Linear Interaction Energy Method Research Articles

Prediction of the binding modes between BB-83698 and peptide deformylase from Bacillus stearothermophilus by docking and molecular dynamics simulation

BB-83698 is a first potent inhibitor of peptide deformylase in this novel class to enter clinical trials. In this study, automated docking, molecular dynamics simulation and binding free energy calculations with the linear interaction energy (LIE) method are first applied to investigate the binding of BB-83698 to the peptide deformylase from Bacillus stearothermophilus. The lowest docking energy structure from each cluster is selected as different representative binding modes. Compared with the experimental data, the results show that the binding of BB-83698 in Mode 1 is the most stable, with a binding free energy of − 41.35 kJ/mol. The average structure of the Mode 1 complex suggests that inhibitor interacts with Ile59 and Gly109 by hydrogen bond interaction and with Pro47, Pro57, Ile59 and Leu146 by hydrophobic interaction are essential for the activity of BB-83698. Mode 2 represents a new binding mode. Additionally, if the hydrophilic group is introduced to the benzo-[1,3]-dioxole ring, the binding affinity of BB-83698 to the peptide deformylase from B. stearothermophilus will be greatly improved.

Discovery of Kinase Inhibitors by High-Throughput Docking and Scoring Based on a Transferable Linear Interaction Energy Model

The linear interaction energy method with continuum electrostatics (LIECE) is evaluated in depth on five kinases. The two multiplicative coefficients for the van der Waals energy and electrostatic free energy are shown to be transferable among different kinases. Moreover, good enrichment factors are obtained for a library of 40375 diverse compounds seeded with 73 known inhibitors of CDK2. Therefore, a general two-parameter LIECE model for kinases is derived by combining large data sets of inhibitors of CDK2, Lck, and p38. This two-parameter model is cross-validated on two kinases not used for fitting; it shows an average error of about 1.5 kcal/mol for the prediction of absolute binding affinity of 37 and 128 known inhibitors of EphB4 and EGFR, respectively. High-throughput docking and ranking by two-parameter LIECE models are shown to be able to identify novel low-micromolar EphB4 and CDK2 inhibitors of low-molecular weight (< or =355 g/mol).

Theoretical Calculations of the Catalytic Triad in Short-Chain Alcohol Dehydrogenases/Reductases

Three highly conserved active site residues (Ser, Tyr, and Lys) of the family of short-chain alcohol dehydrogenases/reductases (SDRs) were demonstrated to be essential for catalytic activity and have been denoted the catalytic triad of SDRs. In this study computational methods were adopted to study the ionization properties of these amino acids in SDRs from Drosophila melanogaster and Drosophila lebanonensis. Three enzyme models, with different ionization scenarios of the catalytic triad that might be possible when inhibitors bind to the enzyme cofactor complex, were constructed. The binding of the two alcohol competitive inhibitors were studied using automatic docking by the Internal Coordinate Mechanics program, molecular dynamic (MD) simulations with the AMBER program package, calculation of the free energy of ligand binding by the linear interaction energy method, and the hydropathic interactions force field. The calculations indicated that deprotonated Tyr acts as a strong base in the binary enzyme-NAD + complex. Molecular dynamic simulations for 5 ns confirmed that deprotonated Tyr is essential for anchoring and orientating the inhibitors at the active site, which might be a general trend for the family of SDRs. The findings here have implications for the development of therapeutically important SDR inhibitors.

Ligand Binding to the Voltage-Gated Kv1.5 Potassium Channel in the Open State—Docking and Computer Simulations of a Homology Model

The binding of blockers to the human voltage-gated Kv1.5 potassium ion channel is investigated using a three-step procedure consisting of homology modeling, automated docking, and binding free energy calculations from molecular dynamics simulations, in combination with the linear interaction energy method. A reliable homology model of Kv1.5 is constructed using the recently published crystal structure of the Kv1.2 channel as a template. This model is expected to be significantly more accurate than earlier ones based on less similar templates. Using the three-dimensional homology model, a series of blockers with known affinities are docked into the cavity of the ion channel and their free energies of binding are calculated. The predicted binding free energies are in very good agreement with experimental data and the binding is predicted to be mainly achieved through nonpolar interactions, whereas the relatively small differences in the polar contribution determine the specificity. Apart from confirming the importance of residues V505, I508, V512, and V516 for ligand binding in the cavity, the results also show that A509 and P513 contribute significantly to the nonpolar binding interactions. Furthermore, we find that pharmacophore models based only on optimized free ligand conformations may not necessarily capture the geometric features of ligands bound to the channel cavity. The calculations herein give a detailed structural and energetic picture of blocker binding to Kv1.5 and this model should thus be useful for further ligand design efforts.

