Experimental characterization of the association of ß-cyclodextrin and eight novel cyclodextrin derivatives with two guest compounds.

We investigate the binding of native ß-cyclodextrin (ß-CD) and eight novel ß-CD derivatives with two different guest compounds, using isothermal calorimetry and 2D NOESY NMR. In all cases, the stoichiometry is 1:1 and binding is exothermic. Overall, modifications at the 3' position of ß-CD, which is at the secondary face, weaken binding by several kJ/mol relative to native ß-CD, while modifications at the 6' position (primary face) maintain or somewhat reduce the binding affinity. The variations in binding enthalpy are larger than the variations in binding free energy, so entropy-enthalpy compensation is observed. Characterization of the bound conformations with NOESY NMR shows that the polar groups of the guests may be situated at either face, depending on the host molecule, and, in some cases, both orientations are populated. The present results were used in the SAMPL7 blinded prediction challenge whose results are detailed in the same special issue of JCAMD.

Bio-inspired CO2 reduction by a rhenium tricarbonyl bipyridine-based catalyst appended to amino acids and peptidic platforms: incorporating proton relays and hydrogen-bonding functional groups.

Herein, we report a new approach to bio-inspired catalyst design. The molecular catalyst employed in these studies is based on the robust and selective Re(bpy)(CO)3Cl-type (bpy = 2,2'-bipyridine) homogeneous catalysts, which have been extensively studied for their ability to reduce CO2 electrochemically or photochemically in the presence of a photosensitizer. These catalysts can be highly active photocatalysts in their own right. In this work, the bipyridine ligand was modified with amino acids and synthetic peptides. These results build on earlier findings wherein the bipyridine ligand was functionalized with amide groups to promote dimer formation and CO2 reduction by an alternate bimolecular mechanism at lower overpotential (ca. 250 mV) than the more commonly observed unimolecular process. The bio-inspired catalysts were designed to allow for the incorporation of proton relays to support reduction of CO2 to CO and H2O. The coupling of amino acids tyrosine and phenylalanine led to the formation of two structurally similar Re catalyst/peptide catalysts for comparison of proton transport during catalysis. This article reports the synthesis and characterization of novel catalyst/peptide hybrids by molecular dynamics (MD simulations of structural dynamics), NMR studies of solution phase structures, and electrochemical studies to measure the activities of new bio-inspired catalysts in the reduction of CO2.

Using protein homology models for structure-based studies: approaches to model refinement.

Homology modeling is a computational methodology to assign a 3-D structure to a target protein when experimental data are not available. The methodology uses another protein with a known structure that shares some sequence identity with the target as a template. The crudest approach is to thread the target protein backbone atoms over the backbone atoms of the template protein, but necessary refinement methods are needed to produce realistic models. In this mini-review anchored within the scope of drug design, we show the validity of using homology models of proteins in the discovery of binders for potential therapeutic targets. We also report several different approaches to homology model refinement, going from very simple to the most elaborate. Results show that refinement approaches are system dependent and that more elaborate methodologies do not always correlate with better performances from built homology models.

Interpreting trends in the binding of cyclic ureas to HIV-1 protease.

The design of new HIV protease inhibitors requires an improved understanding of the physical basis of inhibitor/protein binding. Here, the binding affinities of seven aliphatic cyclic ureas to HIV-1 protease are calculated using a predominant states method and an implicit solvent model based upon finite difference solutions of the Poisson-Boltzmann equation. The calculations are able to reproduce the observed U-shaped trend of binding free energy as a function of aliphatic chain length. Interestingly, the decrease in affinity for the longest chains is attributable primarily to the energy cost of partly desolvating charged aspartic and arginine groups at the mouths of the active site. Even aliphatic chains too short to contact these charged groups directly are subject to considerable desolvation penalties. We are not aware of other systems where binding affinity trends have been attributed to long-ranged electrostatic desolvation of ionized groups. A generalized Born/surface area solvation model yields a much smaller change in desolvation energy with chain length and, therefore, does not reproduce the experimental binding affinity trends. This result suggests that the generalized Born model should be used with caution for complex, partly desolvated systems like protein binding sites. We also find that changing the assumed protonation state of the active site aspartyl dyad significantly affects the computed binding affinity trends. The protonation state of the aspartyl dyad in the presence of cyclic ureas is discussed in light of the observation that the monoprotonated state reproduces the experimental results best.

Ligand-receptor docking with the Mining Minima optimizer.

