Perspective on Free-Energy Perturbation Calculations for Chemical Equilibria

Fascaplysin as a specific inhibitor for CDK4: insights from molecular modelling

Cyclin-dependent kinases (CDKs) play a key role in the cell cycle and are important anti-cancer drug targets. The natural product fascaplysin inhibits CDK4 with surprising selectivity (IC(50) = 0.4 µM) compared to the close homolog CDK2 (IC(50) = 500 µM). Free energy calculations of the positively charged fascaplysin and an uncharged iso-electronic derivative in the CDK2 and CDK4 inhibitor complexes indicate that the positive charge of fascaplysin is crucial for selectivity. This finding will guide further improvements in the design of fascaplysin-based selective inhibitors for CDK4.

Identification of HIV inhibitors guided by free energy perturbation calculations

Free energy perturbation (FEP) theory coupled to molecular dynamics (MD) or Monte Carlo (MC) statistical mechanics offers a theoretically precise method for determining the free energy differences of related biological inhibitors. Traditionally requiring extensive computational resources and expertise, it is only recently that its impact is being felt in drug discovery. A review of computer-aided anti-HIV efforts employing FEP calculations is provided here that describes early and recent successes in the design of human immunodeficiency virus type 1 (HIV-1) protease and non-nucleoside reverse transcriptase inhibitors. In addition, our ongoing work developing and optimizing leads for small molecule inhibitors of cyclophilin A (CypA) is highlighted as an update on the current capabilities of the field. CypA has been shown to aid HIV-1 replication by catalyzing the cis/trans isomerization of a conserved Gly-Pro motif in the Nterminal domain of HIV-1 capsid (CA) protein. In the absence of a functional CypA, e.g., by the addition of an inhibitor such as cyclosporine A (CsA), HIV-1 has reduced infectivity. Our simulations of acylurea-based and 1-indanylketone-based CypA inhibitors have determined that their nanomolar and micromolar binding affinities, respectively, are tied to their ability to stabilize Arg55 and Asn102. A structurally novel 1-(2,6-dichlorobenzamido) indole core was proposed to maximize these interactions. FEP-guided optimization, experimental synthesis, and biological testing of lead compounds for toxicity and inhibition of wild-type HIV-1 and CA mutants have demonstrated a dose-dependent inhibition of HIV-1 infection in two cell lines. While the inhibition is modest compared to CsA, the results are encouraging.

Structural characterization and computer-aided optimization of a small-molecule inhibitor of the Arp2/3 complex, a key regulator of the actin cytoskeleton

CK-666 (1) is a recently discovered small-molecule inhibitor of the actin-related protein 2/3 (Arp2/3) complex, a key actin cytoskeleton regulator with roles in bacterial pathogenesis and cancer cell motility. Although 1 is commercially available, the crystal structure of Arp2/3 complex with 1 bound has not been reported, making its mechanism of action uncertain. Furthermore, its relatively low potency increases its potential for off-target effects in vivo, complicating interpretation of its influence in cell biological studies and precluding its clinical use. Herein we report the crystal structure of 1 bound to Arp2/3 complex, which reveals that 1 binds between the Arp2 and Arp3 subunits to stabilize the inactive conformation of the complex. Based on the crystal structure, we used computational docking and free-energy perturbation calculations of monosubstituted derivatives of 1 to guide optimization efforts. Biochemical assays of ten newly synthesized compounds led to the identification of compound 2, which exhibits a threefold increase in inhibitory activity in vitro relative to 1. In addition, our computational analyses unveiled a surface groove at the interface of the Arp2 and Arp3 subunits that can be exploited for additional structure-based optimization.

Methyl effects on protein-ligand binding

The effects of addition of a methyl group to a lead compound on biological activity are examined. A literature analysis of >2000 cases reveals that an activity boost of a factor of 10 or more is found with an 8% frequency, and a 100-fold boost is a 1 in 200 event. Four cases in the latter category are analyzed in depth to elucidate any unusual aspects of the protein-ligand binding, distribution of water molecules, and changes in conformational energetics. The analyses include Monte Carlo/free-energy perturbation (MC/FEP) calculations for methyl replacements in inhibitor series for p38α MAP kinase, ACK1, PTP1B, and thrombin. Methyl substitutions ortho to an aryl ring can be particularly effective at improving activity by inducing a propitious conformational change. The greatest improvements in activity arise from coupling the conformational gain with the burial of the methyl group in a hydrophobic region of the protein.

