Both protein dynamics and ligand concentration can shift the binding mechanism between conformational selection and induced fit

Proline-based tripodal cages with guest-adaptive features for capturing hydrophilic and amphiphilic fluoride substances

Proteins exhibit remarkable molecular recognition by dynamically adjusting their conformations to selectively interact with ligands at specialized binding sites. To bind hydrated ligands, proteins leverage amino acid residues with similar water affinities as the substrate, minimizing the energy required to strip water molecules from the hydrophilic substrates. In synthetic receptor design, replicating this sophisticated adaptability remains a challenge, as most artificial receptors are optimized to bind desolvated substances. Here, we show that proline-based synthetic receptors can mimic the conformational dynamics of proteins to achieve selective binding of hydrophilic and amphiphilic fluoride substances in aqueous environments. This finding highlights the critical role of receptor flexibility and strategic hydrophilicity in enhancing ligand recognition and affinity in water. Moreover, it establishes a new framework for designing versatile synthetic receptors with tunable hydrophobicity and hydrophilicity profiles.

Programming the Kinetics of Chemical Communication: Induced Fit vs Conformational Selection

Life on Earth depends on chemical communication and the ability of biomolecular switches to integrate various chemical signals that trigger their activation or deactivation over time scales ranging from microseconds to days. The ability to similarly program and control the kinetics of artificial switches would greatly assist the design and optimization of future chemical and nanotechnological systems. Two distinct structure-switching mechanisms are typically employed by biomolecular switches: induced fit (IF) and conformational selection (CS). Despite 60 years of experimental and theoretical investigations, the kinetic and evolutive advantages of these two mechanisms remain unclear. Here, we have created a simple modular DNA switch that can operate through both mechanisms and be easily tuned and adapted to characterize its thermodynamic and kinetic parameters. We show that the fastest activation rate of a switch occurs when the ligand is able to bind its inactive conformation (IF). In contrast, we show that when the ligand can only bind the active conformation of the switch (CS), its activation rate can be easily programmed over many orders of magnitude by a simple tuning of its conformational equilibrium. We demonstrate the programming ability of both these mechanisms by designing a drug delivery vessel that can be programmed to release a drug over different time scales (>1000-fold). Overall, these findings provide a programmable strategy to optimize the kinetics of molecular systems and nanomachines while also illustrating how evolution may have taken advantage of IF and CS mechanisms to optimize the kinetics of biomolecular switches.

Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure

The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.

Flipping the script: Understanding riboswitches from an alternative perspective

Riboswitches are broadly distributed regulatory elements most frequently found in the 5'-leader sequence of bacterial mRNAs that regulate gene expression in response to the binding of a small molecule effector. The occupancy status of the ligand-binding aptamer domain manipulates downstream information in the message that instructs the expression machinery. Currently, there are over 55 validated riboswitch classes, where each class is defined based on the identity of the ligand it binds and/or sequence and structure conservation patterns within the aptamer domain. This classification reflects an "aptamer-centric" perspective that dominates our understanding of riboswitches. In this review, we propose a conceptual framework that groups riboswitches based on the mechanism by which RNA manipulates information directly instructing the expression machinery. This scheme does not replace the established aptamer domain-based classification of riboswitches but rather serves to facilitate hypothesis-driven investigation of riboswitch regulatory mechanisms. Based on current bioinformatic, structural, and biochemical studies of a broad spectrum of riboswitches, we propose three major mechanistic groups: (1) "direct occlusion", (2) "interdomain docking", and (3) "strand exchange". We discuss the defining features of each group, present representative examples of riboswitches from each group, and illustrate how these RNAs couple small molecule binding to gene regulation. While mechanistic studies of the occlusion and docking groups have yielded compelling models for how these riboswitches function, much less is known about strand exchange processes. To conclude, we outline the limitations of our mechanism-based conceptual framework and discuss how critical information within riboswitch expression platforms can inform gene regulation.

Coenzyme-binding pathway on glutamate dehydrogenase suggested from multiple-binding sites visualized by cryo-electron microscopy

The structure of hexameric glutamate dehydrogenase (GDH) in the presence of the coenzyme nicotinamide adenine dinucleotide phosphate (NADP) was visualized using cryogenic transmission electron microscopy to investigate the ligand-binding pathways to the active site of the enzyme. Each subunit of GDH comprises one hexamer-forming core domain and one nucleotide-binding domain (NAD domain), which spontaneously opens and closes the active-site cleft situated between the two domains. In the presence of NADP, the potential map of GDH hexamer, assuming D3 symmetry, was determined at a resolution of 2.4 Å, but the NAD domain was blurred due to the conformational variety. After focused classification with respect to the NAD domain, the potential maps interpreted as NADP molecules appeared at five different sites in the active-site cleft. The subunits associated with NADP molecules were close to one of the four metastable conformations in the unliganded state. Three of the five binding sites suggested a pathway of NADP molecules to approach the active-site cleft for initiating the enzymatic reaction. The other two binding modes may rarely appear in the presence of glutamate, as demonstrated by the reaction kinetics. Based on the visualized structures and the results from the enzymatic kinetics, we discussed the binding modes of NADP to GDH in the absence and presence of glutamate.

All over or overall - Do we understand allostery?

Allostery is probably the most important concept in the regulation of cellular processes. Models to explain allostery are plenty. Each sheds light on different aspects but their entirety conveys an ambiguous feeling of comprehension and disappointment. Here, I discuss the most popular allostery models, their roots, similarities, and limitations. All of them are thermodynamic models. Naturally this bears a certain degree of redundancy, which forms the center of this review. After sixty years, many questions remain unanswered, mainly because our human longing for causality as base for understanding is not satisfied by thermodynamics alone. A description of allostery in terms of pathways, i.e., as a temporal chain of events, has been-, and still is-, a missing piece of the puzzle.

A Kinetic Transition Network Model Reveals the Diversity of Protein Dimer Formation Mechanisms

Protein homodimers have been classified as three-state or two-state dimers depending on whether a folded monomer forms before association, but the details of the folding-binding mechanisms are poorly understood. Kinetic transition networks of conformational states have provided insight into the folding mechanisms of monomeric proteins, but extending such a network to two protein chains is challenging as all the relative positions and orientations of the chains need to be included, greatly increasing the number of degrees of freedom. Here, we present a simplification of the problem by grouping all states of the two chains into two layers: a dissociated and an associated layer. We combined our two-layer approach with the Wako-Saito-Muñoz-Eaton method and used Transition Path Theory to investigate the dimer formation kinetics of eight homodimers. The analysis reveals a remarkable diversity of dimer formation mechanisms. Induced folding, conformational selection, and rigid docking are often simultaneously at work, and their contribution depends on the protein concentration. Pre-folded structural elements are always present at the moment of association, and asymmetric binding mechanisms are common. Our two-layer network approach can be combined with various methods that generate discrete states, yielding new insights into the kinetics and pathways of flexible binding processes.

