Induced fit or conformational selection? The role of the semi-closed state in the maltose binding protein

Analysis of Glycan Recognition by Concanavalin A Using Absolute Binding Free Energy Calculations

Carbohydrates are key biological mediators of molecular recognition and signaling processes. In this case study, we explore the ability of absolute binding free energy (ABFE) calculations to predict the affinities of a set of five related carbohydrate ligands for the lectin protein, concanavalin A, ranging from 27-atom monosaccharides to a 120-atom complex-type N-linked glycan core pentasaccharide. ABFE calculations quantitatively rank and estimate the affinity of the ligands in relation to microcalorimetry, with a mean signed error in the binding free energy of -0.63 ± 0.04 kcal/mol. Consequently, the diminished binding efficiencies of the larger carbohydrate ligands are closely reproduced: the ligand efficiency values from isothermal titration calorimetry for the glycan core pentasaccharide and its constituent trisaccharide and monosaccharide compounds are respectively -0.14, -0.22, and -0.41 kcal/mol per heavy atom. ABFE calculations predict these ligand efficiencies to be -0.14 ± 0.02, -0.24 ± 0.03, and -0.46 ± 0.06 kcal/mol per heavy atom, respectively. Consequently, the ABFE method correctly identifies the high affinity of the key anchoring mannose residue and the negligible contribution to binding of both β-GlcNAc arms of the pentasaccharide. While challenges remain in sampling the conformation and interactions of these polar, flexible, and weakly bound ligands, we nevertheless find that the ABFE method performs well for this lectin system. The approach shows promise as a quantitative tool for predicting and deconvoluting carbohydrate-protein interactions, with potential application to design of therapeutics, vaccines, and diagnostics.

Molecular dynamics in multidimensional space explains how mutations affect the association path of neomycin to a riboswitch

Riboswitches are messenger RNA (mRNA) fragments binding specific small molecules to regulate gene expression. A synthetic N1 riboswitch, inserted into yeast mRNA controls the translation of a reporter gene in response to neomycin. However, its regulatory activity is sensitive to single-point RNA mutations, even those distant from the neomycin binding site. While the association paths of neomycin to N1 and its variants remain unknown, recent fluorescence kinetic experiments indicate a two-step process driven by conformational selection. This raises the question of which step is affected by mutations. To address this, we performed all-atom two-dimensional replica-exchange molecular dynamics simulations for N1 and U14C, U14C[Formula: see text], U15A, and A17G mutants, ensuring extensive conformational sampling of both RNA and neomycin. The obtained neomycin association and binding paths, along with multidimensional free-energy profiles, revealed a two-step binding mechanism, consisting of conformational selection and induced fit. Neomycin binds to a preformed N1 conformation upon identifying a stable upper stem and U-turn motif in the riboswitch hairpin. However, the positioning of neomycin in the binding site occurs at different RNA-neomycin distances for each mutant, which may explain their different regulatory activities. The subsequent induced fit arises from the interactions of the neomycin's N3 amino group with RNA, causing the G9 backbone to rearrange. In the A17G mutant, the critical C6-A17/G17 stacking forms at a closer RNA-neomycin distance compared to N1. These findings together with estimated binding free energies coincide with experiments and elucidate why the A17G mutation decreases and U15A enhances N1 activity in response to neomycin.

Binding to the conserved and stably folded guide RNA pseudoknot induces Cas12a conformational changes during ribonucleoprotein assembly

Ribonucleoproteins (RNPs) comprise one or more RNA and protein molecules that interact to form a stable complex, which commonly involves conformational changes in the more flexible RNA components. Here, we propose that Cas12a RNP assembly with its cognate CRISPR RNA (crRNA) guide instead proceeds primarily through Cas12a conformational changes during binding to more stable, prefolded crRNA 5' pseudoknot handles. Phylogenetic reconstructions and sequence and structure alignments revealed that the Cas12a proteins are divergent in sequence and structure while the crRNA 5' repeat region, which folds into a pseudoknot and anchors binding to Cas12a, is highly conserved. Molecular dynamics simulations of three Cas12a proteins and their cognate guides revealed substantial flexibility for unbound apo-Cas12a. In contrast, crRNA 5' pseudoknots were predicted to be stable and independently folded. Limited trypsin hydrolysis, differential scanning fluorimetry, thermal denaturation, and CD analyses supported conformational changes of Cas12a during RNP assembly and an independently folded crRNA 5' pseudoknot. This RNP assembly mechanism may be rationalized by evolutionary pressure to conserve CRISPR loci repeat sequence, and therefore guide RNA structure, to maintain function across all phases of the CRISPR defense mechanism.

Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles

Prediction of ligand-receptor complex structure is important in both the basic science and the industry such as drug discovery. We report various computation molecular docking methods: fundamental in silico (virtual) screening, ensemble docking, enhanced sampling (generalized ensemble) methods, and other methods to improve the accuracy of the complex structure. We explain not only the merits of these methods but also their limits of application and discuss some interaction terms which are not considered in the in silico methods. In silico screening and ensemble docking are useful when one focuses on obtaining the native complex structure (the most thermodynamically stable complex). Generalized ensemble method provides a free-energy landscape, which shows the distribution of the most stable complex structure and semi-stable ones in a conformational space. Also, barriers separating those stable structures are identified. A researcher should select one of the methods according to the research aim and depending on complexity of the molecular system to be studied.

Redesigned pMAL expression vector for easy and fast purification of active native antimicrobial peptides

AIMS

The aim of this study was to construct the improved pMAL expression vector in order to increase the efficacy of small native peptides purification and their clear-cut separation from MBP tag. The modifications we introduced can be applied to many expression vectors.

