The dynamics of ligand barrier crossing inside the acetylcholinesterase gorge

Putting the Puzzle Together To Get the Whole Picture: Molecular Basis of the Affinity of Two Steroid Derivatives to Acetylcholinesterase

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that has no cure because its etiology is still unknown, and its main treatment is the administration of acetylcholinesterase (AChE) inhibitors. The study of the mechanism of action of this family of compounds is critical for the design of new more potent and specific inhibitors. In this work, we study the molecular basis of an uncompetitive inhibitor (compound 1, 2β, 3α-dihydroxy-5α-cholestan-6-one disulfate), which we have proved to be a peripheral anionic site (PAS)-binding AChE inhibitor. The pipeline designed in this work is key to the development of other PAS inhibitors that not only inhibit the esterase action of the enzyme but could also modulate the non-cholinergic functions of AChE linked to the process of amylogenesis. Our studies showed that 1 inhibits the enzyme not simply by blocking the main gate but by an allosteric mechanism. A detailed and careful analysis of the ligand binding position and the protein dynamics, particularly regarding their secondary gates and active site, was necessary to conclude this. The same analysis was executed with an inactive analogue (compound 2, 2β, 3α-dihydroxy-5α-cholestan-6-one). Our first computational results showed no differences in affinity to AChE between both steroids, making further analysis necessary. This work highlights the variables to be considered and develops a refined methodology, for the successful design of new potent dual-action drugs for AD, particularly PAS inhibitors, an attractive strategy to combat AD.

Computational Studies on Acetylcholinesterase Inhibitors: From Biochemistry to Chemistry

Acetylcholinesterase inhibitors are the most promising therapeutics for Alzheimer's disease treatment as these prevent the loss of acetylcholine and slows the progression of the disease. The drugs approved for the management of Alzheimer's disease by the FDA are acetylcholinesterase inhibitors but are associated with side effects. Consistent and stringent efforts by the researchers with the help of computational methods opened new ways of developing novel molecules with good acetylcholinesterase inhibitory activity. In this manuscript, we reviewed the studies that identified the essential structural features of acetylcholinesterase inhibitors at the molecular level as well as the techniques like molecular docking, molecular dynamics, quantitative structure-activity relationship, virtual screening, and pharmacophore modelling that were used in designing these inhibitors.

Kinetics of Drug Binding and Residence Time

The kinetics of drug binding and unbinding is assuming an increasingly crucial role in the long, costly process of bringing a new medicine to patients. For example, the time a drug spends in contact with its biological target is known as residence time (the inverse of the kinetic constant of the drug-target unbinding, 1/ koff). Recent reports suggest that residence time could predict drug efficacy in vivo, perhaps even more effectively than conventional thermodynamic parameters (free energy, enthalpy, entropy). There are many experimental and computational methods for predicting drug-target residence time at an early stage of drug discovery programs. Here, we review and discuss the methodological approaches to estimating drug binding kinetics and residence time. We first introduce the theoretical background of drug binding kinetics from a physicochemical standpoint. We then analyze the recent literature in the field, starting from the experimental methodologies and applications thereof and moving to theoretical and computational approaches to the kinetics of drug binding and unbinding. We acknowledge the central role of molecular dynamics and related methods, which comprise a great number of the computational methods and applications reviewed here. However, we also consider kinetic Monte Carlo. We conclude with the outlook that drug (un)binding kinetics may soon become a go/no go step in the discovery and development of new medicines.

Impact of protein-ligand solvation and desolvation on transition state thermodynamic properties of adenosine A2A ligand binding kinetics

Ligand-protein binding kinetic rates are growing in importance as parameters to consider in drug discovery and lead optimization. In this study we analysed using surface plasmon resonance (SPR) the transition state (TS) properties of a set of six adenosine A2A receptor inhibitors, belonging to both the xanthine and the triazolo-triazine scaffolds. SPR highlighted interesting differences among the ligands in the enthalpic and entropic components of the TS energy barriers for the binding and unbinding events. To better understand at a molecular level these differences, we developed suMetaD, a novel molecular dynamics (MD)-based approach combining supervised MD and metadynamics. This method allows simulation of the ligand unbinding and binding events. It also provides the system conformation corresponding to the highest energy barrier the ligand is required to overcome to reach the final state. For the six ligands evaluated in this study their TS thermodynamic properties were linked in particular to the role of water molecules in solvating/desolvating the pocket and the small molecules. suMetaD identified kinetic bottleneck conformations near the bound state position or in the vestibule area. In the first case the barrier is mainly enthalpic, requiring the breaking of strong interactions with the protein. In the vestibule TS location the kinetic bottleneck is instead mainly of entropic nature, linked to the solvent behaviour.

