Exploring the energy landscapes of molecular recognition by a genetic algorithm: Analysis of the requirements for robust docking of HIV-1 protease and FKBP-12 complexes

Energy landscapes of molecular recognition are explored by performing “semi-rigid” docking of FK-506 and rapamycin with the Fukisawa binding protein (FKBP-12), and flexible docking simulations of the Ro-31-8959 and AG-1284 inhibitors with HIV-1 protease by a genetic algorithm. The requirements of a molecular recognition model to meet thermodynamic and kinetic criteria of ligand-protein docking simultaneously are investigated using a family of simple molecular recognition energy functions. The critical factor that determines the success rate in predicting the structure of ligand-protein complexes is found to be the roughness of the binding energy landscape, in accordance with a minimal frustration principle. The results suggest that further progress in structure prediction of ligand-protein complexes can be achieved by designing molecular recognition energy functions that generate binding landscapes with reduced frustration. © 1996 Wiley-Liss, Inc.     

Mean field analysis of FKBP12 complexes with FK506 and rapamycin: Implications for a role of crystallographic water molecules in molecular recognition and specificity

Mean field analysis of FKBP12 complexes with FK506 and rapamycin has been performed by using structures obtained from molecular docking simulations on a simple, yet robust molecular recognition energy landscape. When crystallographic water molecules are included in the simulations as an extension of the FKBP12 protein surface, there is an appreciable stability gap between the energy of the native FKBP12–FK506 complex and energies of conformations with the “native-like” binding mode. By contrast, the energy spectrum of the FKBP12–rapamycin complex is dense regardless of the presence of the water molecules. The stability gap in the FKBP12–FK506 system is determined by two critical water molecules from the effector region that participate in a network of specific hydrogen bond interactions. This interaction pattern protects the integrity and precision of the composite ligand-protein effector surface in the binary FKBP12–FK506 complex and is preserved in the crystal structure of the FKBP12–FK506–calcineurin ternary complex. These features of the binding energy landscapes provide useful insights into specific and nonspecific aspects of FK506 and rapamycin recognition. Proteins 28:313–324, 1997. © 1997 Wiley-Liss, Inc.     

Monte Carlo simulations of the peptide recognition at the consensus binding site of the constant fragment of human immunoglobulin G: the energy landscape analysis of a hot spot at the intermolecular interface

Monte Carlo simulations of molecular recognition at the consensus binding site of the constant fragment (Fc) of human immunoglobulin G (Ig) protein have been performed to analyze structural and thermodynamic aspects of binding for the 13-residue cyclic peptide DCAWHLGELVWCT. The energy landscape analysis of a hot spot at the intermolecular interface using alanine scanning and equilibrium-simulated tempering dynamics with the simplified, knowledge-based energy function has enabled the role of the protein hot spot residues in providing the thermodynamic stability of the native structure to be determined. We have found that hydrophobic interactions between the peptide and the Met-252, Ile-253, His-433, and His-435 protein residues are critical to guarantee the thermodynamic stability of the crystallographic binding mode of the complex. Binding free energy calculations, using a molecular mechanics force field and a solvation energy model, combined with alanine scanning have been conducted to determine the energetic contribution of the protein hot spot residues in binding affinity. The conserved Asn-434, Ser-254, and Tyr-436 protein residues contribute significantly to the binding affinity of the peptide-protein complex, serving as an energetic hot spot at the intermolecular interface. The results suggest that evolutionary conserved hot spot protein residues at the intermolecular interface may be partitioned in fulfilling thermodynamic stability of the native binding mode and contributing to the binding affinity of the complex.     