METHODS AND RESULTS

To improve the pMAL expression vector we introduced the His₆ tag and the enterokinase cleavage site (Ek) downstream from the MBP tag and Xa cleavage site on the original vector. For cloning of a desired peptide DNA, the enterokinase site contains a unique BsaBI restriction site adjacent to the original multi-cloning-site. This redesigned pMAL vector was optimized for the purification of cytoplasmic (pMALc5HisEk) and periplasmic (pMALp5HisEk) peptides. The purification of native and active peptide (P) was obtained following two-step affinity chromatography. In the first step the entire MBP-His₆ -Ek-P fusion protein is purified using the Ni-NTA agarose column. This fusion protein was cleaved with active His₆ tagged enterokinase. In the second step, the further purification was performed by column containing the mixture of amylose and Ni-NTA agarose resins. This removes both the MBP-His₆ and His₆ -enterokinase leaving pure native protein in solution. These new vectors and the two-step purification protocol was successfully applied in purification of active native small antimicrobial peptides (AMPs), lactococcin A and human β-defensin.

CONCLUSIONS

We constructed the improved pMAL expression vectors and established the pipeline and optimal conditions for their use in efficient purification of large amounts of active native small peptides.

SIGNIFICANCE AND IMPACT OF THE STUDY

Choice of expression vector impacts on the efficiency of expression and purification of desired proteins. The idea of redesigning pMAL vector was driven by need for rapid purification of larger amounts of active native AMPs. This newly improved pMAL vector, the cloning strategy, expression conditions and two-step purification protocol represent a unique simple approach which can be applied in every laboratory.

The role of C-terminal helix in the conformational transition of an arginine binding protein

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Probe the role of C-ter. helix (CTH) in conformational transition of TmArgBP.

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Presence of CTH almost doubles the barrier to access the closed-state.

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In the absence of CTH, the protein can fluctuate between the two conformations.

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CTH not only constraints the open-state conformation but also guides in accessing it.

The thermotoga maritima arginine binding protein (TmArgBP) is a periplasmic binding protein that has a short helix at the C-terminal end (CTH), which is swapped between the two chains. We apply a coarse-grained structure-based model (SBM) and all-atom MD simulation on this protein to understand the mechanism and the role of CTH in the conformational transition. When the results of SBM simulations of TmArgBP in the presence and absence of CTH are compared, we find that CTH is strategically located at the back of the binding pocket restraining the open-state conformation thereby disengaging access to the closed-state. We also ran all-atom MD simulations of open-state TmArgBP with and without CTH and discovered that in the absence of CTH the protein could reach the closed-state within 250 ns, while in its presence, the protein remained predominantly in its open-state conformation. In the simulation started from unliganded closed-state conformation without CTH, the protein exhibited multiple transitions between the two states, suggesting CTH as an essential structural element to stabilize the open-state conformation. In another simulation that began with an unliganded closed-state conformation with CTH, the protein was able to access the open-state. In this simulation the CTH was observed to reorient itself to interact with the protein emphasizing its role in assisting the conformational change. Based on our findings, we believe that CTH not only acts as a structural element that constraints the protein in its open-state but it may also guide the protein back to its open-state conformation upon ligand unbinding.

Target-binding behavior of IDPs via pre-structured motifs

Pre-Structured Motifs (PreSMos) are transient secondary structures observed in many intrinsically disordered proteins (IDPs) and serve as protein target-binding hot spots. The prefix "pre" highlights that PreSMos exist a priori in the target-unbound state of IDPs as the active pockets of globular proteins pre-exist before target binding. Therefore, a PreSMo is an "active site" of an IDP; it is not a spatial pocket, but rather a secondary structural motif. The classical and perhaps the most effective approach to understand the function of a protein has been to determine and investigate its structure. Ironically or by definition IDPs do not possess structure (here structure refers to tertiary structure only). Are IDPs then entirely structureless? The PreSMos provide us with an atomic-resolution answer to this question. For target binding, IDPs do not rely on the spatial pockets afforded by tertiary or higher structures. Instead, they utilize the PreSMos possessing particular conformations that highly presage the target-bound conformations. PreSMos are recognized or captured by targets via conformational selection (CS) before their conformations eventually become stabilized via structural induction into more ordered bound structures. Using PreSMos, a number of, if not all, IDPs can bind targets following a sequential pathway of CS followed by an induced fit (IF). This chapter presents several important PreSMos implicated in cancers, neurodegenerative diseases, and other diseases along with discussions on their conformational details that mediate target binding, a structural rationale for unstructured proteins.

Sequence of Events during Peptide Unbinding from RNase S: A Complete Experimental Description

The phototriggered unbinding of the intrinsically disordered S-peptide from the RNase S complex is studied with the help of transient IR spectroscopy, covering a wide range of time scales from 100 ps to 10 ms. To that end, an azobenzene moiety has been linked to the S-peptide in a way that its helicity is disrupted by light, thereby initiating its complete unbinding. The full sequence of events is observed, starting from unfolding of the helical structure of the S-peptide on a 20 ns time scale while still being in the binding pocket of the S-protein, S-peptide unbinding after 300 μs, and the structural response of the S-protein after 3 ms. With regard to the S-peptide dynamics, the binding mechanism can be classified as an induced fit, while the structural response of the S-protein is better described as conformational selection.

Unraveling the Coupling between Conformational Changes and Ligand Binding in Ribose Binding Protein Using Multiscale Molecular Dynamics and Free-Energy Calculations

Conformational changes of proteins upon ligand binding are usually explained in terms of several mechanisms including the induced fit, conformational selection, or their mixtures. Due to the slow time scales, conventional molecular dynamics (cMD) simulations based on the atomistic models cannot easily simulate the open-to-closed conformational transition in proteins. In our previous study, we have developed an enhanced sampling scheme (generalized replica exchange with solute tempering selected surface charged residues: gREST_SSCR) for multidomain proteins and applied it to ligand-mediated conformational changes in the G134R mutant of ribose-binding protein (RBPG134R) in solution. The free-energy landscape (FEL) of RBPG134R in the presence of a ribose at the binding site included the open and closed states and two intermediates, open-like and closed-like forms. Only the open and open-like forms existed in the FEL without a ribose. In the current study, the coupling between the conformational changes and ligand binding is further investigated using coarse-grained MD, multiple atomistic cMD, and free-energy calculations. The ribose is easily dissociated from the binding site of wild-type RBP and RBPG134R in the cMD simulations starting from the open and open-like forms. In contrast, it is stable at the binding site in the simulations from the closed and closed-like forms. The free-energy calculations provide the binding affinities of different structures, supporting the results of cMD simulations. Importantly, cMD simulations from the closed-like structures reveal transitions toward the closed one in the presence of a bound ribose. On the basis of the computational results, we propose a molecular mechanism in which conformational selection and induced fit happen in the first and second halves of the open-to-closed transition in RBP, respectively.