Exploring metal-driven stereoselectivity of glycopeptides by free-energy calculations

A formalism to quantify the chemical stereoselectivity, based on free energy of binding calculations, is here discussed. It is used to explain the stereoselectivity of two diastereoisomeric frameworks, comprising the dimer of a copper(II)-peptide core of L- and D-carnosine, respectively, each bound to two chains of D-trehalose, in which copper(II) adopts a type-II coordination geometry. The stereocenter of carnosine is varied both L and D, giving rise to two diastereoisomers. A thermodynamic cycle crossing the formation of the two enantiomeric copper(II) peptide cores was devised. A harmonic restraining potential that depends only on the bond distance was added to ensure reversibility in bond formation and dissociation, for an accurate estimate of the free energy. The calculation of the free energy of binding between D-trehalose and the two enantiomeric copper(II) peptide cores reproduces the free-energy quantities observed from stability constants and isothermal titration calorimetry (ITC) measurements. This is an example of chirality selection based on free-energy difference.

Treatment of Halogen Bonding in the OPLS-AA Force Field; Application to Potent Anti-HIV Agents

The representation of chlorine, bromine, and iodine in aryl halides has been modified in the OPLS-AA and OPLS/CM1A force fields in order to incorporate halogen bonding. The enhanced force fields, OPLS-AAx and OPLS/CM1Ax, have been tested in calculations on gas-phase complexes of halobenzenes with Lewis bases, and for free energies of hydration, densities, and heats of vaporization of halobenzenes. Comparisons with results of MP2/aug-cc-pVDZ(-PP) calculations for the complexes are included. Implementation in the MCPRO software also allowed computation of relative free energies of binding for a series of HIV reverse transcriptase inhibitors via Monte Carlo/free-energy perturbation calculations. The results support the notion that the activity of an unusually potent chloro analog likely benefits from halogen bonding with the carbonyl group of a proline residue.

GMCT : a Monte Carlo simulation package for macromolecular receptors

Generalized Monte Carlo titration (GMCT) is a versatile suite of computer programs for the efficient simulation of complex macromolecular receptor systems as for example proteins. The computational model of the system is based on a microstate description of the receptor and an average description of its surroundings in terms of chemical potentials. The receptor can be modeled in great detail including conformational flexibility and many binding sites with multiple different forms that can bind different ligand types. Membrane embedded systems can be modeled including electrochemical potential gradients. Overall properties of the receptor as well as properties of individual sites can be studied with a variety of different Monte Carlo (MC) simulation methods. Metropolis MC, Wang-Landau MC and efficient free energy calculation methods are included. GMCT is distributed as free open source software at www.bisb.uni-bayreuth.de under the terms of the GNU Affero General Public License.

Computationally-guided optimization of a docking hit to yield catechol diethers as potent anti-HIV agents

A 5-μM docking hit has been optimized to an extraordinarily potent (55 pM) non-nucleoside inhibitor of HIV reverse transcriptase. Use of free energy perturbation (FEP) calculations to predict relative free energies of binding aided the optimizations by identifying optimal substitution patterns for phenyl rings and a linker. The most potent resultant catechol diethers feature terminal uracil and cyanovinylphenyl groups. A halogen bond with Pro95 likely contributes to the extreme potency of compound 42. In addition, several examples are provided illustrating failures of attempted grafting of a substructure from a very active compound onto a seemingly related scaffold to improve its activity.

