Electrostatic influence on the kinetics of ligand binding to acetylcholinesterase. Distinctions between active center ligands and fasciculin

Structure-based development of novel substrate-type G9a inhibitors as epigenetic modulators for sickle cell disease treatment

The discovery and development of structurally distinct lysine methyltransferase G9a inhibitors have been the subject of intense research in epigenetics. Structure-based optimization was conducted, starting with the previously reported seed compound 7a and lead to the identification of a highly potent G9a inhibitor, compound 7i (IC50 = 0.024 μM). X-ray crystallography for the ligand-protein interaction and kinetics study, along with surface plasmon resonance (SPR) analysis, revealed that compound 7i interacts with G9a in a unique binding mode. In addition, compound 7i caused attenuation of cellular H3K9me2 levels and induction of γ-globin mRNA expression in HUDEP-2 cells in a dose-dependent manner.

Similarities and Differences in Ligand Binding to Protein and RNA Targets: The Case of Riboflavin

It is nowadays clear that RNA molecules can play active roles in several biological processes. As a result, an increasing number of RNAs are gradually being identified as potentially druggable targets. In particular, noncoding RNAs can adopt highly organized conformations that are suitable for drug binding. However, RNAs are still considered challenging targets due to their complex structural dynamics and high charge density. Thus, elucidating relevant features of drug-RNA binding is fundamental for advancing drug discovery. Here, by using Molecular Dynamics simulations, we compare key features of ligand binding to proteins with those observed in RNA. Specifically, we explore similarities and differences in terms of (i) conformational flexibility of the target, (ii) electrostatic contribution to binding free energy, and (iii) water and ligand dynamics. As a test case, we examine binding of the same ligand, namely riboflavin, to protein and RNA targets, specifically the riboflavin (RF) kinase and flavin mononucleotide (FMN) riboswitch. The FMN riboswitch exhibited enhanced fluctuations and explored a wider conformational space, compared to the protein target, underscoring the importance of RNA flexibility in ligand binding. Conversely, a similar electrostatic contribution to the binding free energy of riboflavin was found. Finally, greater stability of water molecules was observed in the FMN riboswitch compared to the RF kinase, possibly due to the different shape and polarity of the pockets.

A simple method to resolve rate constants when the binding mechanism obeys induced fit or conformational selection

Many interactions involving a ligand and its molecular target are studied by rapid kinetics using a stopped-flow apparatus. Information obtained from these studies is often limited to a single, saturable relaxation that is insufficient to resolve all independent rate constants even for a two-step mechanism of binding obeying induced fit (IF) or conformational selection (CS). We introduce a simple method of general applicability where this limitation is overcome. The method accurately reproduces the rate constants for ligand binding to the serine protease thrombin determined independently from the analysis of multiple relaxations. Application to the inactive zymogen precursor of thrombin, prethrombin-2, resolves all rate constants for a binding mechanism of IF or CS from a single, saturable relaxation. Comparison with thrombin shows that the prethrombin-2 to thrombin conversion enhances ligand binding to the active site not by improving accessibility through the value of kon but by reducing the rate of dissociation koff. The conclusion holds regardless of whether binding is interpreted in terms of IF or CS and has general relevance for the mechanism of zymogen activation of serine proteases. The method also provides a simple test of the validity of IF and CS and indicates when more complex mechanisms of binding should be considered.

Acetylcholinesterase: A Versatile Template to Coin Potent Modulators of Multiple Therapeutic Targets

ConspectusThe enzyme acetylcholinesterase (AChE) hydrolyzes the neurotransmitter acetylcholine (ACh) at cholinergic synapses of the peripheral and central nervous system. Thus, it is a prime therapeutic target for diseases that occur with a cholinergic deficit, prominently Alzheimer's disease (AD). Working at a rate near the diffusion limit, it is considered one of nature's most efficient enzymes. This is particularly meritorious considering that its catalytic site is buried at the bottom of a 20-Å-deep cavity, which is preceded by a bottleneck with a diameter shorter than that of the trimethylammonium group of ACh, which has to transit through it. Not only the particular architecture and amino acid composition of its active site gorge enable AChE to largely overcome this potential drawback, but it also offers plenty of possibilities for the design of novel inhibitor drug candidates.In this Account, we summarize our different approaches to colonize the vast territory of the AChE gorge in the pursuit of increased occupancy and hence of inhibitors with increased affinity. We pioneered the use of molecular hybridization to design inhibitors with extended binding at the CAS, reaching affinities among the highest reported so far. Further application of molecular hybridization to grow CAS extended binders by attaching a PAS-binding moiety through suitable linkers led to multisite inhibitors that span the whole length of the gorge, reaching the PAS and even interacting with midgorge residues. We show that multisite AChE inhibitors can also be successfully designed the other way around, by starting with an optimized PAS binder and then colonizing the gorge and CAS. Molecular hybridization from a multicomponent reaction-derived PAS binder afforded a single-digit picomolar multisite AChE inhibitor with more than 1.5 million-fold increased potency relative to the initial hit. This illustrates the powerful alliance between molecular hybridization and gorge occupancy for designing potent AChE inhibitors.Beyond AChE, we show that the stereoelectronic requirements imposed by the AChE gorge for multisite binding have a templating effect that leads to compounds that are active in other key biological targets in AD and other neurological and non-neurological diseases, such as BACE-1 and the aggregation of amyloidogenic proteins (β-amyloid, tau, α-synuclein, prion protein, transthyretin, and human islet amyloid polypeptide). The use of known pharmacophores for other targets as the PAS-binding motif enables the rational design of multitarget agents with multisite binding within AChE and activity against a variety of targets or pathological events, such as oxidative stress and the neuroinflammation-modulating enzyme soluble epoxide hydrolase, among others.We hope that our results can contribute to the development of drug candidates that can modify the course of neurodegeneration and may inspire future works that exploit the power of molecular hybridization in other proteins featuring large cavities.

