Binding free energy contributions of interfacial waters in HIV-1 protease/inhibitor complexes

Water molecules are commonly observed in crystal structures of protein-ligand complexes where they mediate protein-ligand binding. It is of considerable theoretical and practical importance to determine quantitatively the individual free energy contributions of these interfacial water molecules to protein-ligand binding and to elucidate factors that influence them. The double-decoupling free energy molecular dynamics simulation method has been used to calculate the binding free energy contribution for each of the four interfacial water molecules observed in the crystal structure of HIV-1 protease complexed with KNI-272, a potent inhibitor. While two of these water molecules contribute significantly to the binding free energy, the other two have close to zero contribution. It was further observed that the protonation states of two catalytic aspartate residues, Asp25 and Asp125, strongly influence the free energy contribution of a conserved water molecule Wat301 and that different inhibitors significantly influence the free energy contribution of Wat301. Our results have important implications on our understanding of the role of interfacial water molecules in protein-ligand binding and to structure-based drug design aimed at incorporating these interfacial water molecules into ligands.     

Classification of water molecules in protein binding sites

Water molecules play a crucial role in mediating the interaction between a ligand and a macromolecular receptor. An understanding of the nature and role of each water molecule in the active site of a protein could greatly increase the efficiency of rational drug design approaches: if the propensity of a water molecule for displacement can be determined, then synthetic effort may be most profitably applied to the design of specific ligands with the displacement of this water molecule in mind. In this paper, a thermodynamic analysis of water molecules in the binding sites of six proteins, each complexed with a number of inhibitors, is presented. Two classes of water molecules were identified: those conserved and not displaced by any of the ligands, and those that are displaced by some ligands. The absolute binding free energies of 54 water molecules were calculated using the double decoupling method, with replica exchange thermodynamic integration in Monte Carlo simulations. It was found that conserved water molecules are on average more tightly bound than displaced water molecules. In addition, Bayesian statistics is used to calculate the probability that a particular water molecule may be displaced by an appropriately designed ligand, given the calculated binding free energy of the water molecule. This approach therefore allows the numerical assessment of whether or not a given water molecule should be targeted for displacement as part of a rational drug design strategy.     

An estimation method of binding free energy in terms of ABEEMσπ/MM and continuum electrostatics fused into LIE method

A method is proposed for the estimation of absolute binding free energy of interaction between proteins and ligands. The linear interaction energy method is combined with atom‐bond electronegativity equalization method at σπ level Force field (fused into molecular mechanics) and generalized Born continuum model calculation of electrostatic solvation for the estimation of the absolute free energy of binding. The parameters of this method are calibrated by using a training set of 24 HIV‐1 protease–inhibitor complexes (PDB entry 1AAQ). A correlation coefficient of 0.93 was obtained with a root mean square deviation of 0.70 kcal mol^?1. This approach is further tested on seven inhibitor and protease complexes, and it provides small root mean square deviation between the calculated binding free energy and experimental binding free energy without reparametrization. By comparing the radii of gyration and the hydrogen bond distances between ligand and protein of three training model molecules, the consistent comparison result of binding free energy is obtained. It proves that this method of calculating the binding free energy with appropriate structural analysis can be applied to quickly assess new inhibitors of HIV‐1 proteases. To test whether the parameters of this method can apply to other drug targets, we have validated this method for the drug target cyclooxygenase‐2. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011     

Accurate predictions of nonpolar solvation free energies require explicit consideration of binding-site hydration

