Rate Constants and Mechanisms of Protein-Ligand Binding

Computational design of an imine reductase: mechanism-guided stereoselectivity reversion and interface stabilization

Imine reductases (IREDs) are important biocatalysts in the asymmetric synthesis of chiral amines. However, a detailed understanding of the stereocontrol mechanism of IRED remains incomplete, making the design of IRED for producing the desired amine enantiomers challenging. In this study, we investigated the stereoselective catalytic mechanism and designed an (R)-stereoselective IRED from Paenibacillus mucilaginosus (PmIR) using pharmaceutically relevant 2-aryl-substituted pyrrolines as substrates. A putative mechanism for controlling stereoselectivity was proposed based on the crucial role of electrostatic interactions in controlling iminium cation orientation and employed to achieve complete inversion of stereoselectivity in PmIR using computational design. The variant PmIR-Re (Q138M/P140M/Y187E/Q190A/D250M/R251N) exhibited opposite (S)-stereoselectivity, with >96% enantiomeric excess (ee) towards tested 2-aryl-substituted pyrrolines. Computational tools were employed to identify stabilizing mutations at the interface between the two subunits. The variant PmIR-6P (P140A/Q190S/R251N/Q217E/A257R/T277M) showed a nearly 5-fold increase in activity and a 12 °C increase in melting temperature. The PmIR-6P successfully produced (R)-2-(2,5-difluorophenyl)-pyrrolidine, a key chiral pharmaceutical intermediate, at a concentration of 400 mM with an ee exceeding 99%. This study provides insight into the stereocontrol elements of IREDs and demonstrates the potential of computational design for tailored stereoselectivity and thermal stability.

Nonspecific vs. specific DNA binding free energetics of a transcription factor domain protein

Transcription factor (TF) proteins regulate gene expression by binding to specific sites on the genome. In the facilitated diffusion model, an optimized search process is achieved by the TF alternating between 3D diffusion in the bulk and 1D diffusion along DNA. While undergoing 1D diffusion, the protein can switch from a search mode for fast diffusion along nonspecific DNA to a recognition mode for stable binding to specific DNA. It was recently noticed that, for a small TF domain protein, reorientations on DNA happen between the nonspecific and specific DNA binding. We here conducted all-atom molecular dynamics simulations with steering forces to reveal the protein-DNA binding free energetics, confirming that the search and recognition modes are distinguished primarily by protein orientations on the DNA. As the binding free energy difference between the specific and nonspecific DNA system slightly deviates from that being estimated directly from dissociation constants on 15-bp DNA constructs, we hypothesize that the discrepancy can come from DNA sequences flanking the 6-bp central binding sites that impact on the dissociation kinetics measurements. The hypothesis is supported by a simplified spherical protein-DNA model along with stochastic simulations and kinetic modeling.

A multiscale predictive digital twin for neurocardiac modulation

Cardiac function is tightly regulated by the autonomic nervous system (ANS). Activation of the sympathetic nervous system increases cardiac output by increasing heart rate and stroke volume, while parasympathetic nerve stimulation instantly slows heart rate. Importantly, imbalance in autonomic control of the heart has been implicated in the development of arrhythmias and heart failure. Understanding of the mechanisms and effects of autonomic stimulation is a major challenge because synapses in different regions of the heart result in multiple changes to heart function. For example, nerve synapses on the sinoatrial node (SAN) impact pacemaking, while synapses on contractile cells alter contraction and arrhythmia vulnerability. Here, we present a multiscale neurocardiac modelling and simulator tool that predicts the effect of efferent stimulation of the sympathetic and parasympathetic branches of the ANS on the cardiac SAN and ventricular myocardium. The model includes a layered representation of the ANS and reproduces firing properties measured experimentally. Model parameters are derived from experiments and atomistic simulations. The model is a first prototype of a digital twin that is applied to make predictions across all system scales, from subcellular signalling to pacemaker frequency to tissue level responses. We predict conditions under which autonomic imbalance induces proarrhythmia and can be modified to prevent or inhibit arrhythmia. In summary, the multiscale model constitutes a predictive digital twin framework to test and guide high-throughput prediction of novel neuromodulatory therapy. KEY POINTS: A multi-layered model representation of the autonomic nervous system that includes sympathetic and parasympathetic branches, each with sparse random intralayer connectivity, synaptic dynamics and conductance based integrate-and-fire neurons generates firing patterns in close agreement with experiment. A key feature of the neurocardiac computational model is the connection between the autonomic nervous system and both pacemaker and contractile cells, where modification to pacemaker frequency drives initiation of electrical signals in the contractile cells. We utilized atomic-scale molecular dynamics simulations to predict the association and dissociation rates of noradrenaline with the β-adrenergic receptor. Multiscale predictions demonstrate how autonomic imbalance may increase proclivity to arrhythmias or be used to terminate arrhythmias. The model serves as a first step towards a digital twin for predicting neuromodulation to prevent or reduce disease.

