Metadynamics in essential coordinates: free energy simulation of conformational changes

We propose an approach that combines an extraction of collective motions of a molecular system with a sampling of its free energy surface. A recently introduced method of metadynamics allows exploration of the free energy surface of a molecular system by means of coarse-grained dynamics with flooding of free energy minima. This free energy surface is defined as a function of a set of collective variables (e.g., interatomic distances, angles, torsions, and others). In this study, essential coordinates determined by essential dynamics (principle component analysis) were used as collective variables in metadynamics. First, dynamics of the model system (explicitly solvated alanine dipeptide, Ace-Ala-Nme) was simulated by a classical molecular dynamics simulation. The trajectory (1 ns) was then analyzed by essential dynamics to obtain essential coordinates. The free energy surface as a function of the first and second essential coordinates was then explored by metadynamics. The resulting free energy surface is in agreement with other studies of this system. We propose that a combination of these two methods (metadynamics and essential dynamics) has great potential in studies of conformational changes in peptides and proteins.     

Prediction of SAMPL4 host–guest binding affinities using funnel metadynamics

Accurately predicting binding affinities between ligands and macromolecules has been a much sought-after goal. A tremendous amount of resources can be saved in the pharmaceutical industry through accurate binding-affinity prediction and hence correct decision-making for the drug discovery processes. Owing to the structural complexity of macromolecules, one of the issues in binding affinity prediction using molecular dynamics is the adequate sampling of the conformational space. Recently, the funnel metadynamics method (Limongelli et al. in Proc Natl Acad Sci USA 110:6358, 2013) was developed to enhance the sampling of the ligand at the binding site as well as in the solvated state, and offer the possibility to predict the absolute binding free energy. We apply funnel metadynamics to predict host–guest binding affinities for the cucurbit[7]uril host as part of the SAMPL4 blind challenge. Using total simulation times of 300–400 ns per ligand, we show that the errors due to inadequate sampling are below 1 kcal/mol. However, despite the large investment in terms of computational time, the results compared to experiment are not better than a random guess. As we obtain differences of up to 11 kcal/mol when switching between two commonly used force fields (with automatically generated parameters), we strongly believe that in the pursuit of accurate binding free energies a more careful force-field parametrization is needed to address this type of system.     

Calculation of ligand binding free energies from molecular dynamics simulations

A recently developed method for predicting binding affinities in ligand–receptor complexes, based on interaction energy averaging and conformational sampling by molecular dynamics simulation, is presented. Polar and nonpolar contributions to the binding free energy are approximated by a linear scaling of the corresponding terms in the average intermolecular interaction energy for the bound and free states of the ligand. While the method originally assumed the validity of electrostatic linear response, we show that incorporation of systematic deviations from linear response derived from free energy perturbation calculations enhances the accuracy of the approach. The method is applied to complexes of wild-type and mutant human dihydrofolate reductases with 2,4-diaminopteridine and 2,4-diaminoquinazoline inhibitors. It is shown that a binding energy accuracy of about 1 kcal/mol is attainable even for multiply ionized compounds, such as methotrexate, for which electrostatic interactions energies are very large. © 1998 John Wiley & Sons, Inc. Int J Quant Chem 69: 77–88, 1998     

On the convergence improvement in the metadynamics simulations: a Wang-Landau recursion approach

As a popular tool in exploring free energy landscapes, the metadynamics method has been widely applied to elucidate various chemical or biochemical processes. As deeply discussed by Laio et al. [J. Phys. Chem. B 109, 6714 (2005)], the size of the updating Gaussian function is pivotal to the free energy convergence toward the target free energy surface. For instance, a greater Gaussian height can facilitate the quick visit of a conformation region of interest; however, it may lead to a larger error of the calculated free energy surface. In contrast, a lower Gaussian height can guarantee a better resolution of the calculated free energy surface; however, it will take longer time for such a simulation to navigate through the defined conformational region. In order to reconcile such confliction, the authors present a method by implementing the Wang-Landau recursion scheme in the metadynamics simulations to adaptively update the height of the unit Gaussian function. As demonstrated in their model studies on both a toy system, and a realistic molecular system treated with the hybrid quantum mechanical and molecular mechanical (QMMM) potential, the present approach can quickly result in more decently converged free energy surfaces, compared with the classical metadynamics simulations employing the fixed Gaussian heights.     