Protein conformational ensembles in function: roles and mechanisms

The sequence-structure-function paradigm has dominated twentieth century molecular biology. The paradigm tacitly stipulated that for each sequence there exists a single, well-organized protein structure. Yet, to sustain cell life, function requires (i) that there be more than a single structure, (ii) that there be switching between the structures, and (iii) that the structures be incompletely organized. These fundamental tenets called for an updated sequence-conformational ensemble-function paradigm. The powerful energy landscape idea, which is the foundation of modernized molecular biology, imported the conformational ensemble framework from physics and chemistry. This framework embraces the recognition that proteins are dynamic and are always interconverting between conformational states with varying energies. The more stable the conformation the more populated it is. The changes in the populations of the states are required for cell life. As an example, in vivo, under physiological conditions, wild type kinases commonly populate their more stable "closed", inactive, conformations. However, there are minor populations of the "open", ligand-free states. Upon their stabilization, e.g., by high affinity interactions or mutations, their ensembles shift to occupy the active states. Here we discuss the role of conformational propensities in function. We provide multiple examples of diverse systems, including protein kinases, lipid kinases, and Ras GTPases, discuss diverse conformational mechanisms, and provide a broad outlook on protein ensembles in the cell. We propose that the number of molecules in the active state (inactive for repressors), determine protein function, and that the dynamic, relative conformational propensities, rather than the rigid structures, are the hallmark of cell life.

Biochemical and biophysical characterization of natural polyreactivity in antibodies

To become specialized binders, antibodies undergo a process called affinity maturation to maximize their binding affinity. Despite this process, some antibodies retain low-affinity binding to diverse epitopes in a phenomenon called polyreactivity. Here we seek to understand the molecular basis of this polyreactivity in antibodies. Our results highlight that polyreactive antigen-binding fragments (Fabs) bind their targets with low affinities, comparable to T cell receptor recognition of autologous classical major histocompatibility complex. Extensive mutagenic studies find no singular amino acid residue or biochemical property responsible for polyreactive interaction, suggesting that polyreactive antibodies use multiple strategies for engagement. Finally, our crystal structures and all-atom molecular dynamics simulations of polyreactive Fabs show increased rigidity compared to their monoreactive relatives, forming a neutral and accessible platform for diverse antigens to bind. Together, these data support a cooperative strategy of rigid neutrality in establishing the polyreactive status of an antibody molecule.

Folding of Staphylococcal Nuclease Induced by Binding of Chemically Modified Substrate Analogues Sheds Light on Mechanisms of Coupled Folding/Binding Reactions

Several proteins have been shown to undergo a shift in the mechanism of ligand binding-induced folding from conformational selection (CS; folding precedes binding) to induced fit (IF; binding precedes folding) with increasing ligand concentration. In previous studies of the coupled folding/binding reaction of staphylococcal nuclease (SNase) in the presence of a substrate analogue, adenosine-3',5'-diphosphate (prAp), we found that the two phosphate groups make important energetic contributions toward stabilizing its complex with the native protein as well as transient conformational states encountered at high ligand concentrations favoring IF. However, the structural contributions of each phosphate group during the reaction remain unclear. To address this question, we relied on fluorescence, nuclear magnetic resonance (NMR), absorption, and isothermal titration calorimetry to study the effects of deletion of the phosphate groups of prAp on the kinetics of ligand-induced folding, using a strategy analogous to mutational ϕ-value analysis to interpret the results. Kinetic measurements over a wide range of ligand concentrations, together with structural characterization of a transient protein-ligand encounter complex using 2D NMR, indicated that, at high ligand concentrations favoring IF, (i) the 5'-phosphate group interacts weakly with denatured SNase during early stages of the reaction, resulting in loose docking of the two domains of SNase, and (ii) the 3'-phosphate group engages in some specific contacts with the polypeptide in the transition state prior to formation of the native SNase-prAp complex.

Competition in drug binding and … the race to equilibrium

Binding kinetics has become a popular topic in pharmacology due to its potential contribution to the selectivity and duration of drug action. Yet, the overall kinetic aspects of complex binding mechanisms are still merely described in terms of elaborate algebraic equations. Interestingly, it has been recommended some 10 years ago to examine such mechanisms in terms of binding fluxes instead of the conventional rate constants. Alike the velocity of product formation in enzymology, those fluxes refer to the velocity by which one target species converts into another one. Novel binding flux-based approaches are utilized to get a better visual insight into the "competition" between two drugs/ligands for a single target as well as between induced fit- and conformational selection pathways for a single ligand within a thermodynamic cycle. The present data were obtained by differential equation-based simulations. Early on, the ligand-binding steps "race" to equilibrium (i.e., when their forward and reverse fluxes are equal) at their individual pace. The overall/global equilibrium is only reached later on. For the competition association assays, this parting might produce a transient "overshoot" of one of the bound target species. A similar overshoot may also show up within a thermodynamic cycle and, at first glance, suggest that the induced fit pathway dominates. Yet, present findings show that under certain circumstances, it could rather be the other way round. Novel binding flux-based approaches offer visually attractive insights into crucial aspects of "complex" binding mechanisms under non-equilibrium conditions.

Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs

Here, we discuss the principles of allosteric activating mutations, propagation downstream of the signals that they prompt, and allosteric drugs, with examples from the Ras signaling network. We focus on Abl kinase where mutations shift the landscape toward the active, imatinib binding-incompetent conformation, likely resulting in the high affinity ATP outcompeting drug binding. Recent pharmacological innovation extends to allosteric inhibitor (GNF-5)-linked PROTAC, targeting Bcr-Abl1 myristoylation site, and broadly, allosteric heterobifunctional degraders that destroy targets, rather than inhibiting them. Designed chemical linkers in bifunctional degraders can connect the allosteric ligand that binds the target protein and the E3 ubiquitin ligase warhead anchor. The physical properties and favored conformational state of the engineered linker can precisely coordinate the distance and orientation between the target and the recruited E3. Allosteric PROTACs, noncompetitive molecular glues, and bitopic ligands, with covalent links of allosteric ligands and orthosteric warheads, increase the effective local concentration of productively oriented and placed ligands. Through covalent chemical or peptide linkers, allosteric drugs can collaborate with competitive drugs, degrader anchors, or other molecules of choice, driving innovative drug discovery.