Possible Interaction between ZnS Nanoparticles and Phosphonates on Mediterranean Clams Ruditapes decussatus

This study aims to evaluate the toxicity of ZnS nanoparticles (ZnS NP50 = 50 µg/L and ZnS NP100 = 100 µg/L) and diethyl (3-cyano-1-hydroxy-2-methyl-1-phenylpropyl)phosphonate or P (P50 = 50 µg/L and P100 = 100 µg/L) in the clams Ruditapes decussatus using chemical and biochemical approaches. The results demonstrated that clams accumulate ZnS NPs and other metallic elements following exposure. Moreover, ZnS NPs and P separately lead to ROS overproduction, while a mixture of both contaminants has no effect. In addition, data showed that exposure to P100 resulted in increased levels of oxidative stress enzyme activities catalase (CAT) in the gills and digestive glands. A similar trend was also observed in the digestive glands of clams treated with ZnS100. In contrast, CAT activity was decreased in the gills at the same concentration. Exposure to ZnS100 and P100 separately leads to a decrease in acetylcholinesterase (AChE) levels in both gills and digestive glands. Thus, AChE and CAT after co-exposure to an environmental mixture of nanoparticles (ZnS100) and phosphonate (P100) did not show any differences between treated and non-treated clams. The outcome of this work certifies the use of biomarkers and chemical assay when estimating the effects of phosphonate and nanoparticles as part of an ecotoxicological assessment program. An exceptional focus was given to the interaction between ZnS NPs and P. The antioxidant activity of P has been demonstrated to have an additive effect on metal accumulation and antagonistic agents against oxidative stress in clams treated with ZnS NPs.

Invited review - the effects of anthropogenic abiotic stressors on the sensory systems of fishes

Climate change is a growing global issue with many countries and institutions declaring a climate state of emergency. Excess CO₂ from anthropogenic sources and changes in land use practices are contributing to many detrimental changes, including increased global temperatures, ocean acidification and hypoxic zones along coastal habitats. All senses are important for aquatic animals, as it is how they can perceive and respond to their environment. Some of these environmental challenges have been shown to impair their sensory systems, including the olfactory, visual, and auditory systems. While most of the research is focused on how ocean acidification affects olfaction, there is also evidence that it negatively affects vision and hearing. The effects that temperature and hypoxia have on the senses have also been investigated, but to a much lesser extent in comparison to ocean acidification. This review assembles the known information on how these anthropogenic challenges affect the sensory systems of fishes, but also highlights what gaps in knowledge remain with suggestions for immediate action. Olfaction, vision, otolith, pH, freshwater, seawater, marine, central nervous system, electrophysiology, mechanism.

ES-Screen: A Novel Electrostatics-Driven Method for Drug Discovery Virtual Screening

Electrostatic interactions drive biomolecular interactions and associations. Computational modeling of electrostatics in biomolecular systems, such as protein-ligand, protein-protein, and protein-DNA, has provided atomistic insights into the binding process. In drug discovery, finding biologically plausible ligand-protein target interactions is challenging as current virtual screening and adjuvant techniques such as docking methods do not provide optimal treatment of electrostatic interactions. This study describes a novel electrostatics-driven virtual screening method called 'ES-Screen' that performs well across diverse protein target systems. ES-Screen provides a unique treatment of electrostatic interaction energies independent of total electrostatic free energy, typically employed by current software. Importantly, ES-Screen uses initial ligand pose input obtained from a receptor-based pharmacophore, thus independent of molecular docking. ES-Screen integrates individual polar and nonpolar replacement energies, which are the energy costs of replacing the cognate ligand for a target with a query ligand from the screening. This uniquely optimizes thermodynamic stability in electrostatic and nonpolar interactions relative to an experimentally determined stable binding state. ES-Screen also integrates chemometrics through shape and other physicochemical properties to prioritize query ligands with the greatest physicochemical similarities to the cognate ligand. The applicability of ES-Screen is demonstrated with in vitro experiments by identifying novel targets for many drugs. The present version includes a combination of many other descriptor components that, in a future version, will be purely based on electrostatics. Therefore, ES-Screen is a first-in-class unique electrostatics-driven virtual screening method with a unique implementation of replacement electrostatic interaction energies with broad applicability in drug discovery.

The emerging potential of interactive virtual reality in drug discovery

INTRODUCTION

The potential of virtual reality (VR) to contribute to drug design and development has been recognized for many years. A recent advance is to use VR not only to visualize and interact with molecules, but also to interact with molecular dynamics simulations 'on the fly' (interactive molecular dynamics in VR, IMD-VR), which is useful for flexible docking and examining binding processes and conformational changes.

AREAS COVERED

The authors use the term 'interactive VR' to refer to software where interactivity is an inherent part of the user VR experience e.g. in making structural modifications or interacting with a physically rigorous molecular dynamics (MD) simulation, as opposed to using VR controllers to rotate and translate the molecule for enhanced visualization. Here, they describe these methods and their application to problems relevant to drug discovery, highlighting the possibilities that they offer in this arena.

EXPERT OPINION

The ease of viewing and manipulating molecular structures and dynamics, using accessible VR hardware, and the ability to modify structures on the fly (e.g. adding or deleting atoms) - and for groups of researchers to work together in the same virtual environment - makes modern interactive VR a valuable tool to add to the armory of drug design and development methods.