The Role of Calcium in Regulating the Conformational Dynamics of d-Galactose/d-Glucose-Binding Protein Revealed by Markov State Model Analysis

The d-glucose/d-galactose-binding protein (GGBP) from Escherichia coli is a substrate-binding protein (SBP) associated with sugar transport and chemotaxis. It is also a calcium-binding protein, which makes it unique in the SBP family. However, the functional importance of Ca²⁺ binding is not fully understood. Here, the calcium-dependent properties of GGBP were explored by all-atom molecular dynamics simulations and Markov state model (MSM) analysis as well as single-molecule Förster resonance energy transfer (smFRET) measurements. In agreement with previous experimental studies, we observed the structure stabilization effect of Ca²⁺ binding on the C-terminal domain of GGBP, especially the Ca²⁺-binding site. Interestingly, the MSMs of calcium-depleted GGBP and calcium-bound GGBP (GGBP/Ca²⁺) demonstrate that Ca²⁺ greatly stabilizes the open conformation, and smFRET measurements confirmed this result. Further analysis reveals that Ca²⁺ binding disturbs the local hydrogen bonding interactions and the conformational dynamics of the hinge region, thereby weakening the long-range interdomain correlations to favor the open conformation. These results suggest an active regulatory role of Ca²⁺ binding in GGBP, which finely tunes the conformational distribution. The work sheds new light on the study of calcium-binding proteins in prokaryotes.

Exploring Large Domain Motions in Proteins Using Atomistic Molecular Dynamics with Enhanced Conformational Sampling

Conformational transitions in multidomain proteins are essential for biological functions. The Apo conformations are typically open and flexible, while the Holo states form more compact conformations stabilized by protein-ligand interactions. Unfortunately, the atomically detailed mechanisms for such open-closed conformational changes are difficult to be accessed experimentally as well as computationally. To simulate the transitions using atomistic molecular dynamics (MD) simulations, efficient conformational sampling algorithms are required. In this work, we propose a new approach based on generalized replica-exchange with solute tempering (gREST) for exploring the open-closed conformational changes in multidomain proteins. Wherein, selected surface charged residues in a target protein are defined as the solute region in gREST simulation and the solute temperatures are different in replicas and exchanged between them to enhance the domain motions. This approach is called gREST selected surface charged residues (gREST_SSCR) and is applied to the Apo and Holo states of ribose binding protein (RBP) in solution. The conformational spaces sampled with gREST_SSCR are much wider than those with the conventional MD, sampling open-closed conformational changes while maintaining RBP domains’ stability. The free-energy landscapes of RBP in the Apo and Holo states are drawn along with twist and hinge angles of the two moving domains. The inter-domain salt-bridges that are not observed in the experimental structures are also important in the intermediate states during the conformational changes.

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.

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.

Zhang, Wu, Feng et al. show that ligand-bound glutamine binding protein assumes multiple metastable binding sites, presenting a more dynamic energy landscape than its ligand-free form. This study provides insights into the ligand-binding mechanisms coupled with protein dynamics that underly the apparent binding affinity.

Scalable molecular dynamics on CPU and GPU architectures with NAMD

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

Different Anomeric Sugar Bound States of Maltose Binding Protein Resolved by a Cytolysin A Nanopore Tweezer

Conformational changes of proteins are essential to their functions. Yet it remains challenging to measure the amplitudes and time scales of protein motions. Here we show that the cytolysin A (ClyA) nanopore was used as a molecular tweezer to trap a single maltose-binding protein (MBP) within its lumen, which allows conformation changes to be monitored as electrical current fluctuations in real time. In contrast to the current two state binding model, the current measurements revealed three distinct ligand-bound states for MBP in the presence of reducing saccharides. Our analysis reveals that these three states represented MBP bound to different isomers of reducing sugars. These findings contribute to the understanding of the mechanism of substrate recognition by MBP and illustrate that the nanopore tweezer is a powerful, label-free, single-molecule approach for studying protein conformational dynamics under functional conditions.

Synergistic Structural Information from Covalent Labeling and Hydrogen-Deuterium Exchange Mass Spectrometry for Protein-Ligand Interactions

Hydrogen-deuterium exchange (HDX) mass spectrometry (MS) and covalent labeling (CL) MS are typically considered to be complementary methods for protein structural analysis, because one probes the protein backbone, while the other probes side chains. For protein-ligand interactions, we demonstrate in this work that the two labeling techniques can provide synergistic structural information about protein-ligand binding when reagents like diethylpyrocarbonate (DEPC) are used for CL because of the differences in the reaction rates of DEPC and HDX. Using three model protein-ligand systems, we show that the slower time scale for DEPC labeling makes it only sensitive to changes in solvent accessibility and insensitive to changes in protein structural fluctuations, whereas HDX is sensitive to changes in both solvent accessibility and structural fluctuations. When used together, the two methods more clearly reveal binding sites and ligand-induced changes to structural fluctuations that are distant from the binding site, which is more comprehensive information than either technique alone can provide. We predict that these two methods will find widespread usage together for more deeply understanding protein-ligand interactions.

Profiling the interaction of 1-phenylbenzimidazoles to cyclooxygenases

In the design of 1-phenylbenzimidazoles as model cyclooxygenase (COX) inhibitors, docking to a series of crystallographic COX structures was performed to evaluate their potential for high-affinity binding and to reproduce the interaction profile of well-known COX inhibitors. The effect of ligand-specific induced fit on the calculations was also studied. To quantitatively compare the pattern of interactions of model compounds to the profile of several cocrystallized COX inhibitors, a geometric parameter, denominated ligand-receptor contact distance (LRCD), was developed. The interaction profile of several model complexes showed similarity to the profile of COX complexes with inhibitors such as iodosuprofen, iodoindomethacin, diclofenac, and flurbiprofen. Shaping of high-affinity binding sites upon ligand-specific induced fit mostly determined both the affinity and the binding mode of the ligands in the docking calculations. The results suggest potential of 1-phenylbenzimidazole derivatives as COX inhibitors on the basis of their predicted affinity and interaction profile to COX enzymes. The analyses also provided insights into the role of induced fit in COX enzymes. While inhibitors produce different local structural changes at the COX ligand binding site, induced fit allows inhibitors in diverse chemical classes to share characteristic interaction patterns that ensure key contacts to be achieved. Different interaction patterns may also be associated with different inhibitory mechanisms.

