Investigating the Roles of Active Site Residues in Mycobacterium tuberculosis Indole-3-glycerol Phosphate Synthase, a Potential Target for Antitubercular Agents

Mycobacterium tuberculosis drug resistance is emerging and new drug targets are needed. Tryptophan biosynthesis is necessary for M. tuberculosis replication and virulence. Indole-3-glycerol phosphate synthase (IGPS) catalyzes a step in M. tuberculosis tryptophan biosynthesis and has been suggested as a potential anti-infective target, but our understanding of this enzyme is limited. To aid in inhibitor design and gain a greater mechanistic picture of this enzyme, there is a need to understand the roles of active site amino acids in ligand binding and catalysis. In this work, we explored the roles of conserved active site amino acids Glu57, Lys59, Lys119, Glu168, and Glu219. Mutation of each to Ala results in loss of all detectable activity. The Glu57Gln, Lys59Arg, Lys119Arg, Glu168Gln, and Glu219Asp mutations result in large activity losses, while Glu219Gln has enhanced activity. Analysis of the enzymatic data yields the following main conclusions: (A) Lys119 is the likely catalytic acid in the CdRP ring closure step. (B) Glu168 stabilizes a charged reaction intermediate and may also be the catalytic base. (C) Glu57, Glu219, and Lys119 form a closely arranged triad in which Glu57 and Glu219 modulate the pKa of Lys119, and thus overall activity. This increased understanding of inter- and intramolecular interactions and demonstration of the highly coordinated nature of the M. tuberculosis IGPS active site provide new mechanistic information and guidance for future work with this potential new drug target.

Catalytic mechanism and pH dependence of a methyltransferase ribozyme (MTR1) from computational enzymology

A methyltransferase ribozyme (MTR1) was selected in vitro to catalyze alkyl transfer from exogenous O6-methylguanine (O6mG) to a target adenine N1, and recently, high-resolution crystal structures have become available. We use a combination of classical molecular dynamics, ab initio quantum mechanical/molecular mechanical (QM/MM) and alchemical free energy (AFE) simulations to elucidate the atomic-level solution mechanism of MTR1. Simulations identify an active reactant state involving protonation of C10 that hydrogen bonds with O6mG:N1. The deduced mechanism involves a stepwise mechanism with two transition states corresponding to proton transfer from C10:N3 to O6mG:N1 and rate-controlling methyl transfer (19.4  kcal·mol-1 barrier). AFE simulations predict the pKa for C10 to be 6.3, close to the experimental apparent pKa of 6.2, further implicating it as a critical general acid. The intrinsic rate derived from QM/MM simulations, together with pKa calculations, enables us to predict an activity-pH profile that agrees well with experiment. The insights gained provide further support for a putative RNA world and establish new design principles for RNA-based biochemical tools.

Redesigning plant specialized metabolism with supervised machine learning using publicly available reactome data

The immense structural diversity of products and intermediates of plant specialized metabolism (specialized metabolites) makes them rich sources of therapeutic medicine, nutrients, and other useful materials. With the rapid accumulation of reactome data that can be accessible on biological and chemical databases, along with recent advances in machine learning, this review sets out to outline how supervised machine learning can be used to design new compounds and pathways by exploiting the wealth of said data. We will first examine the various sources from which reactome data can be obtained, followed by explaining the different machine learning encoding methods for reactome data. We then discuss current supervised machine learning developments that can be employed in various aspects to help redesign plant specialized metabolism.