Novel US-CpHMD Protocol to Study the Protonation-Dependent Mechanism of the ATP/ADP Carrier

We have designed a protocol combining constant-pH molecular dynamics (CpHMD) simulations with an umbrella sampling (US) scheme (US-CpHMD) to study the mechanism of ADP/ATP transport (import and export) by their inner mitochondrial membrane carrier protein [ADP/ATP carrier (AAC)]. The US scheme helped overcome the limitations of sampling the slow kinetics involved in these substrates' transport, while CpHMD simulations provided an unprecedented realism by correctly capturing the associated protonation changes. The import of anionic substrates along the mitochondrial membrane has a strong energetic disadvantage due to a smaller substrate concentration and an unfavorable membrane potential. These limitations may have created an evolutionary pressure on AAC to develop specific features benefiting the import of ADP. In our work, the potential of mean force profiles showed a clear selectivity in the import of ADP compared to ATP, while in the export, no selectivity was observed. We also observed that AAC sequestered both substrates at longer distances in the import compared to the export process. Furthermore, only in the import process do we observe transient protonation of both substrates when going through the AAC cavity, which is an important advantage to counteract the unfavorable mitochondrial membrane potential. Finally, we observed a substrate-induced disruption of the matrix salt-bridge network, which can promote the conformational transition (from the C- to M-state) required to complete the import process. This work unraveled several important structural features where the complex electrostatic interactions were pivotal to interpreting the protein function and illustrated the potential of applying the US-CpHMD protocol to other transport processes involving membrane proteins.

Classification of protein-protein association rates based on biophysical informatics

BACKGROUND

Proteins form various complexes to carry out their versatile functions in cells. The dynamic properties of protein complex formation are mainly characterized by the association rates which measures how fast these complexes can be formed. It was experimentally observed that the association rates span an extremely wide range with over ten orders of magnitudes. Identification of association rates within this spectrum for specific protein complexes is therefore essential for us to understand their functional roles.

RESULTS

To tackle this problem, we integrate physics-based coarse-grained simulations into a neural-network-based classification model to estimate the range of association rates for protein complexes in a large-scale benchmark set. The cross-validation results show that, when an optimal threshold was selected, we can reach the best performance with specificity, precision, sensitivity and overall accuracy all higher than 70%. The quality of our cross-validation data has also been testified by further statistical analysis. Additionally, given an independent testing set, we can successfully predict the group of association rates for eight protein complexes out of ten. Finally, the analysis of failed cases suggests the future implementation of conformational dynamics into simulation can further improve model.

CONCLUSIONS

In summary, this study demonstrated that a new modeling framework that combines biophysical simulations with bioinformatics approaches is able to identify protein-protein interactions with low association rates from those with higher association rates. This method thereby can serve as a useful addition to a collection of existing experimental approaches that measure biomolecular recognition.

Ocean Acidification Amplifies the Olfactory Response to 2-Phenylethylamine: Altered Cue Reception as a Mechanistic Pathway?

With carbon dioxide (CO₂) levels rising dramatically, climate change threatens marine environments. Due to increasing CO₂ concentrations in the ocean, pH levels are expected to drop by 0.4 units by the end of the century. There is an urgent need to understand the impact of ocean acidification on chemical-ecological processes. To date, the extent and mechanisms by which the decreasing ocean pH influences chemical communication are unclear. Combining behaviour assays with computational chemistry, we explore the function of the predator related cue 2-phenylethylamine (PEA) for hermit crabs (Pagurus bernhardus) in current and end-of-the-century oceanic pH. Living in intertidal environments, hermit crabs face large pH fluctuations in their current habitat in addition to climate-change related ocean acidification. We demonstrate that the dietary predator cue PEA for mammals and sea lampreys is an attractant for hermit crabs, with the potency of the cue increasing with decreasing pH levels. In order to explain this increased potency, we assess changes to PEA’s conformational and charge-related properties as one potential mechanistic pathway. Using quantum chemical calculations validated by NMR spectroscopy, we characterise the different protonation states of PEA in water. We show how protonation of PEA could affect receptor-ligand binding, using a possible model receptor for PEA (human TAAR1). Investigating potential mechanisms of pH-dependent effects on olfactory perception of PEA and the respective behavioural response, our study advances the understanding of how ocean acidification interferes with the sense of smell and thereby might impact essential ecological interactions in marine ecosystems.

Mechanisms of ligand binding

Many processes in chemistry and biology involve interactions of a ligand with its molecular target. Interest in the mechanism governing such interactions has dominated theoretical and experimental analysis for over a century. The interpretation of molecular recognition has evolved from a simple rigid body association of the ligand with its target to appreciation of the key role played by conformational transitions. Two conceptually distinct descriptions have had a profound impact on our understanding of mechanisms of ligand binding. The first description, referred to as induced fit, assumes that conformational changes follow the initial binding step to optimize the complex between the ligand and its target. The second description, referred to as conformational selection, assumes that the free target exists in multiple conformations in equilibrium and that the ligand selects the optimal one for binding. Both descriptions can be merged into more complex reaction schemes that better describe the functional repertoire of macromolecular systems. This review deals with basic mechanisms of ligand binding, with special emphasis on induced fit, conformational selection, and their mathematical foundations to provide rigorous context for the analysis and interpretation of experimental data. We show that conformational selection is a surprisingly versatile mechanism that includes induced fit as a mathematical special case and even captures kinetic properties of more complex reaction schemes. These features make conformational selection a dominant mechanism of molecular recognition in biology, consistent with the rich conformational landscape accessible to biological macromolecules being unraveled by structural biology.

