Selected-fit versus induced-fit protein binding: kinetic differences and mutational analysis

Allosteric regulation of pathologic angiogenesis: potential application for angiogenesis-related blindness

Angiogenesis-related blindness (ARB) includes age-related macular degeneration, diabetic retinopathy, and retinopathy of prematurity, all of which are based on pathologic angiogenesis. Current treatment options such as surgery, laser photocoagulation, and steroid have shown limitations because they do not directly resolve the pathologic events in the retina. Furthermore, recently approved and developed therapeutic drugs only focus on direct inhibition of growth factors and suppression of downstream signaling molecules of activated receptor proteins by orthosteric ligands. In this regard, allosteric regulation of receptors and ligands can be a valuable mechanism in the development of novel drugs for ARB. In this review, we briefly address the clinical significance of ARB for further discussion on allosteric regulation of pathologic angiogenesis for ARB. Interestingly, key molecules in the pathogenesis of ARB can be targets for allosteric regulation, sharing characteristics as allosteric proteins. With investigation of allostery by introducing well-established models for allosteric proteins and currently published novel allosteric modulators, we discuss the potential of allosteric regulation for ARB. In conclusion, we hope that allosteric regulation of pathologic angiogenesis in ARB can open new opportunities for drug development.

Stationary distribution of self-organized states and biological information generation

Self-organization, where spontaneous orderings occur under driven conditions, is one of the hallmarks of biological systems. We consider a statistical mechanical treatment of the biased distribution of such organized states, which become favored as a result of their catalytic activity under chemical driving forces. A generalization of the equilibrium canonical distribution describes the stationary state, which can be used to model shifts in conformational ensembles sampled by an enzyme in working conditions. The basic idea is applied to the process of biological information generation from random sequences of heteropolymers, where unfavorable Shannon entropy is overcome by the catalytic activities of selected genes. The ordering process is demonstrated with the genetic distance to a genotype with high catalytic activity as an order parameter. The resulting free energy can have multiple minima, corresponding to disordered and organized phases with first-order transitions between them.

Conformation-based restrictions and scaffold replacements in the design of hepatitis C virus polymerase inhibitors: discovery of deleobuvir (BI 207127)

Conformational restrictions of flexible torsion angles were used to guide the identification of new chemotypes of HCV NS5B inhibitors. Sites for rigidification were based on an acquired conformational understanding of compound binding requirements and the roles of substituents in the free and bound states. Chemical bioisosteres of amide bonds were explored to improve cell-based potency. Examples are shown, including the design concept that led to the discovery of the phase III clinical candidate deleobuvir (BI 207127). The structure-based strategies employed have general utility in drug design.

Effect of short- and long-range interactions on trp rotamer populations determined by site-directed tryptophan fluorescence of tear lipocalin

In the lipocalin family, the conserved interaction between the main α-helix and the β-strand H is an ideal model to study protein side chain dynamics. Site-directed tryptophan fluorescence (SDTF) has successfully elucidated tryptophan rotamers at positions along the main alpha helical segment of tear lipocalin (TL). The rotamers assigned by fluorescent lifetimes of Trp residues corroborate the restriction expected based on secondary structure. Steric conflict constrains Trp residues to two (t, g⁻) of three possible χ₁ (t, g⁻, g⁺) canonical rotamers. In this study, investigation focused on the interplay between rotamers for a single amino acid position, Trp 130 on the α-helix and amino acids Val 113 and Leu 115 on the H strand, i.e. long range interactions. Trp130 was substituted for Phe by point mutation (F130W). Mutations at positions 113 and 115 with combinations of Gly, Ala, Phe residues alter the rotamer distribution of Trp130. Mutations, which do not distort local structure, retain two rotamers (two lifetimes) populated in varying proportions. Replacement of either long range partner with a small amino acid, V113A or L115A, eliminates the dominance of the t rotamer. However, a mutation that distorts local structure around Trp130 adds a third fluorescence lifetime component. The results indicate that the energetics of long-range interactions with Trp 130 further tune rotamer populations. Diminished interactions, evident in W130G113A115, result in about a 22% increase of α-helix content. The data support a hierarchic model of protein folding. Initially the secondary structure is formed by short-range interactions. TL has non-native α-helix intermediates at this stage. Then, the long-range interactions produce the native fold, in which TL shows α-helix to β-sheet transitions. The SDTF method is a valuable tool to assess long-range interaction energies through rotamer distribution as well as the characterization of low-populated rotameric states of functionally important excited protein states.