Shifting the pH Optima of (R)-Selective Transaminases by Protein Engineering

Amine transaminases (ATAs) are powerful biocatalysts for the stereoselective synthesis of chiral amines. However, wild-type ATAs usually show pH optima at slightly alkaline values and exhibit low catalytic activity under physiological conditions. For efficient asymmetric synthesis ATAs are commonly used in combination with lactate dehydrogenase (LDH, optimal pH: 7.5) and glucose dehydrogenase (GDH, optimal pH: 7.75) to shift the equilibrium towards the synthesis of the target chiral amine and hence their pH optima should fit to each other. Based on a protein structure alignment, variants of (R)-selective transaminases were rationally designed, produced in E. coli, purified and subjected to biochemical characterization. This resulted in the discovery of the variant E49Q of the ATA from Aspergillus fumigatus, for which the pH optimum was successfully shifted from pH 8.5 to 7.5 and this variant furthermore had a two times higher specific activity than the wild-type protein at pH 7.5. A possible mechanism for this shift of the optimal pH is proposed. Asymmetric synthesis of (R)-1-phenylethylamine from acetophenone in combination with LDH and GDH confirmed that the variant E49Q shows superior performance at pH 7.5 compared to the wild-type enzyme.

Extending the Stochastic Titration CpHMD to CHARMM36m

The impact of pH on proteins is significant but often neglected in molecular dynamics simulations. Constant-pH Molecular Dynamics (CpHMD) is the state-of-the-art methodology to deal with these effects. However, it still lacks widespread adoption by the scientific community. The stochastic titration CpHMD is one of such methods that, until now, only supported the GROMOS force field family. Here, we extend this method's implementation to include the CHARMM36m force field available in the GROMACS software package. We test this new implementation with a diverse group of proteins, namely, lysozyme, Staphylococcal nuclease, and human and E. coli thioredoxins. All proteins were conformationally stable in the simulations, even at extreme pH values. The RMSE values (pK_a prediction vs experimental) obtained were very encouraging, in particular for lysozyme and human thioredoxin. We have also identified a few residues that challenged the CpHMD simulations, highlighting scenarios where the method still needs improvement independently of the force field. The CHARMM36m all-atom implementation was more computationally efficient when compared with the GROMOS 54A7, taking advantage of a shorter nonbonded interaction cutoff and a less frequent neighboring list update. The new extension will allow the study of pH effects in many systems for which this force field is particularly suited, i.e., proteins, membrane proteins, lipid bilayers, and nucleic acids.

Two-Metal-Ion Catalysis: Inhibition of DNA Polymerase Activity by a Third Divalent Metal Ion

Almost all DNA polymerases (pols) exhibit bell-shaped activity curves as a function of both pH and Mg²⁺ concentration. The pol activity is reduced when the pH deviates from the optimal value. When the pH is too low the concentration of a deprotonated general base (namely, the attacking 3′-hydroxyl of the 3′ terminal residue of the primer strand) is reduced exponentially. When the pH is too high the concentration of a protonated general acid (i.e., the leaving pyrophosphate group) is reduced. Similarly, the pol activity also decreases when the concentration of the divalent metal ions deviates from its optimal value: when it is too low, the binding of the two catalytic divalent metal ions required for the full activity is incomplete, and when it is too high a third divalent metal ion binds to pyrophosphate, keeping it in the replication complex longer and serving as a substrate for pyrophosphorylysis within the complex. Currently, there is a controversy about the role of the third metal ion which we will address in this review.

Beyond the Plateau: pL Dependence of Proton Inventories as a Tool for Studying Ribozyme and Ribonuclease Catalysis

Acid/base catalysis is an important catalytic strategy used by ribonucleases and ribozymes; however, understanding the number and identity of functional groups involved in proton transfer remains challenging. The proton inventory (PI) technique analyzes the dependence of the enzyme reaction rate on the ratio of D₂O to H₂O and can provide information about the number of exchangeable sites that produce isotope effects and their magnitude. The Gross-Butler (GB) equation is used to evaluate H/D fractionation factors from PI data typically collected under conditions (i.e., a "plateau" in the pH-rate profile) assuming minimal change in active site residue ionization. However, restricting PI analysis to these conditions is problematic for many ribonucleases, ribozymes, and their variants due to ambiguity in the roles of active site residues, the lack of a plateau within the accessible pL range, or cooperative interactions between active site functional groups undergoing ionization. Here, we extend the integration of species distributions for alternative enzyme states in noncooperative models of acid/base catalysis into the GB equation, first used by Bevilacqua and colleagues for the HDV ribozyme, to develop a general population-weighted GB equation that allows simulation and global fitting of the three-dimensional relationship of the D₂O ratio (n) versus pL versus k_n/k₀. Simulations using the GPW-GB equation of PI results for RNase A, HDVrz, and VSrz illustrate that data obtained at multiple selected pL values across the pL-rate profile can assist in the planning and interpreting of solvent isotope effect experiments to distinguish alternative mechanistic models.