Elucidating the mechanisms underlying protein conformational switching using NMR spectroscopy

How proteins switch between various ligand-free and ligand-bound structures has been a key biophysical question ever since the postulation of the Monod-Wyman-Changeux and Koshland-Nemethy-Filmer models over six decades ago. The ability of NMR spectroscopy to provide structural and kinetic information on biomolecular conformational exchange places it in a unique position as an analytical tool to interrogate the mechanisms of biological processes such as protein folding and biomolecular complex formation. In addition, recent methodological developments in the areas of saturation transfer and relaxation dispersion have expanded the scope of NMR for probing the mechanics of transitions in systems where one or more states constituting the exchange process are sparsely populated and 'invisible' in NMR spectra. In this review, we highlight some of the strategies available from NMR spectroscopy for examining the nature of multi-site conformational exchange, using five case studies that have employed NMR, either in isolation, or in conjunction with other biophysical tools.

Dissecting the Protein Dynamics Coupled Ligand Binding with Kinetic Models and Single-Molecule FRET

Protein-ligand interactions are crucial to many biological processes. Ligand binding and dissociation are the basic steps that allow proteins to function. Protein conformational dynamics have been shown to play important roles in ligand binding and dissociation. However, it is challenging to determine the ligand binding kinetics of dynamic proteins. Here, we undertook comprehensive single-molecule FRET (smFRET) measurements and kinetic model analysis to characterize the conformational dynamics coupled ligand binding of glutamine-binding protein (GlnBP). We showed that hinge and T118A mutations of GlnBP affect its conformational dynamics as well as the ligand binding affinity. Based on smFRET measurements, the kinetic model of ligand-GlnBP interactions was constructed. Using experimentally measured parameters, we solved the rate equations of the model and obtained the undetectable parameters of the model which allowed us to understand the ligand binding kinetics fully. Our results demonstrate that modulation of the conformational dynamics of GlnBP affects the ligand binding and dissociation rates. This study provides insights into the binding kinetics of ligands, which are related to the protein function itself.

Structural-Energetic Basis for Coupling between Equilibrium Fluctuations and Phosphorylation in a Protein Native Ensemble

The functioning of proteins is intimately tied to their fluctuations in the native ensemble. The structural-energetic features that determine fluctuation amplitudes and hence the shape of the underlying landscape, which in turn determine the magnitude of the functional output, are often confounded by multiple variables. Here, we employ the FF1 domain from human p190A RhoGAP protein as a model system to uncover the molecular basis for phosphorylation of a buried tyrosine, which is crucial to the transcriptional activity associated with transcription factor TFII-I. Combining spectroscopy, calorimetry, statistical-mechanical modeling, molecular simulations, and in vitro phosphorylation assays, we show that the FF1 domain samples a diverse array of conformations in its native ensemble, some of which are phosphorylation-competent. Upon eliminating unfavorable charge-charge interactions through a single charge-reversal (K53E) or charge-neutralizing (K53Q) mutation, we observe proportionately lower phosphorylation extents due to the altered structural coupling, damped equilibrium fluctuations, and a more compact native ensemble. We thus establish a conformational selection mechanism for phosphorylation in the FF1 domain with K53 acting as a "gatekeeper", modulating the solvent exposure of the buried tyrosine. Our work demonstrates the role of unfavorable charge-charge interactions in governing functional events through the modulation of native ensemble characteristics, a feature that could be prevalent in ordered protein domains.

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.

Induced fit versus conformational selection: From rate constants to fluxes… and back to rate constants

Induced fit- (IF) and conformational selection (CS) binding mechanisms have long been regarded to be mutually exclusive. Yet, they are now increasingly considered to produce the final ligand-target complex alongside within a thermodynamic cycle. This viewpoint benefited from the introduction of binding fluxes as a tool for analyzing the overall behavior of such cycle. This study aims to provide more vivid and applicable insights into this emerging field. In this respect, combining differential equation- based simulations and hitherto little explored alternative modes of calculation provide concordant information about the intricate workings of such cycle. In line with previous reports, we observe that the relative contribution of IF increases with the ligand concentration at equilibrium. Yet the baseline contribution may vary from one case to another and simulations as well as calculations show that this parameter is essentially regulated by the dissociation rate of both pathways. Closer attention should be paid to how the contributions of IF and CS compare at physiologically relevant drug/ligand concentrations. To this end, a simple equation discloses how changing a limited set of "microscopic" rate constants can extend the concentration range at which CS contributes most effectively. Finally, it could also be beneficial to extend the utilization of flux- based approaches to more physiologically relevant time scales and alternative binding models.

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.

A Potential Inhibition Process of Ricin Protein with the flavonoids Quercetin and Epigallocatechin Gallate. A Quantum-Chemical and Molecular Docking Study

Castor bean (Ricinus Communis) oil has been reported as one of the most important bio-based fuels; however, high amounts of toxic solid residue are generated in the production. This toxicity is due to several molecules, ricin protein being the most studied compound. The inhibition of the ricin protein is essential for eliminating its toxicity. The objective of this study is to predict the possible inhibition process via the interactions between the ricin protein and the flavonoids quercetin (Q) and epigallocatechin gallate (EGCG). The molecular structures of the complexes formed between the ricin protein and flavonoids were studied using quantum-chemical and molecular docking calculations to analyze the type of interaction, active site of the protein, binding energies, and different conformations in the inhibition process. Different methodologies were applied for the molecular structure determination; the best approximation was obtained with B3LYP/6-31G (d,p) theoretical methodology. Mappings of electrostatic potential (MEP) and frontier molecular orbitals were used for the identification of the probable sites of interaction, which were confirmed by molecular docking. The adjustment and alignment of flavonoid groups before and after the interaction, and charge transfer parameters, showed that Q and EGCG act as electron donors inside of the active site in ricin.