The optimizer developed for the Mining Minima algorithm, which uses ideas from Genetic Algorithms, the Global Underestimator Method, and Poling, has been adapted for use in ligand-receptor docking. The present study describes the resulting methodology and evaluates its accuracy and speed for 27 test systems. The performance of the new docking algorithm appears to be competitive with that of previously published methods. The energy model, an empirical force field with a distance-dependent dielectric treatment of solvation, is adequate for a number of test cases, although incorrect low-energy conformations begin to compete with the correct conformation for larger sampling volumes and for highly solvent-exposed binding sites that impose little steric constraint on the ligand.

The physical basis of nucleic acid base stacking in water.

It has been argued that the stacking of adenyl groups in water must be driven primarily by electrostatic interactions, based upon NMR data showing stacking for two adenyl groups joined by a 3-atom linker but not for two naphthyl groups joined by the same linker. In contrast, theoretical work has suggested that adenine stacking is driven primarily by nonelectrostatic forces, and that electrostatic interactions actually produce a net repulsion between adenines stacking in water. The present study provides evidence that the experimental data for the 3-atom-linked bis-adenyl and bis-naphthyl compounds are consistent with the theory indicating that nonelectrostatic interactions drive adenine stacking. First, a theoretical conformational analysis is found to reproduce the observed ranking of the stacking tendencies of the compounds studied experimentally. A geometric analysis identifies two possible reasons, other than stronger electrostatic interactions, why the 3-atom-linked bis-adenyl compounds should stack more than the bis-naphthyl compounds. First, stacked naphthyl groups tend to lie further apart than stacked adenyl groups, based upon both quantum calculations and crystal structures. This may prevent the bis-naphthyl compound from stacking as extensively as the bis-adenyl compound. Second, geometric analysis shows that more stacked conformations are sterically accessible to the bis-adenyl compound than to the bis-naphthyl compound because the linker is attached to the sides of the adenyl groups, but to the ends of the naphthyl groups. Finally, ab initio quantum mechanics calculations and energy decompositions for relevant conformations of adenine and naphthalene dimers support the view that stacking in these compounds is driven primarily by nonelectrostatic interactions. The present analysis illustrates the importance of considering all aspects of a molecular system when interpreting experimental data, and the value of computer models as an adjunct to chemical intuition.

The binding database: overview and user's guide.

The large and growing body of experimental data on molecular binding is of enormous value in biology, pharmacology, and chemistry. Applications include the assignment of function to biomolecules, drug discovery, molecular modeling, and nanotechnology. However, binding data are difficult to find and access because they are available almost exclusively through scientific journals. BindingDB, a public, web-accessible database of measured binding affinities, is designed to address this problem. BindingDB collects data for natural and modified biomolecules and for synthetic compounds, and provides detailed experimental information. Currently, measurements by isothermal titration calorimetry are fully supported; measurements by enzyme inhibition will soon be included as well. The web site allows data to be searched by a range of criteria, including binding thermodynamics, sequence homology, and chemical structure, substructure, and similarity. Experimentalists are encouraged to publicize their data by entering it into BindingDB via the online forms. Such data can be updated or revised by the depositor, if necessary, and will remain publicly accessible. User involvement and feedback are welcomed.

BindingDB: a web-accessible molecular recognition database.

This paper presents an initial description of the BindingDB, a public web-accessible database of measured binding affinities for various molecular types (http://www.bindingdb.org). The BindingDB allows queries based upon a range of criteria, including chemical similarity or substructure, sequence homology, numerical criteria (e.g. delta G(o) < 5 kcal/mol) and reactant names (e.g. "lysozyme"). Principles of Human-Computer Interactions are being employed in creating the query interface and user-feedback is being solicited. The data specification includes significant experimental detail. A full dictionary has been created for isothermal titration calorimetry data in consultation with experimentalists and data dictionaries for enzyme-inhibition and other measurement techniques are being developed. Currently, the BindingDB contains several data sets of broad interest, such as antigen-antibody binding and cyclodextrin/small molecule binding. However, it is anticipated that online deposition by experimentalists will ultimately contribute to a larger flow of data. We are actively developing software and file specifications to facilitate such deposition.

Modeling molecular recognition: theory and application.