Computational Studies on Acetylcholinesterases

Functions of biomolecules, in particular enzymes, are usually modulated by structural fluctuations. This is especially the case in a gated diffusion-controlled reaction catalyzed by an enzyme such as acetylcholinesterase. The catalytic triad of acetylcholinesterase is located at the bottom of a long and narrow gorge, but it catalyzes the extremely rapid hydrolysis of the neurotransmitter, acetylcholine, with a reaction rate close to the diffusion-controlled limit. Computational modeling and simulation have produced considerable advances in exploring the dynamical and conformational properties of biomolecules, not only aiding in interpreting the experimental data, but also providing insights into the internal motions of the biomolecule at the atomic level. Given the remarkably high catalytic efficiency and the importance of acetylcholinesterase in drug development, great efforts have been made to understand the dynamics associated with its functions by use of various computational methods. Here, we present a comprehensive overview of recent computational studies on acetylcholinesterase, expanding our views of the enzyme from a microstate of a single structure to conformational ensembles, strengthening our understanding of the integration of structure, dynamics and function associated with the enzyme, and promoting the structure-based and/or mechanism-based design of new inhibitors for it.

Estimation of kinetic and thermodynamic ligand-binding parameters using computational strategies

Kinetic and thermodynamic ligand–protein binding parameters are gaining growing importance as key information to consider in drug discovery. The determination of the molecular structures, using particularly x-ray and NMR techniques, is crucial for understanding how a ligand recognizes its target in the final binding complex. However, for a better understanding of the recognition processes, experimental studies of ligand–protein interactions are needed. Even though several techniques can be used to investigate both thermodynamic and kinetic profiles for a ligand–protein complex, these procedures are very often laborious, time consuming and expensive. In the last 10 years, computational approaches have enormous potential in providing insights into each of the above effects and in parsing their contributions to the changes in both kinetic and thermodynamic binding parameters. The main purpose of this review is to summarize the state of the art of computational strategies for estimating the kinetic and thermodynamic parameters of a ligand–protein binding.

Evaluation of protein-ligand affinity prediction using steered molecular dynamics simulations

In computational drug design, ranking a series of compound analogs in a manner that is consistent with experimental affinities remains a challenge. In this study, we evaluated the prediction of protein-ligand binding affinities using steered molecular dynamics simulations. First, we investigated the appropriate conditions for accurate predictions in these simulations. A conic harmonic restraint was applied to the system for efficient sampling of work values on the ligand unbinding pathway. We found that pulling velocity significantly influenced affinity predictions, but that the number of collectable trajectories was less influential. We identified the appropriate pulling velocity and collectable trajectories for binding affinity predictions as 1.25 Å/ns and 100, respectively, and these parameters were used to evaluate three target proteins (FK506 binding protein, trypsin, and cyclin-dependent kinase 2). For these proteins using our parameters, the accuracy of affinity prediction was higher and more stable when Jarzynski's equality was employed compared with the second-order cumulant expansion equation of Jarzynski's equality. Our results showed that steered molecular dynamics simulations are effective for predicting the rank order of ligands; thus, they are a potential tool for compound selection in hit-to-lead and lead optimization processes.

A wrench in the works of human acetylcholinesterase: soman induced conformational changes revealed by molecular dynamics simulations

Irreversible inactivation of human acetylcholinesterase (hAChE) by organophosphorous pesticides (OPs) and chemical weapon agents (CWA) has severe morbidity and mortality consequences. We present data from quantum mechanics/molecular mechanics (QM/MM) and 80 classical molecular dynamics (MD) simulations of the apo and soman-adducted forms of hAChE to investigate the effects on the dynamics and protein structure when the catalytic Serine 203 is phosphonylated. We find that the soman phosphonylation of the active site Ser203 follows a water assisted addition-elimination mechanism with the elimination of the fluoride ion being the highest energy barrier at 6.5 kcal/mole. We observe soman-dependent changes in backbone and sidechain motions compared to the apo form of the protein. These alterations restrict the soman-adducted hAChE to a structural state that is primed for the soman adduct to be cleaved and removed from the active site. The altered motions and resulting structures provide alternative pathways into and out of the hAChE active site. In the soman-adducted protein both side and back door pathways are viable for soman adduct access. Correlation analysis of the apo and soman adducted MD trajectories shows that the correlation of gorge entrance and back door motion is disrupted when hAChE is adducted. This supports the hypothesis that substrate and product can use two different pathways as entry and exit sites in the apo form of the protein. These alternative pathways have important implications for the rational design of medical countermeasures.