pH Effects and Cooperativity among Key Titratable Residues for Escherichia coli Glycinamide Ribonucleotide Transformylase

Human glycinamide ribonucleotide transformylase (GAR Tfase) is a regulatory enzyme in the de novo purine biosynthesis pathway that has been extensively studied as an anticancer target. To some extent, inhibition of GAR Tfase selectively targets cancer cells over normal cells and inhibits purine formation and DNA replication. In this study, we investigated E. coli GAR Tfase, which shares high sequence similarity with the human GAR Tfase, and most functional residues are conserved. Herein, we aim to predict the pH-activity curve through a computational approach. We carried out pH-replica exchange molecular dynamics (pH-REMD) simulations to investigate pH-dependent functions such as structural changes, ligand binding, and catalytic activity. To compute the pH-activity curve, we identified the catalytic residues in specific protonation states, referred to as the catalytic competent protonation states (CCPS), which maintain the structure, keep ligands bound, and facilitate catalysis. Our computed population of CCPS with respect to pH matches well with the experimental pH-activity curve. To compute the microscopic pK_a values in the catalytically active conformation, we devised a thermodynamic model that considers the coupling between protonation states of CCPS residues and conformational states. These results allow us to correctly identify the general acid and base catalysts and interpret the pH-activity curve at an atomistic level.

Scalable molecular dynamics on CPU and GPU architectures with NAMD

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

pH-Dependent Nitrotyrosine Formation in Ribonuclease A is Enhanced in the Presence of Polyethylene Glycol (PEG)

Protein nitration can occur as a result of peroxynitrite-mediated oxidative stress. Excess production of peroxynitrite (PN) within the cellular medium can cause oxidative damage to biomolecules. The in vitro nitration of Ribonuclease A (RNase A) results in nitrotyrosine (NT) formation with a strong dependence on the pH of the medium. In order to mimic the cellular environment in this study, PN-mediated RNase A nitration has been carried out in a crowded medium. The degree of nitration is higher at pH 7.4 (physiological pH) compared to pH 6.0 (tumor cell pH). The extent of nitration increases significantly when PN is added to RNase A in the presence of crowding agents PEG 400 and PEG 6000. PEG has been found to stabilize PN over a prolonged period, thereby increasing the degree of nitration. NT formation in RNase A also results in a significant loss in enzymatic activity.

Dynamical ensemble of the active state and transition state mimic for the RNA-cleaving 8-17 DNAzyme in solution

We perform molecular dynamics simulations, based on recent crystallographic data, on the 8-17 DNAzyme at four states along the reaction pathway to determine the dynamical ensemble for the active state and transition state mimic in solution. A striking finding is the diverse roles played by Na+ and Pb2+ ions in the electrostatically strained active site that impact all four fundamental catalytic strategies, and share commonality with some features recently inferred for naturally occurring hammerhead and pistol ribozymes. The active site Pb2+ ion helps to stabilize in-line nucleophilic attack, provides direct electrostatic transition state stabilization, and facilitates leaving group departure. A conserved guanine residue is positioned to act as the general base, and is assisted by a bridging Na+ ion that tunes the pKa and facilitates in-line fitness. The present work provides insight into how DNA molecules are able to solve the RNA-cleavage problem, and establishes functional relationships between the mechanism of these engineered DNA enzymes with their naturally evolved RNA counterparts. This adds valuable information to our growing body of knowledge on general mechanisms of phosphoryl transfer reactions catalyzed by RNA, proteins and DNA.