Abstract Efficient, reliable methods for calculating the binding affinities of noncovalent complexes would allow advances in a variety of areas such as drug discovery and separation science. We have recently described a method that accommodates significant physical detail while remaining fast enough for use in molecular design. This approach uses the predominant states method to compute free energies, an empirical force field, and an implicit solvation model based upon continuum electrostatics. We review applications of this method to systems ranging from small molecules to protein-ligand complexes.

Nucleic acid base-pairing and N-methylacetamide self-association in chloroform: affinity and conformation.

A recently developed computational method, 'mining minima', is used to examine the hydrogen-bonding interactions of nucleic acid base-pairs and of the N-methylacetamide homodimer in chloroform. The mining minima algorithm aggressively samples molecular conformations, identifies the most important local minima, and computes their contributions to the overall free energy of the system. Here, the CHARMM 98 parameter set is used for the potential energy and the generalized Born/surface area solvent model is used to account for the influence of the solvent. Good agreement with experiment is obtained for the non-covalent binding affinities of a series of complexes. The computational approach used here is applicable to a range of molecular systems.

Thermodynamic linkage between the binding of protons and inhibitors to HIV-1 protease.

The aspartyl dyad of free HIV-1 protease has apparent pK(a)s of approximately 3 and approximately 6, but recent NMR studies indicate that the aspartyl dyad is fixed in the doubly protonated form over a wide pH range when cyclic urea inhibitors are bound, and in the monoprotonated form when the inhibitor KNI-272 is bound. We present computations and measurements related to these changes in protonation and to the thermodynamic linkage between protonation and inhibition. The Poisson-Boltzmann model of electrostatics is used to compute the apparent pK(a)s of the aspartyl dyad in the free enzyme and in complexes with four different inhibitors. The calculations are done with two parameter sets. One assigns epsilon = 4 to the solute interior and uses a detailed model of ionization; the other uses epsilon = 20 for the solute interior and a simplified representation of ionization. For the free enzyme, both parameter sets agree well with previously measured apparent pK(a)s of approximately 3 and approximately 6. However, the calculations with an internal dielectric constant of 4 reproduce the large pKa shifts upon binding of inhibitors, but the calculations with an internal dielectric constant of 20 do not. This observation has implications for the accurate calculation of pK(a)s in complex protein environments. Because binding of a cyclic urea inhibitor shifts the pK(a)s of the aspartyl dyad, changing the pH is expected to change its apparent binding affinity. However, we find experimentally that the affinity is independent of pH from 5.5 to 7.0. Possible explanations for this discrepancy are discussed.

A hierarchical method for generating low-energy conformers of a protein-ligand complex.

A novel dynamical protocol for finding the low-energy conformations of a protein-ligand complex is described. The energy functions examined consist of an empirical force field with four different dielectric screening models; the generalized Born/surface area model also is examined. Application of the method to three complexes of known crystal structure provides insights into the energy functions used for selecting low-energy docked conformations and into the structure of the binding-energy surface. Evidence is presented that the local energy minima of a ligand in a binding site are arranged in a hierarchical fashion. This observation motivates the construction of a hierarchical docking algorithm that substantially enriches the population of ligand conformations close to the crystal conformation. The algorithm is also adapted to permit docking into a flexible binding site and preliminary tests of this method are presented.

Theoretical and experimental analysis of ionization equilibria in ovomucoid third domain.

2D-NMR experiments were used to determine the pKa values ranging from 8.0 to >/=11.1 of seven basic residues in turkey ovomucoid third domain (OMTKY3) and were compared to values predicted as described by Antosiewicz et al. [(1996) Biochemistry 35, 7819-7833]. Lys 13, 29, and 34 were previously attributed with increasing the acidity of numerous acidic residues [Schaller, W., and Robertson, A. D. (1995) Biochemistry 34, 4714-4723]. These interactions were expected to raise the pKa values of those basic groups; however, the pKa values of Lys 13 and 34 are less than the model compound values. The pKa values of the other basic residues are greater than the model compound values and, unlike the acidic residues, all are surprisingly insensitive to salt. While the calculations properly predict the direction of most of the pKa shifts and provide valuable insight into the possible molecular origins of the interactions that perturb pKa values, there is a tendency to overestimate the magnitude of the shifts and their salt dependence. Interestingly, the shapes of both the calculated and observed transitions are often more complex than expected for a simple titration, suggesting that pKa values at many sites are changing during the transition. Differences between predicted and experimental pKa values and titration profiles for some residues may be due to as yet uncharacterized structural changes at the extremes of pH.

The statistical-thermodynamic basis for computation of binding affinities: a critical review.