Efficient discovery of potent anti-HIV agents targeting the Tyr181Cys variant of HIV reverse transcriptase

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) that interfere with the replication of human immunodeficiency virus (HIV) are being pursued with guidance from molecular modeling including free-energy perturbation (FEP) calculations for protein-inhibitor binding affinities. The previously reported pyrimidinylphenylamine 1 and its chloro analogue 2 are potent anti-HIV agents; they inhibit replication of wild-type HIV-1 in infected human T-cells with EC(50) values of 2 and 10 nM, respectively. However, they show no activity against viral strains containing the Tyr181Cys (Y181C) mutation in HIV-RT. Modeling indicates that the problem is likely associated with extensive interaction between the dimethylallyloxy substituent and Tyr181. As an alternative, a phenoxy group is computed to be oriented in a manner diminishing the contact with Tyr181. However, this replacement leads to a roughly 1000-fold loss of activity for 3 (2.5 μM). The present report details the efficient, computationally driven evolution of 3 to novel NNRTIs with sub-10 nM potency toward both wild-type HIV-1 and Y181C-containing variants. The critical contributors were FEP substituent scans for the phenoxy and pyrimidine rings and recognition of potential benefits of addition of a cyanovinyl group to the phenoxy ring.

Computing Alchemical Free Energy Differences with Hamiltonian Replica Exchange Molecular Dynamics (H-REMD) Simulations

Alchemical free energy calculations play a very important role in the field of molecular modeling. Efforts have been made to improve the accuracy and precision of those calculations. One of the efforts is to employ a Hamiltonian replica exchange molecular dynamics (H-REMD) method to enhance conformational sampling. In this paper, we demonstrated that HREMD method not only improves convergence in alchemical free energy calculations but also can be used to compute free energy differences directly via the Free Energy Perturbation (FEP)algorithm. We show a direct mapping between the H-REMD and the usual FEP equations, which are then used directly to compute free energies. The H-REMD alchemical free energy calculation (Replica exchange Free Energy Perturbation, REFEP) was tested on predicting the pK(a) value of the buried Asp26 in thioredoxin. We compare the results of REFEP with TI and regular FEP simulations. REFEP calculations converged faster than those from TI and regular FEP simulations. The final predicted pK(a) value from the H-REMD simulation was also very accurate, only 0.4 pK(a) unit above the experimental value. Utilizing the REFEP algorithm significantly improves conformational sampling, and this in turn improves the convergence of alchemical free energy simulations.

Recent theoretical and computational advances for modeling protein-ligand binding affinities

We review recent theoretical and algorithmic advances for the modeling of protein ligand binding free energies. We first describe a statistical mechanics theory of noncovalent association, with particular focus on deriving the fundamental formulas on which computational methods are based. The second part reviews the main computational models and algorithms in current use or development, pointing out the relations with each other and with the theory developed in the first part. Particular emphasis is given to the modeling of conformational reorganization and entropic effect. The methods reviewed are free energy perturbation, double decoupling, the Binding Energy Distribution Analysis Method, the potential of mean force method, mining minima and MM/PBSA. These models have different features and limitations, and their ranges of applicability vary correspondingly. Yet their origins can all be traced back to a single fundamental theory.

Computational insight into small molecule inhibition of cyclophilins

Cyclophilins (Cyp) are a family of cellular enzymes possessing peptidyl-prolyl isomerase activity, which catalyze the cis-trans interconversion of proline-containing peptide bonds. The two most abundant family members, CypA and CypB, have been identified as valid drug targets for a wide range of diseases, including HCV, HIV, and multiple cancers. However, the development of small molecule inhibitors that possess nM potency and high specificity for a particular Cyp is difficult given the complete conservation of all active site residues between the enzymes. Monte Carlo statistical sampling coupled to free energy perturbation theory (MC/FEP) calculations have been carried out to elucidate the origin of the experimentally observed nM inhibition of CypA by acylurea-based derivatives and the >200-fold in vitro selectivity between CypA and CypB from aryl 1-indanylketone-based μM inhibitors. The computed free-energies of binding were in close accord with those derived from experiments. Binding affinity values for the inhibitors were determined to be dependent upon the stabilization strength of the nonbonded interactions provided toward two catalytic residues: Arg55 and Asn102 in CypA and the analogous Arg63 and Asn110 residues in CypB. Fine-tuning of the hydrophobic interactions allowed for enhanced potency among derivatives. The aryl 1-indanylketones are predicted to differentiate between the cyclophilins by using distinct binding motifs that exploit subtle differences in the active site arrangements. Ideas for the development of new selective compounds with the potential for advancement to low-nanomolar inhibition are presented.