Ligand bioactive conformation plays a critical role in the design of drugs that target the hepatitis C virus NS3 protease

A ligand-focused strategy employed NMR, X-ray, modeling, and medicinal chemistry to expose the critical role that bioactive conformation played in the design of a variety of drugs that target the HCV protease. The bioactive conformation (bound states) were determined for key inhibitors identified along our drug discovery pathway from the hit to clinical compounds. All adopt similar bioactive conformations for the common core derived from the hit peptide DDIVPC. A carefully designed SAR analysis, based on the advanced inhibitor 1 in which the P1 to P3 side chains and the N-terminal Boc were sequentially truncated, revealed a correlation between affinity and the relative predominance of the bioactive conformation in the free state. Interestingly, synergistic conformation effects on potency were also noted. Comparisons with clinical and recently marketed drugs from the pharmaceutical industry showed that all have the same core and similar bioactive conformations. This suggested that the variety of appendages discovered for these compounds also properly satisfy the bioactive conformation requirements and allowed for a large variety of HCV protease drug candidates to be designed.

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

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

Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization

Predicting the effects of mutations on the kinetic rate constants of protein-protein interactions is central to both the modeling of complex diseases and the design of effective peptide drug inhibitors. However, while most studies have concentrated on the determination of association rate constants, dissociation rates have received less attention. In this work we take a novel approach by relating the changes in dissociation rates upon mutation to the energetics and architecture of hotspots and hotregions, by performing alanine scans pre- and post-mutation. From these scans, we design a set of descriptors that capture the change in hotspot energy and distribution. The method is benchmarked on 713 kinetically characterized mutations from the SKEMPI database. Our investigations show that, with the use of hotspot descriptors, energies from single-point alanine mutations may be used for the estimation of off-rate mutations to any residue type and also multi-point mutations. A number of machine learning models are built from a combination of molecular and hotspot descriptors, with the best models achieving a Pearson's Correlation Coefficient of 0.79 with experimental off-rates and a Matthew's Correlation Coefficient of 0.6 in the detection of rare stabilizing mutations. Using specialized feature selection models we identify descriptors that are highly specific and, conversely, broadly important to predicting the effects of different classes of mutations, interface regions and complexes. Our results also indicate that the distribution of the critical stability regions across protein-protein interfaces is a function of complex size more strongly than interface area. In addition, mutations at the rim are critical for the stability of small complexes, but consistently harder to characterize. The relationship between hotregion size and the dissociation rate is also investigated and, using hotspot descriptors which model cooperative effects within hotregions, we show how the contribution of hotregions of different sizes, changes under different cooperative effects.

Conformational selection is a dominant mechanism of ligand binding

Molecular recognition in biological macromolecules is achieved by binding interactions coupled to conformational transitions that precede or follow the binding step, two limiting mechanisms known as conformational selection and induced fit, respectively. Sorting out the contribution of these mechanisms to any binding interaction remains a challenging task of general interest in biochemistry. Here we show that conformational selection is associated with a vast repertoire of kinetic behaviors, can never be disproved a priori as a mechanism of ligand binding, and is sufficient to explain the relaxation kinetics documented experimentally for a large number of systems. On the other hand, induced fit features a narrow spectrum of kinetic behaviors and can be disproved in many cases in which conformational selection offers the only possible explanation. This conclusion offers a paradigm shift in the analysis of relaxation kinetics, with conformational selection acquiring preeminence as a mechanism of ligand binding. The dominant role of conformational selection supports the emerging structural view of the macromolecule as a conformational ensemble from which the ligand selects the initial optimal fit to produce a biological response.

Molecular simulations illuminate the role of regulatory components of the RNA polymerase from the hepatitis C virus in influencing protein structure and dynamics

The RNA polymerase (gene product NS5B) from the hepatitis C virus is responsible for replication of the viral genome and is a validated drug target for new therapeutic agents. NS5B has a structure resembling an open right hand (containing the fingers, palm, and thumb subdomains), a hydrophobic C-terminal region, and two magnesium ions coordinated in the palm domain. Biochemical data suggest that the magnesium ions provide structural stability and are directly involved in catalysis, while the C-terminus plays a regulatory role in NS5B function. Nevertheless, the molecular mechanisms by which these two features regulate polymerase activity remain unclear. To answer this question, we performed molecular dynamics simulations of NS5B variants with different C-terminal lengths in the presence or absence of magnesium ions to determine the impact on enzyme properties. We observed that metal binding increases both the magnitude and the degree of correlated enzyme motions. In contrast, we observed that the C-terminus restricts enzyme dynamics. Under certain conditions, our simulations revealed a fully closed conformation of NS5B that may facilitate de novo initiation of RNA replication. This knowledge is important because it fosters the development of a comprehensive description of RNA replication by NS5B and is relevant to understanding the functional properties of a broad class of related RNA polymerases such as 3D-pol from poliovirus. Ultimately, this information may also be pertinent to designing novel NS5B therapeutics.