Conformational Transitions and Convergence of Absolute Binding Free Energy Calculations

The Binding Energy Distribution Analysis Method (BEDAM) is employed to compute the standard binding free energies of a series of ligands to a FK506 binding protein (FKBP12) with implicit solvation. Binding free energy estimates are in reasonably good agreement with experimental affinities. The conformations of the complexes identified by the simulations are in good agreement with crystallographic data, which was not used to restrain ligand orientations. The BEDAM method is based on λ -hopping Hamiltonian parallel Replica Exchange (HREM) molecular dynamics conformational sampling, the OPLS-AA/AGBNP2 effective potential, and multi-state free energy estimators (MBAR). Achieving converged and accurate results depends on all of these elements of the calculation. Convergence of the binding free energy is tied to the level of convergence of binding energy distributions at critical intermediate states where bound and unbound states are at equilibrium, and where the rate of binding/unbinding conformational transitions is maximal. This finding mirrors similar observations in the context of order/disorder transitions as for example in protein folding. Insights concerning the physical mechanism of ligand binding and unbinding are obtained. Convergence for the largest FK506 ligand is achieved only after imposing strict conformational restraints, which however require accurate prior structural knowledge of the structure of the complex. The analytical AGBNP2 model is found to underestimate the magnitude of the hydrophobic driving force towards binding in these systems characterized by loosely packed protein-ligand binding interfaces. Rescoring of the binding energies using a numerical surface area model corrects this deficiency. This study illustrates the complex interplay between energy models, exploration of conformational space, and free energy estimators needed to obtain robust estimates from binding free energy calculations.     

The role of the peripheral anionic site and cation-pi interactions in the ligand penetration of the human AChE gorge

We study the ligand (tetramethylammonium) recognition by the peripheral anionic site and its penetration of the human AChE gorge by using atomistic molecular dynamics simulations and our recently developed metadynamics method. The role of both the peripheral anionic site and the formation of cation-pi interactions in the ligand entrance are clearly shown. In particular, a simulation with the W286A mutant shows the fundamental role of this residue in anchoring the ligand at the peripheral anionic site of the enzyme and in positioning it prior to the gorge entrance. Once the ligand is properly oriented, the formation of specific and synchronized cation-pi interactions with W86, F295, and Y341 enables the gorge penetration. Eventually, the ligand is stabilized in a free energy basin by means of cation-pi interactions with W86.     

A molecular dynamics investigation of CDK8/CycC and ligand binding: conformational flexibility and implication in drug discovery

Abnormal activity of cyclin-dependent kinase 8 (CDK8) along with its partner protein cyclin C (CycC) is a common feature of many diseases including colorectal cancer. Using molecular dynamics (MD) simulations, this study determined the dynamics of the CDK8-CycC system and we obtained detailed breakdowns of binding energy contributions for four type-I and five type-II CDK8 inhibitors. We revealed system motions and conformational changes that will affect ligand binding, confirmed the essentialness of CycC for inclusion in future computational studies, and provide guidance in development of CDK8 binders. We employed unbiased all-atom MD simulations for 500 ns on twelve CDK8-CycC systems, including apoproteins and protein–ligand complexes, then performed principal component analysis (PCA) and measured the RMSF of key regions to identify protein dynamics. Binding pocket volume analysis identified conformational changes that accompany ligand binding. Next, H-bond analysis, residue-wise interaction calculations, and MM/PBSA were performed to characterize protein–ligand interactions and find the binding energy. We discovered that CycC is vital for maintaining a proper conformation of CDK8 to facilitate ligand binding and that the system exhibits motion that should be carefully considered in future computational work. Surprisingly, we found that motion of the activation loop did not affect ligand binding. Type-I and type-II ligand binding is driven by van der Waals interactions, but electrostatic energy and entropic penalties affect type-II binding as well. Binding of both ligand types affects protein flexibility. Based on this we provide suggestions for development of tighter-binding CDK8 inhibitors and offer insight that can aid future computational studies.     

Ligand binding affinity prediction by linear interaction energy methods

A recent method for estimating ligand binding affinities is extended. This method employs averages of interaction potential energy terms from molecular dynamics simulations or other thermal conformational sampling techniques. Incorporation of systematic deviations from electrostatic linear response, derived from free energy perturbation studies, into the absolute binding free energy expression significantly enhances the accuracy of the approach. This type of method may be useful for computational prediction of ligand binding strengths, e.g., in drug design applications.     

Exploiting Free‐Energy Minima to Design Novel EphA2 Protein–Protein Antagonists: From Simulation to Experiment and Return

The free‐energy surface (FES) of protein–ligand binding contains information useful for drug design. Here we show how to exploit a free‐energy minimum of a protein‐ligand complex identified by metadynamics simulations to design a new EphA2 antagonist with improved inhibitory potency.     