Effects of Water Placement on Predictions of Binding Affinities for p38α MAP Kinase Inhibitors

Monte Carlo free energy perturbation (MC/FEP) calculations have been applied to compute the relative binding affinities of 17 congeneric pyridazo-pyrimidinone inhibitors of the protein p38α MAP kinase. Overall correlation with experiment was found to be modest when the complexes were hydrated using a traditional procedure with a stored solvent box. Significant improvements in accuracy were obtained when the MC/FEP calculations were repeated using initial solvent distributions optimized by the water placement algorithm JAWS. The results underscore the importance of accurate placement of water molecules in a ligand binding site for the reliable prediction of relative free energies of binding.

Computational glycoscience: characterizing the spatial and temporal properties of glycans and glycan-protein complexes

Modern computational methods offer the tools to provide insight into the structural and dynamic properties of carbohydrate-protein complexes, beyond that provided by experimental structural biology. Dynamic properties such as the fluctuation of inter-molecular hydrogen bonds, the residency times of bound water molecules, side chain motions and ligand flexibility may be readily determined computationally. When taken with respect to the unliganded states, these calculations can also provide insight into the entropic and enthalpic changes in free energy associated with glycan binding. In addition, virtual ligand screening may be employed to predict the three dimensional (3D) structures of carbohydrate-protein complexes, given 3D structures for the components. In principle, the 3D structure of the protein may itself be derived by modeling, leading to the exciting--albeit high risk--realm of virtual structure prediction. This latter approach is appealing, given the difficulties associated with generating experimental 3D structures for some classes of glycan binding proteins; however, it is also the least robust. An unexpected outcome of the development of algorithms for modeling carbohydrate-protein interactions has been the discovery of errors in reported experimental 3D structures and a heightened awareness of the need for carbohydrate-specific computational tools for assisting in the refinement and curation of carbohydrate-containing crystal structures. Here we present a summary of the basic strategies associated with employing classical force field based modeling approaches to problems in glycoscience, with a focus on identifying typical pitfalls and limitations. This is not an exhaustive review of the current literature, but hopefully will provide a guide for the glycoscientist interested in modeling carbohydrates and carbohydrate-protein complexes, as well as the computational chemist contemplating such tasks.

The Binding Energy Distribution Analysis Method (BEDAM) for the Estimation of Protein-Ligand Binding Affinities

The Binding Energy Distribution Analysis Method (BEDAM) for the computation of receptor-ligand standard binding free energies with implicit solvation is presented. The method is based on a well established statistical mechanics theory of molecular association. It is shown that, in the context of implicit solvation, the theory is homologous to the test particle method of solvation thermodynamics with the solute-solvent potential represented by the effective binding energy of the protein-ligand complex. Accordingly, in BEDAM the binding constant is computed by means of a weighted integral of the probability distribution of the binding energy obtained in the canonical ensemble in which the ligand is positioned in the binding site but the receptor and the ligand interact only with the solvent continuum. It is shown that the binding energy distribution encodes all of the physical effects of binding. The balance between binding enthalpy and entropy is seen in our formalism as a balance between favorable and unfavorable binding modes which are coupled through the normalization of the binding energy distribution function. An efficient computational protocol for the binding energy distribution based on the AGBNP2 implicit solvent model, parallel Hamiltonian replica exchange sampling and histogram reweighting is developed. Applications of the method to a set of known binders and non-binders of the L99A and L99A/M102Q mutants of T4 lysozyme receptor are illustrated. The method is able to discriminate without error binders from non-binders, and the computed standard binding free energies of the binders are found to be in good agreement with experimental measurements. Analysis of the results reveals that the binding affinities of these systems reflect the contributions from multiple conformations spanning a wide range of binding energies.

Prediction of protein-ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations

Many limitations of current computer-aided drug design arise from the difficulty of reliably predicting the binding affinity of a small molecule to a biological target. There is thus a strong interest in novel computational methodologies that claim predictions of greater accuracy than current scoring functions, and at a throughput compatible with the rapid pace of drug discovery in the pharmaceutical industry. Notably, computational methodologies firmly rooted in statistical thermodynamics have received particular attention in recent years. Yet free energy calculations can be daunting to learn for a novice user because of numerous technical issues and various approaches advocated by experts in the field. The purpose of this article is to provide an overview of the current capabilities of free energy calculations and to discuss the applicability of this technology to drug discovery.