Site Identification by Ligand Competitive Saturation-Biologics Approach for Structure-Based Protein Charge Prediction

Protein-based therapeutics typically require high concentrations of the active protein, which can lead to protein aggregation and high solution viscosity. Such solution behaviors can limit the stability, bioavailability, and manufacturability of protein-based therapeutics and are directly influenced by the charge of a protein. Protein charge is a system property affected by its environment, including the buffer composition, pH, and temperature. Thus, the charge calculated by summing the charges of each residue in a protein, as is commonly done in computational methods, may significantly differ from the effective charge of the protein as these calculations do not account for contributions from bound ions. Here, we present an extension of the structure-based approach termed site identification by ligand competitive saturation-biologics (SILCS-Biologics) to predict the effective charge of proteins. The SILCS-Biologics approach was applied on a range of protein targets in different salt environments for which membrane-confined electrophoresis-determined charges were previously reported. SILCS-Biologics maps the 3D distribution and predicted occupancy of ions, buffer molecules, and excipient molecules bound to the protein surface in a given salt environment. Using this information, the effective charge of the protein is predicted such that the concentrations of the ions and the presence of excipients or buffers are accounted for. Additionally, SILCS-Biologics also produces 3D structures of the binding sites of ions on the proteins, which enable further analyses such as the characterization of protein surface charge distribution and dipole moments in different environments. Notable is the capability of the method to account for competition between salts, excipients, and buffers on the calculated electrostatic properties in different protein formulations. Our study demonstrates the ability of the SILCS-Biologics approach to predict the effective charge of proteins and its applicability in uncovering protein-ion interactions and their contributions to protein solubility and function.

Interplay of Affinity and Surface Tethering in Protein Recognition

Surface-tethered ligand-receptor complexes are key components in biological signaling and adhesion. They also find increasing utility in single-molecule assays and biotechnological applications. Here, we study the real-time binding kinetics between various surface-immobilized peptide ligands and their unrestrained receptors. A long peptide tether increases the association of ligand-receptor complexes, experimentally proving the fly casting mechanism where the disorder accelerates protein recognition. On the other hand, a short peptide tether enhances the complex dissociation. Notably, the rate constants measured for the same receptor, but under different spatial constraints, are strongly correlated to one another. Furthermore, this correlation can be used to predict how surface tethering on a ligand-receptor complex alters its binding kinetics. Our results have immediate implications in the broad areas of biomolecular recognition, intrinsically disordered proteins, and biosensor technology.

De novo designed EBAI as a potential inhibitor of the viral protein BHRF1. Research in silico

Epstein-Barr virus is a DNA-containing virus that, according to current data, is associated with approximately 1% of all cancers in the world. This viral effect on the human body is associated with its pronounced antiapoptotic activity. An important role in this process is played by the protein BHRF1, which is a structural and functional homologue of antiapoptotic proteins of the BCL-2 family. In this study, we investigate the selective low molecular weight inhibitor of the above viral protein - EBAI (Epstein-Barr virus Antiapoptotic Inhibitor), which we designed using in silico methods. We conducted two parallel simulation experiments where EBAI was intentionally destabilized to demonstrate its high-affinity recognition potential of the BHRF1 pocket, which binds BH3.Thus, although the potential inhibitor was in close proximity to the site of interaction, it contacted it only through orientation interactions (hydrogen and Coulomb interactions). Despite this complication of the standard ligand-receptor complex simulation procedure, we demonstrated in two parallel computational experiments the high affinity of EBAI for the BH3-binding pocket of BHRF1. In both cases, in the first nanoseconds of modeling, our inhibitor underwent the necessary conformational rearrangements and formed all the required interactions for effective complexation. Thus, further in vitro studies are logical and necessary step to fully evaluate the potential of EBAI as an inhibitor of the antiapoptotic protein BHRF1 of Epstein-Barr virus.Communicated by Ramaswamy H. Sarma.

Multiscale Approach for Computing Gated Ligand Binding from Molecular Dynamics and Brownian Dynamics Simulations

We develop an approach to characterize the effects of gating by a multiconformation protein consisting of macrostate conformations that are either accessible or inaccessible to ligand binding. We first construct a Markov state model of the apo-protein from atomistic molecular dynamics simulations from which we identify macrostates and their conformations, compute their relative macrostate populations and interchange kinetics, and structurally characterize them in terms of ligand accessibility. We insert the calculated first-order rate constants for conformational transitions into a multistate gating theory from which we derive a gating factor γ that quantifies the degree of conformational gating. Applied to HIV-1 protease, our approach yields a kinetic network of three accessible (semi-open, open, and wide-open) and two inaccessible (closed and a newly identified, "parted") macrostate conformations. The parted conformation sterically partitions the active site, suggesting a possible role in product release. We find that the binding kinetics of drugs and drug-like inhibitors to HIV-1 protease falls in the slow gating regime. However, because γ = 0.75, conformational gating only modestly slows ligand binding. Brownian dynamics simulations of the diffusional association of eight inhibitors to the protease─having a wide range of experimental association constants (∼10⁴-10¹⁰ M^-1 s^-1)─yields gated rate constants in the range of ∼0.5-5.7 × 10⁸ M^-1 s^-1. This indicates that, whereas the association rate of some inhibitors could be described by the model, for many inhibitors either subsequent conformational transitions or alternate binding mechanisms may be rate-limiting. For systems known to be modulated by conformational gating, the approach could be scaled computationally efficiently to screen association kinetics for a large number of ligands.

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.

The Effects of Temperature and Pressure on Protein-Ligand Binding in the Presence of Mars-Relevant Salts

Simple Summary

Interactions of ligands with proteins are central to all reactions in the biological cell. How such reactions are affected by harsh environmental conditions, such as low temperatures, high pressures, and high concentrations of biologically destructive salts, is still largely unknown. Our work focused on specific salts found on Mars to understand whether the planet’s potentially liquid, water-rich subsurface harbors conditions that are theoretically favorable for life. Our data show that, while magnesium chloride and sulfate do not significantly alter protein–ligand interactions, the perchlorate ion strongly affects protein–ligand binding. However, the temperature and pressure conditions encountered on Mars do not necessarily preclude protein–ligand interactions of the type studied here.