Investigating drug-target association and dissociation mechanisms using metadynamics-based algorithms

CONSPECTUS: This Account highlights recent advances and discusses major challenges in the field of drug-target recognition, binding, and unbinding studied using metadynamics-based approaches, with particular emphasis on their role in structure-based design. Computational chemistry has significantly contributed to drug design and optimization in an extremely broad range of areas, including prediction of target druggability and drug likeness, de novo design, fragment screening, ligand docking, estimation of binding affinity, and modulation of ADMET (absorption, distribution, metabolism, excretion, toxicity) properties. Computationally driven drug discovery must continuously adapt to keep pace with the evolving knowledge of the factors that modulate the pharmacological action of drugs. There is thus an urgent need for novel computational approaches that integrate the vast amount of complex information currently available for small (bio)organic compounds, biologically relevant targets and their complexes, while also accounting accurately for the thermodynamics and kinetics of drug-target association, the intrinsic dynamical behavior of biomolecular systems, and the complexity of protein-protein networks. Understanding the mechanism of drug binding to and unbinding from biological targets is fundamental for optimizing lead compounds and designing novel biologically active ones. One major challenge is the accurate description of the conformational complexity prior to and upon formation of drug-target complexes. Recently, enhanced sampling methods, including metadynamics and related approaches, have been successfully applied to investigate complex mechanisms of drugs binding to flexible targets. Metadynamics is a family of enhanced sampling techniques aimed at enhancing the rare events and reconstructing the underlying free energy landscape as a function of a set of order parameters, usually referred to as collective variables. Studies of drug binding mechanisms have predicted the most probable association and dissociation pathways and the related binding free energy profile. In addition, the availability of an efficient open-source implementation, running on cost-effective GPU (i.e., graphical processor unit) architectures, has considerably decreased the learning curve and the computational costs of the methods, and increased their adoption by the community. Here, we review the recent contributions of metadynamics and other enhanced sampling methods to the field of drug-target recognition and binding. We discuss how metadynamics has been used to search for transition states, to predict binding and unbinding paths, to treat conformational flexibility, and to compute free energy profiles. We highlight the importance of such predictions in drug discovery. Major challenges in the field and possible solutions will finally be discussed.

Unbinding free energy of acetylcholinesterase bound oxime drugs along the gorge pathway from metadynamics-umbrella sampling investigation

Because of the pivotal role that the nerve enzyme, acetylcholinesterase plays in terminating nerve impulses at cholinergic synapses. Its active site, located deep inside a 20 Å gorge, is a vulnerable target of the lethal organophosphorus compounds. Potent reactivators of the intoxicated enzyme are nucleophiles, such as bispyridinium oxime that binds to the peripheral anionic site and the active site of the enzyme through suitable cation-π interactions. Atomic scale molecular dynamics and free energy calculations in explicit water are used to study unbinding pathways of two oxime drugs (Ortho-7 and Obidoxime) from the gorge of the enzyme. The role of enzyme-drug cation-π interactions are explored with the metadynamics simulation. The metadynamics discovered potential of mean force (PMF) of the unbinding events is refined by the umbrella sampling (US) corrections. The bidimensional free energy landscape of the metadynamics runs are further subjected to finite temperature string analysis to obtain the transition tube connecting the minima and bottlenecks of the unbinding pathway. The PMF is also obtained from US simulations using the biasing potential constructed from the transition tube and are found to be consistent with the metadynamics-US corrected results. Although experimental structural data clearly shows analogous coordination of the two drugs inside the gorge in the bound state, the PMF of the drug trafficking along the gorge pathway point, within an equilibrium free energy context, to a multistep process that differs from one another. Routes, milestones and subtlety toward the unbinding pathway of the two oximes at finite temperature are identified.