Heating and flooding: a unified approach for rapid generation of free energy surfaces

We propose a general framework for the efficient sampling of conformational equilibria in complex systems and the generation of associated free energy hypersurfaces in terms of a set of collective variables. The method is a strategic synthesis of the adiabatic free energy dynamics approach, previously introduced by us and others, and existing schemes using Gaussian-based adaptive bias potentials to disfavor previously visited regions. In addition, we suggest sampling the thermodynamic force instead of the probability density to reconstruct the free energy hypersurface. All these elements are combined into a robust extended phase-space formalism that can be easily incorporated into existing molecular dynamics packages. The unified scheme is shown to outperform both metadynamics and adiabatic free energy dynamics in generating two-dimensional free energy surfaces for several example cases including the alanine dipeptide in the gas and aqueous phases and the met-enkephalin oligopeptide. In addition, the method can efficiently generate higher dimensional free energy landscapes, which we demonstrate by calculating a four-dimensional surface in the Ramachandran angles of the gas-phase alanine tripeptide.     

Fast,metadynamics‐based method for prediction of the stereochemistry‐dependent relative free energies of ligand–receptor interactions

The computational approach applicable for the molecular dynamics (MD)‐based techniques is proposed to predict the ligand–protein binding affinities dependent on the ligand stereochemistry. All possible stereoconfigurations are expressed in terms of one set of force‐field parameters [stereoconfiguration‐independent potential (SIP)], which allows for calculating all relative free energies by only single simulation. SIP can be used for studying diverse, stereoconfiguration‐dependent phenomena by means of various computational techniques of enhanced sampling. The method has been successfully tested on the β₂‐adrenergic receptor (β₂‐AR) binding the four fenoterol stereoisomers by both metadynamics simulations and replica‐exchange MD. Both the methods gave very similar results, fully confirming the presence of stereoselective effects in the fenoterol‐β₂‐AR interactions. However, the metadynamics‐based approach offered much better efficiency of sampling which allows for significant reduction of the unphysical region in SIP. © 2014 Wiley Periodicals, Inc.     

The free energy landscape of small peptides as obtained from metadynamics with umbrella sampling corrections

There is considerable interest in developing methodologies for the accurate evaluation of free energies, especially in the context of biomolecular simulations. Here, we report on a reexamination of the recently developed metadynamics method, which is explicitly designed to probe "rare events" and areas of phase space that are typically difficult to access with a molecular dynamics simulation. Specifically, we show that the accuracy of the free energy landscape calculated with the metadynamics method may be considerably improved when combined with umbrella sampling techniques. As test cases, we have studied the folding free energy landscape of two prototypical peptides: Ace-(Gly)(2)-Pro-(Gly)(3)-Nme in vacuo and trialanine solvated by both implicit and explicit water. The method has been implemented in the classical biomolecular code AMBER and is to be distributed in the next scheduled release of the code.     

Essential energy space random walk via energy space metadynamics method to accelerate molecular dynamics simulations

To overcome the possible pseudoergodicity problem, molecular dynamic simulation can be accelerated via the realization of an energy space random walk. To achieve this, a biased free energy function (BFEF) needs to be priori obtained. Although the quality of BFEF is essential for sampling efficiency, its generation is usually tedious and nontrivial. In this work, we present an energy space metadynamics algorithm to efficiently and robustly obtain BFEFs. Moreover, in order to deal with the associated diffusion sampling problem caused by the random walk in the total energy space, the idea in the original umbrella sampling method is generalized to be the random walk in the essential energy space, which only includes the energy terms determining the conformation of a region of interest. This essential energy space generalization allows the realization of efficient localized enhanced sampling and also offers the possibility of further sampling efficiency improvement when high frequency energy terms irrelevant to the target events are free of activation. The energy space metadynamics method and its generalization in the essential energy space for the molecular dynamics acceleration are demonstrated in the simulation of a pentanelike system, the blocked alanine dipeptide model, and the leucine model.     

Role of protein flexibility in the design of Bcl-XL targeting agents: insight from molecular dynamics

Detailed understanding of protein–ligand interactions is crucial to the design of more effective drugs. This is particularly true when targets are protein interfaces which have flexible, shallow binding sites that exhibit substantial structural rearrangement upon ligand binding. In this study, we use molecular dynamics simulations and free energy calculations to explore the role of ligand-induced conformational changes in modulating the activity of three generations of Bcl-X_L inhibitors. We show that the improvement in the binding affinity of each successive ligand design is directly related to a unique and measurable reduction in local flexibility of specific regions of the binding groove, accompanied by the corresponding changes in the secondary structure of the protein. Dynamic analysis of ligand–protein interactions reveals that the latter evolve with each new design consistent with the observed increase in protein stability, and correlate well with the measured binding affinities. Moreover, our free energy calculations predict binding affinities which are in qualitative agreement with experiment, and indicate that hydrogen bonding to Asn100 could play a prominent role in stabilizing the bound conformations of latter generation ligands, which has not been recognized previously. Overall our results suggest that molecular dynamics simulations provide important information on the dynamics of ligand–protein interactions that can be useful in guiding the design of small-molecule inhibitors of protein interfaces. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Active site pressurization: a new tool for structure-guided drug design and other studies of protein flexibility