Cleaning Up Mechanistic Debris Generated by Twister Ribozymes Using Computational RNA Enzymology

The catalytic properties of RNA have been a subject of fascination and intense research since their discovery over 30 years ago. Very recently, several classes of nucleolytic ribozymes have emerged and been characterized structurally. Among these, the twister ribozyme has been center-stage, and a topic of debate about its architecture and mechanism owing to conflicting interpretations of different crystal structures, and in some cases conflicting interpretations of the same functional data. In the present work, we attempt to clean up the mechanistic "debris" generated by twister ribozymes using a comprehensive computational RNA enzymology approach aimed to provide a unified interpretation of existing structural and functional data. Simulations in the crystalline environment and in solution provide insight into the origins of observed differences in crystal structures, and coalesce on a common active site architecture, and dynamical ensemble in solution. We use GPU-accelerated free energy methods with enhanced sampling to ascertain microscopic nucleobase pK a values of the implicated general acid and base, from which predicted activity-pH profiles can be compared directly with experiments. Next, ab initio quantum mechanical/molecular mechanical (QM/MM) simulations with full dynamic solvation under periodic boundary conditions are used to determine mechanistic pathways through multi-dimensional free energy landscapes for the reaction. We then characterize the rate-controlling transition state, and make predictions about kinetic isotope effects and linear free energy relations. Computational mutagenesis is performed to explain the origin of rate effects caused by chemical modifications and make experimentally testable predictions. Finally, we provide evidence that helps to resolve conflicting issues related to the role of metal ions in catalysis. Throughout each stage, we highlight how a conserved L-platform structural motif, to- gether with a key L-anchor residue, forms the characteristic active site scaffold enabling each of the catalytic strategies to come together not only for the twister ribozyme, but the majority of the known small nucleolytic ribozyme classes.

Tailoring enzyme microenvironment: State-of-the-art strategy to fulfill the quest for efficient bio-catalysis

Enzymes as green industrial biocatalysts have become a powerful norm that offers several advantages over traditional catalytic agents with regard to process efficiency, reusability, sustainability, and overall cost-effective ratio. However, enzymes obtained from natural origins are often engineered/tailored since their native forms do not fulfill the acute need for the industrial application. Revolutionary developments in protein engineering provide excellent opportunities for designing and constructing novel industrial biocatalysts with improved functional properties including catalytic activity, stability, substrate specificity, and reaction product inhibition. Momentum in enzyme immobilization has enabled robustness and optimal functions in extreme industrial environments, such as high temperature or organic solvents. The emergence of multi-enzyme catalytic cascade based on a combination of biocatalysts presents multifarious opportunities in biosynthesis, biocatalysis, and biotransformation. This review focuses on the emerging and state-of-the-art enzyme engineering trends and approaches to constructing innovative nano- and microstructured biocatalysts with enhanced catalytic activity and stability features requisite for industrial exploitation. Continuous key developments in this direction together with protein engineering in unique ways might offer ever-increasing opportunities for future biocatalysis-based industrial bioprocesses.

GPU-Accelerated Molecular Dynamics and Free Energy Methods in Amber18: Performance Enhancements and New Features

We report progress in graphics processing unit (GPU)-accelerated molecular dynamics and free energy methods in Amber18. Of particular interest is the development of alchemical free energy algorithms, including free energy perturbation and thermodynamic integration methods with support for nonlinear soft-core potential and parameter interpolation transformation pathways. These methods can be used in conjunction with enhanced sampling techniques such as replica exchange, constant-pH molecular dynamics, and new 12-6-4 potentials for metal ions. Additional performance enhancements have been made that enable appreciable speed-up on GPUs relative to the previous software release.

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.