Abstract

Protein–ligand interactions are fundamental to all biochemical processes. Generally, these processes are studied at ambient temperature and pressure conditions. We investigated the binding of the small ligand 8-anilinonaphthalene-1-sulfonic acid (ANS) to the multifunctional protein bovine serum albumin (BSA) at ambient and low temperatures and at high pressure conditions, in the presence of ions associated with the surface and subsurface of Mars, including the chaotropic perchlorate ion. We found that salts such as magnesium chloride and sulfate only slightly affect the protein–ligand complex formation. In contrast, magnesium perchlorate strongly affects the interaction between ANS and BSA at the single site level, leading to a change in stoichiometry and strength of ligand binding. Interestingly, both a decrease in temperature and an increase in pressure favor the ligand binding process, resulting in a negative change in protein–ligand binding volume. This suggests that biochemical reactions that are fundamental for the regulation of biological processes are theoretically possible outside standard temperature and pressure conditions, such as in the harsh conditions of the Martian subsurface.

Kinetics of the multitasking high-affinity Win binding site of WDR5 in restricted and unrestricted conditions

Recent advances in quantitative proteomics show that WD40 proteins play a pivotal role in numerous cellular networks. Yet, they have been fairly unexplored and their physical associations with other proteins are ambiguous. A quantitative understanding of these interactions has wide-ranging significance. WD40 repeat protein 5 (WDR5) interacts with all members of human SET1/MLL methyltransferases, which regulate methylation of the histone 3 lysine 4 (H3K4). Here, using real-time binding measurements in a high-throughput setting, we identified the kinetic fingerprint of transient associations between WDR5 and 14-residue WDR5 interaction (Win) motif peptides of each SET1 protein (SET1Win). Our results reveal that the high-affinity WDR5-SET1Win interactions feature slow association kinetics. This finding is likely due to the requirement of SET1Win to insert into the narrow WDR5 cavity, also named the Win binding site. Furthermore, our explorations indicate fairly slow dissociation kinetics. This conclusion is in accordance with the primary role of WDR5 in maintaining the functional integrity of a large multisubunit complex, which regulates the histone methylation. Because the Win binding site is considered a key therapeutic target, the immediate outcomes of this study could form the basis for accelerated developments in medical biotechnology.

Structure-Guided Development of Potent Benzoylurea Inhibitors of BCL-XL and BCL-2

The BCL-2 family of proteins (including the prosurvival proteins BCL-2, BCL-X_L, and MCL-1) is an important target for the development of novel anticancer therapeutics. Despite the challenges of targeting protein-protein interaction (PPI) interfaces with small molecules, a number of inhibitors (called BH3 mimetics) have entered the clinic and the BCL-2 inhibitor, ABT-199/venetoclax, is already proving transformative. For BCL-X_L, new validated chemical series are desirable. Here, we outline the crystallography-guided development of a structurally distinct series of BCL-X_L/BCL-2 inhibitors based on a benzoylurea scaffold, originally proposed as α-helix mimetics. We describe structure-guided exploration of a cryptic "p5" pocket identified in BCL-X_L. This work yields novel inhibitors with submicromolar binding, with marked selectivity toward BCL-X_L. Extension into the hydrophobic p2 pocket yielded the most potent inhibitor in the series, binding strongly to BCL-X_L and BCL-2 (nanomolar-range half-maximal inhibitory concentration (IC₅₀)) and displaying mechanism-based killing in cells engineered to depend on BCL-X_L for survival.

Molecular Mechanics Study of Flow and Surface Influence in Ligand-Protein Association

Ligand–protein association is the first and critical step for many biological and chemical processes. This study investigated the molecular association processes under different environments. In biology, cells have different compartments where ligand–protein binding may occur on a membrane. In experiments involving ligand–protein binding, such as the surface plasmon resonance and continuous flow biosynthesis, a substrate flow and surface are required in experimental settings. As compared with a simple binding condition, which includes only the ligand, protein, and solvent, the association rate and processes may be affected by additional ligand transporting forces and other intermolecular interactions between the ligand and environmental objects. We evaluated these environmental factors by using a ligand xk263 binding to HIV protease (HIVp) with atomistic details. Using Brownian dynamics simulations, we modeled xk263 and HIVp association time and probability when a system has xk263 diffusion flux and a non-polar self-assembled monolayer surface. We also examined different protein orientations and accessible surfaces for xk263. To allow xk263 to access to the dimer interface of immobilized HIVp, we simulated the system by placing the protein 20Å above the surface because immobilizing HIVp on a surface prevented xk263 from contacting with the interface. The non-specific interactions increased the binding probability while the association time remained unchanged. When the xk263 diffusion flux increased, the effective xk263 concentration around HIVp, xk263–HIVp association time and binding probability decreased non-linearly regardless of interacting with the self-assembled monolayer surface or not. The work sheds light on the effects of the solvent flow and surface environment on ligand–protein associations and provides a perspective on experimental design.