Phosphite binding by the HtxB periplasmic binding protein depends on the protonation state of the ligand

Phosphorus acquisition is critical for life. In low phosphate conditions, some species of bacteria have evolved mechanisms to import reduced phosphorus compounds, such as phosphite and hypophosphite, as alternative phosphorus sources. Uptake is facilitated by high-affinity periplasmic binding proteins (PBPs) that bind cargo in the periplasm and shuttle it to an ATP-binding cassette (ABC)-transporter in the bacterial inner membrane. PtxB and HtxB are the PBPs responsible for binding phosphite and hypophosphite, respectively. They recognize the P-H bond of phosphite/hypophosphite via a conserved P-H...π interaction, which confers nanomolar dissociation constants for their respective ligands. PtxB also has a low-level binding affinity for phosphate and hypophosphite, whilst HtxB can facilitate phosphite uptake in vivo. However, HtxB does not bind phosphate, thus the HtxBCDE transporter has recently been successfully exploited for biocontainment of genetically modified organisms by phosphite-dependent growth. Here we use a combination of X-ray crystallography, NMR and Microscale Thermophoresis to show that phosphite binding to HtxB depends on the protonation state of the ligand, suggesting that pH may effect the efficiency of phosphite uptake by HtxB in biotechnology applications.

Both Ligands and Macromolecular Crowders Preferentially Bind to Closed Conformations of Maltose Binding Protein

In cellular environments, proteins not only interact with their specific partners but also encounter a high concentration of bystander macromolecules, or crowders. Nonspecific interactions with macromolecular crowders modulate the activities of proteins, but our knowledge about the rules of nonspecific interactions is still very limited. In previous work, we presented experimental evidence that macromolecular crowders acted competitively in inhibiting the binding of maltose binding protein (MBP) with its ligand maltose. Competition between a ligand and an inhibitor may result from binding to either the same site or different conformations of the protein. Maltose binds to the cleft between two lobes of MBP, and in a series of mutants, the affinities increased with an increase in the extent of lobe closure. Here we investigated whether macromolecular crowders also have a conformational or site preference when binding to MBP. The affinities of a polymer crowder, Ficoll70, measured by monitoring tryptophan fluorescence were 3-6-fold higher for closure mutants than for wild-type MBP. Competition between the ligand and crowder, as indicated by fitting of titration data and directly by nuclear magnetic resonance spectroscopy, and their similar preferences for closed MBP conformations further suggest the scenario in which the crowder, like maltose, preferentially binds to the interlobe cleft of MBP. Similar observations were made for bovine serum albumin as a protein crowder. Conformational and site preferences in MBP-crowder binding allude to the paradigm that nonspecific interactions can possess hallmarks of molecular recognition, which may be essential for intracellular organizations including colocalization of proteins and liquid-liquid phase separation.

Differential Substrate Recognition by Maltose Binding Proteins Influenced by Structure and Dynamics

The genome of the hyperthermophile Thermotoga maritima contains three isoforms of maltose binding protein (MBP) that are high-affinity receptors for di-, tri-, and tetrasaccharides. Two of these proteins (tmMBP1 and tmMBP2) share significant sequence identity, approximately 90%, while the third (tmMBP3) shares less than 40% identity. MBP from Escherichia coli (ecMBP) shares 35% sequence identity with the tmMBPs. This subset of MBP isoforms offers an interesting opportunity to investigate the mechanisms underlying the evolution of substrate specificity and affinity profiles in a genome where redundant MBP genes are present. In this study, the X-ray crystal structures of tmMBP1, tmMBP2, and tmMBP3 are reported in the absence and presence of oligosaccharides. tmMBP1 and tmMBP2 have binding pockets that are larger than that of tmMBP3, enabling them to bind to larger substrates, while tmMBP1 and tmMBP2 also undergo substrate-induced hinge bending motions (∼52°) that are larger than that of tmMBP3 (∼35°). Small-angle X-ray scattering was used to compare protein behavior in solution, and computer simulations provided insights into dynamics of these proteins. Comparing quantitative protein-substrate interactions and dynamical properties of tmMBPs with those of the promiscuous ecMBP and disaccharide selective Thermococcus litoralis MBP provides insights into the features that enable selective binding. Collectively, the results provide insights into how the structure and dynamics of tmMBP homologues enable them to differentiate between a myriad of chemical entities while maintaining their common fold.

An integrated perspective on RNA aptamer ligand-recognition models: clearing muddy waters

Riboswitches are short RNA motifs that sensitively and selectively bind cognate ligands to modulate gene expression. Like protein receptor-ligand pairs, their binding dynamics are traditionally categorized as following one of two paradigmatic mechanisms: conformational selection and induced fit. In conformational selection, ligand binding stabilizes a particular state already present in the receptor's dynamic ensemble. In induced fit, ligand-receptor interactions enable the system to overcome the energetic barrier into a previously inaccessible state. In this article, we question whether a polarized division of RNA binding mechanisms truly meets the conceptual needs of the field. We will review the history behind this classification of RNA-ligand interactions, and the way induced fit in particular has been rehabilitated by single-molecule studies of RNA aptamers. We will highlight several recent results from single-molecule experimental studies of riboswitches that reveal gaps or even contradictions between common definitions of the two terms, and we will conclude by proposing a more robust framework that considers the range of RNA behaviors unveiled in recent years as a reality to be described, rather than an increasingly unwieldy set of exceptions to the traditional models.