Quantum mechanical/molecular mechanical modeling finds Diels-Alder reactions are accelerated less on the surface of water than in water

Quantum and molecular mechanics calculations for the Diels-Alder reactions of cyclopentadiene with 1,4-naphthoquinone, methyl vinyl ketone, and acrylonitrile have been carried out at the vacuum-water interface and in the gas phase. In conjunction with previous studies of these cycloadditions in dilute solution, a more complete picture of aqueous environmental effects emerges with implications for the origin of observed rate accelerations using heterogeneous aqueous suspensions, "on water" conditions. The pure TIP4P water slab maintains the bulk density and hydrogen-bonding properties in central water layers. The bulk region merges to vacuum over a ca. 5 A band with progressive diminution of the density and hydrogen bonding. The relative free energies of activation and transition structures for the reactions at the interface are found to be intermediate between those calculated in the gas phase and in bulk water; i.e., for the reaction with 1,4-naphthoquinone, the DeltaDeltaG(++) values relative to the gas phase are -3.6 and -7.3 kcal/mol at the interface and in bulk water, respectively. Thus, the results do not support the notion that a water surface is more effective than bulk water for catalysis of such pericyclic reactions. The trend is in qualitative agreement with expectations based on density considerations and estimates of experimental rate constants for the gas phase, a heterogeneous aqueous suspension, and a dilute aqueous solution for the reaction of cyclopentadiene with methyl vinyl ketone. Computed energy pair distributions reveal a uniform loss of 0.5-1.0 hydrogen bond for the reactants and transition states in progressing from bulk water to the vacuum-water interface. Orientational effects are apparent at the surface; e.g., the carbonyl group in the methyl vinyl ketone transition structure is preferentially oriented into the surface. Also, the transition structure for the 1,4-naphthoquinone case is buried more in the surface, and the free energy of activation for this reaction is most similar to the result in bulk water.

Eastern extension of azoles as non-nucleoside inhibitors of HIV-1 reverse transcriptase; cyano group alternatives

Design of non-nucleoside inhibitors of HIV-1 reverse transcriptase is being pursued with the assistance of free energy perturbation (FEP) calculations to predict relative free energies of binding. Extension of azole-containing inhibitors into an 'eastern' channel between Phe227 and Pro236 has led to the discovery of potent and structurally novel derivatives.

Advances in quantum and molecular mechanical (QM/MM) simulations for organic and enzymatic reactions

Application of combined quantum and molecular mechanical (QM/MM) methods focuses on predicting activation barriers and the structures of stationary points for organic and enzymatic reactions. Characterization of the factors that stabilize transition structures in solution and in enzyme active sites provides a basis for design and optimization of catalysts. Continued technological advances allowed for expansion from prototypical cases to mechanistic studies featuring detailed enzyme and condensed-phase environments with full integration of the QM calculations and configurational sampling. This required improved algorithms featuring fast QM methods, advances in computing changes in free energies including free-energy perturbation (FEP) calculations, and enhanced configurational sampling. In particular, the present Account highlights development of the PDDG/PM3 semi-empirical QM method, computation of multi-dimensional potentials of mean force (PMF), incorporation of on-the-fly QM in Monte Carlo (MC) simulations, and a polynomial quadrature method for efficient modeling of proton-transfer reactions. The utility of this QM/MM/MC/FEP methodology is illustrated for a variety of organic reactions including substitution, decarboxylation, elimination, and pericyclic reactions. A comparison to experimental kinetic results on medium effects has verified the accuracy of the QM/MM approach in the full range of solvents from hydrocarbons to water to ionic liquids. Corresponding results from ab initio and density functional theory (DFT) methods with continuum-based treatments of solvation reveal deficiencies, particularly for protic solvents. Also summarized in this Account are three specific QM/MM applications to biomolecular systems: (1) a recent study that clarified the mechanism for the reaction of 2-pyrone derivatives catalyzed by macrophomate synthase as a tandem Michael-aldol sequence rather than a Diels-Alder reaction, (2) elucidation of the mechanism of action of fatty acid amide hydrolase (FAAH), an unusual Ser-Ser-Lys proteolytic enzyme, and (3) the construction of enzymes for Kemp elimination of 5-nitrobenzisoxazole that highlights the utility of QM/MM in the design of artificial enzymes.