Markov State Models to Elucidate Ligand Binding Mechanism

Molecular dynamics simulations can now routinely access the microsecond timescale, making feasible direct sampling of ligand association events. While Markov State Model (MSM) approaches offer a useful framework for analyzing such trajectory data to gain insight into binding mechanisms, accurate modeling of ligand association pathways and kinetics must be done carefully. We describe methods and good practices for constructing MSMs of ligand binding from unbiased trajectory data and discuss how to use time-lagged independent component analysis (tICA) to build informative models, using as an example recent simulation work to model the binding of phenylalanine to the regulatory ACT domain dimer of phenylalanine hydroxylase. We describe a variety of methods for estimating association rates from MSMs and discuss how to distinguish between conformational selection and induced-fit mechanisms using MSMs. In addition, we review some examples of MSMs constructed to elucidate the mechanisms by which p53 transactivation domain (TAD) and related peptides bind the oncoprotein MDM2.

Understanding the Impacts of Conformational Dynamics on the Regulation of Protein-Protein Association by a Multiscale Simulation Method

Complexes formed among diverse proteins carry out versatile functions in nearly all physiological processes. Association rates which measure how fast proteins form various complexes are of fundamental importance to characterize their functions. The association rates are not only determined by the energetic features at binding interfaces of a protein complex but also influenced by the intrinsic conformational dynamics of each protein in the complex. Unfortunately, how this conformational effect regulates protein association has never been calibrated on a systematic level. To tackle this problem, we developed a multiscale strategy to incorporate the information on protein conformational variations from Langevin dynamic simulations into a kinetic Monte Carlo algorithm of protein-protein association. By systematically testing this approach against a large-scale benchmark set, we found the association of a protein complex with a relatively rigid structure tends to be reduced by its conformational fluctuations. With specific examples, we further show that higher degrees of structural flexibility in various protein complexes can facilitate the searching and formation of intermolecular interactions and thereby accelerate their associations. In general, the integration of conformational dynamics can improve the correlation between experimentally measured association rates and computationally derived association probabilities. Finally, we analyzed the statistical distributions of different secondary structural types on protein-protein binding interfaces and their preference to the change of association rates. Our study, to the best of our knowledge, is the first computational method that systematically estimates the impacts of protein conformational dynamics on protein-protein association. It throws lights on the molecular mechanisms of how protein-protein recognition is kinetically modulated.

Capturing Protein-Ligand Recognition Pathways in Coarse-Grained Simulation

Protein-ligand recognition is dynamic and complex. A key approach in deciphering the mechanism underlying the recognition process is to capture the kinetic process of the ligand in its act of binding to its designated protein cavity. Toward this end, ultralong all-atom molecular dynamics simulation has recently emerged as a popular method of choice because of its ability to record these events at high spatial and temporal resolution. However, success via this route comes at an exorbitant computational cost. Herein, we demonstrate that coarse-grained models of the protein, when systematically optimized to maintain its tertiary fold, can capture the complete process of spontaneous protein-ligand binding from bulk media to the cavity at crystallographic precision and within wall clock time that is orders of magnitude shorter than that of all-atom simulations. The exhaustive sampling of ligand exploration in protein and solvent, harnessed by coarse-grained simulation, leads to elucidation of new ligand recognition pathways and discovery of non-native binding poses.

Sequence-Dependent Correlated Segments in the Intrinsically Disordered Region of ChiZ

How sequences of intrinsically disordered proteins (IDPs) code for their conformational dynamics is poorly understood. Here, we combined NMR spectroscopy, small-angle X-ray scattering (SAXS), and molecular dynamics (MD) simulations to characterize the conformations and dynamics of ChiZ1-64. MD simulations, first validated by SAXS and secondary chemical shift data, found scant α-helices or β-strands but a considerable propensity for polyproline II (PPII) torsion angles. Importantly, several blocks of residues (e.g., 11–29) emerge as “correlated segments”, identified by their frequent formation of PPII stretches, salt bridges, cation-π interactions, and sidechain-backbone hydrogen bonds. NMR relaxation experiments showed non-uniform transverse relaxation rates (R₂s) and nuclear Overhauser enhancements (NOEs) along the sequence (e.g., high R₂s and NOEs for residues 11–14 and 23–28). MD simulations further revealed that the extent of segmental correlation is sequence-dependent; segments where internal interactions are more prevalent manifest elevated “collective” motions on the 5–10 ns timescale and suppressed local motions on the sub-ns timescale. Amide proton exchange rates provides corroboration, with residues in the most correlated segment exhibiting the highest protection factors. We propose the correlated segment as a defining feature for the conformations and dynamics of IDPs.

Ligand-binding assays with OBPs and CSPs

Assessing the ligand-binding properties of OBPs and CSPs is essential for understanding their physiological function. It also provides basic information when these proteins are used as biosensing elements for instrumental measurement of odors. Although different approaches have been applied in the past to evaluate the affinity of receptors and soluble binding proteins to their ligands, using a fluorescent reporter represents the method of choice for OBPs and CSPs. It offers the advantages of working at the equilibrium, being simple, fast and inexpensive, without requiring the use of radioactive tracers. However, as an indirect method, the fluorescence competitive binding approach presents drawbacks and sometimes requires an elaborate analysis to explain unexpected results. Here, after a brief survey of the different approaches to evaluate affinity constants, we focus on the fluorescence binding assay as applied to OBPs and CSPs, discussing situations that may require closer inspection of the results.