Increased surface charge in the protein chaperone Spy enhances its anti-aggregation activity

Chaperones are essential components of the protein homeostasis network. There is a growing interest in optimizing chaperone function, but exactly how to achieve this aim is unclear. Here, using a model chaperone, the bacterial protein Spy, we demonstrate that substitutions that alter the electrostatic potential of Spy's concave, client-binding surface enhance Spy's anti-aggregation activity. We show that this strategy is more efficient than one that enhances the hydrophobicity of Spy's surface. Our findings thus challenge the traditional notion that hydrophobic interactions are the major driving forces that guide chaperone-substrate binding. Kinetic data revealed that both charge- and hydrophobicity-enhanced Spy variants release clients more slowly, resulting in a greater "holdase" activity. However, increasing short-range hydrophobic interactions deleteriously affected Spy's ability to capture substrates, thus reducing its in vitro chaperone activity toward fast-aggregating substrates. Our strategy in chaperone surface engineering therefore sought to fine-tune the different molecular forces involved in chaperone-substrate interactions rather than focusing on enhancing hydrophobic interactions. These results improve our understanding of the mechanistic basis of chaperone-client interactions and illustrate how protein surface-based mutational strategies can facilitate the rational improvement of molecular chaperones.

Protein electrostatics: From computational and structural analysis to discovery of functional fingerprints and biotechnological design

Computationally driven engineering of proteins aims to allow them to withstand an extended range of conditions and to mediate modified or novel functions. Therefore, it is crucial to the biotechnological industry, to biomedicine and to afford new challenges in environmental sciences, such as biocatalysis for green chemistry and bioremediation. In order to achieve these goals, it is important to clarify molecular mechanisms underlying proteins stability and modulating their interactions. So far, much attention has been given to hydrophobic and polar packing interactions and stability of the protein core. In contrast, the role of electrostatics and, in particular, of surface interactions has received less attention. However, electrostatics plays a pivotal role along the whole life cycle of a protein, since early folding steps to maturation, and it is involved in the regulation of protein localization and interactions with other cellular or artificial molecules. Short- and long-range electrostatic interactions, together with other forces, provide essential guidance cues in molecular and macromolecular assembly. We report here on methods for computing protein electrostatics and for individual or comparative analysis able to sort proteins by electrostatic similarity. Then, we provide examples of electrostatic analysis and fingerprints in natural protein evolution and in biotechnological design, in fields as diverse as biocatalysis, antibody and nanobody engineering, drug design and delivery, molecular virology, nanotechnology and regenerative medicine.

[Ligand-receptor binding kinetics in drug design]

Traditionally, the thermodynamic values of affinity are considered as the main criterion for the development of new drugs. Usually, these values for drugs are measured <i>in vitro</i> at steady concentrations of the receptor and ligand, which are differed from <i>in vivo</i> environment. Recent studies have shown that the kinetics of the process of drug binding to its receptor make significant contribution in the drug effectiveness. This has increased attention in characterizing and predicting the rate constants of association and dissociation of the receptor ligand at the stage of preclinical studies of drug candidates. A drug with a long residence time can determine ligand-receptor selectivity (kinetic selectivity), maintain pharmacological activity of the drug at its low concentration in vivo. The paper discusses the theoretical basis of protein-ligand binding, molecular determinants that control the kinetics of the drug-receptor binding. Understanding the molecular features underlying the kinetics of receptor-ligand binding will contribute to the rational design of drugs with desired properties.

Upregulation of acetylcholinesterase caused by downregulation of microRNA-132 is responsible for the development of dementia after ischemic stroke

MicroRNA-132 (miR-132) has been shown to participate in many diseases. This study aimed to understand the correlation between the level of miR-132 and the severity of dementia post-ischemic stroke. An online tool (www.mirdb.org) was used to find the miR-132 binding site in acetylcholinesterase (ACHE) 3'-untranslated region (UTR), followed by a luciferase reporter assay to validate ACHE as a miR-132 target. A similar relationship between miR-132 and ACHE was also established in cerebrospinal fluid samples collected from human subjects. A negative correlation was established between ACHE and miR-132 by measuring the relative luciferase activity. Meanwhile, Western blot analysis and real-time polymerase chain reaction were also conducted to compare the levels of ACHE messenger RNA and protein between two groups (dementia positive, n = 26 and dementia negative, n = 26) or among cells treated with miR-132 mimics, ACHE small interfering RNA, and miR-132 inhibitors. As shown in the results, miR-132 can reduce the expression of ACHE. Further experiments were also carried out to study the effect of miR-132 and ACHE on cell viability and apoptosis, and the results demonstrated that miR-132 enhanced cell viability while suppressing apoptosis. In addition, ACHE reduced cell viability while promoting apoptosis. miR-132 targeted ACHE and suppressed its expression. Additionally, miR-132 and ACHE have been shown to affect the cell viability and apoptosis in the central nervous system.

Neurobiology and therapeutic utility of neurotoxins targeting postsynaptic mechanisms of neuromuscular transmission

The neuromuscular junction (NMJ) is the principal site for the translation of motor neurochemical signals to muscle activity. Therefore, the release and sensing machinery of acetylcholine (ACh) along with muscle contraction are two of the main targets of natural toxins and pathogens, causing paralysis. Given pharmacology and medical advances, the active ingredients of toxins that target postsynaptic mechanisms have become of major interest, showing promise as drug leads. Herein, we review key facets of prevalent toxins modulating the mechanisms of ACh sensing and generation of the postsynaptic response, with muscle contraction. We consider the correlation between their outstanding selectivity and potency plus effects on motor function, and discuss emerging data advocating their usage for the development of therapies alleviating neuromuscular dysfunction.