Improving the Accuracy of the Linear Interaction Energy Method for Solvation Free Energies.

A linear response method for estimating the free energy of solvation is presented and validated using explicit solvent molecular dynamics, thermodynamic perturbation calculations, and experimental data. The electrostatic contribution to the solvation free energy is calculated using a linear response estimate, which is obtained by comparison to the free energy calculated using thermodynamic perturbation. Systematic deviations from the value of (1)/2 in the potential energy scaling factor are observed for some types of compounds, and these are taken into account by introducing specific coefficients for different chemical groups. The derived model reduces the rms error of the linear response estimate significantly from 1.6 to 0.3 kcal/mol on a training set of 221 molecules used to parametrize the model and from 3.7 to 1.3 kcal/mol on a test set of 355 molecules that were not used in the derivation of the model. The total solvation free energy is estimated by combining the derived model with an empirical size dependent term for predicting the nonpolar contribution. Using this model, the experimental hydration free energies for 192 molecules are reproduced with an rms error of 1.1 kcal/mol. The use of LIE in simplified binding free energy calculations to predict protein-ligand binding free energies is also discussed.

Calculation of binding affinities of HIV-1 RT and β-secretase inhibitors using the linear interaction energy method with explicit and continuum solvation approaches

The linear interaction energy (LIE) approach has been applied to estimate the binding free energies of representative sets of HIV-1 RT and beta-Secretase inhibitors, using both molecular dynamics (MD) and tethered energy minimization sampling protocols with the OPLS-AA potential, using a range of solvation methodologies. Generalized Born (GB), 'shell' and periodic boundary condition (PBC) solvation were used, the latter with reaction field (RF) electrostatics. Poisson-Boltzmann (PB) and GB continuum electrostatics schemes were applied to the simulation trajectories for each solvation type to estimate the electrostatic ligand-water interaction energy in both the free and bound states. Reasonable agreement of the LIE predictions was obtained with respect to experimental binding free energy estimates for both systems: for instance, 'PB' fits on MD trajectories carried out with PBC solvation and RF electrostatics led to models with standard errors of 1.11 and 1.03 kcal mol(-1) and coefficients of determination, r (2) of 0.76 and 0.75 for the HIV-1 RT and beta-Secretase sets. However, it was also found that results from MD sampling using PBC solvation provided only slightly better fits than from simulations using shell or Born solvation or tethered energy minimization sampling.

Computational inhibitor design against malaria plasmepsins.

Plasmepsins are aspartic proteases involved in the degradation of the host cell hemoglobin that is used as a food source by the malaria parasite. Plasmepsins are highly promising as drug targets, especially when combined with the inhibition of falcipains that are also involved in hemoglobin catabolism. In this review, we discuss the mechanism of plasmepsins I-IV in view of the interest in transition state mimetics as potential compounds for lead development. Inhibitor development against plasmepsin II as well as relevant crystal structures are summarized in order to give an overview of the field. Application of computational techniques, especially binding affinity prediction by the linear interaction energy method, in the development of malarial plasmepsin inhibitors has been highly successful and is discussed in detail. Homology modeling and molecular docking have been useful in the current inhibitor design project, and the combination of such methods with binding free energy calculations is analyzed.

P2Y1 Antagonists: Combining Receptor-Based Modeling and QSAR for a Quantitative Prediction of the Biological Activity Based on Consensus Scoring

P2Y1 is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y1 homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.

Calculation of Protein-Ligand Binding Affinities

Accurate methods of computing the affinity of a small molecule with a protein are needed to speed the discovery of new medications and biological probes. This paper reviews physics-based models of binding, beginning with a summary of the changes in potential energy, solvation energy, and configurational entropy that influence affinity, and a theoretical overview to frame the discussion of specific computational approaches. Important advances are reported in modeling protein-ligand energetics, such as the incorporation of electronic polarization and the use of quantum mechanical methods. Recent calculations suggest that changes in configurational entropy strongly oppose binding and must be included if accurate affinities are to be obtained. The linear interaction energy (LIE) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods are analyzed, as are free energy pathway methods, which show promise and may be ready for more extensive testing. Ultimately, major improvements in modeling accuracy will likely require advances on multiple fronts, as well as continued validation against experiment.