The thermodynamic signature of ligand binding to histone deacetylase-like amidohydrolases is most sensitive to the flexibility in the L2-loop lining the active site pocket

BackgroundThe analysis of the thermodynamic driving forces of ligand-protein binding has been suggested to be a key component for the selection and optimization of active compounds into drug candidates. The binding enthalpy as deduced from isothermal titration calorimetry (ITC) is usually interpreted assuming single-step binding of a ligand to one conformation of the target protein. Although successful in many cases, these assumptions are oversimplified approximations of the reality with flexible proteins and complicated binding mechanism in many if not most cases. The relationship between protein flexibility and thermodynamic signature of ligand binding is largely understudied.MethodsDirected mutagenesis, X-ray crystallography, enzyme kinetics and ITC methods were combined to dissect the influence of loop flexibility on the thermodynamics and mechanism of ligand binding to histone deacetylase (HDAC)-like amidohydrolases.ResultsThe general ligand-protein binding mechanism comprises an energetically demanding gate opening step followed by physical binding. Increased flexibility of the L2-loop in HDAC-like amidohydrolases facilitates access of ligands to the binding pocket resulting in predominantly enthalpy-driven complex formation.ConclusionsThe study provides evidence for the great importance of flexibility adjacent to the active site channel for the mechanism and observed thermodynamic driving forces of molecular recognition in HDAC like enzymes.General significanceThe flexibility or malleability in regions adjacent to binding pockets should be given more attention when designing better drug candidates. The presented case study also suggests that the observed binding enthalpy of protein-ligand systems should be interpreted with caution, since more complicated binding mechanisms may obscure the significance regarding potential drug likeness.     

Complexity and simplicity of ligand-macromolecule interactions: the energy landscape perspective

The energy landscape approach has contributed to recent progress in understanding the complexity and simplicity of ligand-macromolecule interactions. Significant advances in computational structure prediction of ligand-protein complexes have been made using approaches that include the effects of protein flexibility and incorporate a hierarchy of energy functions. The results suggest that the complexity of structure prediction in molecular recognition may be determined by low-resolution properties of the underlying binding energy landscapes and by the nature of the energy funnels near the native structures of the complexes.     

Peptide binding to the PDZ3 domain by conformational selection

The PDZ domains, a large family of peptide recognition proteins, bind to the C‐terminal segment of membrane ion channels and receptors thereby mediating their localization. The peptide binding process is not known in detail and seems to differ among different PDZ domains. For the third PDZ domain of the synaptic protein PSD‐95 (PDZ3), a lock‐and‐key mechanism was postulated on the basis of the almost perfect overlap of the crystal structures in the presence and absence of its peptide ligand. Here, peptide binding to PDZ3 is investigated by explicit solvent molecular dynamics (MD) simulations (for a total of 1.3 μs) and the cut‐based free energy profile method for determining free energy barriers and basins. The free energy landscape of apo PDZ3 indicates that there are multiple basins within the native state. These basins differ by the relative orientation of the α2 helix and β2 strand, the two secondary structure elements that make up the peptide binding site. Only the structure with the smallest aperture of the binding site is populated in the MD simulations of the complex whose analysis reveals that the peptide ligand binds to PDZ3 by selecting one of three conformations. Thus, the dynamical information obtained by the atomistic simulations increment the static, that is, partial, picture of the PDZ3 binding mechanism based on the X‐ray crystallography data. Importantly, the simulation results show for the first time that conformational selection is a possible mechanism of peptide binding by PDZ domains in general. Proteins 2012. © 2012 Wiley Periodicals, Inc.     

Stochastic roadmap simulation: an efficient representation and algorithm for analyzing molecular motion.

Classic molecular motion simulation techniques, such as Monte Carlo (MC) simulation, generate motion pathways one at a time and spend most of their time in the local minima of the energy landscape defined over a molecular conformation space. Their high computational cost prevents them from being used to compute ensemble properties (properties requiring the analysis of many pathways). This paper introduces stochastic roadmap simulation (SRS) as a new computational approach for exploring the kinetics of molecular motion by simultaneously examining multiple pathways. These pathways are compactly encoded in a graph, which is constructed by sampling a molecular conformation space at random. This computation, which does not trace any particular pathway explicitly, circumvents the local-minima problem. Each edge in the graph represents a potential transition of the molecule and is associated with a probability indicating the likelihood of this transition. By viewing the graph as a Markov chain, ensemble properties can be efficiently computed over the entire molecular energy landscape. Furthermore, SRS converges to the same distribution as MC simulation. SRS is applied to two biological problems: computing the probability of folding, an important order parameter that measures the "kinetic distance" of a protein's conformation from its native state; and estimating the expected time to escape from a ligand-protein binding site. Comparison with MC simulations on protein folding shows that SRS produces arguably more accurate results, while reducing computation time by several orders of magnitude. Computational studies on ligand-protein binding also demonstrate SRS as a promising approach to study ligand-protein interactions.     