Network of Conformational Transitions Revealed by Molecular Dynamics Simulations of the Carbonic Anhydrase II Apo-Enzyme

Human carbonic anhydrase II (HCA II) is an enzyme that catalyzes the reversible hydration of CO2 into bicarbonate (HCO3-) and a proton (H+) as well as other reactions at an extremely high rate. This enzyme plays fundamental roles in human physiology/pathology, such as controlling the pH level in cells and so on. However, the binding mechanism between apo-HCA II and CO2 or other ligands as well as related conformational changes remains poorly understood, and atomic investigation into it could promote our understanding of related internal physiological/pathological mechanisms. In this study, long-time atomic molecular dynamics simulations as well as the clustering and free-energy analysis were performed to reveal the dynamics of apo-HCA II as well as the mechanism upon ligand binding. Our simulations indicate that the crystallographic B-factors considerably underestimate the loop dynamics: multiple conformations can be adopted by loops 1 and 2, especially for loop 1 because loop 1 is one side of the binding pocket, and its left-to-right movement can compress or extend the binding pocket, leading to one inactive (closed) state, three intermediate (semiopen) states, and one active (open) state; CO2 cannot get into the binding pocket of the inactive state but can get into those of intermediate and active states. The coexistence of multiple conformational states proposes a possible conformational selection model for the binding mechanism between apo-HCA II and CO2 or other ligands, revising our previous view of its functional mechanism of conformational change upon ligand binding and offering valuable structural insights into the workings of HCA II.

Mechanism of mRNA-STAR domain interaction: Molecular dynamics simulations of Mammalian Quaking STAR protein

STAR proteins are evolutionary conserved mRNA-binding proteins that post-transcriptionally regulate gene expression at all stages of RNA metabolism. These proteins possess conserved STAR domain that recognizes identical RNA regulatory elements as YUAAY. Recently reported crystal structures show that STAR domain is composed of N-terminal QUA1, K-homology domain (KH) and C-terminal QUA2, and mRNA binding is mediated by KH-QUA2 domain. Here, we present simulation studies done to investigate binding of mRNA to STAR protein, mammalian Quaking protein (QKI). We carried out conventional MD simulations of STAR domain in presence and absence of mRNA, and studied the impact of mRNA on the stability, dynamics and underlying allosteric mechanism of STAR domain. Our unbiased simulations results show that presence of mRNA stabilizes the overall STAR domain by reducing the structural deviations, correlating the ‘within-domain’ motions, and maintaining the native contacts information. Absence of mRNA not only influenced the essential modes of motion of STAR domain, but also affected the connectivity of networks within STAR domain. We further explored the dissociation of mRNA from STAR domain using umbrella sampling simulations, and the results suggest that mRNA binding to STAR domain occurs in multi-step: first conformational selection of mRNA backbone conformations, followed by induced fit mechanism as nucleobases interact with STAR domain.

Osmolyte-Like Stabilizing Effects of Low GdnHCl Concentrations on d-Glucose/d-Galactose-Binding Protein

The ability of d-glucose/d-galactose-binding protein (GGBP) to reversibly interact with its ligands, glucose and galactose, makes this protein an attractive candidate for sensing elements of glucose biosensors. This potential is largely responsible for attracting researchers to study the conformational properties of this protein. Previously, we showed that an increase in the fluorescence intensity of the fluorescent dye 6-bromoacetyl-2-dimetylaminonaphtalene (BADAN) is linked to the holo-form of the GGBP/H152C mutant in solutions containing sub-denaturing concentrations of guanidine hydrochloride (GdnHCl). It was hypothesized that low GdnHCl concentrations might lead to compaction of the protein, thereby facilitating ligand binding. In this work, we utilize BADAN fluorescence spectroscopy, intrinsic protein UV fluorescence spectroscopy, and isothermal titration calorimetry (ITC) to show that the sub-denaturing GdnHCl concentrations possess osmolyte-like stabilizing effects on the structural dynamics, conformational stability, and functional activity of GGBP/H152C and the wild type of this protein (wtGGBP). Our data are consistent with the model where low GdnHCl concentrations promote a shift in the dynamic distribution of the protein molecules toward a conformational ensemble enriched in molecules with a tighter structure and a more closed conformation. This promotes the increase in the configurational complementarity between the protein and glucose molecules that leads to the increase in glucose affinity in both GGBP/H152C and wtGGBP.

A Network of Conformational Transitions in the Apo Form of NDM-1 Enzyme Revealed by MD Simulation and a Markov State Model

New Delhi metallo-β-lactamase-1 (NDM-1) is a novel β-lactamase enzyme that confers enteric bacteria with nearly complete resistance to all β-lactam antibiotics, so it raises a formidable and global threat to human health. However, the binding mechanism between apo-NDM-1 and antibiotics as well as related conformational changes remains poorly understood, which largely hinders the overcoming of its antibiotic resistance. In our study, long-time conventional molecular dynamics simulation and Markov state models were applied to reveal both the dynamical and conformational landscape of apo-NDM-1: the MD simulation demonstrates that loop L3, which is responsible for antibiotic binding, is the most flexible and undergoes dramatic conformational changes; moreover, the Markov state model built from the simulation maps four metastable states including open, semiopen, and closed conformations of loop L3 as well as frequent transitions between the states. Our findings propose a possible conformational selection model for the binding mechanism between apo-NDM-1 and antibiotics, which facilitates the design of novel inhibitors and antibiotics.

A Network of Conformational Transitions Revealed by Molecular Dynamics Simulations of the Binary Complex of Escherichia coli 6-Hydroxymethyl-7,8-dihydropterin Pyrophosphokinase with MgATP

6-Hydroxymethyl-7,8-dihydropterin pyrophosphokinase (HPPK) catalyzes the first reaction in the folate biosynthetic pathway. Comparison of its X-ray and nuclear magnetic resonance structures suggests that the enzyme undergoes significant conformational change upon binding to its substrates, especially in three catalytic loops. Experimental research has shown that, in its binary form, even bound by analogues of MgATP, loops 2 and 3 remain rather flexible; this raises questions about the putative large-scale induced-fit conformational change of the HPPK-MgATP binary complex. In this work, long-time all-atomic molecular dynamics simulations were conducted to investigate the loop dynamics in this complex. Our simulations show that, with loop 3 closed, multiple conformations of loop 2, including the open, semiopen, and closed forms, are all accessible to the binary complex. These results provide valuable structural insights into the details of conformational changes upon 6-hydroxymethyl-7,8-dihydropterin (HP) binding and biological activities of HPPK. Conformational network analysis and principal component analysis related to the loops are also discussed.