Ligand binding free-energy calculations with funnel metadynamics

The accurate resolution of the binding mechanism of a ligand to its molecular target is fundamental to develop a successful drug design campaign. Free-energy calculations, which provide the energy value of the ligand-protein binding complex, are essential for resolving the binding mode of the ligand. The accuracy of free-energy calculation methods is counteracted by their poor user-friendliness, which hampers their broad application. Here we present the Funnel-Metadynamics Advanced Protocol (FMAP), which is a flexible and user-friendly graphical user interface (GUI)-based protocol to perform funnel metadynamics, a binding free-energy method that employs a funnel-shape restraint potential to reveal the ligand binding mode and accurately calculate the absolute ligand-protein binding free energy. FMAP guides the user through all phases of the free-energy calculation process, from preparation of the input files, to production simulation, to analysis of the results. FMAP delivers the ligand binding mode and the absolute protein-ligand binding free energy as outputs. Alternative binding modes and the role of waters are also elucidated, providing a detailed description of the ligand binding mechanism. The entire protocol on the paradigmatic system benzamidine-trypsin, composed of ~105 k atoms, took ~2.8 d using the Cray XC50 piz Daint cluster at the Swiss National Supercomputing Centre.

Challenges in protein docking

Current developments in protein docking aim at improvement of applicability, accuracy and utility of modeling macromolecular complexes. The challenges include the need for greater emphasis on protein docking to molecules of different types, proper accounting for conformational flexibility upon binding, new promising methodologies based on residue co-evolution and deep learning, affinity prediction, and further development of fully automated docking servers. Importantly, new developments increasingly focus on realistic modeling of protein interactions in vivo, including crowded environment inside a cell, which involves multiple transient encounters, and propagating the system in time. This opinion paper offers the author's perspective on these challenges in structural modeling of protein interactions and the future of protein docking.

Energetics and kinetics of substrate analog-coupled staphylococcal nuclease folding revealed by a statistical mechanical approach

Protein conformational changes associated with ligand binding, especially those involving intrinsically disordered proteins, are mediated by tightly coupled intra- and intermolecular events. Such reactions are often discussed in terms of two limiting kinetic mechanisms, conformational selection (CS), where folding precedes binding, and induced fit (IF), where binding precedes folding. It has been shown that coupled folding/binding reactions can proceed along both CS and IF pathways with the flux ratio depending on conditions such as ligand concentration. However, the structural and energetic basis of such complex reactions remains poorly understood. Therefore, we used experimental, theoretical, and computational approaches to explore structural and energetic aspects of the coupled-folding/binding reaction of staphylococcal nuclease in the presence of the substrate analog adenosine-3',5'-diphosphate. Optically monitored equilibrium and kinetic data, combined with a statistical mechanical model, gave deeper insight into the relative importance of specific and Coulombic protein-ligand interactions in governing the reaction mechanism. We also investigated structural aspects of the reaction at the residue level using NMR and all-atom replica-permutation molecular dynamics simulations. Both approaches yielded clear evidence for accumulation of a transient protein-ligand encounter complex early in the reaction under IF-dominant conditions. Quantitative analysis of the equilibrium/kinetic folding revealed that the ligand-dependent CS-to-IF shift resulted from stabilization of the compact transition state primarily by weakly ligand-dependent Coulombic interactions with smaller contributions from specific binding energies. At a more macroscopic level, the CS-to-IF shift was represented as a displacement of the reaction "route" on the free energy surface, which was consistent with a flux analysis.

Structure dictates the mechanism of ligand recognition in the histidine and maltose binding proteins

Two mechanisms, induced fit (IF) and conformational selection (CS), have been proposed to explain ligand recognition coupled conformational changes. The histidine binding protein (HisJ) adopts the CS mechanism, in which a pre-equilibrium is established between the open and the closed states with the ligand binding to the closed state. Despite being structurally similar to HisJ, the maltose binding protein (MBP) adopts the IF mechanism, in which the ligand binds the open state and induces a transition to the closed state. To understand the molecular determinants of this difference, we performed molecular dynamics (MD) simulations of coarse-grained dual structure based models. We find that intra-protein contacts unique to the closed state are sufficient to promote the conformational transition in HisJ, indicating a CS-like mechanism. In contrast, additional ligand-mimicking contacts are required to “induce” the conformational transition in MBP suggesting an IF-like mechanism. In agreement with experiments, destabilizing modifications to two structural features, the spine helix (SH) and the balancing interface (BI), present in MBP but absent in HisJ, reduce the need for ligand-mimicking contacts indicating that SH and BI act as structural restraints that keep MBP in the open state. We introduce an SH like element into HisJ and observe that this can impede the conformational transition increasing the importance of ligand-mimicking contacts. Similarly, simultaneous mutations to BI and SH in MBP reduce the barrier to conformational transitions significantly and promote a CS-like mechanism. Together, our results show that structural restraints present in the protein structure can determine the mechanism of conformational transitions and even simple models that correctly capture such structural features can predict their positions. MD simulations of such models can thus be used, in conjunction with mutational experiments, to regulate protein ligand interactions, and modulate ligand binding affinities.

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MBP operates by induced fit, HisJ by the conformational selection mechanism.

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Dual structure based models (dSBMs) encode two structures of a protein.

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MD simulations of dSBMs can identify the mechanism of conformational transitions.

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Locks, absent in HisJ, hold MBP open with ligand contacts required for closing.

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Binding mechanisms can be modified by altering such structural locks.

Ligand-bound glutamine binding protein assumes multiple metastable binding sites with different binding affinities

Protein dynamics plays key roles in ligand binding. However, the microscopic description of conformational dynamics-coupled ligand binding remains a challenge. In this study, we integrate molecular dynamics simulations, Markov state model (MSM) analysis and experimental methods to characterize the conformational dynamics of ligand-bound glutamine binding protein (GlnBP). We show that ligand-bound GlnBP has high conformational flexibility and additional metastable binding sites, presenting a more complex energy landscape than the scenario in the absence of ligand. The diverse conformations of GlnBP demonstrate different binding affinities and entail complex transition kinetics, implicating a concerted ligand binding mechanism. Single molecule fluorescence resonance energy transfer measurements and mutagenesis experiments are performed to validate our MSM-derived structure ensemble as well as the binding mechanism. Collectively, our study provides deeper insights into the protein dynamics-coupled ligand binding, revealing an intricate regulatory network underlying the apparent binding affinity.