Enzymatic detoxication, conformational selection, and the role of molten globule active sites

The role of conformational ensembles in enzymatic reactions remains unclear. Discussion concerning "induced fit" versus "conformational selection" has, however, ignored detoxication enzymes, which exhibit catalytic promiscuity. These enzymes dominate drug metabolism and determine drug-drug interactions. The detoxication enzyme glutathione transferase A1-1 (GSTA1-1), exploits a molten globule-like active site to achieve remarkable catalytic promiscuity wherein the substrate-free conformational ensemble is broad with barrierless transitions between states. A quantitative index of catalytic promiscuity is used to compare engineered variants of GSTA1-1 and the catalytic promiscuity correlates strongly with characteristics of the thermodynamic partition function, for the substrate-free enzymes. Access to chemically disparate transition states is encoded by the substrate-free conformational ensemble. Pre-steady state catalytic data confirm an extension of the conformational selection model, wherein different substrates select different starting conformations. The kinetic liability of the conformational breadth is minimized by a smooth landscape. We propose that "local" molten globule behavior optimizes detoxication enzymes.

Global conformational selection and local induced fit for the recognition between intrinsic disordered p53 and CBP

The transactivation domain (TAD) of tumor suppressor p53 can bind with the nuclear coactivator binding domain (NCBD) of cyclic-AMP response element binding protein (CBP) and activate transcription. NMR experiments demonstrate that both apo-NCBD and TAD are intrinsic disordered and bound NCBD/TAD undergoes a transition to well folded. The recognition mechanism between intrinsic disordered proteins is still hotly debated. Molecular dynamics (MD) simulations in explicit solvent are used to study the recognition mechanism between intrinsic disordered TAD and NCBD. The average RMSD values between bound and corresponding apo states and Kolmogorov-Smirnov P test analysis indicate that TAD and NCBD may follow an induced fit mechanism. Quantitative analysis indicates there is also a global conformational selection. In summary, the recognition of TAD and NCBD might obey a local induced fit and global conformational selection. These conclusions are further supported by high-temperature unbinding kinetics and room temperature landscape analysis. These methods can be used to study the recognition mechanism of other intrinsic disordered proteins.

A unified conformational selection and induced fit approach to protein-peptide docking

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.

HDAC8 substrates: Histones and beyond

The lysine deacetylase family of enzymes (HDACs) was first demonstrated to catalyze deacetylation of acetyllysine residues on histones. In subsequent years, HDACs have been shown to recognize a large pool of acetylated nonhistone proteins as substrates. Recently, thousands of acetylated proteins have been discovered, yet in most cases, the HDAC that catalyzes deacetylation in vivo has not been identified. This gap has created the need for better in vivo, in vitro, and in silico approaches for determining HDAC substrates. While HDAC8 is the best kinetically and structurally characterized HDAC, few efficient substrates have yet been substantiated in vivo. In this review, we delineate factors that may be important for determining HDAC8 substrate recognition and catalytic activity, including structure, complex formation, and post-translational modifications. This summary provides insight into the challenges of identifying in vivo substrates for HDAC8, and provides a good vantage point for understanding the variables important for predicting HDAC substrate recognition.

How conformational changes can affect catalysis, inhibition and drug resistance of enzymes with induced-fit binding mechanism such as the HIV-1 protease

A central question is how the conformational changes of proteins affect their function and the inhibition of this function by drug molecules. Many enzymes change from an open to a closed conformation upon binding of substrate or inhibitor molecules. These conformational changes have been suggested to follow an induced-fit mechanism in which the molecules first bind in the open conformation in those cases where binding in the closed conformation appears to be sterically obstructed such as for the HIV-1 protease. In this article, we present a general model for the catalysis and inhibition of enzymes with induced-fit binding mechanism. We derive general expressions that specify how the overall catalytic rate of the enzymes depends on the rates for binding, for the conformational changes, and for the chemical reaction. Based on these expressions, we analyze the effect of mutations that mainly shift the conformational equilibrium on catalysis and inhibition. If the overall catalytic rate is limited by product unbinding, we find that mutations that destabilize the closed conformation relative to the open conformation increase the catalytic rate in the presence of inhibitors by a factor exp(ΔΔGC/RT) where ΔΔGC is the mutation-induced shift of the free-energy difference between the conformations. This increase in the catalytic rate due to changes in the conformational equilibrium is independent of the inhibitor molecule and, thus, may help to understand how non-active-site mutations can contribute to the multi-drug-resistance that has been observed for the HIV-1 protease. A comparison to experimental data for the non-active-site mutation L90M of the HIV-1 protease indicates that the mutation slightly destabilizes the closed conformation of the enzyme. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.

Kinetics of ligand-receptor interaction reveals an induced-fit mode of binding in a cyclic nucleotide-activated protein

Many receptors and ion channels are activated by ligands. One key question concerns the binding mechanism. Does the ligand induce conformational changes in the protein via the induced-fit mechanism? Or does the protein preexist as an ensemble of conformers and the ligand selects the most complementary one, via the conformational selection mechanism? Here, we study ligand binding of a tetrameric cyclic nucleotide-gated channel from Mesorhizobium loti and of its monomeric binding domain (CNBD) using rapid mixing, mutagenesis, and structure-based computational biology. Association rate constants of ∼10(7) M(-1) s(-1) are compatible with diffusion-limited binding. Ligand binding to the full-length CNG channel and the isolated CNBD differ, revealing allosteric control of the CNBD by the effector domain. Finally, mutagenesis of allosteric residues affects only the dissociation rate constant, suggesting that binding follows the induced-fit mechanism. This study illustrates the strength of combining mutational, kinetic, and computational approaches to unravel important mechanistic features of ligand binding.