Neurotoxicology of bis(n)-tacrines on Blattella germanica and Drosophila melanogaster acetylcholinesterase

A series of bis(n)-tacrines were used as pharmacological probes of the acetylcholinesterase (AChE) catalytic and peripheral sites of Blattella germanica and Drosophila melanogaster, which express AChE-1 and AChE-2 isoforms, respectively. In general, the potency of bis(n)-tacrines was greater in D. melanogaster AChE (DmAChE) than in B. germanica AChE (BgAChE). The change in potency with tether length was high in DmAChE and low in BgAChE, associated with 90-fold and 5.2-fold maximal potency gain, respectively, compared to the tacrine monomer. The optimal tether length for Blattella was 8 carbons and for Drosophila was 10 carbons. The two species differed by only about twofold in their sensitivity to tacrine monomer, indicating that differential potency occurred among dimeric bis(n)-tacrines due to structural differences in the peripheral site. Multiple sequence alignment and in silico homology modeling suggest that aromatic residues of DmAChE confer higher affinity binding, and the lack of same at the BgAChE peripheral site may account, at least in part, to the greater overall sensitivity of DmAChE to bis(n)-tacrines, as reflected by in vitro assay data. Topical and injection assays in cockroaches found minimal toxicity of bis(n)-tacrines. Electrophysiological studies on D. melanogaster central nervous system showed that dimeric tacrines do not readily cross the blood brain barrier, explaining the observed nonlethality to insects. Although the bis(n)-tacrines were not good insecticide candidates, the information obtained in this study should aid in the design of selective bivalent ligands targeting insect, pests, and disease vectors.

Energetics of Ortho-7 (oxime drug) translocation through the active-site gorge of tabun conjugated acetylcholinesterase

Oxime drugs translocate through the 20 Å active-site gorge of acetylcholinesterase in order to liberate the enzyme from organophosphorus compounds' (such as tabun) conjugation. Here we report bidirectional steered molecular dynamics simulations of oxime drug (Ortho-7) translocation through the gorge of tabun intoxicated enzyme, in which time dependent external forces accelerate the translocation event. The simulations reveal the participation of drug-enzyme hydrogen bonding, hydrophobic interactions and water bridges between them. Employing nonequilibrium theorems that recovers the free energy from irreversible work done, we reconstruct potential of mean force along the translocation pathway such that the desired quantity represents an unperturbed system. The potential locates the binding sites and barriers for the drug to translocate inside the gorge. Configurational entropic contribution of the protein-drug binding entity and the role of solvent translational mobility in the binding energetics is further assessed.

Internal Diffusion-Controlled Enzyme Reaction: The Acetylcholinesterase Kinetics

Acetylcholinesterase is an enzyme with a very high turnover rate; it quenches the neurotransmitter, acetylcholine, at the synapse. We have investigated the kinetics of the enzyme reaction by calculating the diffusion rate of the substrate molecule along an active site channel inside the enzyme from atomic-level molecular dynamics simulations. In contrast to the previous works, we have found that the internal substrate diffusion is the determinant of the acetylcholinesterase kinetics in the low substrate concentration limit. Our estimate of the overall bimolecular reaction rate constant for the enzyme is in good agreement with the experimental data. In addition, the present calculation provides a reasonable explanation for the effects of the ionic strength of solution and the mutation of surface residues of the enzyme. The study suggests that internal diffusion of the substrate could be a key factor in understanding the kinetics of enzymes of similar characteristics.

Exploring inhibitor release pathways in histone deacetylases using random acceleration molecular dynamics simulations

Molecular channel exploration perseveres to be the prominent solution for eliciting structure and accessibility of active site and other internal spaces of macromolecules. The volume and silhouette characterization of these channels provides answers for the issues of substrate access and ligand swapping between the obscured active site and the exterior of the protein. Histone deacetylases (HDACs) are metal-dependent enzymes that are involved in the cell growth, cell cycle regulation, and progression, and their deregulations have been linked with different types of cancers. Hence HDACs, especially the class I family, are widely recognized as the important cancer targets, and the characterizations of their structures and functions have been of special interest in cancer drug discovery. The class I HDACs are known to possess two different protein channels, an 11 Å and a 14 Å (named channels A and B1, respectively), of which the former is a ligand or substrate occupying tunnel that leads to the buried active site zinc ion and the latter is speculated to be involved in product release. In this work, we have carried out random acceleration molecular dynamics (RAMD) simulations coupled with the classical molecular dynamics to explore the release of the ligand, N-(2-aminophenyl) benzamide (LLX) from the active sites of the recently solved X-ray crystal structure of HDAC2 and the computationally modeled HDAC1 proteins. The RAMD simulations identified significant structural and dynamic features of the HDAC channels, especially the key 'gate-keeping' amino acid residues that control these channels and the ligand release events. Further, this study identified a novel and unique channel B2, a subchannel from channel B1, in the HDAC1 protein structure. The roles of water molecules in the LLX release from the HDAC1 and HDAC2 enzymes are also discussed. Such structural and dynamic properties of the HDAC protein channels that govern the ligand escape reactions will provide further mechanistic insights into the HDAC enzymes, which, in the long run, have a potential to bring new ideas for developing more promising HDAC inhibitors as well as extend our atomic level understandings on their mechanisms of action.