In Silico Binding Free Energy Predictability by Using the Linear Interaction Energy (LIE) Method: Bromobenzimidazole CK2 Inhibitors as a Case Study

Protein kinase CK2 is essential for cell viability, and its control regards a broad series of cellular events such as gene expression, RNA, and protein synthesis. Evidence of its involvement in tumor development and viral replication indicates CK2 as a potential target of antineoplastic and antiviral drugs. In this study the Linear Interaction Energy (LIE) Method with the Surface Generalized Born (SGB) continuum solvation model was used to study several bromobenzimidazole CK2 inhibitors. This methodology, developed by Aqvist, finds a plausible compromise between accuracy and computational speed in evaluating binding free energy (DeltaGbind) values. In this study, two different free binding energy models, named "CK2scoreA" and "CK2scoreB", were developed using 22 inhibitors as the training set in a stepwise approach useful to appropriately select both the tautomeric form and the starting binding position of each inhibitor. Both models are statistically acceptable. Indeed, the better one is characterized by a correlation coefficient (r2) of 0.81, and the predictive accuracy was 0.65 kcal/mol. The corresponding validation, using an external test set of 16 analogs, showed a correlation coefficient (q2) of 0.68 and a prediction root-mean-square error of 0.78 kcal/mol. In this case, the LIE approach has been proved to be an efficient methodology to rationalize the difference of activity, the key interactions, and the different possible binding modes of this specific class of potent CK2 inhibitors.

Energetics of Codon−Anticodon Recognition on the Small Ribosomal Subunit

Recent crystal structures of the small ribosomal subunit have made it possible to examine the detailed energetics of codon recognition on the ribosome by computational methods. The binding of cognate and near-cognate anticodon stem loops to the ribosome decoding center, with mRNA containing the Phe UUU and UUC codons, are analyzed here using explicit solvent molecular dynamics simulations together with the linear interaction energy (LIE) method. The calculated binding free energies are in excellent agreement with experimental binding constants and reproduce the relative effects of mismatches in the first and second codon position versus a mismatch at the wobble position. The simulations further predict that the Leu2 anticodon stem loop is about 10 times more stable than the Ser stem loop in complex with the Phe UUU codon. It is also found that the ribosome significantly enhances the intrinsic stability differences of codon-anticodon complexes in aqueous solution. Structural analysis of the simulations confirms the previously suggested importance of the universally conserved nucleotides A1492, A1493, and G530 in the decoding process.

Inhibitor Binding to the Plasmepsin IV Aspartic Protease from Plasmodium falciparum

Plasmepsin IV (Plm IV) is one of the aspartic proteases present in the food vacuole of the malaria parasite Plasmodium falciparum involved in host hemoglobin degradation by the parasite. Using a series of previously synthesized plasmepsin inhibitors [Ersmark, K., et al. (2005) J. Med. Chem. 48, 6090-106], we report here experimental data and theoretical analysis of their inhibitory activity toward Plm IV. All compounds share a 1,2-dihydroxyethylene unit as the transition state mimic. They possess symmetric P1 and P1' side chains and either a diacylhydrazine, a five-membered oxadiazole ring, or a retroamide at the P2 and P2' positions. Experimental binding affinities are compared to those predicted by the linear interaction energy (LIE) method and an empirical scoring function, using both a crystal structure and a homology model for the enzyme. Molecular dynamics (MD) simulations of the modeled complexes allow a rational interpretation of the structural determinants for inhibitor binding. A ligand bearing a P2 and P2' symmetric oxadiazole which is devoid of amide bonds is identified both experimentally and theoretically as the most potent inhibitor of Plm IV. For the P2 and P2' asymmetric compounds, the results are consistent with earlier predictions regarding the mode of binding of this class of inhibitors to Plm II. Theoretical estimation of selectivity for some compounds is also reported. Significant features of the Plm IV binding pocket are discussed in comparison to related enzymes, and the results obtained here should be helpful for further optimization of inhibitors.