Phosphodiester models for cleavage of nucleic acids

Nucleic acids that store and transfer biological information are polymeric diesters of phosphoric acid. Cleavage of the phosphodiester linkages by protein enzymes, nucleases, is one of the underlying biological processes. The remarkable catalytic efficiency of nucleases, together with the ability of ribonucleic acids to serve sometimes as nucleases, has made the cleavage of phosphodiesters a subject of intensive mechanistic studies. In addition to studies of nucleases by pH-rate dependency, X-ray crystallography, amino acid/nucleotide substitution and computational approaches, experimental and theoretical studies with small molecular model compounds still play a role. With small molecules, the importance of various elementary processes, such as proton transfer and metal ion binding, for stabilization of transition states may be elucidated and systematic variation of the basicity of the entering or departing nucleophile enables determination of the position of the transition state on the reaction coordinate. Such data is important on analyzing enzyme mechanisms based on synergistic participation of several catalytic entities. Many nucleases are metalloenzymes and small molecular models offer an excellent tool to construct models for their catalytic centers. The present review tends to be an up to date summary of what has been achieved by mechanistic studies with small molecular phosphodiesters.

Complexity in pH-Dependent Ribozyme Kinetics: Dark pKa Shifts and Wavy Rate-pH Profiles

Charged bases occur in RNA enzymes, or ribozymes, where they play key roles in catalysis. Cationic bases donate protons and perform electrostatic catalysis, while anionic bases accept protons. We previously published simulations of rate-pH profiles for ribozymes in terms of species plots for the general acid and general base that have been useful for understanding how ribozymes respond to pH. In that study, we did not consider interaction between the general acid and general base or interaction with other species on the RNA. Since that report, diverse small ribozyme classes have been discovered, many of which have charged nucleobases or metal ions in the active site that can either directly interact and participate in catalysis or indirectly interact as "influencers". Herein, we simulate experimental rate-pH profiles in terms of species plots in which reverse protonated charged nucleobases interact. These analyses uncover two surprising features of pH-dependent enzyme kinetics. (1) Cooperativity between the general acid and general base enhances population of the functional forms of a ribozyme and manifests itself as hidden or "dark" pK_a shifts, real pK_a shifts that accelerate the reaction but are not readily observed by standard experimental approaches, and (2) influencers favorably shift the pK_as of proton-transferring nucleobases and manifest themselves as "wavy" rate-pH profiles. We identify parallels with the protein enzyme literature, including reverse protonation and wavelike behavior, while pointing out that RNA is more prone to reverse protonation. The complexities uncovered, which arise from simple pairwise interactions, should aid deconvolution of complex rate-pH profiles for RNA and protein enzymes and suggest veiled catalytic devices for promoting catalysis that can be tested by experiment and calculation.

Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins

Proteins change their charge state through protonation and redox reactions as well as through binding charged ligands. The free energy of these reactions is dominated by solvation and electrostatic energies and modulated by protein conformational relaxation in response to the ionization state changes. Although computational methods for calculating these interactions can provide very powerful tools for predicting protein charge states, they include several critical approximations of which users should be aware. This chapter discusses the strengths, weaknesses, and approximations of popular computational methods for predicting charge states and understanding the underlying electrostatic interactions. The goal of this chapter is to inform users about applications and potential caveats of these methods as well as outline directions for future theoretical and computational research.

Sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the Cape sundew, Drosera capensis

Carnivorous plants represent a so far underexploited reservoir of novel proteases with potentially useful activities. Here we investigate 44 cysteine proteases from the Cape sundew, Drosera capensis, predicted from genomic DNA sequences. D. capensis has a large number of cysteine protease genes; analysis of their sequences reveals homologs of known plant proteases, some of which are predicted to have novel properties. Many functionally significant sequence and structural features are observed, including targeting signals and occluding loops. Several of the proteases contain a new type of granulin domain. Although active site residues are conserved, the sequence identity of these proteases to known proteins is moderate to low; therefore, comparative modeling with all-atom refinement and subsequent atomistic MD-simulation is used to predict their 3D structures. The structure prediction data, as well as analysis of protein structure networks, suggest multifarious variations on the papain-like cysteine protease structural theme. This in silico methodology provides a general framework for investigating a large pool of sequences that are potentially useful for biotechnology applications, enabling informed choices about which proteins to investigate in the laboratory.