Continuum solvation methods are frequently used to increase the efficiency of computational methods to estimate free energies. In this paper, we have evaluated how well such methods estimate the nonpolar solvation free-energy change when a ligand binds to a protein. Three different continuum methods at various levels of approximation were considered, viz., the polarized continuum model (PCM), a method based on cavity and dispersion terms (CD), and a method based on a linear relation to the solvent-accessible surface area (SASA). Formally rigorous double-decoupling thermodynamic integration was used as a benchmark for the continuum methods. We have studied four protein-ligand complexes with binding sites of varying solvent exposure, namely the binding of phenol to ferritin, a biotin analogue to avidin, 2-aminobenzimidazole to trypsin, and a substituted galactoside to galectin-3. For ferritin and avidin, which have relatively hidden binding sites, rather accurate nonpolar solvation free energies could be obtained with the continuum methods if the binding site is prohibited to be filled by continuum water in the unbound state, even though the simulations and experiments show that the ligand replaces several water molecules upon binding. For the more solvent exposed binding sites of trypsin and galectin-3, no accurate continuum estimates could be obtained, even if the binding site was allowed or prohibited to be filled by continuum water. This shows that continuum methods fail to give accurate free energies on a wide range of systems with varying solvent exposure because they lack a microscopic picture of binding-site hydration as well as information about the entropy of water molecules that are in the binding site before the ligand binds. Consequently, binding affinity estimates based upon continuum solvation methods will give absolute binding energies that may differ by up to 200 kJ/mol depending on the method used. Moreover, even relative energies between ligands with the same scaffold may differ by up to 75 kJ/mol. We have tried to improve the continuum solvation methods by adding information about the solvent exposure of the binding site or the hydration of the binding site, and the results are promising at least for this small set of complexes.     

Semiempirical calculations of binding enthalpy for protein–ligand complexes

A systematic semiempirical quantum mechanical study of the interactions between proteins and ligands has been performed to determine the ability of this approach for the accurate estimation of the enthalpic contribution to the binding free energy of the protein–ligand systems. This approach has been applied for eight test protein–ligand complexes with experimentally known binding enthalpies. The calculations were performed using the semiempirical PM3 approach incorporated in the MOPAC 97, ZAVA originally elaborated in Algodign, and MOPAC 2002 with MOZYME facility packages. Special attention was paid to take into account structural water molecules, which were located in the protein–ligand binding site. It was shown that the results of binding enthalpy calculations fit experimental data within ～2 kcal/mol in the presented approach. © 2003 Wiley Periodicals, Inc. Int J Quantum Chem, 2004     

Efficient free energy calculations on small molecule host-guest systems - a combined linear interaction energy/one-step perturbation approach

Two efficient methods to calculate binding affinities of ligands with proteins have been critically evaluated by using sixteen small ligand host-guest complexes. It is shown that both the one-step (OS) perturbation method and the linear interaction energy (LIE) method have complementing strengths and weaknesses and can be optimally combined in a new manner. The OS method has a sound theoretical basis to address the free energy of cavity formation, whereas the LIE approach is more versatile and efficient to calculate the free energy of adding charges to such cavities. The off-term, which is neglected in the original LIE equation, can be calculated without additional costs from the OS, offering a powerful synergy between the two methods. The LIE/OS approach presented here combines the best of two worlds and for the model systems studied here, is more accurate than and as efficient as the original methods. It has a sound theoretical background and no longer requires any empirical parameters. The method appears very well suited for application in lead-optimization programmes in drug research, where the structure and dynamics of a series of molecules is of interest, together with an accurate calculation of the binding free energy.     

<Emphasis Type="Italic">In-silico</Emphasis> Screening using Flexible Ligand Binding Pockets: A Molecular Dynamics-based Approach

Summary In-silico screening of flexible ligands against flexible ligand binding pockets (LBP) is an emerging approach in structure-based drug discovery. Here, we describe a molecular dynamics (MD) based docking approach to investigate the influence on the high-throughput in-silico screening of small molecules against flexible ligand binding pockets. In our approach, an ensemble of 51 energetically favorable structures of the LBP of human estrogen receptor α (hERα) were collected from 3 ns MD simulations. In-silico screening of 3500 endocrine disrupting compounds against these flexible ligand binding pockets resulted in thousands of ER–ligand complexes of which 582 compounds were unique. Detailed analysis of MD generated structures showed that only 17 of the LBP residues significantly contribute to the overall binding pocket flexibility. Using the flexible LBP conformations generated, we have identified 32 compounds that bind better to the flexible ligand-binding pockets compared to the crystal structure. These compounds, though chemically divergent, are structurally similar to the natural hormone. Our MD-based approach in conjunction with grid–based distributed computing could be applied routinely for in-silico screening of large databases against any given target.     

RNA and the Small Molecule World

A key role in essential cellular processes is played by RNA molecules, and these are attractive targets for drug design. The functional diversity of RNA can be attributed to the sophisticated three-dimensional structures it assumes. These intricate folds create potential binding pockets for ions, low molecular weight ligands, and proteins. Recent experiments have demonstrated that small molecules such as tobramycin ( 1 ) can regulate gene expression in living cells through specific interactions with a messenger RNA (mRNA).     