Molecular simulations reveal that the long range fluctuations of human DPP III change upon ligand binding

The experimentally determined structures of human dipeptidyl peptidase III (DPP III) for the wild-type protein and for the complex of its E451A mutant with the peptide substrate, tynorphin, differ significantly in their overall shape. The two domains of the enzyme are separated by a wide cleft in the structure of the ligand-free enzyme, while in the ligand-bound mutant they are very close to each other, and the protein structure is extremely compact. Here, we applied a range of molecular dynamics simulation techniques to investigate the DPP III conformational landscape and the influence of ligand binding on the protein structure and dynamics. We used conventional, accelerated and steered methods to simulate DPP III and its complexes with tynorphin and with the preferred, synthetic, substrate Arg-Arg-2-naphthylamide. We found that DPP III can adopt a number of different forms in solution. The compact forms are more stable, but the open and partially closed states, spanning a wide range of conformations, can more effectively recognize the substrate which preferentially binds to the five-stranded β-core of the lower DPP III domain. The simulations indicated the existence of a dynamic equilibrium between open and semi-closed states and revealed two ways that the protein can close, leading to two distinct compact structures. The way in which the protein closes depends on the presence of the ligand.

Protein Conformational Changes Are Detected and Resolved Site Specifically by Second-Harmonic Generation

We present here a straightforward, broadly applicable technique for real-time detection and measurement of protein conformational changes in solution. This method is based on tethering proteins labeled with a second-harmonic generation (SHG) active dye to supported lipid bilayers. We demonstrate our method by measuring the conformational changes that occur upon ligand binding with three well-characterized proteins labeled at lysine residues: calmodulin (CaM), maltose-binding protein (MBP), and dihydrofolate reductase (DHFR). We also create a single-site cysteine mutant of DHFR engineered within the Met20 catalytic loop region and study the protein’s structural motion at this site. Using published x-ray crystal structures, we show that the changes in the SHG signals upon ligand binding are the result of structural motions that occur at the labeled sites between the apo and ligand-bound forms of the proteins, which are easily distinguished from each other. In addition, we demonstrate that different magnitudes of the SHG signal changes are due to different and specific ligand-induced conformational changes. Taken together, these data illustrate the potential of the SHG approach for detecting and measuring protein conformational changes for a wide range of biological applications.

Conformational selection and induced fit for RNA polymerase and RNA/DNA hybrid backtracked recognition

RNA polymerase catalyzes transcription with a high fidelity. If DNA/RNA mismatch or DNA damage occurs downstream, a backtracked RNA polymerase can proofread this situation. However, the backtracked mechanism is still poorly understood. Here we have performed multiple explicit-solvent molecular dynamics (MD) simulations on bound and apo DNA/RNA hybrid to study backtracked recognition. MD simulations at room temperature suggest that specific electrostatic interactions play key roles in the backtracked recognition between the polymerase and DNA/RNA hybrid. Kinetics analysis at high temperature shows that bound and apo DNA/RNA hybrid unfold via a two-state process. Both kinetics and free energy landscape analyses indicate that bound DNA/RNA hybrid folds in the order of DNA/RNA contracting, the tertiary folding and polymerase binding. The predicted Φ-values suggest that C7, G9, dC12, dC15, and dT16 are key bases for the backtracked recognition of DNA/RNA hybrid. The average RMSD values between the bound structures and the corresponding apo ones and Kolmogorov-Smirnov (KS) P-test analyses indicate that the recognition between DNA/RNA hybrid and polymerase might follow an induced fit mechanism for DNA/RNA hybrid and conformation selection for polymerase. Furthermore, this method could be used to relative studies of specific recognition between nucleic acid and protein.

Molecular dynamics simulations of the Escherichia coli HPPK apo-enzyme reveal a network of conformational transitions

6-Hydroxymethyl-7,8-dihydropterin pyrophosphokinase (HPPK) catalyzes the first reaction in the folate biosynthetic pathway. Comparison of its X-ray and nuclear magnetic resonance structures suggests that the enzyme undergoes significant conformational change upon binding to its substrates, especially in three catalytic loops. Experimental research has shown that even when confined by crystal contacts, loops 2 and 3 remain rather flexible when the enzyme is in its apo form, raising questions about the putative large-scale induced-fit conformational change of HPPK. To investigate the loop dynamics in a crystal-free environment, we performed conventional molecular dynamics simulations of the apo-enzyme at two different temperatures (300 and 350 K). Our simulations show that the crystallographic B-factors considerably underestimate the loop dynamics; multiple conformations of loops 2 and 3, including the open, semi-open, and closed conformations that an enzyme must adopt throughout its catalytic cycle, are all accessible to the apo-enzyme. These results revise our previous view of the functional mechanism of conformational change upon MgATP binding and offer valuable structural insights into the workings of HPPK. In this paper, conformational network analysis and principal component analysis related to the loops are discussed to support the presented conclusions.

Watching conformational dynamics of ABC transporters with single-molecule tools

ATP-binding cassette (ABC) transporters play crucial roles in cellular processes, such as nutrient uptake, drug resistance, cell-volume regulation and others. Despite their importance, all proposed molecular models for transport are based on indirect evidence, i.e. functional interpretation of static crystal structures and ensemble measurements of function and structure. Thus, classical biophysical and biochemical techniques do not readily visualize dynamic structural changes. We recently started to use single-molecule fluorescence techniques to study conformational states and changes of ABC transporters in vitro, in order to observe directly how the different steps during transport are coordinated. This review summarizes our scientific strategy and some of the key experimental advances that allowed the substrate-binding mechanism of prokaryotic ABC importers and the transport cycle to be explored. The conformational states and transitions of ABC-associated substrate-binding domains (SBDs) were visualized with single-molecule FRET, permitting a direct correlation of structural and kinetic information of SBDs. We also delineated the different steps of the transport cycle. Since information in such assays are restricted by proper labelling of proteins with fluorescent dyes, we present a simple approach to increase the amount of protein with FRET information based on non-specific interactions between a dye and the size-exclusion chromatography (SEC) column material used for final purification.