Although the statistical thermodynamics of noncovalent binding has been considered in a number of theoretical papers, few methods of computing binding affinities are derived explicitly from this underlying theory. This has contributed to uncertainty and controversy in certain areas. This article therefore reviews and extends the connections of some important computational methods with the underlying statistical thermodynamics. A derivation of the standard free energy of binding forms the basis of this review. This derivation should be useful in formulating novel computational methods for predicting binding affinities. It also permits several important points to be established. For example, it is found that the double-annihilation method of computing binding energy does not yield the standard free energy of binding, but can be modified to yield this quantity. The derivation also makes it possible to define clearly the changes in translational, rotational, configurational, and solvent entropy upon binding. It is argued that molecular mass has a negligible effect upon the standard free energy of binding for biomolecular systems, and that the cratic entropy defined by Gurney is not a useful concept. In addition, the use of continuum models of the solvent in binding calculations is reviewed, and a formalism is presented for incorporating a limited number of solvent molecules explicitly.

A new class of models for computing receptor-ligand binding affinities.

Models for predicting the binding affinities of molecules in solution are either very detailed, making them computationally intensive and hard to test, or very simple, and thus less informative than one might wish. A new class of models that focus on the predominant states of the binding molecules promise to capture the essential physics of binding at modest computational cost.

The determinants of pKas in proteins.

Although validation studies show that theoretical models for predicting the pKas of ionizable groups in proteins are increasingly accurate, a number of important questions remain: (1) What factors limit the accuracy of current models? (2) How can conformational flexibility of proteins best be accounted for? (3) Will use of solution structures in the calculations, rather than crystal structures, improve the accuracy of the computed pKas? and (4) Why does accurate prediction of protein pKas seem to require that a high dielectric constant be assigned to the protein interior? This paper addresses these and related issues. Among the conclusions are the following: (1) computed pKas averaged over NMR structure sets are more accurate than those based upon single crystal structures; (2) use of atomic parameters optimized to reproduce hydration energies of small molecules improves agreement with experiment when a low protein dielectric constant is assumed; (3) despite use of NMR structures and optimized atomic parameters, pKas computed with a protein dielectric constant of 20 are more accurate than those computed with a low protein dielectric constant; (4) the pKa shifts in ribonuclease A that result from phosphate binding are reproduced reasonably well by calculations; (5) the substantial pKa shifts observed in turkey ovomucoid third domain result largely from interactions among ionized groups; and (6) both experimental data and calculations indicate that proteins tend to lower the pKas of Asp side chains but have little overall effect upon the pKas of other ionizable groups.

Binding of tacrine and 6-chlorotacrine by acetylcholinesterase.

Multiconfiguration thermodynamic integration was used to determine the relative binding strength of tacrine and 6-chlorotacrine by Torpedo californica acetylcholinesterase. 6-Chlorotacrine appears to be bound stronger by 0.7+/-0.4 kcal/mol than unsubstituted tacrine when the active site triad residue His-440 is deprotonated. This result is in excellent agreement with experimental inhibition data on electric eel acetylcholinesterase. Electrostatic Poisson-Boltzmann calculations confirm that order of binding strength, resulting in deltaG of binding of -2.9 and -3.3 kcal/mol for tacrine and chlorotacrine, respectively, and suggest inhibitor binding does not occur when His-440 is charged. Our results suggest that electron density redistribution upon tacrine chlorination is mainly responsible for the increased attraction potential between pronated inhibitor molecule and adjacent aromatic groups of Phe-330 and Trp-84.

Simulation of charge-mutant acetylcholinesterases.

A recent experimental study of human acetylcholinesterase has shown that the mutation of surface acidic residues has little effect on the rate constant for hydrolysis of acetylthiocholine. It was concluded, on this basis, that the reaction is not diffusion controlled and that electrostatic steering plays only a minor role in determining the rate. Here we examine this issue through Brownian dynamics simulations on Torpedo californica acetylcholinesterase in which the surface acidic residues homologous with those mutated in the human enzyme are artificially neutralized. The computed effects of the mutations on the rate constants reproduce quite well the modest effects of the mutations upon the measured encounter rates. Nonetheless, the electrostatic field of the enzyme is found to increase the rate constants by about an order of magnitude in both the wild type and the mutants. We therefore conclude that the mutation experiments do not disprove that electrostatic steering substantially affects the catalytic rate of acetylcholinesterase.