Simple and Rapid Hollow Fiber Liquid Phase Microextraction Followed by High Performance Liquid Chromatography Method for Determination of Drug-protein Binding

A method was established using hollow fiber-liquid phase microextraction(HF-LPME) followed by high performance liquid chromatography(HPLC) to determine the concentration of the free(unbound) drug in the solution of the drug and protein. Measurements of drug-protein binding ratios and free drug concentrations were then analyzed with the Klotz equation to determine the equilibrium binding constant and number of binding sites for drug-protein interaction. The optimized method allows one to perform the efficient extraction and separation of free drug from protein-bound drug, protein, and other interfering substances. This approach was used to characterize the binding of the anticholinergic drugs atropine sulfate and scopolamine hydrobromide to proteins in human plasma and bovine serum albumin(BSA). The results demonstrate the utility of HF-LPME method for measuring free drug concentrations in protein-drug mixtures and determining the protein binding parameters of a pharmacologically important class of drugs.     

Structure-based identification of small molecule binding sites using a free energy model

We separately have shown that the maximal druglike affinity of a given binding site on a protein can be calculated on the basis of the binding-site structure alone by using a desolvation-based free energy model along with the notion that druglike ligands fall into certain physiochemical property ranges. Here, we present an approach where we reformulate the calculated druggability affinity as an additive free energy to facilitate the searching of whole protein surfaces for druglike binding sites. The highest-scoring patches in many cases represent known ligand-binding sites for druggable targets, but not for difficult targets. This approach differs from other approaches in that it does not simply identify pockets with the greatest volume but instead identifies pockets that are likely to be amenable to druglike small-molecule binding. Combining the method with a functional residue prediction method called SCA (statistical coupling analysis) results in the prediction of potentially druggable allosteric binding sites on p38alpha kinase.     

Electrostatics of ligand binding: parametrization of the generalized Born model and comparison with the Poisson-Boltzmann approach

An accurate and fast evaluation of the electrostatics in ligand-protein interactions is crucial for computer-aided drug design. The pairwise generalized Born (GB) model, a fast analytical method originally developed for studying the solvation of organic molecules, has been widely applied to macromolecular systems, including ligand-protein complexes. However, this model involves several empirical scaling parameters, which have been optimized for the solvation of organic molecules, peptides, and nucleic acids but not for energetics of ligand binding. Studies have shown that a good solvation energy does not guarantee a correct model of solvent-mediated interactions. Thus, in this study, we have used the Poisson-Boltzmann (PB) approach as a reference to optimize the GB model for studies of ligand-protein interactions. Specifically, we have employed the pairwise descreening approximation proposed by Hawkins et al.(1) for GB calculations and DelPhi for PB calculations. The AMBER all-atom force field parameters have been used in this work. Seventeen protein-ligand complexes have been used as a training database, and a set of atomic descreening parameters has been selected with which the pairwise GB model and the PB model yield comparable results on atomic Born radii, the electrostatic component of free energies of ligand binding, and desolvation energies of the ligands and proteins. The energetics of the 15 test complexes calculated with the GB model using this set of parameters also agrees well with the energetics calculated with the PB method. This is the first time that the GB model has been parametrized and thoroughly compared with the PB model for the electrostatics of ligand binding.     

Top-down characterization of proteins and drug-protein complexes using nanoelectrospray tandem mass spectrometry

We report a 'top-down' approach for characterization of proteins, and identification of binding sites in protein-drug complexes using nanoelectrospray ionization hybrid quadrupole time-of-flight tandem mass spectrometry (nanoESI-MS/MS). The efficiency of direct fragmentation of intact protein ions and the feasibility of this method were initially demonstrated using several well-characterized proteins with different molecular weights including metallothionein (6126 Da), cytochrome c (horse, 12360 Da), myoglobin (horse, 16592 Da), and hemoglobin (human, 64453 Da). Simply varying collision energy without enzyme digestion and gel or LC separation generated a range of peptide fragments of these proteins. Over 80% of these peptide ions matched those in the SWISS-PROT database with mass accuracy of 8 to 32 ppm with external calibration. This technique was further applied to fragment a cisplatin-metallothionein complex to identify the binding sites, demonstrating a potential application in the study of drug-protein binding.     