Enhancement of RNA/Ligand Association Kinetics via an Electrostatic Anchor

The diverse biological processes mediated by RNA rest upon its recognition of various ligands, including small molecules and nucleic acids. Nevertheless, a recent literature survey suggests that RNA molecular recognition of these ligands is slow, with association rate constants orders of magnitude below the diffusional limit. Thus, we were prompted to consider strategies for increasing RNA association kinetics. Proteins can accelerate ligand association via electrostatic forces, and here, using the Tetrahymena group I ribozyme, we provide evidence that electrostatic forces can accelerate RNA/ligand association. This RNA enzyme (E) catalyzes cleavage of an oligonucleotide substrate (S) by an exogenous guanosine (G) cofactor. The G 2′- and 3′-OH groups interact with an active site metal ion, termed M_C, within E·S·G, and we perturbed each of these contacts via −NH₃⁺ substitution. New and prior data indicate that G(2′NH₃⁺) and G(3′NH₃⁺) bind as strongly as G, suggesting that the −NH₃⁺ substituents of these analogues avoid repulsive interactions with M_C and make alternative interactions. Unexpectedly, removal of the adjacent −OH via −H substitution to give G(2′H,3′NH₃⁺) and G(2′NH₃⁺_,3′H) enhanced binding, in stark contrast to the deleterious effect of these substitutions on G binding. Pulse–chase experiments indicate that the −NH₃⁺ moiety of G(2′H,3′NH₃⁺) increases the rate of G association. These results suggest that the positively charged −NH₃⁺ group can act as a molecular “anchor” to increase the residence time of the encounter complex and thereby enhance productive binding. Electrostatic anchors may provide a broadly applicable strategy for the development of fast binding RNA ligands and RNA-targeted therapeutics.

Drug-Target Association Kinetics in Drug Discovery

The important role of ligand-receptor binding kinetics in drug design and discovery is increasingly recognized by the drug research community. Over the past decade, accumulating evidence has shown that optimizing the ligand's dissociation rate constant can lead to desirable duration of in vivo target occupancy and, hence, improved pharmacodynamic properties. However, the association rate constant as a pharmacological principle remains less investigated, whereas it can play an equally important role in the selection of drug candidates. This review provides a compilation and discussion of otherwise scarce and dispersed information on this topic, bringing to light the importance of drug-target association in kinetics-directed drug design and discovery.

Unbiased Atomistic Insight into the Mechanisms and Solvent Role for Globular Protein Dimer Dissociation

Association and dissociation of proteins are fundamental processes in nature. Although simple to understand conceptually, the details of the underlying mechanisms and role of the solvent are poorly understood. Here, we investigate the dissociation of the hydrophilic β-lactoglobulin dimer by employing transition path sampling. Analysis of the sampled path ensembles reveals a variety of mechanisms: (1) a direct aligned dissociation (2) a hopping and rebinding transition followed by unbinding, and (3) a sliding transition before unbinding. Reaction coordinate and transition-state analysis predicts that, besides native contact and neighboring salt-bridge interactions, solvent degrees of freedom play an important role in the dissociation process. Bridging waters, hydrogen-bonded to both proteins, support contacts in the native state and nearby lying transition-state regions, whereas they exhibit faster dynamics in further lying transition-state regions, rendering the proteins more mobile and assisting in rebinding. Analysis of the structure and dynamics of the solvent molecules reveals that the dry native interface induces enhanced populations of both disordered hydration water near hydrophilic residues and tetrahedrally ordered hydration water nearby hydrophobic residues. Although not exhaustive, our sampling of rare unbiased reactive molecular dynamics trajectories enhances the understanding of protein dissociation via complex pathways including (multiple) rebinding events.

Peeking at G-protein-coupled receptors through the molecular dynamics keyhole

Molecular dynamics is a state of the art computational tool for the investigation of biophysics phenomenon at a molecular scale, as it enables the modeling of dynamic processes, such as conformational motions, molecular solvation and ligand binding. The recent advances in structural biology have led to a bloom in published G-protein-coupled receptor structures, representing a solid and valuable resource for molecular dynamics studies. During the last decade, indeed, a plethora of physiological and pharmacological facets of this membrane protein superfamily have been addressed by means of molecular dynamics simulations, including the activation mechanism, allosterism and, very recently, biased signaling. Here, we try to recapitulate some of the main contributions that molecular dynamics has recently produced in the field.

Slow molecular recognition by RNA

Molecular recognition is central to biological processes, function, and specificity. Proteins associate with ligands with a wide range of association rate constants, with maximal values matching the theoretical limit set by the rate of diffusional collision. As less is known about RNA association, we compiled association rate constants for all RNA/ligand complexes that we could find in the literature. Like proteins, RNAs exhibit a wide range of association rate constants. However, the fastest RNA association rates are considerably slower than those of the fastest protein associations and fall well below the diffusional limit. The apparently general observation of slow association with RNAs has implications for evolution and for modern-day biology. Our compilation highlights a quantitative molecular property that can contribute to biological understanding and underscores our need to develop a deeper physical understanding of molecular recognition events.

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.

Kinetic Insights into the Binding between the nSH3 Domain of CrkII and Proline-Rich Motifs in cAbl

The interaction between CrkII and cAbl is implicated in diverse cellular processes. This interaction starts with the binding of the N-terminal Src homology 3 (nSH3) domain of CrkII to the proline-rich motifs of cAbl (PRMs^cAbl). Despite its critical importance, the detailed binding mechanism between the nSH3 domain and PRMs remains elusive. In this study, we used nuclear magnetic resonance Carr-Purcell-Meiboom-Gill relaxation dispersion experiment to study the binding kinetics between the nSH3 domain of CrkII and PRMs^cAbl. Our results highlight that the nSH3 domain binds to three PRMs^cAbl with very high on- and off-rate constants, indicating the transient nature of the binding. To further characterize the binding transition state, we conducted the Eyring and linear free energy relationship analyses using temperature-dependent kinetic data. These data indicate that the binding transition state of the nSH3 domain and PRM is accompanied by small activation enthalpy, owing to partial desolvation of the transition state. These results also highlight the similarity between the transition and free states, in terms of structure and energetics. Although the binding of the nSH3 domain and PRM displays the features consistent with a diffusion-limited process within our experimental conditions, further tests are necessary to determine if the binding is a true diffusion-limited process.