Alteration of Protein Binding Affinities by Aqueous Two-Phase Systems Revealed by Pressure Perturbation

Interactions between proteins and ligands, which are fundamental to many biochemical processes essential to life, are mostly studied at dilute buffer conditions. The effects of the highly crowded nature of biological cells and the effects of liquid-liquid phase separation inducing biomolecular droplet formation as a means of membrane-less compartmentalization have been largely neglected in protein binding studies. We investigated the binding of a small ligand (ANS) to one of the most multifunctional proteins, bovine serum albumin (BSA) in an aqueous two-phase system (ATPS) composed of PEG and Dextran. Also, aiming to shed more light on differences in binding mode compared to the neat buffer data, we examined the effect of high hydrostatic pressure (HHP) on the binding process. We observe a marked effect of the ATPS on the binding characteristics of BSA. Not only the binding constants change in the ATPS system, but also the integrity of binding sites is partially lost, which is most likely due to soft enthalpic interactions of the BSA with components in the dense droplet phase of the ATPS. Using pressure modulation, differences in binding sites could be unravelled by their different volumetric and hydration properties. Regarding the vital biological relevance of the study, we notice that extreme biological environments, such as HHP, can markedly affect the binding characteristics of proteins. Hence, organisms experiencing high-pressure stress in the deep sea need to finely adjust the volume changes of their biochemical reactions in cellulo.

Arbitrary Resolution with Two Bead Types Coarse-Grained Strategy and Applications to Protein Recognition

Molecular recognition is a fundamental step in essentially any biological process. However, the kinetic processes during association and dissociation are difficult to be efficiently sampled by direct all-atom molecular dynamics simulations because of the large spatial and temporal scales. Here we propose an arbitrary resolution with two bead types (ART) coarse-grained (CG) strategy that is adept in molecular recognition. ART is a universal user-customized CG strategy that can generate a system-specific CG force field anytime and be applied to any system with an arbitrary CG resolution according to research requirements. ART CG simulations can be very efficiently performed with implicit solvation in prevalent simulation packages and provide interfaces for any enhanced sampling method. We used three applications, HLA-HIV epitope recognition, barnase-barstar association, and trimeric TRAF2 self-assembly, to validate the feasibility of the ART CG strategy, its advantages in protein recognition, and its high performance in simulations. Regular CG simulations can successfully achieve valid protein recognitions without any prior bound structure.

Allostery of multidomain proteins with disordered linkers

Intrinsically disordered regions are often involved in allosteric regulation of multidomain proteins. They can act as disordered linkers to connect and interact with domains, resulting in rather complex allosteric mechanism and novel protein behavior. Therefore, it is necessary to analyze the diverse functions of disordered linkers in order to better understand allostery and relevant regulation process. Here we summarize recent advances in understanding the function of linkers and the advantages of adopting mutlidomain architecture with disorder linkers. It was shown that linkers between domains enhance the local domain concentration and make the allosteric regulation of weakly interacting partners possible, while linkers with only one tethered end cause an entropy effect to reduce binding affinity and prevent aggregation.

Probe-dependence of competitive fluorescent ligand binding assays to odorant-binding proteins

Ligand binding experiments between small chemicals and proteins and the evaluation of dissociation constants of their complexes in competitive binding assays often rely on displacement of reporter probes by the tested ligand. The most widely adopted protocol uses a fluorescent ligand which changes its emission spectrum when bound to a protein. A decrease of fluorescence, caused by the addition of a second ligand to the complex is generally interpreted as displacement of the fluorescent probe by the ligand, and therefore as a measure of the affinity of the ligand for the protein. Working with an odorant-binding protein (OBP), we found drastic differences in the calculated affinities when using 1-aminoanthracene or N-phenyl-1-naphthylamine as the fluorescent reporter. This fact was quite unexpected, as OBPs are small compact proteins with a single binding pocket without allosteric sites. Such observation raises doubts on the reliability of the fluorescent binding assay, perhaps the most widely used approach to evaluate affinities of small organic compounds to OBPs and other binding proteins. We recommend that the results of fluorescent binding experiments with OBPs should be confirmed by using two different probes or alternative methods. The reliability of current protocols for ligand binding assays is rather limited, while we still wait for a label-free approach that could be simple, fast and free from the use of radioactive tracers.

Ligand Binding Rate Constants in Heme Proteins Using Markov State Models and Molecular Dynamics Simulations

Computer simulation studies of the molecular basis for ligand migration in proteins allow the description of key events such as the transition between docking sites, displacement of existing ligands and solvent molecules, and open/closure of specific "gates", among others. In heme proteins, ligand migration from the solvent to the active site preludes the binding to the heme iron and triggers different functions. In this work, molecular dynamics simulations, a Markov State Model of migration and empirical kinetic equations are combined to study the migration of O₂ and NO in two truncated hemoglobins of Mycobacterium tuberculosis (Mt-TrHbN and Mt-TrHbO). For Mt-TrHbN, we show that the difference in the association constant in the oxy and deoxy states relies mainly in the displacement of water molecules anchored in the distal cavity in the deoxy form. The results here provide a valuable approach to study ligand migration in globins.