Steric and allosteric effects of fatty acids on the binding of warfarin to human serum albumin revealed by molecular dynamics and free energy calculations

Human serum albumin (HSA) binds with drugs and fatty acids (FAs). This study was initiated to elucidate the relationship between the warfarin binding affinity of HSA and the positions of bound FA molecules. Molecular dynamics simulations of 11 HSA-warfarin-myristate complexes were performed. HSA-warfarin binding free energy was then calculated for each of the complexes by the molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) method. The results indicated that the magnitude of the binding free energy was smaller in HSA-warfarin complexes that had 4 or more myristate molecules than in complexes with no myristate molecules. The unfavorable effect on the HSA-warfarin binding affinity was caused sterically by the binding of a myristate molecule to the FA binding site closest to the warfarin binding site. On the other hand, the magnitude of HSA-warfarin binding free energy was largest when 3 myristate molecules were bound to the high-affinity sites. The strongest HSA-warfarin binding was attributable to favorable entropic contribution related to larger atomic fluctuations of the amino acid residues at the warfarin binding site. In the binding of 2 myristate molecules to the sites with the highest and second-highest affinities, allosteric modulation that enhanced electrostatic interactions between warfarin and some of the amino acid residues around the warfarin binding site was observed. This study clarified the structural and energetic properties of steric/allosteric effects of FAs on the HSA-warfarin binding affinity and illustrated the approach to analyze protein-ligand interactions in situations such that multiple ligands bind to the other sites of the protein.     

PEARLS: program for energetic analysis of receptor-ligand system

Analysis of the energetics of small molecule ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions facilitates the quantitative understanding of molecular interactions that regulate the function and conformation of proteins. It has also been extensively used for ranking potential new ligands in virtual drug screening. We developed a Web-based software, PEARLS (Program for Energetic Analysis of Ligand-Receptor Systems), for computing interaction energies of ligand-protein, ligand-nucleic acid, protein-nucleic acid, and ligand-protein-nucleic acid complexes from their 3D structures. AMBER molecular force field, Morse potential, and empirical energy functions are used to compute the van der Waals, electrostatic, hydrogen bond, metal-ligand bonding, and water-mediated hydrogen bond energies between the binding molecules. The change in the solvation free energy of molecular binding is estimated by using an empirical solvation free energy model. Contribution from ligand conformational entropy change is also estimated by a simple model. The computed free energy for a number of PDB ligand-receptor complexes were studied and compared to experimental binding affinity. A substantial degree of correlation between the computed free energy and experimental binding affinity was found, which suggests that PEARLS may be useful in facilitating energetic analysis of ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions. PEARLS can be accessed at http://ang.cz3.nus.edu.sg/cgi-bin/prog/rune.pl.     

Free enthalpies of replacing water molecules in protein binding pockets

Water molecules in the binding pocket of a protein and their role in ligand binding have increasingly raised interest in recent years. Displacement of such water molecules by ligand atoms can be either favourable or unfavourable for ligand binding depending on the change in free enthalpy. In this study, we investigate the displacement of water molecules by an apolar probe in the binding pocket of two proteins, cyclin-dependent kinase 2 and tRNA-guanine transglycosylase, using the method of enveloping distribution sampling (EDS) to obtain free enthalpy differences. In both cases, a ligand core is placed inside the respective pocket and the remaining water molecules are converted to apolar probes, both individually and in pairs. The free enthalpy difference between a water molecule and a CH₃ group at the same location in the pocket in comparison to their presence in bulk solution calculated from EDS molecular dynamics simulations corresponds to the binding free enthalpy of CH₃ at this location. From the free enthalpy difference and the enthalpy difference, the entropic contribution of the displacement can be obtained too. The overlay of the resulting occupancy volumes of the water molecules with crystal structures of analogous ligands shows qualitative correlation between experimentally measured inhibition constants and the calculated free enthalpy differences. Thus, such an EDS analysis of the water molecules in the binding pocket may give valuable insight for potency optimization in drug design.     

BALLDock/SLICK: a new method for protein-carbohydrate docking

Protein-ligand docking is an essential technique in computer-aided drug design. While generally available docking programs work well for most drug classes, carbohydrates and carbohydrate-like compounds are often problematic for docking. We present a new docking method specifically designed to handle docking of carbohydrate-like compounds. BALLDock/SLICK combines an evolutionary docking algorithm for flexible ligands and flexible receptor side chains with carbohydrate-specific scoring and energy functions. The scoring function has been designed to identify accurate ligand poses, while the energy function yields accurate estimates of the binding free energies of these poses. On a test set of known protein-sugar complexes we demonstrate the ability of the approach to generate correct poses for almost all of the structures and achieve very low mean errors for the predicted binding free energies.     