Predicting structural effects in HIV-1 protease mutant complexes with flexible ligand docking and protein side-chain optimization

We present a computational approach for predicting structures of ligand-protein complexes and analyzing binding energy landscapes that combines Monte Carlo simulated annealing technique to determine the ligand bound conformation with the dead-end elimination algorithm for side-chain optimization of the protein active site residues. Flexible ligand docking and optimization of mobile protein side-chains have been performed to predict structural effects in the V32I/I47V/V82I HIV-1 protease mutant bound with the SB203386 ligand and in the V82A HIV-1 protease mutant bound with the A77003 ligand. The computational structure predictions are consistent with the crystal structures of these ligand-protein complexes. The emerging relationships between ligand docking and side-chain optimization of the active site residues are rationalized based on the analysis of the ligand-protein binding energy landscape. Proteins 33:295–310, 1998. © 1998 Wiley-Liss, Inc.     

Conformational diversity of ligands bound to proteins

The phenomenon of molecular recognition, which underpins almost all biological processes, is dynamic, complex and subtle. Establishing an interaction between a pair of molecules involves mutual structural rearrangements guided by a highly convoluted energy landscape, the accurate mapping of which continues to elude us. Increased understanding of the degree to which the conformational space of a ligand is restricted upon binding may have important implications for docking studies, structure refinement and for function prediction methods based on geometrical comparisons of ligands or their binding sites. Here, we present an analysis of the conformational variability exhibited by three of the most ubiquitous biological ligands in nature, ATP, NAD and FAD. First, we demonstrate qualitatively that these ligands bind to proteins in widely varying conformations, including several cases in which parts of the molecule assume energetically unfavourable orientations. Next, by comparing the distribution of bound ligand shapes with the set of all possible molecular conformations, we provide a quantitative assessment of previous observations that ligands tend to unfold when binding to proteins. We show that, while extended forms of ligands are indeed common in ligand-protein structures, instances of ligands in almost maximally compact arrangements can also be found. Thirdly, we compare the conformational variation in two sets of ligand molecules, those bound to homologous proteins, and those bound to unrelated proteins. Although most superfamilies bind ligands in a fairly conserved manner, we find several cases in which significant variation in ligand configuration is observed.     

In silico elucidation of the recognition dynamics of ubiquitin

Elucidation of the mechanism of biomacromolecular recognition events has been a topic of intense interest over the past century. The inherent dynamic nature of both protein and ligand molecules along with the continuous reshaping of the energy landscape during the binding process renders it difficult to characterize this process at atomic detail. Here, we investigate the recognition dynamics of ubiquitin via microsecond all-atom molecular dynamics simulation providing both thermodynamic and kinetic information. The high-level of consistency found with respect to experimental NMR data lends support to the accuracy of the in silico representation of the conformational substates and their interconversions of free ubiquitin. Using an energy-based reweighting approach, the statistical distribution of conformational states of ubiquitin is monitored as a function of the distance between ubiquitin and its binding partner Hrs-UIM. It is found that extensive and dense sampling of conformational space afforded by the μs MD trajectory is essential for the elucidation of the binding mechanism as is Boltzmann sampling, overcoming inherent limitations of sparsely sampled empirical ensembles. The results reveal a population redistribution mechanism that takes effect when the ligand is at intermediate range of 1-2 nm from ubiquitin. This mechanism, which may be depicted as a superposition of the conformational selection and induced fit mechanisms, also applies to other binding partners of ubiquitin, such as the GGA3 GAT domain.     