Single-molecule observation of the induction of k-turn RNA structure on binding L7Ae protein

The k-turn is a commonly occurring structural motif that introduces a tight kink into duplex RNA. In free solution, it can exist in an extended form, or by folding into the kinked structure. Binding of proteins including the L7Ae family can induce the formation of the kinked geometry, raising the question of whether this occurs by passive selection of the kinked structure, or a more active process in which the protein manipulates the RNA structure. We have devised a single-molecule experiment whereby immobilized L7Ae protein binds Cy3-Cy5-labeled RNA from free solution. We find that all bound RNA is in the kinked geometry, with no evidence for transitions to an extended form at the millisecond timescale of the camera. Furthermore, real-time binding experiments provide no evidence for a more extended intermediate even at the earliest times, at a time resolution of 16 ms. The data support a passive conformational selection model by which the protein selects a fraction of RNA that is already in the kinked conformation, thereby drawing the equilibrium into this form.

On the binding affinity of macromolecular interactions: daring to ask why proteins interact

Interactions between proteins are orchestrated in a precise and time-dependent manner, underlying cellular function. The binding affinity, defined as the strength of these interactions, is translated into physico-chemical terms in the dissociation constant (K_d), the latter being an experimental measure that determines whether an interaction will be formed in solution or not. Predicting binding affinity from structural models has been a matter of active research for more than 40 years because of its fundamental role in drug development. However, all available approaches are incapable of predicting the binding affinity of protein–protein complexes from coordinates alone. Here, we examine both theoretical and experimental limitations that complicate the derivation of structure–affinity relationships. Most work so far has concentrated on binary interactions. Systems of increased complexity are far from being understood. The main physico-chemical measure that relates to binding affinity is the buried surface area, but it does not hold for flexible complexes. For the latter, there must be a significant entropic contribution that will have to be approximated in the future. We foresee that any theoretical modelling of these interactions will have to follow an integrative approach considering the biology, chemistry and physics that underlie protein–protein recognition.

Modulation of a ligand's energy landscape and kinetics by the chemical environment

Understanding how the chemical environment modulates the predominant conformations and kinetics of flexible molecules is a core interest of biochemistry and a prerequisite for the rational design of synthetic catalysts. This study combines molecular dynamics simulation and Markov state models (MSMs) to a systematic computational strategy for investigating the effect of the chemical environment of a molecule on its conformations and kinetics. MSMs allow quantities to be computed that are otherwise difficult to access, such as the metastable sets, their free energies, and the relaxation time scales related to the rare transitions between metastable states. Additionally, MSMs are useful to identify observables that may act as sensors for the conformational or binding state of the molecule, thus guiding the design of experiments. In the present study, the conformation dynamics of UDP-GlcNAc are studied in vacuum, water, water + Mg(2+), and in the protein UDP-GlcNAc 2-epimerase. It is found that addition of Mg(2+) significantly affects the conformational stability, thermodynamics, and kinetics of UDP-GlcNAc. In particular, the slowest structural process, puckering of the GlcNAc sugar, depends on the overall conformation of UDP-GlcNAc and may thus act as a sensor of whether Mg(2+) is bound or not. Interestingly, transferring the molecule from vacuum to water makes the protein-binding conformations UDP-GlcNAc first accessible, while adding Mg(2+) further stabilizes them by specifically associating to binding-competent conformations. While Mg(2+) is not cocrystallized in the UDP-GlcNAc 2-epimerase complex, the selectively stabilized Mg(2+)/UDP-GlcNAc complex may be a template for the bound state, and Mg(2+) may accompany the binding-competent ligand conformation to the binding pocket. This serves as a possible explanation of the enhanced epimerization rate in the presence of Mg(2+). This role of Mg(2+) has previously not been described and opens the question whether "binding co-factors" may be a concept of general relevance for protein-ligand binding.

The kinetics and folding pathways of intramolecular G-quadruplex nucleic acids

The folding kinetics of G-quadruplex forming sequences is critical to their capacity to influence biological function. While G-quadruplex structure and stability have been relatively well studied, little is known about the kinetics of their folding. We employed a stopped-flow mixing technique to systematically investigate the potassium-dependent folding kinetics of telomeric RNA and DNA G-quadruplexes and RNA G-quadruplexes containing only two G-quartets formed from sequences r[(GGA)(3)GG] and r[(GGUUA)(3)GG]. Our findings suggest a folding mechanism that involves two kinetic steps with initial binding of a single K(+), irrespective of the number of G-quartets involved or whether the G-quadruplex is formed from RNA or DNA. The folding rates for telomeric RNA and DNA G-quadruplexes are comparable at near physiological [K(+)] (90 mM) (τ = ~60 ms). The folding of a 2-quartet RNA G-quadruplex with single nucleotide A loops is considerably slower (τ = ~700 ms), and we found that the time required to fold a UUA looped variant (τ > 100 s, 500 mM K(+)) exceeds the lifetimes of some regulatory RNAs. We discuss the implications of these findings with respect to the fundamental properties of G-quadruplexes and their potential functions in biology.