Exploring the Ligand Binding/Unbinding Pathway by Selectively Enhanced Sampling of Ligand in a Protein-Ligand Complex

Understanding the protein-ligand binding is of fundamental biological interest and is essential for structure-based drug design. The difficulty in capturing the dynamic process, however, poses a great challenge for current experimental and theoretical simulation techniques. A selective integrated-tempering-sampling molecular dynamics (SITSMD) method offering an option for selectively enhanced sampling of the ligand in a protein-ligand complex was utilized to quantitatively illuminate the binding of benzamidine to the wild-type trypsin protease and its two mutants (S214E and S214K). The SITSMD simulations could produce consistent results as the extensive conventional MD simulation and gave additional insights into the binding pathway for the test protein-ligand complex system using significantly saved computational resource and time, indicating the potential of such a method in investigating protein-ligand binding. Additionally, the simulations identified the different roles of trypsin-benzamidine van der Waals (vdW) and electrostatic interactions in the binding: the former interaction works as the driving force for dragging the benzamidine close to the native binding pocket, and the latter interaction mainly contributes to stabilizing the benzamidine inside the pocket. The S214E mutation introduces more favorable electrostatic interactions, and as a result, both vdW and electrostatic interactions drive the benzamidine binding, lowering the binding and unbinding free energy barrier. In contrast, the S214K mutation prohibits the binding of the benzamidine to the native ligand binding pocket by introducing disliked charge-charge interactions. In summary, these findings suggest that the change in specific residues could modify the protein druggability, including the binding kinetics and thermodynamics.

Thienopyrimidinone Derivatives That Inhibit Bacterial tRNA (Guanine37-N1)-Methyltransferase (TrmD) by Restructuring the Active Site with a Tyrosine-Flipping Mechanism

Among the >120 modified ribonucleosides in the prokaryotic epitranscriptome, many tRNA modifications are critical to bacterial survival, which makes their synthetic enzymes ideal targets for antibiotic development. Here we performed a structure-based design of inhibitors of tRNA-(N¹G37) methyltransferase, TrmD, which is an essential enzyme in many bacterial pathogens. On the basis of crystal structures of TrmDs from Pseudomonas aeruginosa and Mycobacterium tuberculosis, we synthesized a series of thienopyrimidinone derivatives with nanomolar potency against TrmD in vitro and discovered a novel active site conformational change triggered by inhibitor binding. This tyrosine-flipping mechanism is uniquely found in P. aeruginosa TrmD and renders the enzyme inaccessible to the cofactor S-adenosyl-l-methionine (SAM) and probably to the substrate tRNA. Biophysical and biochemical structure–activity relationship studies provided insights into the mechanisms underlying the potency of thienopyrimidinones as TrmD inhibitors, with several derivatives found to be active against Gram-positive and mycobacterial pathogens. These results lay a foundation for further development of TrmD inhibitors as antimicrobial agents.

Measurements of aptamer-protein binding kinetics using graphene field-effect transistors

Quantifying interactions between biomolecules subject to various environmental conditions is essential for applications such as drug discovery and precision medicine. This paper presents an investigation of the kinetics of environmentally dependent biomolecular binding using an electrolyte-gated graphene field-effect transistor (GFET) nanosensor. In this approach, biomolecular binding occurring on and in the vicinity of a graphene surface induces a change in carrier concentration, whose resulting conductance change is measured. This allows a systematic study of the kinetic properties of the binding system. We apply this approach to the specific binding of human immunoglobulin E (IgE), an antibody involved in parasite immunity, with an aptamer at different ionic strengths (Na⁺ and Mg²⁺) and temperatures. Experimental results demonstrate increased-rate binding kinetics at higher salt-ion concentrations and temperatures. In particular, the divalent cation Mg²⁺ yields more pronounced changes in the conformational structure of the aptamer than the monovalent cation Na⁺. In addition, the dissociation of the aptamer-protein complex at room temperature is found to be characterized by large unfavorable changes in the activation enthalpy and entropy.

Designed Mutations Alter the Binding Pathways of an Intrinsically Disordered Protein

Many cellular functions, including signaling and regulation, are carried out by intrinsically disordered proteins (IDPs) binding to their targets. Experimental and computational studies have now significantly advanced our understanding of these binding processes. In particular, IDPs that become structured upon binding typically follow a dock-and-coalesce mechanism, whereby the docking of one IDP segment initiates the process, followed by on-target coalescence of remaining IDP segments. Multiple dock-and-coalesce pathways may exist, but one may dominate, by relying on electrostatic attraction and molecular flexibility for fast docking and fast coalescing, respectively. Here we critically test this mechanistic understanding by designing mutations that alter the dominant pathway. This achievement marks an important step toward precisely manipulating IDP functions.

What Are We Missing by Not Measuring the Net Charge of Proteins?

The net electrostatic charge (Z) of a folded protein in solution represents a bird's eye view of its surface potentials-including contributions from tightly bound metal, solvent, buffer, and cosolvent ions-and remains one of its most enigmatic properties. Few tools are available to the average biochemist to rapidly and accurately measure Z at pH≠pI. Tools that have been developed more recently seem to go unnoticed. Most scientists are content with this void and estimate the net charge of a protein from its amino acid sequence, using textbook values of pK_a . Thus, Z remains unmeasured for nearly all folded proteins at pH≠pI. When marveling at all that has been learned from accurately measuring the other fundamental property of a protein-its mass-one wonders: what are we missing by not measuring the net charge of folded, solvated proteins? A few big questions immediately emerge in bioinorganic chemistry. When a single electron is transferred to a metalloprotein, does the net charge of the protein change by approximately one elementary unit of charge or does charge regulation dominate, that is, do the pK_a values of most ionizable residues (or just a few residues) adjust in response to (or in concert with) electron transfer? Would the free energy of charge regulation (ΔΔG_z ) account for most of the outer sphere reorganization energy associated with electron transfer? Or would ΔΔG_z contribute more to the redox potential? And what about metal binding itself? When an apo-metalloprotein, bearing minimal net negative charge (e.g., Z=-2.0) binds one or more metal cations, is the net charge abolished or inverted to positive? Or do metalloproteins regulate net charge when coordinating metal ions? The author's group has recently dusted off a relatively obscure tool-the "protein charge ladder"-and used it to begin to answer these basic questions.