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

A full characterization of the thermodynamic forces underlying ligand-associated conformational changes in proteins is essential for understanding and manipulating diverse biological processes, including transport, signaling, and enzymatic activity. Recent experiments on the maltose binding protein (MBP) have provided valuable data about the different conformational states implicated in the ligand recognition process; however, a complete picture of the accessible pathways and the associated changes in free energy remains elusive. Here we describe results from advanced accelerated molecular dynamics (aMD) simulations, coupled with adaptively biased force (ABF) and thermodynamic integration (TI) free energy methods. The combination of approaches allows us to track the ligand recognition process on the microsecond time scale and provides a detailed characterization of the protein's dynamic and the relative energy of stable states. We find that an induced-fit (IF) mechanism is most likely and that a mechanism involving both a conformational selection (CS) step and an IF step is also possible. The complete recognition process is best viewed as a "Pac Man" type action where the ligand is initially localized to one domain and naturally occurring hinge-bending vibrations in the protein are able to assist the recognition process by increasing the chances of a favorable encounter with side chains on the other domain, leading to a population shift. This interpretation is consistent with experiments and provides new insight into the complex recognition mechanism. The methods employed here are able to describe IF and CS effects and provide formally rigorous means of computing free energy changes. As such, they are superior to conventional MD and flexible docking alone and hold great promise for future development and applications to drug discovery.     

A molecular dynamics study of a miRNA:mRNA interaction

In this paper we present a methodology to evaluate the binding free energy of a miRNA:mRNA complex through molecular dynamics (MD)–thermodynamic integration (TI) simulations. We applied our method to the Caenorhabditis elegans let-7 miRNA:lin-41 mRNA complex—a validated miRNA:mRNA interaction—in order to estimate the energetic stability of the structure. To make the miRNA:mRNA simulation possible and realistic, the methodology introduces specific solutions to overcome some of the general challenges of nucleic acid simulations and binding free energy computations that have been discussed widely in many previous research reports. The main features of the proposed methodology are: (1) positioning of the restraints imposed on the simulations in order to guarantee complex stability; (2) optimal sampling of the phase space to achieve satisfactory accuracy in the binding energy value; (3) determination of a suitable trade-off between computational costs and accuracy of binding free energy computation by the assessment of the scalability characteristics of the parallel simulations required for the TI. The experiments carried out demonstrate that MD simulations are a viable strategy for the study of miRNA binding characteristics, opening the way to the development of new computational target prediction methods based on three-dimensional structure information.     

Molecular dynamics simulations and MM–PBSA calculations of the lectin from snowdrop (Galanthus nivalis)

Galanthus nivalis agglutinin (GNA), a mannose-specific lectin from snowdrop bulbs, is a member of the monocot mannose-specific lectin family and exhibits antiviral activity toward HIV. In the present study, molecular dynamics (MD) simulations were performed to study the interaction between GNA and its carbohydrate ligand over a specific time span. By analysis of the secondary structures, it was observed that the GNA conformation maintains rather stable along the trajectories and the high fluctuations were only centered on the carbohydrate recognition domains. Our MD simulations also reproduced most of the hydrogen bonds observed in the x-ray crystal structure. Furthermore, the obtained MD trajectories were used to estimate the binding free energy of the complex using the molecular mechanics/Poisson Boltzmann surface area (MM-PBSA) method. It was revealed by the inspection of the binding free energy components that the major contributions to the complex stability arose from electrostatic interactions.     