β-Lactamase of Mycobacterium tuberculosis Shows Dynamics in the Active Site That Increase upon Inhibitor Binding

The Mycobacterium tuberculosis β-lactamase BlaC is a broad-spectrum β-lactamase that can convert a range of β-lactam antibiotics. Enzymes with low specificity are expected to exhibit active-site flexibility. To probe the motions in BlaC, we studied the dynamic behavior in solution using nuclear magnetic resonance (NMR) spectroscopy. ¹⁵N relaxation experiments show that BlaC is mostly rigid on the pico- to nanosecond timescale. Saturation transfer experiments indicate that also on the high-millisecond timescale BlaC is not dynamic. Using relaxation dispersion experiments, clear evidence was obtained for dynamics in the low-millisecond range, with an exchange rate of ca. 860 s^-1 The dynamic amide groups are localized in the active site. Upon formation of an adduct with the inhibitor avibactam, extensive line broadening occurs, indicating an increase in magnitude of the active-site dynamics. Furthermore, the rate of the motions increases significantly. Upon reaction with the inhibitor clavulanic acid, similar line broadening is accompanied by duplication of NMR signals, indicative of at least one additional, slower exchange process (exchange rate, k _ex, of <100 s^-1), while for this inhibitor also loss of pico- to nanosecond timescale rigidity is observed for some amides in the α domain. Possible sources of the observed dynamics, such as motions in the omega loop and rearrangements of active-site residues, are discussed. The increase in dynamics upon ligand binding argues against a model of inhibitor binding through conformational selection. Rather, the induced dynamics may serve to maximize the likelihood of sampling the optimal conformation for hydrolysis of the bound ligand.

Stochastic or Not? Method To Predict and Quantify the Stochastic Effects on the Association Reaction Equilibria in Nanoscopic Systems

The stochastic nature of chemical reaction and impact of the stochasticity on their evolution is soundly documented. Both theoretical predictions and emerging experimental evidence indicate the influence of stochastic effects on the equilibrium state of association reaction. In this work simple mathematical formulas are introduced to estimate these effects. First, the dependence of the ratio of observed reactants (apparent association constant, equivalent of macroscopic association constant in stochastic analysis) on the volume and the number of molecules of reagents is discussed and the limiting factors of this effect are shown. Next, the apparent association constant is approximated for nanoscale systems by closed-form formulas derived for this purpose. Finally, an estimation for the macroscopic constant value from the apparent one is provided and validated on the published experimental data. This work was inspired by chemical reactions occurring in biological compartments, but the results can be used for all systems belonging to the stochastic regime of chemical reactions.

DROIDS 3.0-Detecting Genetic and Drug Class Variant Impact on Conserved Protein Binding Dynamics

The application of statistical methods to comparatively framed questions about the molecular dynamics (MD) of proteins can potentially enable investigations of biomolecular function beyond the current sequence and structural methods in bioinformatics. However, the chaotic behavior in single MD trajectories requires statistical inference that is derived from large ensembles of simulations representing the comparative functional states of a protein under investigation. Meaningful interpretation of such complex forms of big data poses serious challenges to users of MD. Here, we announce Detecting Relative Outlier Impacts from Molecular Dynamic Simulation (DROIDS) 3.0, a method and software package for comparative protein dynamics that includes maxDemon 1.0, a multimethod machine learning application that trains on large ensemble comparisons of concerted protein motions in opposing functional states generated by DROIDS and deploys learned classifications of these states onto newly generated MD simulations. Local canonical correlations in learning patterns generated from independent, yet identically prepared, MD validation runs are used to identify regions of functionally conserved protein dynamics. The subsequent impacts of genetic and/or drug class variants on conserved dynamics can also be analyzed by deploying the classifiers on variant MD simulations and quantifying how often these altered protein systems display opposing functional states. Here, we present several case studies of complex changes in functional protein dynamics caused by temperature, genetic mutation, and binding interactions with nucleic acids and small molecules. We demonstrate that our machine learning algorithm can properly identify regions of functionally conserved dynamics in ubiquitin and TATA-binding protein (TBP). We quantify the impact of genetic variation in TBP and drug class variation targeting the ATP-binding region of Hsp90 on conserved dynamics. We identify regions of conserved dynamics in Hsp90 that connect the ATP binding pocket to other functional regions. We also demonstrate that dynamic impacts of various Hsp90 inhibitors rank accordingly with how closely they mimic natural ATP binding.

Binding-induced folding under unfolding conditions: Switching between induced fit and conformational selection mechanisms

The chemistry of protein-ligand binding is the basis of virtually every biological process. Ligand binding can be essential for a protein to function in the cell by stabilizing or altering the conformation of a protein, particularly for partially or completely unstructured proteins. However, the mechanisms by which ligand binding impacts disordered proteins or influences the role of disorder in protein folding is not clear. To gain insight into this question, the mechanism of folding induced by the binding of a Pro-rich peptide ligand to the SH3 domain of phosphatidylinositol 3-kinase unfolded in the presence of urea has been studied using kinetic methods. Under strongly denaturing conditions, folding was found to follow a conformational selection (CS) mechanism. However, under mildly denaturing conditions, a ligand concentration-dependent switch in the mechanism was observed. The folding mechanism switched from being predominantly a CS mechanism at low ligand concentrations to being predominantly an induced fit (IF) mechanism at high ligand concentrations. The switch in the mechanism manifests itself as an increase in the reaction flux along the IF pathway at high ligand concentrations. The results indicate that, in the case of intrinsically disordered proteins too, the folding mechanism is determined by the concentration of the ligand that induces structure formation.

Features of molecular recognition of intrinsically disordered proteins via coupled folding and binding

The sequence-structure-function paradigm of proteins has been revolutionized by the discovery of intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). In contrast to traditional ordered proteins, IDPs/IDRs are unstructured under physiological conditions. The absence of well-defined three-dimensional structures in the free state of IDPs/IDRs is fundamental to their function. Folding upon binding is an important mode of molecular recognition for IDPs/IDRs. While great efforts have been devoted to investigating the complex structures and binding kinetics and affinities, our knowledge on the binding mechanisms of IDPs/IDRs remains very limited. Here, we review recent advances on the binding mechanisms of IDPs/IDRs. The structures and kinetic parameters of IDPs/IDRs can vary greatly, and the binding mechanisms can be highly dependent on the structural properties of IDPs/IDRs. IDPs/IDRs can employ various combinations of conformational selection and induced fit in a binding process, which can be templated by the target and/or encoded by the IDP/IDR. Further studies should provide deeper insights into the molecular recognition of IDPs/IDRs and enable the rational design of IDP/IDR binding mechanisms in the future.