AFFINImeter: A software to analyze molecular recognition processes from experimental data

The comprehension of molecular recognition phenomena demands the understanding of the energetic and kinetic processes involved. General equations valid for the thermodynamic analysis of any observable that is assessed as a function of the concentration of the involved compounds are described, together with their implementation in the AFFINImeter software. Here, a maximum of three different molecular species that can interact with each other to form an enormous variety of supramolecular complexes are considered. The corrections currently employed to take into account the effects of dilution, volume displacement, concentration errors and those due to external factors, especially in the case of ITC measurements, are included. The methods used to fit the model parameters to the experimental data, and to generate the uncertainties are described in detail. A simulation tool and the so called kinITC analysis to get kinetic information from calorimetric experiments are also presented. An example of how to take advantage of the AFFINImeter software for the global multi-temperature analysis of a system exhibiting cooperative 1:2 interactions is presented and the results are compared with data previously published. Some useful recommendations for the analysis of experiments aimed at studying molecular interactions are provided.

Does Ionic Screening Lower Activation Barriers for Conformational Transitions in Proteins?

In this work, we investigated the kinetics of binding of hen egg-white lysozyme with tri- N-acetylglucosamine in aqueous solutions, at two values of pH, 3.2 and 11, as a function of ionic strength, by a stopped-flow method with tryptophyl fluorescence observation of the transients. We analyzed registered reaction progress curves by employing numerical integration of appropriate chemical master equations. We discriminated between several binding models and established that the process observed in experiments follows a two-step mechanism, composed of four elementary stages: diffusional formation of an encounter complex, dissociation of the encounter complex, conformational transition of the encounter complex to the final complex, and the reverse transformation, i.e., from the final complex to the encounter complex. We evaluated rate constants of these elementary stages and determined their dependencies on solution ionic strength. Regardless of solution pH, rate constants of both forward and reverse conformational transitions increase with an increasing ionic strength. This suggests that ionic screening of intramolecular electrostatic interactions may act to lower the activation barrier for conformational transition in proteins.

Transition path times of coupled folding and binding reveal the formation of an encounter complex

The association of biomolecules is the elementary event of communication in biology. Most mechanistic information of how the interactions between binding partners form or break is, however, hidden in the transition paths, the very short parts of the molecular trajectories from the encounter of the two molecules to the formation of a stable complex. Here we use single-molecule spectroscopy to measure the transition path times for the association of two intrinsically disordered proteins that form a folded dimer upon binding. The results reveal the formation of a metastable encounter complex that is electrostatically favored and transits to the final bound state within tens of microseconds. Such measurements thus open a new window into the microscopic events governing biomolecular interactions.

Structural and dynamic basis of substrate permissiveness in hydroxycinnamoyltransferase (HCT)

Substrate permissiveness has long been regarded as the raw materials for the evolution of new enzymatic functions. In land plants, hydroxycinnamoyltransferase (HCT) is an essential enzyme of the phenylpropanoid metabolism. Although essential enzymes are normally associated with high substrate specificity, HCT can utilize a variety of non-native substrates. To examine the structural and dynamic basis of substrate permissiveness in this enzyme, we report the crystal structure of HCT from Selaginella moellendorffii and molecular dynamics (MD) simulations performed on five orthologous HCTs from several major lineages of land plants. Through altogether 17-μs MD simulations, we demonstrate the prevalent swing motion of an arginine handle on a submicrosecond timescale across all five HCTs, which plays a key role in native substrate recognition by these intrinsically promiscuous enzymes. Our simulations further reveal how a non-native substrate of HCT engages a binding site different from that of the native substrate and diffuses to reach the catalytic center and its co-substrate. By numerically solving the Smoluchowski equation, we show that the presence of such an alternative binding site, even when it is distant from the catalytic center, always increases the reaction rate of a given substrate. However, this increase is only significant for enzyme-substrate reactions heavily influenced by diffusion. In these cases, binding non-native substrates ‘off-center’ provides an effective rationale to develop substrate permissiveness while maintaining the native functions of promiscuous enzymes.

Examples abound of enzymes that can process substrates other than their native ones. However, the structural and dynamic basis of this promiscuity remains to be fully understood. In this work, we examine HCT, an intrinsically promiscuous acyltransferase with conserved function in all land plants. We uncover the sub-microsecond swing motion of a key arginine residue facilitating the recognition of both native and non-native substrates of HCT. We also quantify the impact of an off-center binding site on the non-native reaction rate. Although our calculations were inspired by HCT, the results apply in general, i.e., for enzymes heavily influenced by diffusion, binding non-native substrates ‘off-center’, even with rather weak affinity, can accelerate non-native reactions to appreciable levels.