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning

Protein–protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

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.

Electrostatic attraction of weak monoacid anions increases probability for protonation and passage through aquaporins

A positive electrostatic field emanating from the center of the aquaporin (AQP) water and solute channel is responsible for the repulsion of cations. At the same time, however, a positive field will attract anions. In this regard, l-lactate/lactic acid permeability has been shown for various isoforms of the otherwise highly water and neutral substrate selective AQP family. The structural requirements rendering certain AQPs permeable for weak monoacids and the mechanism of conduction have remained unclear. Here, we show by profiling pH-dependent substrate permeability, measurements of media alkalization, and proton decoupling that AQP9 acts as a channel for the protonated, neutral monocarboxylic acid species. Intriguingly, the obtained permeability rates indicate an up to 10 times higher probability of passage via AQP9 than given by the fraction of the protonated acid substrate at a certain pH. We generated AQP9 point mutants showing that this effect is independent from properties of the channel interior but caused by the protein surface electrostatics. Monocarboxylic acid-conducting AQPs thus employ a mechanism similar to the family of formate-nitrite transporters for weak monoacids. On a more general basis, our data illustrate semiquantitatively the contribution of surface electrostatics to the interaction of charged molecule substrates or ligands with target proteins, such as channels, transporters, enzymes, or receptors.

Elucidating the Origin of Long Residence Time Binding for Inhibitors of the Metalloprotease Thermolysin

Kinetic parameters of protein-ligand interactions are progressively acknowledged as valuable information for rational drug discovery. However, a targeted optimization of binding kinetics is not easy to achieve, and further systematic studies are necessary to increase the understanding about molecular mechanisms involved. We determined association and dissociation rate constants for 17 inhibitors of the metalloprotease thermolysin by surface plasmon resonance spectroscopy and correlated kinetic data with high-resolution crystal structures in complex with the protein. From the structure-kinetics relationship, we conclude that the strength of interaction with Asn112 correlates with the rate-limiting step of dissociation. This residue is located at the beginning of a β-strand motif that lines the binding cleft and is commonly believed to align a substrate for catalysis. A reduced mobility of the Asn112 side chain owing to an enhanced engagement in charge-assisted hydrogen bonds prevents the conformational adjustment associated with ligand release and transformation of the enzyme to its open state. This hypothesis is supported by kinetic data of ZF^PLA, a known pseudopeptidic inhibitor of thermolysin, which blocks the conformational transition of Asn112. Interference with this retrograde induced-fit mechanism results in variation of the residence time of thermolysin inhibitors by a factor of 74 000. The high conservation of this structural motif within the M4 and M13 metalloprotease families underpins the importance of this feature and has significant implications for drug discovery.

Charged Substrate and Product Together Contribute Like a Nonreactive Species to the Overall Electrostatic Steering in Diffusion-Reaction Processes

The Debye-Hückel limiting law is used to study the binding kinetics of substrate-enzyme system as well as to estimate the reaction rate of a electrostatically steered diffusion-controlled reaction process. It is based on a linearized Poisson-Boltzmann model and known for its accurate predictions in dilute solutions. However, the substrate and product particles are in nonequilibrium states and are possibly charged, and their contributions to the total electrostatic field cannot be explicitly studied in the Poisson-Boltzmann model. Hence the influences of substrate and product on reaction rate coefficient were not known. In this work, we consider all the charged species, including the charged substrate, product, and mobile salt ions in a Poisson-Nernst-Planck model, and then compare the results with previous work. The results indicate that both the charged substrate and product can significantly influence the reaction rate coefficient with different behaviors under different setups of computational conditions. It is interesting to find that when substrate and product are both considered, under an overall neutral boundary condition for all the bulk charged species, the computed reaction rate kinetics recovers a similar Debye-Hückel limiting law again. This phenomenon implies that the charged product counteracts the influence of charged substrate on reaction rate coefficient. Our analysis discloses the fact that the total charge concentration of substrate and product, though in a nonequilibrium state individually, obeys an equilibrium Boltzmann distribution, and therefore contributes as a normal charged ion species to ionic strength. This explains why the Debye-Hückel limiting law still works in a considerable range of conditions even though the effects of charged substrate and product particles are not specifically and explicitly considered in the theory.

Accelerating the Association of the Most Stable Protein-Ligand Complex by More than Two Orders of Magnitude

The complex between the bacterial type 1 pilus subunit FimG and the peptide corresponding to the N-terminal extension (termed donor strand, Ds) of the partner subunit FimF (DsF) shows the strongest reported noncovalent molecular interaction, with a dissociation constant (KD ) of 1.5×10(-20)  m. However, the complex only exhibits a slow association rate of 330 m(-1)  s(-1) that limits technical applications, such as its use in affinity purification. Herein, a structure-based approach was used to design pairs of FimGt (a FimG variant lacking its own N-terminal extension) and DsF variants with enhanced electrostatic surface complementarity. Association of the best mutant FimGt/DsF pairs was accelerated by more than two orders of magnitude, while the dissociation rates and 3D structures of the improved complexes remained essentially unperturbed. A KD  value of 8.8×10(-22)  m was obtained for the best mutant complex, which is the lowest value reported to date for a protein/ligand complex.