Adaptation of the bound intrinsically disordered protein YAP to mutations at the YAP:TEAD interface

Many interactions between proteins are mediated by intrinsically disordered regions (IDRs). Intrinsically disordered proteins (IDPs) do not adopt a stable three-dimensional structure in their unbound form, but they become more structured upon binding to their partners. In this communication, we study how a bound IDR adapts to mutations, preventing the formation of hydrogen bonds at the binding interface that needs a precise positioning of the interacting residues to be formed. We use as a model the YAP:TEAD interface, where one YAP (IDP) and two TEAD residues form hydrogen bonds via their side chain. Our study shows that the conformational flexibility of bound YAP and the reorganization of water molecules at the interface help to reduce the energetic constraints created by the loss of H-bonds at the interface. The residual flexibility/dynamic of bound IDRs and water might, therefore, be a key for the adaptation of IDPs to different interface landscapes and to mutations occurring at binding interfaces.

Duplexed aptamers: history, design, theory, and application to biosensing

Nucleic acid aptamers are single stranded DNA or RNA sequences that specifically bind a cognate ligand. In addition to their widespread use as stand-alone affinity binding reagents in analytical chemistry, aptamers have been engineered into a variety of ligand-specific biosensors, termed aptasensors. One of the most common aptasensor formats is the duplexed aptamer (DA). As defined herein, DAs are aptasensors containing two nucleic acid elements coupled via Watson-Crick base pairing: (i) an aptamer sequence, which serves as a ligand-specific receptor, and (ii) an aptamer-complementary element (ACE), such as a short DNA oligonucleotide, which is designed to hybridize to the aptamer. The ACE competes with ligand binding, such that DAs generate a signal upon ligand-dependent ACE-aptamer dehybridization. DAs possess intrinsic advantages over other aptasensor designs. For example, DA biosensing designs generalize across DNA and RNA aptamers, DAs are compatible with many readout methods, and DAs are inherently tunable on the basis of nucleic acid hybridization. However, despite their utility and popularity, DAs have not been well defined in the literature, leading to confusion over the differences between DAs and other aptasensor formats. In this review, we introduce a framework for DAs based on ACEs, and use this framework to distinguish DAs from other aptasensor formats and to categorize cis- and trans-DA designs. We then explore the ligand binding dynamics and chemical properties that underpin DA systems, which fall under conformational selection and induced fit models, and which mirror classical SN1 and SN2 models of nucleophilic substitution reactions. We further review a variety of in vitro and in vivo applications of DAs in the chemical and biological sciences, including riboswitches and riboregulators. Finally, we present future directions of DAs as ligand-responsive nucleic acids. Owing to their tractability, versatility and ease of engineering, DA biosensors bear a great potential for the development of new applications and technologies in fields ranging from analytical chemistry and mechanistic modeling to medicine and synthetic biology.

BCL::MolAlign: Three-Dimensional Small Molecule Alignment for Pharmacophore Mapping

Small molecule flexible alignment is a critical component of both ligand- and structure-based methods in computer-aided drug discovery. Despite its importance, the availability of high-quality flexible alignment software packages is limited. Here, we present BCL::MolAlign, a freely available property-based molecular alignment program. BCL::MolAlign accommodates ligand flexibility through a combination of pregenerated conformers and on-the-fly bond rotation. BCL::MolAlign converges on alignment poses by sampling the relative orientations of mutually matching atom pairs between molecules through Monte Carlo Metropolis sampling. Across six diverse ligand data sets, BCL::MolAlign flexible alignment outperforms MOE, ROCS, and FLEXS in recovering native ligand binding poses. Moreover, the BCL::MolAlign alignment score is more predictive of ligand activity than maximum common substructure similarity across 10 data sets. Finally, on a recently published benchmark set of 20 high quality congeneric ligand-protein complexes, BCL::MolAlign is able to recover a larger fraction of native binding poses than maximum common substructure-based alignment and RosettaLigand. BCL::MolAlign can be obtained as part of the Biology and Chemistry Library (BCL) software package freely with an academic license or can be accessed via Web server at http://meilerlab.org/index.php/servers/molalign .

Conformational selection turns on phenylalanine hydroxylase

Phenylalanine hydroxylase catalyzes a critical step in the phenylalanine catabolic pathway, and impairment of the human enzyme is linked to phenylketonuria. Phenylalanine is also a positive allosteric regulator of the enzyme, and the allosteric binding site has been determined by crystallography. However, the allosteric activation mechanism remains unclear. Using large-scale simulations to explore how phenylalanine binds to the regulatory site, Ge et al. discovered gating motions of the protein that suggest a conformational selection mechanism.

The influence of intrinsic folding mechanism of an unfolded protein on the coupled folding-binding process during target recognition

Intrinsically disordered proteins (IDPs) are extensively involved in dynamic signaling processes which require a high association rate and a high dissociation rate for rapid binding/unbinding events and at the same time a sufficient high affinity for specific recognition. Although the coupled folding-binding processes of IDPs have been extensively studied, it is still impossible to predict whether an unfolded protein is suitable for molecular signaling via coupled folding-binding. In this work, we studied the interplay between intrinsic folding mechanisms and coupled folding-binding process for unfolded proteins through molecular dynamics simulations. We first studied the folding process of three representative IDPs with different folded structures, that is, c-Myb, AF9, and E3 rRNase. We found the folding free energy landscapes of IDPs are downhill or show low barriers. To further study the influence of intrinsic folding mechanism on the binding process, we modulated the folding mechanism of barnase via circular permutation and simulated the coupled folding-binding process between unfolded barnase permutant and folded barstar. Although folding of barnase was coupled to target binding, the binding kinetics was significantly affected by the intrinsic folding free energy barrier, where reducing the folding free energy barrier enhances binding rate up to two orders of magnitude. This accelerating effect is different from previous results which reflect the effect of structure flexibility on binding kinetics. Our results suggest that coupling the folding of an unfolded protein with no/low folding free energy barrier with its target binding may provide a way to achieve high specificity and rapid binding/unbinding kinetics simultaneously.

Conformational Selection of a Polyproline Peptide by Ebola Virus VP30

An adaptive temperature-based replica-exchange simulation of a peptide extracted from the Ebola virus nucleoprotein containing a polyproline sequence motif is reported. The simulation results of applying the CHARMM36m force field with a generalized Born solvent model is presented. Conformational heterogeneity is described by potentials of mean force (PMFs) for a set of reaction coordinates that define the topological fold space. Starting from an extended backbone conformation of the peptide observed in an X-ray crystallographic assembly with the Ebola virus protein VP30, the PMFs report a conformational landscape populated by chain excursions to collapsed states with limited transitions to either an extended fold or a canonical polyproline type II helix. Clustering of the conformations and applying an elastic network interpolation model yield a multistep pathway of conformational selection that minimizes the net transition-state cost from the population hub to the bound state. Related difference between the pathway endpoints taken from the PMFs reveal a significant free-energy penalty in reaching a population shift. To evaluate sequence fitness of the Ebola virus peptide in generating probability distributions, two human sequence variants are modeled and are found to produce profiles that show extensive deviations, thus suggesting either dissimilar binding mechanisms or the lack of recognition by VP30.