Flexible receptor docking for drug discovery

INTRODUCTION

Molecular docking has become a popular method for virtual screening. Docking small molecules to a rigid biological receptor is fast but could produce many false negatives and identify less diverse compounds. Flexible receptor docking has alleviated this problem.

AREAS COVERED

This article focuses on reviewing ensemble docking as an approximate but inexpensive method to incorporate receptor flexibility in molecular docking. It outlines key features and recent advances of this method and points out problem areas that need to be addressed to make it even more useful in drug discovery.

EXPERT OPINION

Among the different methods introduced for flexible receptor docking, ensemble docking represents one of the most popular approaches, especially for high-throughput virtual screening. One can generate structural ensembles by using experimental structures, by structural modeling and by various types of molecular simulations. In building a structural ensemble, a judicious choice of the structures to be included can improve performance. Furthermore, reducing the size of the structural ensemble can cut computational costs, and removing the structures that can bind few ligands well could enrich the number of true actives identified by ensemble docking. The ability of ensemble docking to identify more true positives at the top of a rank-ordered list also depends on the choice of the methods to score and rank compounds, an area that needs further research.

Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes

Protein-carbohydrate recognition is crucial in many vital biological processes including host-pathogen recognition, cell-signaling, and catalysis. Accordingly, computational prediction of protein-carbohydrate binding free energies is of enormous interest for drug design. However, the accuracy of current force fields (FFs) for predicting binding free energies of protein-carbohydrate complexes is not well understood owing to technical challenges such as the highly polar nature of the complexes, anomerization, and conformational flexibility of carbohydrates. The present study evaluated the performance of alchemical predictions of binding free energies with the GAFF1.7/AM1-BCC and GLYCAM06j force fields for modeling protein-carbohydrate complexes. Mean unsigned errors of 1.1 ± 0.06 (GLYCAM06j) and 2.6 ± 0.08 (GAFF1.7/AM1-BCC) kcal·mol(-1) are achieved for a large data set of monosaccharide ligands for Ralstonia solanacearum lectin (RSL). The level of accuracy provided by GLYCAM06j is sufficient to discriminate potent, moderate, and weak binders, a goal that has been difficult to achieve through other scoring approaches. Accordingly, the protocols presented here could find useful applications in carbohydrate-based drug and vaccine developments.

Role of water in ligand binding to maltose-binding protein: insight from a new docking protocol based on the 3D-RISM-KH molecular theory of solvation

Maltose-binding protein is a periplasmic binding protein responsible for transport of maltooligosaccarides through the periplasmic space of Gram-negative bacteria, as a part of the ABC transport system. The molecular mechanisms of the initial ligand binding and induced large scale motion of the protein's domains still remain elusive. In this study, we use a new docking protocol that combines a recently proposed explicit water placement algorithm based on the 3D-RISM-KH molecular theory of solvation and conventional docking software (AutoDock Vina) to explain the mechanisms of maltotriose binding to the apo-open state of a maltose-binding protein. We confirm the predictions of previous NMR spectroscopic experiments on binding modes of the ligand. We provide the molecular details on the binding mode that was not previously observed in the X-ray experiments. We show that this mode, which is defined by the fine balance between the protein-ligand direct interactions and solvation effects, can trigger the protein's domain motion resulting in the holo-closed structure of the maltose-binding protein with the maltotriose ligand in excellent agreement with the experimental data. We also discuss the role of water in blocking unfavorable binding sites and water-mediated interactions contributing to the stability of observable binding modes of maltotriose.

Calculating binding free energies for protein-carbohydrate complexes

A variety of computational techniques may be applied to compute theoretical binding free energies for protein-carbohydrate complexes. Elucidation of the intermolecular interactions, as well as the thermodynamic effects, that contribute to the relative strength of receptor binding can shed light on biomolecular recognition, and the resulting initiation or inhibition of a biological process. Three types of free energy methods are discussed here, including MM-PB/GBSA, thermodynamic integration, and a non-equilibrium alternative utilizing SMD. Throughout this chapter, the well-known concanavalin A lectin is employed as a model system to demonstrate the application of these methods to the special case of carbohydrate binding.

Evidence of conformational selection driving the formation of ligand binding sites in protein-protein interfaces

Many protein-protein interactions (PPIs) are compelling targets for drug discovery, and in a number of cases can be disrupted by small molecules. The main goal of this study is to examine the mechanism of binding site formation in the interface region of proteins that are PPI targets by comparing ligand-free and ligand-bound structures. To avoid any potential bias, we focus on ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) techniques and deposited in the Protein Data Bank, rather than on ensembles specifically generated for this study. The measures used for structure comparison are based on detecting binding hot spots, i.e., protein regions that are major contributors to the binding free energy. The main tool of the analysis is computational solvent mapping, which explores the surface of proteins by docking a large number of small “probe” molecules. Although we consider conformational ensembles obtained by NMR techniques, the analysis is independent of the method used for generating the structures. Finding the energetically most important regions, mapping can identify binding site residues using ligand-free models based on NMR data. In addition, the method selects conformations that are similar to some peptide-bound or ligand-bound structure in terms of the properties of the binding site. This agrees with the conformational selection model of molecular recognition, which assumes such pre-existing conformations. The analysis also shows the maximum level of similarity between unbound and bound states that is achieved without any influence from a ligand. Further shift toward the bound structure assumes protein-peptide or protein-ligand interactions, either selecting higher energy conformations that are not part of the NMR ensemble, or leading to induced fit. Thus, forming the sites in protein-protein interfaces that bind peptides and can be targeted by small ligands always includes conformational selection, although other recognition mechanisms may also be involved.