Energetics of displacing water molecules from protein binding sites: consequences for ligand optimization

A strategy in drug design is to consider enhancing the affinity of lead molecules with structural modifications that displace water molecules from a protein binding site. Because success of the approach is uncertain, clarification of the associated energetics was sought in cases where similar structural modifications yield qualitatively different outcomes. Specifically, free-energy perturbation calculations were carried out in the context of Monte Carlo statistical mechanics simulations to investigate ligand series that feature displacement of ordered water molecules in the binding sites of scytalone dehydratase, p38-alphaMAP kinase, and EGFR kinase. The change in affinity for a ligand modification is found to correlate with the ease of displacement of the ordered water molecule. However, as in the EGFR example, the binding affinity may diminish if the free-energy increase due to the removal of the bound water molecule is not more than compensated by the additional interactions of the water-displacing moiety. For accurate computation of the effects of ligand modifications, a complete thermodynamic analysis is shown to be needed. It requires identification of the location of water molecules in the protein-ligand interface and evaluation of the free-energy changes associated with their removal and with the introduction of the ligand modification. Direct modification of the ligand in free-energy calculations is likely to trap the ordered molecule and provide misleading guidance for lead optimization.

Prediction of the water content in protein binding sites

An efficient molecular simulation methodology has been developed to determine the positioning of water molecules in the binding site of a protein or protein-ligand complex. Occupancies and absolute binding free energies of water molecules are computed using a statistical thermodynamics approach. The methodology, referred to as Just Add Water Molecules (JAWS), features "theta-water" molecules that can appear and disappear on a binding-site grid. Key approximations render the technique far more efficient than conventional free energy simulations. Testing of JAWS on five diverse examples (neuraminidase, scytalone dehydratase, major urinary protein 1, beta-lactoglobulin, and COX-2) demonstrates its accuracy in locating hydration sites in comparison to results from high-resolution crystal structures. Possible applications include aid in refinement of protein crystal structures, drug lead optimization, setup of docking calculations, and simulations of protein-ligand complexes.

Vancomycin analogs: Seeking improved binding of d-Ala-d-Ala and d-Ala-d-Lac peptides by side-chain and backbone modifications

In order to seek vancomycin analogs with improved performance against VanA and VanB resistant bacterial strains, extensive computational investigations have been performed to examine the effects of side-chain and backbone modifications. Changes in binding affinities for tripeptide cell-wall precursor mimics, Ac(2)-l-Lys-d-Ala-d-Ala (3) and Ac(2)-l-Lys-d-Ala-d-Lac (4), with vancomycin analogs were computed with Monte Carlo/free energy perturbation (MC/FEP) calculations. Replacements of the 3-hydroxyl group in residue 7 with small alkyl or alkoxy groups, which improve contacts with the methyl side chain of the ligands'd-Ala residue, are predicted to be the most promising to enhance binding for both ligands. The previously reported amine backbone modification as in 5 is shown to complement the hydrophobic modifications for binding monoacetylated tripeptides. In addition, replacement of the hydroxyl groups in residues 5 and 7 by fluorine is computed to have negligible impact on binding the tripeptides, though it may be pharmacologically advantageous.

Efficient drug lead discovery and optimization

During the 1980s, advances in the abilities to perform computer simulations of chemical and biomolecular systems and to calculate free energy changes led to the expectation that such methodology would soon show great utility for guiding molecular design. Important potential applications included design of selective receptors, catalysts, and regulators of biological function including enzyme inhibitors. This time also saw the rise of high-throughput screening and combinatorial chemistry along with complementary computational methods for de novo design and virtual screening including docking. These technologies appeared poised to deliver diverse lead compounds for any biological target. As with many technological advances, realization of the expectations required significant additional effort and time. However, as summarized here, striking success has now been achieved for computer-aided drug lead generation and optimization. De novo design using both molecular growing and docking are illustrated for lead generation, and lead optimization features free energy perturbation calculations in conjunction with Monte Carlo statistical mechanics simulations for protein-inhibitor complexes in aqueous solution. The specific applications are to the discovery of non-nucleoside inhibitors of HIV reverse transcriptase (HIV-RT) and inhibitors of the binding of the proinflammatory cytokine MIF to its receptor CD74. A standard protocol is presented that includes scans for possible additions of small substituents to a molecular core, interchange of heterocycles, and focused optimization of substituents at one site. Initial leads with activities at low-micromolar concentrations have been advanced rapidly to low-nanomolar inhibitors.