Simulations of the regulatory ACT domain of human phenylalanine hydroxylase (PAH) unveil its mechanism of phenylalanine binding

Phenylalanine hydroxylase (PAH) regulates phenylalanine (Phe) levels in mammals to prevent neurotoxicity resulting from high Phe concentrations as observed in genetic disorders leading to hyperphenylalaninemia and phenylketonuria. PAH senses elevated Phe concentrations by transient allosteric Phe binding to a protein-protein interface between ACT domains of different subunits in a PAH tetramer. This interface is present in an activated PAH (A-PAH) tetramer and absent in a resting-state PAH (RS-PAH) tetramer. To investigate this allosteric sensing mechanism, here we used the GROMACS molecular dynamics simulation suite on the Folding@home computing platform to perform extensive molecular simulations and Markov state model (MSM) analysis of Phe binding to ACT domain dimers. These simulations strongly implicated a conformational selection mechanism for Phe association with ACT domain dimers and revealed protein motions that act as a gating mechanism for Phe binding. The MSMs also illuminate a highly mobile hairpin loop, consistent with experimental findings also presented here that the PAH variant L72W does not shift the PAH structural equilibrium toward the activated state. Finally, simulations of ACT domain monomers are presented, in which spontaneous transitions between resting-state and activated conformations are observed, also consistent with a mechanism of conformational selection. These mechanistic details provide detailed insight into the regulation of PAH activation and provide testable hypotheses for the development of new allosteric effectors to correct structural and functional defects in PAH.

Tuning the chain length of new pyrene derivatives for site-selective photocleavage of avidin

Rational design of photoreagents with systematic modifications of their structures can provide valuable information for a better understanding of the protein photocleavage mechanism by these reagents. Variation of the length of the linker connecting the photoactive moiety with the protein anchoring-group allowed us to investigate the control of the protein photocleavage site. A series of new photochemical reagents (PMA-1A, PMA-2A and PMA-3A) with increasing chain lengths is examined in the current study. Using avidin as a model system, we examined the interaction of these probes by UV-Vis, fluorescence spectroscopic methods, photocleavage and computational docking studies. Hypochromism of the absorption spectrum was observed for the binding of these new photochemical reagents with estimated binding constants (K_b) of 6.2 × 10⁵, 6.7 × 10⁵ and 4.6 × 10⁵ M^-1, respectively. No significant changes of Stern-Volmer quenching constant (K_sv) with Co(NH₃)₆Cl₃ has been noted and the data indicated that the probes bind near the surface of the protein with sufficient exposure to the solvent. Photoexcitation of the probe-avidin complex, in the presence of Co(NH₃)₆Cl₃, resulted in protein fragmentation, and the cleavage yield decreased with the increase in the linker length, and paralleled with the observed K_sv values. Amino acid sequencing of the photofragments indicated that avidin is cleaved between Thr77 and Val78, as a major cleavage site for all the three photoreagents. This site is proximate to the biotin binding site on avidin, and molecular docking studies indicated that the H-bonding interactions between the polar end-group of the photoreagents and hydrophilic amino acids of avidin were important in positioning the reagent on the protein. The major cleavage site, at residues 77-78, was within 5 Å of the pyrenyl moiety of the probe, and hence, molecular tuning of the linker provided a simple approach to position the photoreagent along the potential photocleavage site.

From radioactive ligands to biosensors: binding methods with olfactory proteins

In this paper, we critically review the binding protocols currently reported in the literature to measure the affinity of odorants and pheromones to soluble olfactory proteins, such as odorant-binding proteins (OBPs), chemosensory proteins (CSPs) and Niemann-Pick class C2 (NPC2) proteins. The first part contains a brief introduction on the principles of binding and a comparison of the techniques adopted or proposed so far, discussing advantages and problems of each technique, as well as their suitable application to soluble olfactory proteins. In the second part, we focus on the fluorescent binding assay, currently the most widely used approach. We analyse advantages and drawbacks, trying to identify the causes of anomalous behaviours that have been occasionally observed, and suggest how to interpret the experimental data when such events occur. In the last part, we describe the state of the art of biosensors for odorants, using soluble olfactory proteins immobilised on biochips, and discuss the possibility of using such approach as an alternative way to measure binding events and dissociation constants.

Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation

Charged and polar groups, through forming ion pairs, hydrogen bonds, and other less specific electrostatic interactions, impart important properties to proteins. Modulation of the charges on the amino acids, e.g., by pH and by phosphorylation and dephosphorylation, have significant effects such as protein denaturation and switch-like response of signal transduction networks. This review aims to present a unifying theme among the various effects of protein charges and polar groups. Simple models will be used to illustrate basic ideas about electrostatic interactions in proteins, and these ideas in turn will be used to elucidate the roles of electrostatic interactions in protein structure, folding, binding, condensation, and related biological functions. In particular, we will examine how charged side chains are spatially distributed in various types of proteins and how electrostatic interactions affect thermodynamic and kinetic properties of proteins. Our hope is to capture both important historical developments and recent experimental and theoretical advances in quantifying electrostatic contributions of proteins.

New approaches for computing ligand-receptor binding kinetics

The recent and growing evidence that the efficacy of a drug can be correlated to target binding kinetics has seeded the development of a multitude of novel methods aimed at computing rate constants for receptor-ligand binding processes, as well as gaining an understanding of the binding and unbinding pathways and the determinants of structure-kinetic relationships. These new approaches include various types of enhanced sampling molecular dynamics simulations and the combination of energy-based models with chemometric analysis. We assess these approaches in the light of the varying levels of complexity of protein-ligand binding processes.