Ubiquitin dynamics in complexes reveal molecular recognition mechanisms beyond induced fit and conformational selection

Protein-protein interactions play an important role in all biological processes. However, the principles underlying these interactions are only beginning to be understood. Ubiquitin is a small signalling protein that is covalently attached to different proteins to mark them for degradation, regulate transport and other functions. As such, it interacts with and is recognised by a multitude of other proteins. We have conducted molecular dynamics simulations of ubiquitin in complex with 11 different binding partners on a microsecond timescale and compared them with ensembles of unbound ubiquitin to investigate the principles of their interaction and determine the influence of complex formation on the dynamic properties of this protein. Along the main mode of fluctuation of ubiquitin, binding in most cases reduces the conformational space available to ubiquitin to a subspace of that covered by unbound ubiquitin. This behaviour can be well explained using the model of conformational selection. For lower amplitude collective modes, a spectrum of zero to almost complete coverage of bound by unbound ensembles was observed. The significant differences between bound and unbound structures are exclusively situated at the binding interface. Overall, the findings correspond neither to a complete conformational selection nor induced fit scenario. Instead, we introduce a model of conformational restriction, extension and shift, which describes the full range of observed effects.

The dynamics of drug-target interactions: drug-target residence time and its impact on efficacy and safety

The extent and duration of pharmacological action is determined by the lifetime of drug occupancy on a molecular target. This lifetime is defined by dynamic processes that control the rates of drug association and dissociation from the target. Recently, the term residence time has been coined to describe experimental measurements that can be related to the lifetime of the binary drug-target complex, and this in turn to durable, pharmacodynamic activity. The residence time concept and its impact on drug optimization are reviewed here. Examples are provided that demonstrate how a long residence time can improve drug efficacy in vivo. Additionally, optimization of drug-target residence time can help to mitigate off-target mediated toxicity, hence, improving drug safety and tolerability. Recent applications of the residence time concept to both drug discovery and development are also presented.

A folding-after-binding mechanism describes the recognition between the transactivation domain of c-Myb and the KIX domain of the CREB-binding protein

A large body of evidence suggests that a considerable fraction of the human proteome may be at least in part intrinsically unstructured. While disordered, intrinsically unstructured proteins are nevertheless functional and mediate many interactions. Despite their significant role in regulation, however, little is known about the molecular mechanism whereby intrinsically unstructured proteins exert their function. This basic problem is critical to establish the role, if any, of disorder in cellular systems. Here we present kinetic experiments supporting a mechanism of binding-induced-folding when the KIX domain of the CREB-binding protein binds the transactivation domain of c-Myb, an intrinsically unstructured domain. The high-resolution structure of this physiologically important complex was previously determined by NMR spectroscopy. Our data reveal that c-Myb recognizes KIX by first forming a weak encounter complex in a disordered conformation, which is subsequently locked-in by a folding step, i.e. binding precedes folding. On the basis of the pH dependence of the observed combination and dissociation rate constants we propose a plausible mechanism for complex formation. The implications of our results in the light of previous work on intrinsically unstructured systems are discussed.

Thumb inhibitor binding eliminates functionally important dynamics in the hepatitis C virus RNA polymerase

Hepatitis C virus (HCV) has infected almost 200 million people worldwide, typically causing chronic liver damage and severe complications such as liver failure. Currently, there are few approved treatments for viral infection. Thus, the HCV RNA-dependent RNA polymerase (gene product NS5B) has emerged as an important target for small molecule therapeutics. Potential therapeutic agents include allosteric inhibitors that bind distal to the enzyme active site. While their mechanism of action is not conclusively known, it has been suggested that certain inhibitors prevent a conformational change in NS5B that is crucial for RNA replication. To gain insight into the molecular origin of long-range allosteric inhibition of NS5B, we employed molecular dynamics simulations of the enzyme with and without an inhibitor bound to the thumb domain. These studies indicate that the presence of an inhibitor in the thumb domain alters both the structure and internal motions of NS5B. Principal components analysis identified motions that are severely attenuated by inhibitor binding. These motions may have functional relevance by facilitating interactions between NS5B and RNA template or nascent RNA duplex, with presence of the ligand leading to enzyme conformations with narrower and thus less accessible RNA binding channels. This study provides the first evidence for a mechanistic basis of allosteric inhibition in NS5B. Moreover, we present evidence that allosteric inhibition of NS5B results from intrinsic features of the enzyme free energy landscape, suggesting a common mechanism for the action of diverse allosteric ligands.