Protein dynamic communities from elastic network models align closely to the communities defined by molecular dynamics

Dynamic communities in proteins comprise the cohesive structural units that individually exhibit rigid body motions. These can correspond to structural domains, but are usually smaller parts that move with respect to one another in a protein's internal motions, key to its functional dynamics. Previous studies emphasized their importance to understand the nature of ligand-induced allosteric regulation. These studies reported that mutations to key community residues can hinder transmission of allosteric signals among the communities. Usually molecular dynamic (MD) simulations (~ 100 ns or longer) have been used to identify the communities-a demanding task for larger proteins. In the present study, we propose that dynamic communities obtained from MD simulations can also be obtained alternatively with simpler models-the elastic network models (ENMs). To verify this premise, we compare the specific communities obtained from MD and ENMs for 44 proteins. We evaluate the correspondence in communities from the two methods and compute the extent of agreement in the dynamic cross-correlation data used for community detection. Our study reveals a strong correspondence between the communities from MD and ENM and also good agreement for the residue cross-correlations. Importantly, we observe that the dynamic communities from MD can be closely reproduced with ENMs. With ENMs, we also compare the community structures of stable and unstable mutant forms of T4 Lysozyme with its wild-type. We find that communities for unstable mutants show substantially poorer agreement with the wild-type communities than do stable mutants, suggesting such ENM-based community structures can serve as a means to rapidly identify deleterious mutants.

Exploring the structural origins of cryptic sites on proteins

Molecular dynamics (MD) simulations of proteins reveal the existence of many transient surface pockets; however, the factors determining what small subset of these represent druggable or functionally relevant ligand binding sites, called "cryptic sites," are not understood. Here, we examine multiple X-ray structures for a set of proteins with validated cryptic sites, using the computational hot spot identification tool FTMap. The results show that cryptic sites in ligand-free structures generally have a strong binding energy hot spot very close by. As expected, regions around cryptic sites exhibit above-average flexibility, and close to 50% of the proteins studied here have unbound structures that could accommodate the ligand without clashes. Nevertheless, the strong hot spot neighboring each cryptic site is almost always exploited by the bound ligand, suggesting that binding may frequently involve an induced fit component. We additionally evaluated the structural basis for cryptic site formation, by comparing unbound to bound structures. Cryptic sites are most frequently occluded in the unbound structure by intrusion of loops (22.5%), side chains (19.4%), or in some cases entire helices (5.4%), but motions that create sites that are too open can also eliminate pockets (19.4%). The flexibility of cryptic sites frequently leads to missing side chains or loops (12%) that are particularly evident in low resolution crystal structures. An interesting observation is that cryptic sites formed solely by the movement of side chains, or of backbone segments with fewer than five residues, result only in low affinity binding sites with limited use for drug discovery.

Multiple Pathways and Time Scales for Conformational Transitions in apo-Adenylate Kinase

The open/close transition in adenylate kinase (AK) is regarded as a representative example for large-scale conformational transition in proteins, yet its mechanism remains unclear despite numerous experimental and computational studies. Using extensive (∼50 μs) explicit solvent atomistic simulations and Markov state analysis, we shed new lights on the mechanism of this transition in the apo form of AK. The closed basin of apo AK features an open NMP domain while the LID domain closes and rotates toward it. Therefore, although the computed structural properties of the closed ensemble are consistent with previously reported FRET and PRE measurements, our simulations suggest that NMP closure is likely to follow AMP binding, in contrast to the previous interpretation of FRET and PRE data that the apo state was able to sample the fully closed conformation for "ligand selection". The closed state ensemble is found to be kinetically heterogeneous; multiple pathways and time scales are associated with the open/close transition, providing new clues to the disparate time scales observed in different experiments. Besides interdomain interactions, a novel mutual information analysis identifies specific intradomain interactions that correlate strongly to transition kinetics, supporting observations from previous chimera experiments. While our results underscore the role of internal domain properties in determining the kinetics of open/close transition in apo AK, no evidence is observed for any significant degree of local unfolding during the transition. These observations about AK have general implications to our view of conformational states, transition pathways, and time scales of conformational changes in proteins. The key features and time scales of observed transition pathways are robust and similar from simulations using two popular fixed charge force fields.

Unified understanding of folding and binding mechanisms of globular and intrinsically disordered proteins

Extensive experimental and theoretical studies have advanced our understanding of the mechanisms of folding and binding of globular proteins, and coupled folding and binding of intrinsically disordered proteins (IDPs). The forces responsible for conformational changes and binding are common in both proteins; however, these mechanisms have been separately discussed. Here, we attempt to integrate the mechanisms of coupled folding and binding of IDPs, folding of small and multi-subdomain proteins, folding of multimeric proteins, and ligand binding of globular proteins in terms of conformational selection and induced-fit mechanisms as well as the nucleation–condensation mechanism that is intermediate between them. Accumulating evidence has shown that both the rate of conformational change and apparent rate of binding between interacting elements can determine reaction mechanisms. Coupled folding and binding of IDPs occurs mainly by induced-fit because of the slow folding in the free form, while ligand binding of globular proteins occurs mainly by conformational selection because of rapid conformational change. Protein folding can be regarded as the binding of intramolecular segments accompanied by secondary structure formation. Multi-subdomain proteins fold mainly by the induced-fit (hydrophobic collapse) mechanism, as the connection of interacting segments enhances the binding (compaction) rate. Fewer hydrophobic residues in small proteins reduce the intramolecular binding rate, resulting in the nucleation–condensation mechanism. Thus, the folding and binding of globular proteins and IDPs obey the same general principle, suggesting that the coarse-grained, statistical mechanical model of protein folding is promising for a unified theoretical description of all mechanisms.

Protein conformational flexibility modulates kinetics and thermodynamics of drug binding

Structure-based drug design has often been restricted by the rather static picture of protein-ligand complexes presented by crystal structures, despite the widely accepted importance of protein flexibility in biomolecular recognition. Here we report a detailed experimental and computational study of the drug target, human heat shock protein 90, to explore the contribution of protein dynamics to the binding thermodynamics and kinetics of drug-like compounds. We observe that their binding properties depend on whether the protein has a loop or a helical conformation in the binding site of the ligand-bound state. Compounds bound to the helical conformation display slow association and dissociation rates, high-affinity and high cellular efficacy, and predominantly entropically driven binding. An important entropic contribution comes from the greater flexibility of the helical relative to the loop conformation in the ligand-bound state. This unusual mechanism suggests increasing target flexibility in the bound state by ligand design as a new strategy for drug discovery.