Computations of standard binding free energies with molecular dynamics simulations

An increasing number of studies have reported computations of the standard (absolute) binding free energy of small ligands to proteins using molecular dynamics (MD) simulations and explicit solvent molecules that are in good agreement with experiments. This encouraging progress suggests that physics-based approaches hold the promise of making important contributions to the process of drug discovery and optimization in the near future. Two types of approaches are principally used to compute binding free energies with MD simulations. The most widely known is the alchemical double decoupling method, in which the interaction of the ligand with its surroundings are progressively switched off. It is also possible to use a potential of mean force (PMF) method, in which the ligand is physically separated from the protein receptor. For both of these computational approaches, restraining potentials may be activated and released during the simulation for sampling efficiently the changes in translational, rotational, and conformational freedom of the ligand and protein upon binding. Because such restraining potentials add bias to the simulations, it is important that their effects be rigorously removed to yield a binding free energy that is properly unbiased with respect to the standard state. A review of recent results is presented, and differences in computational methods are discussed. Examples of computations with T4-lysozyme mutants, FKBP12, SH2 domain, and cytochrome P450 are discussed and compared. Remaining difficulties and challenges are highlighted.

Chemogenomics with protein secondary-structure mimetics

During molecular recognition of proteins in biological systems, helices, reverse turns, and beta-sheets are dominant motifs. Often there are therapeutic reasons for blocking such recognition sites, and significant progress has been made by medicinal chemists in the design and synthesis of semirigid molecular scaffolds on which to display amino acid side chains. The basic premise is that preorganization of the competing ligand enhances the binding affinity and potential selectivity of the inhibitor. In this chapter, current progress in these efforts is reviewed.

Vancomycin resistance: modeling backbone variants with D-Ala-D-Ala and D-Ala-D-Lac peptides

To seek vancomycin analogs with broader antibacterial activity, effects of backbone modifications for the agylcon 2 on binding with D-Ala-D-Ala- and D-Ala-D-Lac-containing peptides were investigated by Monte Carlo/free energy perturbation (MC/FEP) calculations. The experimental trend in binding affinities for 2 with three tripeptides was well reproduced. Possible modifications of the peptide bond between residues 4 and 5 were then considered, specifically for conversion of the OCNH linkage to CH(2)NH(2)(+) (6), FCCH (7), HCCH (8), and HNCO (9). The MC/FEP results did not yield binding improvements for 7, 8, and 9, though the fluorovinyl replacement is relatively benign. The previously reported analog 6 remains as the only variant that exhibits improved affinity for the D-Ala-D-Lac sequence and acceptable affinity for the D-Ala-D-Ala sequence.

Optimization of azoles as anti-human immunodeficiency virus agents guided by free-energy calculations

Efficient optimization of an inactive 2-anilinyl-5-benzyloxadiazole core has been guided by free energy perturbation (FEP) calculations to provide potent non-nucleoside inhibitors of human immunodeficiency virus (HIV) reverse transcriptase (NNRTIs). An FEP "chlorine scan" was performed to identify the most promising sites for substitution of aryl hydrogens. This yielded NNRTIs 8 and 10 with activities (EC50) of 820 and 310 nM for protection of human T-cells from infection by wild-type HIV-1. FEP calculations for additional substituent modifications and change of the core heterocycle readily led to oxazoles 28 and 29, which were confirmed as highly potent anti-HIV agents with activities in the 10-20 nM range. The designed compounds were also monitored for possession of desirable pharmacological properties by use of additional computational tools. Overall, the trends predicted by the FEP calculations were well borne out by the assay results. FEP-guided lead optimization is confirmed as a valuable tool for molecular design including drug discovery; chlorine scans are particularly attractive since they are both straightforward to perform and highly informative.