Insights into Ligand-Protein Binding from Local Mechanical Response

Computational studies of ligand–protein binding are crucial for properly designing novel compounds of potential pharmacological interest. In this respect, researchers are increasingly interested in steered molecular dynamics for ligand–protein binding and unbinding studies. In particular, it has been suggested that analyzing the work profiles along the ligand–protein undocking paths could be fruitful. Here, we propose that small portions of work profiles, termed “local mechanical responses” of the system to a steering force, could serve as a universal measure for capturing relevant information about the system under investigation. Specifically, we first collected a high number of steering trajectories using two biological systems of increasing complexity (i.e., alanine dipeptide and (R)-roscovitine/CDK5 complex). Then, we devised a novel postprocessing tool to be applied to the local mechanical responses, to extract structural information related to the biological processes under investigation. Despite the out-of-equilibrium character of the trajectories, the analysis carried out on the work profiles provided pivotal information about the investigated biological processes. This could eventually be applied to drug design.

Gated Diffusion-controlled Reactions

The binding and active sites of proteins are often dynamically occluded by motion of the nearby polypeptide. A variety of theoretical and computational methods have been developed to predict rates of ligand binding and reactivity in such cases. Two general approaches exist, "protein centric" approaches that explicitly treat only the protein target, and more detailed dynamical simulation approaches in which target and ligand are both treated explicitly. This mini-review describes recent work in this area and some of the biological implications.

Free-energy-based methods for binding profile determination in a congeneric series of CDK2 inhibitors

Free-energy pathway methods show great promise in computing the mode of action and the free energy profile associated with the binding of small molecules with proteins, but are generally very computationally demanding. Here we apply a novel approach based on metadynamics and path collective variables. We show that this combination is able to find an optimal reaction coordinate and the free energy profile of binding with explicit solvent and full flexibility, while minimizing human intervention and computational costs. We apply it to predict the binding affinity of a congeneric series of 5 CDK2 inhibitors. The predicted binding free energy profiles are in accordance with experiment.

Pathways and mechanisms for product release in the engineered haloalkane dehalogenases explored using classical and random acceleration molecular dynamics simulations

Eight mutants of the DhaA haloalkane dehalogenase carrying mutations at the residues lining two tunnels, previously observed by protein X-ray crystallography, were constructed and biochemically characterized. The mutants showed distinct catalytic efficiencies with the halogenated substrate 1,2,3-trichloropropane. Release pathways for the two dehalogenation products, 2,3-dichloropropane-1-ol and the chloride ion, and exchange pathways for water molecules, were studied using classical and random acceleration molecular dynamics simulations. Five different pathways, denoted p1, p2a, p2b, p2c, and p3, were identified. The individual pathways showed differing selectivity for the products: the chloride ion releases solely through p1, whereas the alcohol releases through all five pathways. Water molecules play a crucial role for release of both products by breakage of their hydrogen-bonding interactions with the active-site residues and shielding the charged chloride ion during its passage through a hydrophobic tunnel. Exchange of the chloride ions, the alcohol product, and the waters between the buried active site and the bulk solvent can be realized by three different mechanisms: (i) passage through a permanent tunnel, (ii) passage through a transient tunnel, and (iii) migration through a protein matrix. We demonstrate that the accessibility of the pathways and the mechanisms of ligand exchange were modified by mutations. Insertion of bulky aromatic residues in the tunnel corresponding to pathway p1 leads to reduced accessibility to the ligands and a change in mechanism of opening from permanent to transient. We propose that engineering the accessibility of tunnels and the mechanisms of ligand exchange is a powerful strategy for modification of the functional properties of enzymes with buried active sites.

Standard Free Energy of Binding from a One-Dimensional Potential of Mean Force

A practical approach that enables one to calculate the standard free energy of binding from a one-dimensional potential of mean force (PMF) is proposed. Umbrella sampling and the weighted histogram analysis method are used to generate a PMF along the reaction coordinate of binding. At each point, a restraint is applied orthogonal to the reaction coordinate to make possible the determination of the volume sampled by the ligand. The free energy of binding from an arbitrary unbound volume to the restrained bound form is calculated from the ratio of the PMF integrated over the bound region to that of the unbound. Adding the free energy changes from the standard-state volume to the unbound volume and from the restrained to the unrestrained bound state gives the standard free energy of binding. Exploration of the best choice of binding paths is also made. This approach is first demonstrated on a model binding system and then tested on the benzamidine-trypsin system for which reasonable agreement with experiment is found. A comparison is made with other methods to obtain the standard free energy of binding from the PMF.