We present a new molecular dynamics methodology to assist in structure-based drug design and other studies that seek to predict protein deformability. Termed Active Site Pressurization (ASP), the new methodology simply injects a resin into the ligand binding-site of a protein during the course of a molecular dynamics simulation such that novel, energetically reasonable protein conformations are generated in an unbiased way that may be better representations of the ligand binding conformation than are currently available. Here we apply two different versions of the ASP methodology to three proteins, cytochrome P450cam, PcrA helicase, and glycogen synthase kinase 3beta (GSK3beta), and show that the method is capable of inducing significant conformational changes when compared to the X-ray crystal structures. Application of the ASP methodology therefore provides a view of binding site flexibility that is a rich source of data for inclusion in a variety of further investigations, including high-throughput virtual screening, lead hopping, revealing alternative modes of deformation, and revealing hidden exit and entrance tunnels.     

Studying functional dynamics in bio-molecules using accelerated molecular dynamics

Many biologically important processes such as enzyme catalysis, signal transduction, ligand binding and allosteric regulation occur on the micro- to millisecond time-scale. Despite the sustained and rapid increase in available computational power and the development of efficient simulation algorithms, molecular dynamics (MD) simulations of proteins and bio-machines are generally limited to time-scales of tens to hundreds of nano-seconds. In this perspective article we present a comprehensive review of Accelerated Molecular Dynamics (AMD), an extended biased potential molecular dynamics approach that allows for the efficient study of bio-molecular systems up to time-scales several orders of magnitude greater than those accessible using standard classical MD methods, whilst still maintaining a fully atomistic representation of the system. Compared to many other approaches, AMD affords efficient enhanced conformational space sampling without any a priori understanding of the underlying free energy surface, nor does it require the specific prior definition of a reaction coordinate or a set of collective variables. Successful applications of the AMD method, including the study of slow time-scale functional dynamics in folded proteins and the conformational behavior of natively unstructured proteins are discussed and an outline of the different variants and extensions to the standard AMD approach is presented.     

An unconventional ligand-binding mechanism of substrate-binding proteins: MD simulation and Markov state model analysis of BtuF

In conventional “Venus Flytrap” mechanism, substrate-binding proteins (SBPs) interconvert between the open and closed conformations. Upon ligand binding, SBPs form a tightly closed conformation with the ligand bound at the interface of two domains. This mechanism was later challenged by many type III SBPs, such as the vitamin B₁₂-binding protein BtuF, in which the apo- and holo-state proteins adopt very similar conformations. Here, we combined molecular dynamics simulation and Markov state model analysis to study the conformational dynamics of apo- and B₁₂-bound BtuF. The results indicate that the crystal structures represent the only stable conformation of BtuF. Meanwhile, both apo- and holo-BtuF undergo large-scale interdomain motions with little energy cost. B₁₂ binding casts little restraints on the interdomain motions, suggesting that ligand binding affinity is enhanced by the remaining conformational entropy of holo-BtuF. These results reveal a new paradigm of ligand recognition mechanism of SBPs. © 2019 Wiley Periodicals, Inc.     

WATsite: Hydration site prediction program with PyMOL interface

Water molecules that mediate protein–ligand interactions or are released from the binding site on ligand binding can contribute both enthalpically and entropically to the free energy of ligand binding. To elucidate the thermodynamic profile of individual water molecules and their potential contribution to ligand binding, a hydration site analysis program WATsite was developed together with an easy‐to‐use graphical user interface based on PyMOL. WATsite identifies hydration sites from a molecular dynamics simulation trajectory with explicit water molecules. The free energy profile of each hydration site is estimated by computing the enthalpy and entropy of the water molecule occupying a hydration site throughout the simulation. The results of the hydration site analysis can be displayed in PyMOL. A key feature of WATsite is that it is able to estimate the protein desolvation free energy for any user specified ligand. The WATsite program and its PyMOL plugin are available free of charge from http://people.pnhs.purdue.edu/~mlill/software . © 2014 Wiley Periodicals, Inc.     

From A to B in free energy space

The authors present a new method for searching low free energy paths in complex molecular systems at finite temperature. They introduce two variables that are able to describe the position of a point in configurational space relative to a preassigned path. With the help of these two variables the authors combine features of approaches such as metadynamics or umbrella sampling with those of path based methods. This allows global searches in the space of paths to be performed and a new variational principle for the determination of low free energy paths to be established. Contrary to metadynamics or umbrella sampling the path can be described by an arbitrary large number of variables, still the energy profile along the path can be calculated. The authors exemplify the method numerically by studying the conformational changes of alanine dipeptide.