Are Automated Molecular Dynamics Simulations and Binding Free Energy Calculations Realistic Tools in Lead Optimization? An Evaluation of the Linear Interaction Energy (LIE) Method

An extensive evaluation of the linear interaction energy (LIE) method for the prediction of binding affinity of docked compounds has been performed, with an emphasis on its applicability in lead optimization. An automated setup is presented, which allows for the use of the method in an industrial setting. Calculations are performed for four realistic examples, retinoic acid receptor gamma, matrix metalloprotease 3, estrogen receptor alpha, and dihydrofolate reductase, focusing on different aspects of the procedure. The obtained LIE models are evaluated in terms of the root-mean-square (RMS) errors from experimental binding free energies and the ability to rank compounds appropriately. The results are compared to the best empirical scoring function, selected from a set of 10 scoring functions. In all cases, good LIE models can be obtained in terms of free-energy RMS errors, although reasonable ranking of the ligands of dihydrofolate reductase proves difficult for both the LIE method and scoring functions. For the other proteins, the LIE model results in better predictions than the best performing scoring function. These results indicate that the LIE approach, as a tool to evaluate docking results, can be a valuable asset in computational lead optimization programs.

Continuum Solvation Models in the Linear Interaction Energy Method

The linear interaction energy (LIE) method in combination with two different continuum solvent models has been applied to calculate protein-ligand binding free energies for a set of inhibitors against the malarial aspartic protease plasmepsin II. Ligand-water interaction energies are calculated from both Poisson-Boltzmann (PB) and Generalized Born (GB) continuum models using snapshots from explicit solvent simulations of the ligand and protein-ligand complex. These are compared to explicit solvent calculations, and we find close agreement between the explicit water and PB solvation models. The GB model overestimates the change in solvation energy, and this is caused by consistent underestimation of the effective Born radii in the protein-ligand complex. The explicit solvent LIE calculations and LIE-PB, with our standard parametrization, reproduce absolute experimental binding free energies with an average unsigned error of 0.5 and 0.7 kcal/mol, respectively. The LIE-GB method, however, requires a constant offset to approach the same level of accuracy.

Free Energy Simulations of Uncatalyzed DNA Replication Fidelity: Structure and Stability of T·G and dTTP·G Terminal DNA Mismatches Flanked by a Single Dangling Nucleotide

A reference system for DNA replication fidelity was studied by free energy perturbation (FEP) and linear interaction energy (LIE) methods. The studied system included a hydrated duplex DNA with the 5'-CG dangling end of the templating strand, and dCTP4-.Mg2+ or dTTP4-.Mg2+ inserted opposite the dangling G to form a correct (i.e., Watson-Crick) or incorrect (i.e., wobble) base pair, respectively. The average distance between the 3'-terminal oxygen of the primer strand and the alpha-phosphorus of dNTP was found to be 0.2 A shorter for the correct base pair than for the incorrect base pair. Binding of the incorrect dNTP was found to be disfavored by 0.4 kcal/mol relative to the correct dNTP. We estimated that improved binding and more near-attack configurations sampled by the correct base pair should translate in aqueous solution and in the absence of DNA polymerase into a six times faster rate for the incorporation of the correct dNTP into DNA. The accuracy of the calculated binding free energy difference was verified by examining the relative free energy for melting duplex DNA containing GC and GT terminal base pairs flanked by a 5' dangling C. The calculated LIE and FEP free energies of 1.7 and 1.1 kcal/mol, respectively, compared favorably with the experimental estimate of 1.4 kcal/mol obtained using the nearest neighbor parameters. To decompose the calculated free energies into additive electrostatic and van der Waals contributions and to provide a set of rigorous theoretical data for the parametrization of the LIE method, we suggested a variant of the FEP approach, for which we coined a binding-relevant free energy (BRFE) acronym. BRFE approach is characterized by its unique perturbation pathway and by its exclusion of the intramolecular energy of a rigid part of the ligand from the total potential energy.

A Spectral and Molecular Dynamics Simulation Study of β-Cyclodextrin Inclusion Complexes with Solvatochromic Dyes Derived from Barbituric Acid

The linear interaction energy (LIE) method was applied to the molecular-dynamics-simulation study of the interactions in water between β-cyclodextrin and two solvatochromic dyes derived from N,N-dimethylbarbituric acid, the 5-[(4-dimethylaminophenyl)methylene]- (1), and the 5-[bis(4-dimethylaminophenyl) methylene]-2,4,6-(1H,3H,5H)-pyrimidinetrione (2). Both compounds interact with β-CD by insertion of an aminophenyl ring into its hydrophobic cavity. Theoretical and spectral evidences point to a greater association of compound (1) than dye (2) with cyclodextrin in water.