Forces Driving Chaperone Action

It is still unclear what molecular forces drive chaperone-mediated protein folding. Here, we obtain a detailed mechanistic understanding of the forces that dictate the four key steps of chaperone-client interaction: initial binding, complex stabilization, folding, and release. Contrary to the common belief that chaperones recognize unfolding intermediates by their hydrophobic nature, we discover that the model chaperone Spy uses long-range electrostatic interactions to rapidly bind to its unfolded client protein Im7. Short-range hydrophobic interactions follow, which serve to stabilize the complex. Hydrophobic collapse of the client protein then drives its folding. By burying hydrophobic residues in its core, the client's affinity to Spy decreases, which causes client release. By allowing the client to fold itself, Spy circumvents the need for client-specific folding instructions. This mechanism might help explain how chaperones can facilitate the folding of various unrelated proteins.

Numerical calculation of protein-ligand binding rates through solution of the Smoluchowski equation using smoothed particle hydrodynamics

Background

The calculation of diffusion-controlled ligand binding rates is important for understanding enzyme mechanisms as well as designing enzyme inhibitors.

Methods

We demonstrate the accuracy and effectiveness of a Lagrangian particle-based method, smoothed particle hydrodynamics (SPH), to study diffusion in biomolecular systems by numerically solving the time-dependent Smoluchowski equation for continuum diffusion. Unlike previous studies, a reactive Robin boundary condition (BC), rather than the absolute absorbing (Dirichlet) BC, is considered on the reactive boundaries. This new BC treatment allows for the analysis of enzymes with “imperfect” reaction rates.

Results

The numerical method is first verified in simple systems and then applied to the calculation of ligand binding to a mouse acetylcholinesterase (mAChE) monomer. Rates for inhibitor binding to mAChE are calculated at various ionic strengths and compared with experiment and other numerical methods. We find that imposition of the Robin BC improves agreement between calculated and experimental reaction rates.

Conclusions

Although this initial application focuses on a single monomer system, our new method provides a framework to explore broader applications of SPH in larger-scale biomolecular complexes by taking advantage of its Lagrangian particle-based nature.

Electrostatic interactions in the binding pathway of a transient protein complex studied by NMR and isothermal titration calorimetry

Much of our knowledge of protein binding pathways is derived from extremely stable complexes that interact very tightly, with lifetimes of hours to days. Much less is known about weaker interactions and transient complexes because these are challenging to characterize experimentally. Nevertheless, these types of interactions are ubiquitous in living systems. The combination of NMR relaxation dispersion Carr-Purcell-Meiboom-Gill (CPMG) experiments and isothermal titration calorimetry allows the quantification of rapid binding kinetics for complexes with submillisecond lifetimes that are difficult to study using conventional techniques. We have used this approach to investigate the binding pathway of the Src homology 3 (SH3) domain from the Fyn tyrosine kinase, which forms complexes with peptide targets whose lifetimes are on the order of about a millisecond. Long range electrostatic interactions have been shown to play a critical role in the binding pathways of tightly binding complexes. The role of electrostatics in the binding pathways of transient complexes is less well understood. Similarly to previously studied tight complexes, we find that SH3 domain association rates are enhanced by long range electrostatics, whereas short range interactions are formed late in the docking process. However, the extent of electrostatic association rate enhancement is several orders of magnitudes less, whereas the electrostatic-free basal association rate is significantly greater. Thus, the SH3 domain is far less reliant on electrostatic enhancement to achieve rapid association kinetics than are previously studied systems. This suggests that there may be overall differences in the role played by electrostatics in the binding pathways of extremely stable versus transient complexes.

Neuronal AChE splice variants and their non-hydrolytic functions: redefining a target of AChE inhibitors?

AChE enzymatic inhibition is a core focus of pharmacological intervention in Alzheimer's disease (AD). Yet, AChE has also been ascribed non-hydrolytic functions, which seem related to its appearance in various isoforms. Neuronal AChE presents as a tailed form (AChE-T) predominantly found on the neuronal synapse, and a facultatively expressed readthough form (AChE-R), which exerts short to medium-term protective effects. Notably, this latter form is also found in the periphery. While these non-hydrolytic functions of AChE are most controversially discussed, there is evidence for them being additional targets of AChE inhibitors. This review aims to provide clarification as to the role of these AChE splice variants and their interplay with other cholinergic parameters and their being targets of AChE inhibition: AChE-R is particularly involved in the mediation of (anti-)apoptotic events in cholinergic cells, involving adaptation of various cholinergic parameters and a time-dependent link to the expression of neuroprotective factors. The AChE-T C-terminus is central to AChE activity regulation, while isolated AChE-T C-terminal fragments mediate toxic effects via the α7 nicotinic acetylcholine receptor. There is direct evidence for roles of AChE-T and AChE-R in neurodegeneration and neuroprotection, with these roles involving AChE as a key modulator of the cholinergic system: in vivo data further encourages the use of AChE inhibitors in the treatment of neurodegenerative conditions such as AD since effects on both enzymatic activity and the enzyme's non-hydrolytic functions can be postulated. It also suggests that novel AChE inhibitors should enhance protective AChE-R, while avoiding the concomitant up-regulation of AChE-T.

Equilibrium and dynamic design principles for binding molecules engineered for reagentless biosensors

Reagentless biosensors rely on the interaction of a binding partner and its target to generate a change in fluorescent signal using an environment-sensitive fluorophore or Förster resonance energy transfer. Binding affinity can exert a significant influence on both the equilibrium and the dynamic response characteristics of such a biosensor. We here develop a kinetic model for the dynamic performance of a reagentless biosensor. Using a sinusoidal signal for ligand concentration, our findings suggest that it is optimal to use a binding moiety whose equilibrium dissociation constant matches that of the average predicted input signal, while maximizing both the association rate constant and the dissociation rate constant at the necessary ratio to create the desired equilibrium constant. Although practical limitations constrain the attainment of these objectives, the derivation of these design principles provides guidance for improved reagentless biosensor performance and metrics for quality standards in the development of biosensors. These concepts are broadly relevant to reagentless biosensor modalities.