Investigating the binding behaviour of two avidin‐based testosterone binders using molecular recognition force spectroscopy

Molecular recognition force spectroscopy, a biosensing atomic force microscopy technique allows to characterise the dissociation of ligand–receptor complexes at the molecular level. Here, we used molecular recognition force spectroscopy to study the binding capability of recently developed testosterone binders. The two avidin‐based proteins called sbAvd‐1 and sbAvd‐2 are expected to bind both testosterone and biotin but differ in their binding behaviour towards these ligands. To explore the ligand binding and dissociation energy landscape of these proteins, we tethered biotin or testosterone to the atomic force microscopy probe while the testosterone‐binding protein was immobilized on the surface. Repeated formation and rupture of the ligand–receptor complex at different pulling velocities allowed determination of the loading rate dependence of the complex‐rupturing force. In this way, we obtained the molecular dissociation rate (k_off) and energy landscape distances (x_β) of the four possible complexes: sbAvd‐1‐biotin, sbAvd‐1‐testosterone, sbAvd‐2‐biotin and sbAvd‐2‐testosterone. It was found that the kinetic off‐rates for both proteins and both ligands are similar. In contrast, the x_β values, as well as the probability of complex formations, varied considerably. In addition, competitive binding experiments with biotin and testosterone in solution differ significantly for the two testosterone‐binding proteins, implying a decreased cross‐reactivity of sbAvd‐2. Unravelling the binding behaviour of the investigated testosterone‐binding proteins is expected to improve their usability for possible sensing applications. Copyright © 2014 John Wiley & Sons, Ltd.     

Multiscale simulations of protein folding: application to formation of secondary structures

A multiscale simulation method of protein folding is proposed, using atomic representation of protein and solvent, combing genetic algorithms to determine the key protein structures from a global view, with molecular dynamic simulations to reveal the local folding pathways, thus providing an integrated landscape of protein folding. The method is found to be superior to previously investigated global search algorithms or dynamic simulations alone. For secondary structure formation of a selected peptide, RN24, the structures and dynamics produced by this method agree well with corresponding experimental results. Three most populated conformations are observed, including hairpin, β-sheet and α-helix. The energetic barriers separating these three structures are comparable to the kinetic energy of the atoms of the peptide, implying that the transition between these states can be easily triggered by kinetic perturbations, mainly through electrostatic interactions between charged atoms. Transitions between α-helix and β-sheet should jump over at least two energy barriers and may stay in the energetic trap of hairpin. It is proposed that the structure of proteins should be jointly governed by thermodynamic and dynamic factors; free energy is not the exclusive dominant for stability of proteins.     

Elucidating quantitative stability/flexibility relationships within thioredoxin and its fragments using a distance constraint model

Numerous quantitative stability/flexibility relationships, within Escherichia coli thioredoxin (Trx) and its fragments are determined using a minimal distance constraint model (DCM). A one-dimensional free energy landscape as a function of global flexibility reveals Trx to fold in a low-barrier two-state process, with a voluminous transition state. Near the folding transition temperature, the native free energy basin is markedly skewed to allow partial unfolded forms. Under native conditions the skewed shape is lost, and the protein forms a compact structure with some flexibility. Predictions on ten Trx fragments are generally consistent with experimental observations that they are disordered, and that complementary fragments reconstitute. A hierarchical unfolding pathway is uncovered using an exhaustive computational procedure of breaking interfacial cross-linking hydrogen bonds that span over a series of fragment dissociations. The unfolding pathway leads to a stable core structure (residues 22-90), predicted to act as a kinetic trap. Direct connection between degree of rigidity within molecular structure and non-additivity of free energy is demonstrated using a thermodynamic cycle involving fragments and their hierarchical unfolding pathway. Additionally, the model provides insight about molecular cooperativity within Trx in its native state, and about intermediate states populating the folding/unfolding pathways. Native state cooperativity correlation plots highlight several flexibly correlated regions, giving insight into the catalytic mechanism that facilitates access to the active site disulfide bond. Residual native cooperativity correlations are present in the core substructure, suggesting that Trx can function when it is partly unfolded. This natively disordered kinetic trap, interpreted as a molten globule, has a wide temperature range of metastability, and it is identified as the "slow intermediate state" observed in kinetic experiments. These computational results are found to be in overall agreement with a large array of experimental data.     