An adaptive weighted ensemble procedure for efficient computation of free energies and first passage rates

We introduce an adaptive weighted-ensemble procedure (aWEP) for efficient and accurate evaluation of first-passage rates between states for two-state systems. The basic idea that distinguishes aWEP from conventional weighted-ensemble (WE) methodology is the division of the configuration space into smaller regions and equilibration of the trajectories within each region upon adaptive partitioning of the regions themselves into small grids. The equilibrated conditional∕transition probabilities between each pair of regions lead to the determination of populations of the regions and the first-passage times between regions, which in turn are combined to evaluate the first passage times for the forward and backward transitions between the two states. The application of the procedure to a non-trivial coarse-grained model of a 70-residue calcium binding domain of calmodulin is shown to efficiently yield information on the equilibrium probabilities of the two states as well as their first passage times. Notably, the new procedure is significantly more efficient than the canonical implementation of the WE procedure, and this improvement becomes even more significant at low temperatures.

Single amino acid exchange in bacteriophage HK620 tailspike protein results in thousand-fold increase of its oligosaccharide affinity

Bacteriophage HK620 recognizes and cleaves the O-antigen polysaccharide of Escherichia coli serogroup O18A1 with its tailspike protein (TSP). HK620TSP binds hexasaccharide fragments with low affinity, but single amino acid exchanges generated a set of high-affinity mutants with submicromolar dissociation constants. Isothermal titration calorimetry showed that only small amounts of heat were released upon complex formation via a large number of direct and solvent-mediated hydrogen bonds between carbohydrate and protein. At room temperature, association was both enthalpy- and entropy-driven emphasizing major solvent rearrangements upon complex formation. Crystal structure analysis showed identical protein and sugar conformers in the TSP complexes regardless of their hexasaccharide affinity. Only in one case, a TSP mutant bound a different hexasaccharide conformer. The extended sugar binding site could be dissected in two regions: first, a hydrophobic pocket at the reducing end with minor affinity contributions. Access to this site could be blocked by a single aspartate to asparagine exchange without major loss in hexasaccharide affinity. Second, a region where the specific exchange of glutamate for glutamine created a site for an additional water molecule. Side-chain rearrangements upon sugar binding led to desolvation and additional hydrogen bonding which define this region of the binding site as the high-affinity scaffold.

pH effects on binding between the anthrax protective antigen and the host cellular receptor CMG2

The anthrax protective antigen (PA) binds to the host cellular receptor capillary morphogenesis protein 2 (CMG2) with high affinity. To gain a better understanding of how pH may affect binding to the receptor, we have investigated the kinetics of binding as a function of pH to the full-length monomeric PA and to two variants: a 2-fluorohistidine-labeled PA (2-FHisPA), which is ∼1 pH unit more stable to variations in pH than WT, and an ∼1 pH unit less stable variant in which Trp346 in the domain 2β(3) -2β(4) loop is substituted with a Phe (W346F). We show using stopped-flow fluorescence that the binding rate increases as the pH is lowered for all proteins, with little influence on the rate of dissociation. In addition, we have crystallized PA and the two variants and examine the influence of pH on structure. In contrast to previous X-ray studies, the domain 2β(3) -2β(4) loop undergoes little change in structure from pH ∼8 to 5.5 for the WT protein, but for the 2-FHis labeled and W346F mutant there are changes in structure consistent with previous X-ray studies. In accord with pH stability studies, we find that the average B-factor values increase by ∼20-30% for all three proteins at low pH. Our results suggest that for the full-length PA, low pH increases the binding affinity, likely through a change in structure that favors a more "bound-like" conformation.

SKEMPI: a Structural Kinetic and Energetic database of Mutant Protein Interactions and its use in empirical models

MOTIVATION

Empirical models for the prediction of how changes in sequence alter protein-protein binding kinetics and thermodynamics can garner insights into many aspects of molecular biology. However, such models require empirical training data and proper validation before they can be widely applied. Previous databases contained few stabilizing mutations and no discussion of their inherent biases or how this impacts model construction or validation.

RESULTS

We present SKEMPI, a database of 3047 binding free energy changes upon mutation assembled from the scientific literature, for protein-protein heterodimeric complexes with experimentally determined structures. This represents over four times more data than previously collected. Changes in 713 association and dissociation rates and 127 enthalpies and entropies were also recorded. The existence of biases towards specific mutations, residues, interfaces, proteins and protein families is discussed in the context of how the data can be used to construct predictive models. Finally, a cross-validation scheme is presented which is capable of estimating the efficacy of derived models on future data in which these biases are not present.

AVAILABILITY

The database is available online at http://life.bsc.es/pid/mutation_database/.

Protein flexibility in docking and surface mapping

Structure-based drug design has become an essential tool for rapid lead discovery and optimization. As available structural information has increased, researchers have become increasingly aware of the importance of protein flexibility for accurate description of the native state. Typical protein-ligand docking efforts still rely on a single rigid receptor, which is an incomplete representation of potential binding conformations of the protein. These rigid docking efforts typically show the best performance rates between 50 and 75%, while fully flexible docking methods can enhance pose prediction up to 80-95%. This review examines the current toolbox for flexible protein-ligand docking and receptor surface mapping. Present limitations and possibilities for future development are discussed.