Predicting affinity- and specificity-enhancing mutations at protein-protein interfaces

Manipulations of PPIs (protein-protein interactions) are important for many biological applications such as synthetic biology and drug design. Combinatorial methods have been traditionally used for such manipulations, failing, however, to explain the effects achieved. We developed a computational method for prediction of changes in free energy of binding due to mutation that bring about deeper understanding of the molecular forces underlying binding interactions. Our method could be used for computational scanning of binding interfaces and subsequent analysis of the interfacial sequence optimality. The computational method was validated in two biological systems. Computational saturated mutagenesis of a high-affinity complex between an enzyme AChE (acetylcholinesterase) and a snake toxin Fas (fasciculin) revealed the optimal nature of this interface with only a few predicted affinity-enhancing mutations. Binding measurements confirmed high optimality of this interface and identified a few mutations that could further improve interaction fitness. Computational interface scanning of a medium-affinity complex between TIMP-2 (tissue inhibitor of metalloproteinases-2) and MMP (matrix metalloproteinase) 14 revealed a non-optimal nature of the binding interface with multiple mutations predicted to stabilize the complex. Experimental results corroborated our computational predictions, identifying a large number of mutations that improve the binding affinity for this interaction and some mutations that enhance binding specificity. Overall, our computational protocol greatly facilitates the discovery of affinity- and specificity-enhancing mutations and thus could be applied for design of potent and highly specific inhibitors of any PPI.

Mapping of the binding landscape for a picomolar protein-protein complex through computation and experiment

Our understanding of protein evolution would greatly benefit from mapping of binding landscapes, i.e., changes in protein-protein binding affinity due to all single mutations. However, experimental generation of such landscapes is a tedious task due to a large number of possible mutations. Here, we use a simple computational protocol to map the binding landscape for two homologous high-affinity complexes, involving a snake toxin fasciculin and acetylcholinesterase from two different species. To verify our computational predictions, we experimentally measure binding between 25 Fas mutants and the 2 enzymes. Both computational and experimental results demonstrate that the Fas sequence is close to the optimum when interacting with its targets, yet a few mutations could further improve Kd, kon, and koff. Our computational predictions agree well with experimental results and generate distributions similar to those observed in other high-affinity PPIs, demonstrating the potential of simple computational protocols in capturing realistic binding landscapes.

Interaction of acetylcholinesterase with neurexin-1β regulates glutamatergic synaptic stability in hippocampal neurons

Background

Excess expression of acetylcholinesterase (AChE) in the cortex and hippocampus causes a decrease in the number of glutamatergic synapses and alters the expression of neurexin and neuroligin, trans-synaptic proteins that control synaptic stability. The molecular sequence and three-dimensional structure of AChE are homologous to the corresponding aspects of the ectodomain of neuroligin. This study investigated whether excess AChE interacts physically with neurexin to destabilize glutamatergic synapses.

Results

The results showed that AChE clusters colocalized with neurexin assemblies in the neurites of hippocampal neurons and that AChE co-immunoprecipitated with neurexin from the lysate of these neurons. Moreover, when expressed in human embryonic kidney 293 cells, N-glycosylated AChE co-immunoprecipitated with non-O–glycosylated neurexin-1β, with N-glycosylation of the AChE being required for this co-precipitation to occur. Increasing extracellular AChE decreased the association of neurexin with neuroligin and inhibited neuroligin-induced synaptogenesis. The number and activity of excitatory synapses in cultured hippocampal neurons were reduced by extracellular catalytically inactive AChE.

Conclusions

Excessive glycosylated AChE could competitively disrupt a subset of the neurexin–neuroligin junctions consequently impairing the integrity of glutamatergic synapses. This might serve a molecular mechanism of excessive AChE induced neurodegeneration.

Remarkably fast coupled folding and binding of the intrinsically disordered transactivation domain of cMyb to CBP KIX

Association rates for interactions between folded proteins have been investigated extensively, allowing the development of computational and theoretical prediction methods. Less is known about association rates for complexes where one or more partner is initially disordered, despite much speculation about how they may compare to those for folded proteins. We have attached a fluorophore to the N-terminus of the 25 amino acid cMyb peptide used previously in NMR and equilibrium studies (termed FITC-cMyb), and used this to monitor the kinetics of its interaction with the KIX protein. We have investigated the ionic strength and temperature dependence of the kinetics, and conclude that the association process is extremely fast, apparently exceeding the rates predicted by formulations applicable to interactions between pairs of folded proteins. This is despite the fact that not all collisions result in complex formation (there is an observable activation energy for the association process). We propose that this is partially a result of the disordered nature of the FITC-cMyb peptide itself.

Slow, reversible, coupled folding and binding of the spectrin tetramerization domain

Many intrinsically disordered proteins (IDPs) are significantly unstructured under physiological conditions. A number of these IDPs have been shown to undergo coupled folding and binding reactions whereby they can gain structure upon association with an appropriate partner protein. In general, these systems display weaker binding affinities than do systems with association between completely structured domains, with micromolar K(d) values appearing typical. One such system is the association between α- and β-spectrin, where two partially structured, incomplete domains associate to form a fully structured, three-helix bundle, the spectrin tetramerization domain. Here, we use this model system to demonstrate a method for fitting association and dissociation kinetic traces where, using typical biophysical concentrations, the association reactions are expected to be highly reversible. We elucidate the unusually slow, two-state kinetics of spectrin assembly in solution. The advantages of studying kinetics in this regime include the potential for gaining equilibrium constants as well as rate constants, and for performing experiments with low protein concentrations. We suggest that this approach would be particularly appropriate for high-throughput mutational analysis of two-state reversible binding processes.