Intrinsic conformational flexibility of acetylcholinesterase

Proteins have been metaphorically described--due to the introduction and extraordinary advances in biomolecular dynamics and computational biophysics over the past decades--as "kicking and screaming" molecules [G. Weber, Adv. Protein Chem. 29 (1975) 1-83]. In fact, dynamic fluctuations in protein structural conformation have been known to play an important role in protein function. However, fundamental mechanisms by which protein fluctuations couple with catalytic function of particular enzymes remain poorly understood. To understand the dynamical properties of acetylcholinesterase (AChE) in rapid termination of cationic neurotransmitter, acetylcholine at neurosynaptic junctions, multiple molecular dynamics (MD) trajectories of AChE in the presence and absence of its inhibitors [J.M. Bui, J.A. McCammon, Proc. Natl. Acad. Sci. U.S.A. 103 (2006) 15451-15456; J.M. Bui, Z. Radic, P. Taylor, J.A. McCammon, Biophys. J. 90 (2006) 3280-3287; J.M. Bui, K. Tai, J.A. McCammon, J. Am. Chem. Soc. 126 (2004) 7198-7205; J.M. Bui, R.H. Henchman, J.A. McCammon, Biophys. J. 85 (2003) 2267-2272] have been conducted and correlated with its inhibitory mechanisms. The intrinsic flexibilities of AChE, particularly of the long omega loop, are important in facilitating the ligand's inhibition of the enzyme.

Acetylcholinesterase: how is structure related to function?

In accordance with its biological role, termination of neurotransmission at cholinergic synapses by rapid hydrolysis of the neurotransmitter, acetylcholine, acetylcholinesterase is one of nature's most efficient enzymes. Solution of its three-dimensional structure revealed that its active site is located at the bottom of a deep and narrow gorge. Such an architecture was unanticipated in view of its high turnover number. The present review examines how the highly specialized structure of acetylcholinesterase, with its sequestered active site, contributes to its catalytic efficacy, and discusses how the traffic of substrate and products to and from the active site is controlled.

The role of Li + , Na + , and K + in the ligand binding inside the human acetylcholinesterase gorge

Alkali cations can affect the catalytic efficiency of enzymes. This is particularly true when dealing with enzymes whose substrate bears a formal positive charge. Computational and biochemical approaches have been combined to shed light on the atomic aspects of the role of Li(+), Na(+), and K(+) on human acetylcholinesterase (hAChE) ligand binding. In this respect, molecular dynamics simulations and our recently developed metadynamics method were applied to study the entrance of the three cations in the gorge of hAChE, and their effect on the dynamical motion of a ligand (tetramethylammonium) from the bulk of the solvent into the deep narrow enzyme gorge. Furthermore, in order to support the theoretical results, K(M) and k(cat) for the acetylcholine hydrolysis in the presence of the three cations were evaluated by using an approach based on the Ellman's method. The combination of computational and biochemical experiments clearly showed that Li(+), Na(+), and K(+) may influence the ligand binding at the hAChE gorge.

Molecular dynamics simulations of human butyrylcholinesterase

Herein, we present results from molecular dynamics (MD) simulations of the human butyrylcholinesterase (BuChE) enzyme in aqueous solution. Two configurations of the unbound form of BuChE differing in the presence or absence of a sodium ion inside the protein gorge were simulated for 10 and 5 ns, respectively. Besides complementing the structural information provided by X-ray data, the MD simulations give insight into the structure of the native BuChE enzyme. For example, it is shown that: the nucleophilic Ser(198) residue and the various binding subsites in the BuChE catalytic cavity are readily accessible from the exterior of the protein; the presence of the sodium ion dynamically explores two different binding sites in the gorge leading to the active site and stabilizes the productive conformation of the Glu(325)/His(438)/Ser(198) catalytic triad; several long-lived water bridges are fully integrated into the architecture of the active site; the positions of the residues at the rim of the gorge region display large deviations with respect to the crystal structure; and two side doors, constituted by residues situated at the tip of the acyl- and Omega-loops, respectively, open wide enough to allow the passage of water molecules. In conclusion, we compare our theoretical results with those from previous work on mouse acetylcholinesterase and discuss their implications for substrate binding and catalysis in BuChE.