Kinetic rate constant prediction supports the conformational selection mechanism of protein binding

The prediction of protein-protein kinetic rate constants provides a fundamental test of our understanding of molecular recognition, and will play an important role in the modeling of complex biological systems. In this paper, a feature selection and regression algorithm is applied to mine a large set of molecular descriptors and construct simple models for association and dissociation rate constants using empirical data. Using separate test data for validation, the predicted rate constants can be combined to calculate binding affinity with accuracy matching that of state of the art empirical free energy functions. The models show that the rate of association is linearly related to the proportion of unbound proteins in the bound conformational ensemble relative to the unbound conformational ensemble, indicating that the binding partners must adopt a geometry near to that of the bound prior to binding. Mirroring the conformational selection and population shift mechanism of protein binding, the models provide a strong separate line of evidence for the preponderance of this mechanism in protein-protein binding, complementing structural and theoretical studies.

Expanding the conformational selection paradigm in protein-ligand docking

Conformational selection emerges as a theme in macromolecular interactions. Data validate it as a prevailing mechanism in protein-protein, protein-DNA, protein-RNA, and protein-small molecule drug recognition. This raises the question of whether this fundamental biomolecular binding mechanism can be used to improve drug docking and discovery. Actually, in practice this has already been taking place for some years in increasing numbers. Essentially, it argues for using not a single conformer, but an ensemble. The paradigm of conformational selection holds that because the ensemble is heterogeneous, within it there will be states whose conformation matches that of the ligand. Even if the population of this state is low, since it is favorable for binding the ligand, it will bind to it with a subsequent population shift toward this conformer. Here we suggest expanding it by first modeling all protein interactions in the cell by using Prism, an efficient motif-based protein-protein interaction modeling strategy, followed by ensemble generation. Such a strategy could be particularly useful for signaling proteins, which are major targets in drug discovery and bind multiple partners through a shared binding site, each with some-minor or major-conformational change.

Conformational adaptation in drug-target interactions and residence time

Although drug-target interactions are commonly illustrated in terms of structurally static binding and dissociation events, such descriptions are inadequate to explain the impact of conformational dynamics on these processes. For high-affinity interactions, both the association and dissociation of drug molecules to and from their targets are often controlled by conformational changes of the target. Conformational adaptation can greatly influence the residence time of a drug on its target (i.e., the lifetime of the binary drug-target complex); long residence time can lead to sustained pharmacology and may also mitigate off-target toxicity. In this perspective, the kinetics of drug-target association and dissociation reactions are explored, with particular emphasis on the impact of conformational adaptation on drug-target residence time.

Promiscuity in protein-RNA interactions: conformational ensembles facilitate molecular recognition in the spliceosome: conformational diversity in U2AF⁶⁵ facilitates binding to diverse RNA sequences

Here I discuss findings that suggest a universal mechanism for proteins (and RNA) to recognize and interact with various binding partners by selectively binding to different conformations that pre-exist in the free protein's conformational ensemble. The tandem RNA recognition motif domains of splicing factor U2AF⁶⁵ fluctuate in solution between a predominately closed conformation in which the RNA binding site of one of the domains is blocked, and a lowly populated open conformation in which both RNA binding pockets are accessible. RNA binding to U2AF⁶⁵ may thus occur through the weakly populated open conformation, and the binding interaction stabilizes the open conformation. The conformational diversity observed in U2AF⁶⁵ might also facilitate binding to diverse RNA sequences as found in the polypyrimidine tracts that help define 3' splice sites. Similar binding pathways in other systems have important consequences in biological regulation, molecular evolution, and information storage.

Dynamics and mechanisms of coupled protein folding and binding reactions

Protein folding coupled to binding of a specific ligand is frequently observed in biological processes. In recent years numerous studies have addressed the structural properties of the unfolded proteins in the absence of their ligands. Surprisingly few time-resolved investigations on coupled folding and binding reactions have been published up to date and the dynamics and kinetic mechanisms of these processes are still only poorly understood. Especially, it is still unsolved for most systems which conformation of the protein is recognized by the ligand (conformational selection vs. folding-after-binding) and whether the ligand influences the folding kinetics. Here we review experimental methods, kinetic models and time-resolved experimental studies of coupled folding and binding reactions.