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44 new cysteine proteases from the carnivorous plant Drosera capensis are described.

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Structure prediction and molecular dynamics simulation predict overall folds similar to papain.

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Functionally significant sequence and structural features are observed, including targeting signals and occluding loops.

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Several of the proteases contain a new type of granulin domain.

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Protein structure networks reveal global differences in interactions among chemical groups.

Unraveling HIV protease flaps dynamics by Constant pH Molecular Dynamics simulations

The active site of HIV protease (HIV-PR) is covered by two flaps. These flaps are known to be essential for the catalytic activity of the HIV-PR, but their exact conformations at the different stages of the enzymatic pathway remain subject to debate. Understanding the correct functional dynamics of the flaps might aid the development of new HIV-PR inhibitors. It is known that, the HIV-PR catalytic efficiency is pH-dependent, likely due to the influence of processes such as charge transfer and protonation/deprotonation of ionizable residues. Several Molecular Dynamics (MD) simulations have reported information about the HIV-PR flaps. However, in MD simulations the protonation of a residue is fixed and thus it is not possible to study the correlation between conformation and protonation state. To address this shortcoming, this work attempts to capture, through Constant pH Molecular Dynamics (CpHMD), the conformations of the apo, substrate-bound and inhibitor-bound HIV-PR, which differ drastically in their flap arrangements. The results show that the HIV-PR flaps conformations are defined by the protonation of the catalytic residues Asp25/Asp25' and that these residues are sensitive to pH changes. This study suggests that the catalytic aspartates can modulate the opening of the active site and substrate binding.

Ribozyme Catalysis with a Twist: Active State of the Twister Ribozyme in Solution Predicted from Molecular Simulation

We present results from molecular dynamics simulations and free energy calculations of the twister ribozyme at different stages along the reaction path to gain insight into its mechanism. The results, together with recent biochemical experiments, provide support for a mechanism involving general-acid catalysis by a conserved adenine residue in the active site. Although adenine has been previously implicated as a general acid acting through the N1 position in other ribozymes such as the hairpin and VS ribozymes, in the twister ribozyme there may be a twist. Biochemical experiments suggest that general acid catalysis may occur through the N3 position, which has never before been implicated in this role; however, currently, there is a lack of a detailed structural model for the active state of the twister ribozyme in solution that is consistent with these and other experiments. Simulations in a crystalline environment reported here are consistent with X-ray crystallographic data, and suggest that crystal packing contacts trap the RNA in an inactive conformation with U-1 in an extruded state that is incompatible with an in-line attack to the scissile phosphate. Simulations in solution, on the other hand, reveal this region to be dynamic and able to adopt a conformation where U-1 is stacked with G33. In this state, the nucleophile is in line with the scissile phosphate, and the N1 position of G33 and N3 position of A1 are poised to act as a general base and acid, respectively, as supported by mutational experiments. Free energy calculations further predict the electrostatic environment causes a shift of the microscopic pKa at the N3 position of A1 toward neutrality by approximately 5 pKa units. These results offer a unified interpretation of a broad range of currently available experimental data that points to a novel mode of general acid catalysis through the N3 position of an adenine nucleobase, thus expanding the repertoire of known mechanistic strategies employed by small nucleolytic ribozymes.