Predicting proteinase specificities from free energy calculations

The role of the primary binding residue (P1) in complexes between three different subtilases (subtilisin Carlsberg, thermitase and proteinase K) and their canonical protein inhibitor eglin c have been studied by free energy calculations. Based on the crystal structures of eglin c in complex with subtilisin Carlsberg and thermitase, and a homology model of the eglin c–proteinase K complex, a total of 57 mutants have been constructed and docked into their host proteins. The binding free energy was then calculated using molecular dynamics (MD) simulations combined with the linear interaction energy (LIE) method for all complexes differing only in the nature of the amino acid at the P1 position. LIE calculations for 19 different complexes for each subtilase were thus carried out excluding proline. The effects of substitutions at the P1 position on the binding free energies are found to be very large, and positively charged residues (Arg, Lys and His) are particularly deleterious for all three enzymes. The charged variants of the acidic side chains are found to bind more favorably as compared to their protonated states in all three subtilases. Furthermore, hydrophobic amino acids are accommodated most favorably at the S1-site in all three enzymes. Comparison of the three series of binding free energies shows only minor differences in the 19 computed relative binding free energies among these subtilases. This is further reflected in the correlation coefficient between the 23 relative binding free energies obtained, including the possible protonation states of ionizable side chains, but excluding the P1 Pro, for subtilisin Carlsberg versus thermitase (0.95), subtilisin versus proteinase K (0.94) and thermitase versus proteinase K (0.96).

Calculations of solute and solvent entropies from molecular dynamics simulations

The translational, rotational and conformational (vibrational) entropy contributions to ligand-receptor binding free energies are analyzed within the standard formulation of statistical thermodynamics. It is shown that the partitioning of the binding entropy into different components is to some extent arbitrary, but an appropriate method to calculate both translational and rotational entropy contributions to noncovalent association is by estimating the configurational volumes of the ligand in the bound and free states. Different approaches to calculating solute entropies using free energy perturbation calculations, configurational volumes based on root-mean-square fluctuations and covariance matrix based quasiharmonic analysis are illustrated for some simple molecular systems. Numerical examples for the different contributions demonstrate that theoretically derived results are well reproduced by the approximations. Calculation of solvent entropies, either using total potential energy averages or van't Hoff plots, are carried out for the case of ion solvation in water. Although convergence problems will persist for large and complex simulation systems, good agreement with experiment is obtained here for relative and absolute ion hydration entropies. We also outline how solvent and solute entropic contributions are taken into account in empirical binding free energy calculations using the linear interaction energy method. In particular it is shown that empirical scaling of the nonpolar intermolecular ligand interaction energy effectively takes into account size dependent contributions to the binding free energy.

Molecular insight into pseudolysin inhibition using the MM-PBSA and LIE methods

Pseudolysin, the extracellullar elastase of Pseudomonas aeruginosa (EC: 3.4.24.26) plays an important role in the pathogenesis of P. aeruginosa infections. In the present study, molecular dynamics simulations and theoretical affinity predictions were used to gain molecular insight into pseudolysin inhibition. Four low molecular weight inhibitors were docked at their putative binding sites and molecular dynamics (MD) simulations were performed for 5.0 ns, and the free energy of binding was calculated by the linear interaction energy method. The number and the contact surface area of stabilizing hydrophobic, aromatic, and hydrogen bonding interactions appears to reflect the affinity differences between the inhibitors. The proteinaceous inhibitor, Streptomyces metalloproteinase inhibitor (SMPI) was docked in three different binding positions and MD simulations were performed for 3.0 ns. The MD trajectories were used for molecular mechanics-Poisson–Boltzmann surface area analysis of the three binding positions. Computational alanine scanning of the average pseudolysin–SMPI complexes after MD revealed residues at the pseudolysin–SMPI interface giving the main contribution to the free energy of binding. The calculations indicated that SMPI interacts with pseudolysin via the rigid active site loop, but that also contact sites outside this loop contribute significantly to the free energy of association.

Macrocyclic inhibitors of the malarial aspartic proteases plasmepsin I, II, and IV

The first macrocyclic inhibitor of the Plasmodium falciparum aspartic proteases plasmepsin I, II, and IV with considerable selectivity over the human aspartic protease cathepsin D has been identified. A series of macrocyclic compounds were designed and synthesized. Cyclizations were accomplished using ring-closing metathesis with the second generation Grubbs catalyst. These compounds contain either a 13-membered or a 16-membered macrocycle and incorporate a 1,2-dihydroxyethylene as transition state mimicking unit. The binding mode of this new class of compounds was predicted with automated docking and molecular dynamics simulations, with an estimation of the binding affinities through the linear interaction energy (LIE) method.