Disparate degrees of hypervariable loop flexibility control T-cell receptor cross-reactivity, specificity, and binding mechanism

αβ T-cell receptors (TCRs) recognize multiple antigenic peptides bound and presented by major histocompatibility complex molecules. TCR cross-reactivity has been attributed in part to the flexibility of TCR complementarity-determining region (CDR) loops, yet there have been limited direct studies of loop dynamics to determine the extent of its role. Here we studied the flexibility of the binding loops of the αβ TCR A6 using crystallographic, spectroscopic, and computational methods. A significant role for flexibility in binding and cross-reactivity was indicated only for the CDR3α and CDR3β hypervariable loops. Examination of the energy landscapes of these two loops indicated that CDR3β possesses a broad, smooth energy landscape, leading to rapid sampling in the free TCR of a range of conformations compatible with different ligands. The landscape for CDR3α is more rugged, resulting in more limited conformational sampling that leads to specificity for a reduced set of peptides as well as the major histocompatibility complex protein. In addition to informing on the mechanisms of cross-reactivity and specificity, the energy landscapes of the two loops indicate a complex mechanism for TCR binding, incorporating elements of both conformational selection and induced fit in a manner that blends features of popular models for TCR recognition.

Role of dynamics in the autoinhibition and activation of the exchange protein directly activated by cyclic AMP (EPAC)

The exchange protein directly activated by cAMP (EPAC) is a key receptor of cAMP in eukaryotes and controls critical signaling pathways. Currently, no residue resolution information is available on the full-length EPAC dynamics, which are known to be pivotal determinants of allostery. In addition, no information is presently available on the intermediates for the classical induced fit and conformational selection activation pathways. Here these questions are addressed through molecular dynamics simulations on five key states along the thermodynamic cycle for the cAMP-dependent activation of a fully functional construct of EPAC2, which includes the cAMP-binding domain and the integral catalytic region. The simulations are not only validated by the agreement with the experimental trends in cAMP-binding domain dynamics determined by NMR, but they also reveal unanticipated dynamic attributes, rationalizing previously unexplained aspects of EPAC activation and autoinhibition. Specifically, the simulations show that cAMP binding causes an extensive perturbation of dynamics in the distal catalytic region, assisting the recognition of the Rap1b substrate. In addition, analysis of the activation intermediates points to a possible hybrid mechanism of EPAC allostery incorporating elements of both the induced fit and conformational selection models. In this mechanism an entropy compensation strategy results in a low free-energy pathway of activation. Furthermore, the simulations indicate that the autoinhibitory interactions of EPAC are more dynamic than previously anticipated, leading to a revised model of autoinhibition in which dynamics fine tune the stability of the autoinhibited state, optimally sensitizing it to cAMP while avoiding constitutive activation.

Basic statistical recipes for the emergence of biochemical discernment

An essential step towards understanding life would be to identify the very basic mechanisms responsible for the discerning behaviour of living biochemical systems, absent from randomly reacting chemical soups. One intuitively feels that this question goes beyond the particular nature of the biological molecules and should relate to general physical principles. The pre-eminent physicist Ludwig Boltzmann early envisioned life as a struggle for entropy, in concordance with the subsequent principle of self-organization out of equilibrium. Re-examination of elementary steady state biochemical systems from a statistical perspective supports this view and shows that sigmoidal responses arising from microstates elimination, are sufficient to explain innermost characteristics of life, including its capacity to convert random molecular interactions into accurate biological reactions. A primary operating strategy to achieve this goal is the introduction of time-irreversible transitions in molecular state conversion cycles by injection of free energy, which confers decisional capacity to single macromolecules. Selected examples from various fields of molecular biology such as enzymology and gene expression, are provided to show that these non-equilibrium steady state mechanisms remain important in contemporary biochemical systems. But in addition, information archiving allowed the emergence of the time-reversible counterparts of these mechanisms, mediated by evolutionary pre-organized macromolecular complexes capable of generating discernment in a non-dissipative manner.

Beyond microscopic reversibility: Are observable non-equilibrium processes precisely reversible?

Although the principle of microscopic reversibility has been studied for many decades, there remain ambiguities in its application to non-equilibrium processes of importance to chemistry, physics and biology. Examples include whether protein unfolding should follow the same pathways and in the same proportions as folding, and whether unbinding should likewise mirror binding. Using continuum-space calculations which extend previous kinetic analyses, we demonstrate formally that the precise symmetry of forward and reverse processes is expected only under certain special conditions. Approximate symmetry will be exhibited under a separate set of conditions. Exact, approximate, and broken symmetry scenarios are verified in several ways: using numerical calculations on toy and molecular systems; using exact calculations on kinetic models of induced fit in protein-ligand binding; and based on reported experimental results. The analysis highlights intrinsic challenges and ambiguities in the design and analysis of both experiments and simulations.

Efficient incorporation of protein flexibility and dynamics into molecular docking simulations

Flexibility and dynamics are protein characteristics that are essential for the process of molecular recognition. Conformational changes in the protein that are coupled to ligand binding are described by the biophysical models of induced fit and conformational selection. Different concepts that incorporate protein flexibility into protein-ligand docking within the context of these two models are reviewed. Several computational studies that discuss the validity and possible limitations of such approaches will be presented. Finally, different approaches that incorporate protein dynamics, e.g., configurational entropy, and solvation effects into docking will be highlighted.