Many protein-protein interfaces (PPIs) are biologically compelling drug targets. Disrupting the interaction between two large proteins by a small inhibitor requires forming a high affinity binding site in the interface that generally can bind both peptides and drug-like compounds. Here we investigate whether such sites are induced by peptide or ligand binding, or already exist in the unbound state. The analysis requires comparing ligand-free and ligand-bound structures. To avoid any potential bias, we study ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) rather than generated by simulations. The analysis is based on computational solvent mapping, which explores the surface of the target protein by docking a large number of small “probe” molecules. Results show that ensembles of ligand-free models always include conformations that are fairly similar to some peptide-bound or ligand-bound structure in terms of the properties of the binding site. The analysis also identifies the models that are the most similar to a bound state, and shows the maximum level of similarity that is achieved without any influence from a ligand. While forming the binding site may require a combination of recognition mechanisms, there is preference for the spontaneous formation of bound-like structures.

Dynamic conformational change regulates the protein-DNA recognition: an investigation on binding of a Y-family polymerase to its target DNA

Protein-DNA recognition is a central biological process that governs the life of cells. A protein will often undergo a conformational transition to form the functional complex with its target DNA. The protein conformational dynamics are expected to contribute to the stability and specificity of DNA recognition and therefore may control the functional activity of the protein-DNA complex. Understanding how the conformational dynamics influences the protein-DNA recognition is still challenging. Here, we developed a two-basin structure-based model to explore functional dynamics in Sulfolobus solfataricus DNA Y-family polymerase IV (DPO4) during its binding to DNA. With explicit consideration of non-specific and specific interactions between DPO4 and DNA, we found that DPO4-DNA recognition is comprised of first 3D diffusion, then a short-range adjustment sliding on DNA and finally specific binding. Interestingly, we found that DPO4 is under a conformational equilibrium between multiple states during the binding process and the distributions of the conformations vary at different binding stages. By modulating the strength of the electrostatic interactions, the flexibility of the linker, and the conformational dynamics in DPO4, we drew a clear picture on how DPO4 dynamically regulates the DNA recognition. We argue that the unique features of flexibility and conformational dynamics in DPO4-DNA recognition have direct implications for low-fidelity translesion DNA synthesis, most of which is found to be accomplished by the Y-family DNA polymerases. Our results help complete the description of the DNA synthesis process for the Y-family polymerases. Furthermore, the methods developed here can be widely applied for future investigations on how various proteins recognize and bind specific DNA substrates.

Protein-DNA recognition is crucial for many key biological processes in cells. Protein often undergoes large-scale conformational change during DNA recognition. However, the physical and global understanding of flexible protein-DNA binding is still challenging. Here, we developed a theoretical approach to investigate binding of a Y-family DNA polymerase to its target DNA during the DNA synthesis process. The results of electrostatic-controlled multi-step DNA binding process accompanied with multi-state conformational transition of protein occurring throughout are in remarkable agreement with experiments. During the process of protein-DNA recognition, the flexibility is found to facilitate both the conformational transition of protein (intra-chain dynamics) and DNA binding (inter-chain dynamics) simultaneously. Therefore, we provided a quantitative description of protein-DNA binding mechanism that flexibility or conformational change regulates DNA recognition dynamically, leading to high efficiency and specificity of function for protein-DNA recognition.

Quantitatively characterizing the ligand binding mechanisms of choline binding protein using Markov state model analysis

Protein-ligand recognition plays key roles in many biological processes. One of the most fascinating questions about protein-ligand recognition is to understand its underlying mechanism, which often results from a combination of induced fit and conformational selection. In this study, we have developed a three-pronged approach of Markov State Models, Molecular Dynamics simulations, and flux analysis to determine the contribution of each model. Using this approach, we have quantified the recognition mechanism of the choline binding protein (ChoX) to be ∼90% conformational selection dominant under experimental conditions. This is achieved by recovering all the necessary parameters for the flux analysis in combination with available experimental data. Our results also suggest that ChoX has several metastable conformational states, of which an apo-closed state is dominant, consistent with previous experimental findings. Our methodology holds great potential to be widely applied to understand recognition mechanisms underlining many fundamental biological processes.

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

This study aimed to shed light on the long debate over whether conformational selection (CS) or induced fit (IF) is the governing mechanism for protein-ligand binding. The main difference between the two scenarios is whether the conformational transition of the protein from the unbound form to the bound form occurs before or after encountering the ligand. Here we introduce the IF fraction (i.e., the fraction of binding events achieved via IF), to quantify the binding mechanism. Using simulations of a model protein-ligand system, we demonstrate that both the rate of the conformational transition and the concentration of ligand molecules can affect the IF fraction. CS dominates at slow conformational transition and low ligand concentration. An increase in either quantity results in a higher IF fraction. Despite the many-body nature of the system and the involvement of multiple, disparate types of dynamics (i.e., ligand diffusion, protein conformational transition, and binding reaction), the overall binding kinetics over wide ranges of parameters can be fit to a single exponential, with the apparent rate constant exhibiting a linear dependence on ligand concentration. The present study may guide future kinetics experiments and dynamics simulations in determining the IF fraction.

Kink turn sRNA folding upon L7Ae binding using molecular dynamics simulations

The kink-turn sRNA motif in archaea, whose combination with protein L7Ae initializes the assembly of small ribonucleoprotein particles (sRNPs), plays a key role in ribosome maturation and the translation process. Although many studies have been reported on this motif, the mechanism of sRNA folding coupled with protein binding is still poorly understood. Here, room and high temperature molecular dynamics (MD) simulations were performed on the complex of 25-nt kink-turn sRNA and L7Ae. The average RMSD values between the bound and corresponding apo structures and Kolmogorov-Smirnov P test analysis indicate that sRNA may follow an induced fit mechanism upon binding with L7Ae, both locally and globally. These conclusions are further supported by high-temperature unfolding kinetic analysis. Principal component analysis (PCA) found both closing and opening motions of the kink-turn sRNA. This might play a key role in the sRNP assembly and methylation catalysis. These combined computational methods can be used to study the specific recognition of other sRNAs and proteins.