Free energy simulations for protein ligand binding and stability

Abstract

We summarize several computational techniques to determine relative free energies for condensed-phase systems. The focus is on practical considerations which are capable of making direct contact with experiments. Particular applications include the thermodynamic stability of apo- and holo-myoglobin, insulin dimerization free energy, ligand binding in lysozyme, and ligand diffusion in globular proteins. In addition to provide differential free energies between neighboring states, converged umbrella sampling simulations provide insight into migration barriers and ligand dissociation barriers and analysis of the trajectories yield additional insight into the structural dynamics of fundamental processes. Also, such simulations are useful tools to quantify relative stability changes for situations where experiments are difficult. This is illustrated for NO-bound myoglobin. For the dissociation of benzonitrile from lysozyme it is found that long umbrella sampling simulations are required to approximately converge the free energy profile. Then, however, the resulting differential free energy between the bound and unbound state is in good agreement with estimates from molecular mechanics with generalized Born surface area simulations. Furthermore, comparing the barrier height for ligand escape suggests that ligand dissociation contains a non-equilibrium component.     

Cation-mediated interplay of loops in chaperonin-10

The ubiquitously occurring chaperonins consist of a large tetradecameric Chaperonin-60, forming a cylindrical assembly, and a smaller heptameric Chaperonin-10. For a functional protein folding cycle, Chaperonin-10 caps the cylindrical Chaperonin-60 from one end forming an asymmetric complex. The oligomeric assembly of Chaperonin-10 is known to be highly plastic in nature. In Mycobacterium tuberculosis, the plasticity has been shown to be modulated by reversible binding of divalent cations. Binding of cations confers rigidity to the metal binding loop, and also promotes stability of the oligomeric structure. We have probed the conformational effects of cation binding on the Chaperonin-10 structure through fluorescence studies and molecular dynamics simulations. Fluorescence studies show that cation binding induces reduced exposure and flexibility of the dome loop. The simulations corroborate these results and further indicate a complex landscape of correlated motions between different parts of the molecule. They also show a fascinating interplay between two distantly spaced loops, the metal binding "dome loop" and the GroEL-binding "mobile loop", suggesting an important cation-mediated role in the recognition of Chaperonin-60. In the presence of cations the mobile loop appears poised to dock onto the Chaperonin-60 structure. The divalent metal ions may thus act as key elements in the protein folding cycle, and trigger a conformational switch for molecular recognition.     

Exploring the binding properties of agonists interacting with glucocorticoid receptor: an in silico approach

The glucocorticoid receptors (GR) are members of the nuclear receptor superfamily that regulate growth, development, and many of the biological functions, including metabolism and inflammation, in a ligand dependent behavior. Thus, GRs are vital as therapeutic targets with steroid hormones and steroidal analogues, especially including the glucocorticoids. Studying the molecular mechanism of binding between GR and ligands is fundamentally important to develop applications in the pharmacological industry. The present study was carried out via molecular docking and molecular dynamic (MD) simulations of three GR-ligand complexes formed between the ligand binding domain (LBD) of GR with cortisol (a natural steroid), dexamethasone (a well-known synthetic steroid drug), and chonemorphine (a steroid virtually screened from the “Sri Lankan Flora” web-based information system). The investigation was mainly carried out in terms of macroscopic properties of the ligand-protein interactions and conformational fluctuations of the protein. The results indicated greater stability and a similar behavior of the GR protein in the chonemorphine-GR complex, compared to the other two complexes, GR-dexamethasone and GR-cortisol, in an aqueous medium. The integrity of the protein-substrate complexes was preserved by strong hydrogen bonds formed between the amino acid residues of the binding site of the proteins and ligands. The findings revealed that chonemorphine is a promising agonist to GR and may produce a pharmacological effect like that produced by glucocorticoids. Thus, the obtained knowledge could lead to further investigations of the pharmaceutical potential of chonemorphine and biological functions of GR in vivo.