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

The advancement of multidimensional QSAR for novel drug discovery - where are we headed?

INTRODUCTION

The Multidimensional quantitative structure-activity relationship (multidimensional-QSAR) method is one of the most popular computational methods employed to predict interesting biochemical properties of existing or hypothetical molecules. With continuous progress, the QSAR method has made remarkable success in various fields, such as medicinal chemistry, material science and predictive toxicology. Areas covered: In this review, the authors cover the basic elements of multidimensional -QSAR including model construction, validation and application. It includes and emphasizes the very recent developments of multidimensional -QSAR such as: HQSAR, G-QSAR, MIA-QSAR, multi-target QSAR. The advantages and disadvantages of each method are also discussed and typical examples of their application are detailed. Expert opinion: Although there are defects in multidimensional-QSAR modeling, it is still of enormous help to chemists, biologists and other researchers in various fields. In the authors' opinion, the latest more precise and feasible QSAR models should be further developed by integrating new descriptors, algorithms and other relevant computational techniques. Apart from being applied in traditional fields (e.g. lead optimization and predictive risk assessment), QSAR should be used more widely as a routine method in other emerging research fields including the modeling of nanoparticles(NPs), mixture toxicity and peptides.

Rate Constants and Mechanisms of Protein-Ligand Binding

Whereas protein-ligand binding affinities have long-established prominence, binding rate constants and binding mechanisms have gained increasing attention in recent years. Both new computational methods and new experimental techniques have been developed to characterize the latter properties. It is now realized that binding mechanisms, like binding rate constants, can and should be quantitatively determined. In this review, we summarize studies and synthesize ideas on several topics in the hope of providing a coherent picture of and physical insight into binding kinetics. The topics include microscopic formulation of the kinetic problem and its reduction to simple rate equations; computation of binding rate constants; quantitative determination of binding mechanisms; and elucidation of physical factors that control binding rate constants and mechanisms.

A Kinetic Signature for Parallel Pathways: Conformational Selection and Induced Fit. Links and Disconnects between Observed Relaxation Rates and Fractional Equilibrium Flux under Pseudo-First-Order Conditions

Molecular association plays a ubiquitous role in biochemistry and is often accompanied by conformational exchange in one or both binding partners. Traditionally, two limiting mechanisms are considered for the association of two molecules. In a conformational selection (CS) mechanism, a ligand preferentially binds to a subset of conformations in its binding partner. In contrast, an induced fit (IF) mechanism describes the ligand-dependent isomerization of the binding partner in which binding occurs prior to conformational exchange. Measurements of the ligand concentration dependence of observed rates of relaxation are commonly used to probe whether CS or IF is taking place. Here we consider a four-state thermodynamic cycle subject to detailed balance and demonstrate the existence of a relatively unexplored class of kinetic signatures where an initial decrease in the observed rate is followed by a subsequent increase under pseudo-first-order conditions. We elucidate regions of rate space necessary to generate a nonmonotonic observed rate and show that, under certain conditions, the position of the minimum of the observed rate correlates with a transition in equilibrium flux between CS and IF pathways. Furthermore, we demonstrate that monotonic trends in the observed rate can occur when both CS and IF mechanisms are taking place, suggesting that caution must be taken not to overinterpret monotonic trends as evidence of the absence of either CS or IF. Lastly, we conclude that a nonmonotonic kinetic signature is uniquely unambiguous in the sense that when this trend is observed, one may conclude that both CS and IF mechanistic paths are utilized.

Understanding the core of RNA interference: The dynamic aspects of Argonaute-mediated processes

At the core of RNA interference, the Argonaute proteins (Ago) load and utilize small guide nucleic acids to silence mRNAs or cleave foreign nucleic acids in a sequence specific manner. In recent years, based on extensive structural studies of Ago and its interaction with the nucleic acids, considerable progress has been made to reveal the dynamic aspects of various Ago-mediated processes. Here we review these novel insights into the guide-strand loading, duplex unwinding, and effects of seed mismatch, with a focus on two representative Agos, the human Ago 2 (hAgo2) and the bacterial Thermus thermophilus Ago (TtAgo). In particular, comprehensive molecular simulation studies revealed that although sharing similar overall structures, the two Agos have vastly different conformational landscapes and guide-strand loading mechanisms because of the distinct rigidity of their L1-PAZ hinge. Given the central role of the PAZ motions in regulating the exposure of the nucleic acid binding channel, these findings exemplify the importance of protein motions in distinguishing the overlapping, yet distinct, mechanisms of Ago-mediated processes in different organisms.

How to Distinguish Conformational Selection and Induced Fit Based on Chemical Relaxation Rates

Protein binding often involves conformational changes. Important questions are whether a conformational change occurs prior to a binding event (‘conformational selection’) or after a binding event (‘induced fit’), and how conformational transition rates can be obtained from experiments. In this article, we present general results for the chemical relaxation rates of conformational-selection and induced-fit binding processes that hold for all concentrations of proteins and ligands and, thus, go beyond the standard pseudo-first-order approximation of large ligand concentration. These results allow to distinguish conformational-selection from induced-fit processes—also in cases in which such a distinction is not possible under pseudo-first-order conditions—and to extract conformational transition rates of proteins from chemical relaxation data.

The function of proteins is affected by their conformational dynamics, i.e. by transitions between lower-energy ground-state conformations and higher-energy excited-state conformations of the proteins. Advanced NMR and single-molecule experiments indicate that higher-energy conformations in the unbound state of proteins can be similar to ground-state conformations in the bound state, and vice versa. These experiments illustrate that the conformational change of a protein during binding may occur before a binding event, rather than being induced by this binding event. However, determining the temporal order of conformational transitions and binding events typically requires additional information from chemical relaxation experiments that probe the relaxation kinetics of a mixture of proteins and ligands into binding equilibrium. These chemical relaxation experiments are usually performed and analysed at ligand concentrations that are much larger than the protein concentrations. At such high ligand concentrations, the temporal order of conformational transitions and binding events can only be inferred in special cases. In this article, we present general equations that describe the dominant chemical relaxation kinetics for all protein and ligand concentrations. Our general equations allow to clearly infer from relaxation data whether a conformational transition occurs prior to a binding event, or after the binding event.