Free-energy component analysis of 40 protein-DNA complexes: a consensus view on the thermodynamics of binding at the molecular level

Noncovalent association of proteins to specific target sites on DNA--a process central to gene expression and regulation--has thus far proven to be idiosyncratic and elusive to generalizations on the nature of the driving forces. The spate of structural information on protein--DNA complexes sets the stage for theoretical investigations on the molecular thermodynamics of binding aimed at identifying forces responsible for specific macromolecular recognition. Computation of absolute binding free energies for systems of this complexity transiting from structural information is a stupendous task. Adopting some recent progresses in treating atomic level interactions in proteins and nucleic acids including solvent and salt effects, we have put together an energy component methodology cast in a phenomenological mode and amenable to systematic improvements and developed a computational first atlas of the free energy contributors to binding in approximately 40 protein-DNA complexes representing a variety of structural motifs and functions. Illustrating vividly the compensatory nature of the free energy components contributing to the energetics of recognition for attaining optimal binding, our results highlight unambiguously the roles played by packing, electrostatics including hydrogen bonds, ion and water release (cavitation) in protein-DNA binding. Cavitation and van der Waals contributions without exception favor complexation. The electrostatics is marginally unfavorable in a consensus view. Basic residues on the protein contribute favorably to binding despite the desolvation expense. The electrostatics arising from the acidic and neutral residues proves unfavorable to binding. An enveloping mode of binding to short stretches of DNA makes for a strong unfavorable net electrostatics but a highly favorable van der Waals and cavitation contribution. Thus, noncovalent protein-DNA association is a system-specific fine balancing act of these diverse competing forces. With the advances in computational methods as applied to macromolecular recognition, the challenge now seems to be to correlate the differential (initial vs. final) energetics to substituent effects in drug design and to move from affinity to specificity.     

Fluoroalkyl and alkyl chains have similar hydrophobicities in binding to the "hydrophobic wall" of carbonic anhydrase

The hydrophobic effect, the free-energetically favorable association of nonpolar solutes in water, makes a dominant contribution to binding of many systems of ligands and proteins. The objective of this study was to examine the hydrophobic effect in biomolecular recognition using two chemically different but structurally similar hydrophobic groups, aliphatic hydrocarbons and aliphatic fluorocarbons, and to determine whether the hydrophobicity of the two groups could be distinguished by thermodynamic and biostructural analysis. This paper uses isothermal titration calorimetry (ITC) to examine the thermodynamics of binding of benzenesulfonamides substituted in the para position with alkyl and fluoroalkyl chains (H(2)NSO(2)C(6)H(4)-CONHCH(2)(CX(2))(n)CX(3), n = 0-4, X = H, F) to human carbonic anhydrase II (HCA II). Both alkyl and fluoroalkyl substituents contribute favorably to the enthalpy and the entropy of binding; these contributions increase as the length of chain of the hydrophobic substituent increases. Crystallography of the protein-ligand complexes indicates that the benzenesulfonamide groups of all ligands examined bind with similar geometry, that the tail groups associate with the hydrophobic wall of HCA II (which is made up of the side chains of residues Phe131, Val135, Pro202, and Leu204), and that the structure of the protein is indistinguishable for all but one of the complexes (the longest member of the fluoroalkyl series). Analysis of the thermodynamics of binding as a function of structure is compatible with the hypothesis that hydrophobic binding of both alkyl and fluoroalkyl chains to hydrophobic surface of carbonic anhydrase is due primarily to the release of nonoptimally hydrogen-bonded water molecules that hydrate the binding cavity (including the hydrophobic wall) of HCA II and to the release of water molecules that surround the hydrophobic chain of the ligands. This study defines the balance of enthalpic and entropic contributions to the hydrophobic effect in this representative system of protein and ligand: hydrophobic interactions, here, seem to comprise approximately equal contributions from enthalpy (plausibly from strengthening networks of hydrogen bonds among molecules of water) and entropy (from release of water from configurationally restricted positions).