Computation of pH-dependent binding free energies

Protein-ligand binding accompanies changes in the surrounding electrostatic environments of the two binding partners and may lead to changes in protonation upon binding. In cases where the complex formation results in a net transfer of protons, the binding process is pH-dependent. However, conventional free energy computations or molecular docking protocols typically employ fixed protonation states for the titratable groups in both binding partners set a priori, which are identical for the free and bound states. In this review, we draw attention to these important yet largely ignored binding-induced protonation changes in protein-ligand association by outlining physical origins and prevalence of the protonation changes upon binding. Following a summary of various theoretical methods for pKa prediction, we discuss the theoretical framework to examine the pH dependence of protein-ligand binding processes.

Conformational Dynamics and Binding Free Energies of Inhibitors of BACE-1: From the Perspective of Protonation Equilibria

BACE-1 is the β-secretase responsible for the initial amyloidogenesis in Alzheimer’s disease, catalyzing hydrolytic cleavage of substrate in a pH-sensitive manner. The catalytic mechanism of BACE-1 requires water-mediated proton transfer from aspartyl dyad to the substrate, as well as structural flexibility in the flap region. Thus, the coupling of protonation and conformational equilibria is essential to a full in silico characterization of BACE-1. In this work, we perform constant pH replica exchange molecular dynamics simulations on both apo BACE-1 and five BACE-1-inhibitor complexes to examine the effect of pH on dynamics and inhibitor binding properties of BACE-1. In our simulations, we find that solution pH controls the conformational flexibility of apo BACE-1, whereas bound inhibitors largely limit the motions of the holo enzyme at all levels of pH. The microscopic pK_a values of titratable residues in BACE-1 including its aspartyl dyad are computed and compared between apo and inhibitor-bound states. Changes in protonation between the apo and holo forms suggest a thermodynamic linkage between binding of inhibitors and protons localized at the dyad. Utilizing our recently developed computational protocol applying the binding polynomial formalism to the constant pH molecular dynamics (CpHMD) framework, we are able to obtain the pH-dependent binding free energy profiles for various BACE-1-inhibitor complexes. Our results highlight the importance of correctly addressing the binding-induced protonation changes in protein-ligand systems where binding accompanies a net proton transfer. This work comprises the first application of our CpHMD-based free energy computational method to protein-ligand complexes and illustrates the value of CpHMD as an all-purpose tool for obtaining pH-dependent dynamics and binding free energies of biological systems.

Formation of insoluble amyloid plaques in the vascular and hippocampal areas of the brain characterizes Alzheimer’s disease, a devastating neurodegenerative disorder causing dementia. Site-specific hydrolytic catalysis of β-secretase, or BACE-1, is responsible for production of oligomerative amyloid β-peptide. As the catalytic activity of BACE-1 is pH-dependent and its structural dynamics are intrinsic to the catalysis, we examine the dependence of dynamics of BACE-1 on solution pH and its implications on the catalytic mechanism of BACE-1. Also, we highlight the importance of accurate description of protonation states of the titratable groups in computer-aided drug discovery targeting BACE-1. We hope the understanding of pH dependence of the dynamics and inhibitor binding properties of BACE-1 will aid the structure-based inhibitor design efforts against Alzheimer’s disease.

Multiscale methods for computational RNA enzymology

RNA catalysis is of fundamental importance to biology and yet remains ill-understood due to its complex nature. The multidimensional "problem space" of RNA catalysis includes both local and global conformational rearrangements, changes in the ion atmosphere around nucleic acids and metal ion binding, dependence on potentially correlated protonation states of key residues, and bond breaking/forming in the chemical steps of the reaction. The goal of this chapter is to summarize and apply multiscale modeling methods in an effort to target the different parts of the RNA catalysis problem space while also addressing the limitations and pitfalls of these methods. Classical molecular dynamics simulations, reference interaction site model calculations, constant pH molecular dynamics (CpHMD) simulations, Hamiltonian replica exchange molecular dynamics, and quantum mechanical/molecular mechanical simulations will be discussed in the context of the study of RNA backbone cleavage transesterification. This reaction is catalyzed by both RNA and protein enzymes, and here we examine the different mechanistic strategies taken by the hepatitis delta virus ribozyme and RNase A.