(Extra)thermodynamics of the drug-receptor interaction

Entropy-enthalpy Compensation of Biomolecular Systems in Aqueous Phase: a Dry Perspective

We survey thermodynamic measurements on processes involving biological macromolecules in aqueous solution, which illustrate well the ubiquitous phenomenon of entropy-enthalpy compensation. The processes include protein folding/unfolding and ligand binding/unbinding, with compensation temperatures varying by about 50 K around an average near 293 K. We show that incorporating both near-exact entropy-enthalpy compensation (due to solvent relaxation) and multi-excitation entropy (from vibrational quanta) leads to a compensation temperature in water of about 230 K. We illustrate a general procedure for subtracting solvent and environment-related terms to determine the bare Gibbs free energy changes of chemical processes.

Ligand binding assays at equilibrium: validation and interpretation

The focus of this review paper is factors affecting data interpretation in ligand binding assays under equilibrium conditions. Protocols for determining K(d) (the equilibrium dissociation constant) and K(dA) (the equilibrium inhibitor constant) for receptor ligands are discussed. The basic theory describing the interaction of a radiotracer and an unlabelled competitor ligand with a receptor is developed. Inappropriate experimental design may result in ligand depletion and non-attainment of equilibrium, distorting the calculation of K(d) and K(dA) . Strategies, both theoretical and practical, will be given to avoid and correct such errors, thus leading to the determination of reliable values for these constants. In determining K(dA) from competition binding studies, two additional concepts are discussed. First, the necessity to measure an adequate specific binding signal from the bound radiotracer ligand limits the range of affinity constants that can be measured: a particular set of assay conditions may lead to an upper limit on the apparent affinity of unlabelled ligands. Second, an extension of the basic assay methodology can indicate whether the interaction between the tracer and a test ligand is mediated by a competitive or an allosteric mechanism. Finally, the review ends with a discussion of two factors that are often overlooked: buffer composition and the temperature at which the assay is conducted, and the impact these can have on affinity measurements and the understanding of drug interactions.

Recognition forces in ligand-protein complexes: blending information from different sources

A variety of ligands interact with proteins in many biological processes; shape complementarity, electrostatic forces and hydrophobicity are the main factors governing these interactions. Although this is accepted by the scientific community, confusion about the significance of certain terms (e.g. hydrophobicity, salt bridge) and the difficulty of discussing the balance of acting forces rather than their single contributions, are two of the main problems encountered by researchers working in the field. These difficulties are sometimes enhanced by the unskilled use of informatics tools, which give great help in understanding the topic (especially from the visual standpoint), but only if used critically. After explaining some general chemical concepts, the commentary discusses the main forces governing ligand-protein interactions, focusing on those generating confusion among scientists with different backgrounds. Three examples of ligand-protein interactions are then discussed to illustrate the advantages and drawbacks of some in silico tools, highlighting the main interactions responsible for complex formation. The same examples are used to point out the limits in separating forces that are mandatory for occurrence of a given interaction and additional forces.

Designing allosteric peptide ligands targeting a globular protein

Patented signal analytic algorithms applied to hydrophobically transformed, numerical amino acid sequences have previously been used to design short, protein-targeted, L or D retro-inverso peptides. These peptides have demonstrated allosteric and/or indirect agonist effects on a variety of G-protein and tyrosine kinase coupled membrane receptors with 30% to over 80% hit rates. Here we extend these approaches to a globular protein target. We designed eight peptide ligands targeting an ELISA antibody responsive protein, beta-galactosidase, betaGAL. Three of the eight 14mer peptides allosterically activated betaGAL with ELISA methodology. Using Bayesian statistics, this 38% hit rate would have occurred 2 x 10(-9) by chance. These peptides demonstrated binding site competitive or noncompetitive interactions, suggesting allosteric site multiplicity with respect to their betaGAL binding-mediated ELISA signal. Kinetic studies demonstrated the temperature dependence of the betaGAL peptide binding functions. Using the van't Hoff relation, we found evidence for enthalpy-entropy compensation. This relation is often found for hydrophobic interactions in aqueous media, and is consistent with the postulated hydrophobic series encoding underlying our protein-targeted, peptide design methods. It appears that our algorithmic, hydrophobic autocovariance eigenvector template approach to the design of allosteric peptides targeting membrane receptors may also be applicable to the design of peptide ligands targeting nonmembrane involved globular proteins.

Biospectra Analysis: Model Proteome Characterizations for Linking Molecular Structure and Biological Response

Establishing quantitative relationships between molecular structure and broad biological effects has been a long-standing goal in drug discovery. Evaluation of the capacity of molecules to modulate protein functions is a prerequisite for understanding the relationship between molecular structure and in vivo biological response. A particular challenge in these investigations is to derive quantitative measurements of a molecule's functional activity pattern across different proteins. Herein we describe an operationally simple probabilistic structure-activity relationship (SAR) approach, termed biospectra analysis, for identifying agonist and antagonist effect profiles of medicinal agents by using pattern similarity between biological activity spectra (biospectra) of molecules as the determinant. Accordingly, in vitro binding data (percent inhibition values of molecules determined at single high drug concentration in a battery of assays representing a cross section of the proteome) are useful for identifying functional effect profile similarity between medicinal agents. To illustrate this finding, the relationship between biospectra similarity of 24 molecules, identified by hierarchical clustering of a 1567 molecule dataset as being most closely aligned with the neurotransmitter dopamine, and their agonist or antagonist properties was probed. Distinguishing the results described in this study from those obtained with affinity-based methods, the observed association between biospectra and biological response profile similarity remains intact even upon removal of putative drug targets from the dataset (four dopaminergic [D1/D2/D3/D4] and two adrenergic [alpha1 and alpha2] receptors). These findings indicate that biospectra analysis provides an unbiased new tool for forecasting structure-response relationships and for translating broad biological effect information into chemical structure design.

Biological spectra analysis: Linking biological activity profiles to molecular structure

Establishing quantitative relationships between molecular structure and broad biological effects has been a longstanding challenge in science. Currently, no method exists for forecasting broad biological activity profiles of medicinal agents even within narrow boundaries of structurally similar molecules. Starting from the premise that biological activity results from the capacity of small organic molecules to modulate the activity of the proteome, we set out to investigate whether descriptor sets could be developed for measuring and quantifying this molecular property. Using a 1,567-compound database, we show that percent inhibition values, determined at single high drug concentration in a battery of in vitro assays representing a cross section of the proteome, provide precise molecular property descriptors that identify the structure of molecules. When broad biological activity of molecules is represented in spectra form, organic molecules can be sorted by quantifying differences between biological spectra. Unlike traditional structure-activity relationship methods, sorting of molecules by using biospectra comparisons does not require knowledge of a molecule's putative drug targets. To illustrate this finding, we selected as starting point the biological activity spectra of clotrimazole and tioconazole because their putative target, lanosterol demethylase (CYP51), was not included in the bioassay array. Spectra similarity obtained through profile similarity measurements and hierarchical clustering provided an unbiased means for establishing quantitative relationships between chemical structures and biological activity spectra. This methodology, which we have termed biological spectra analysis, provides the capability not only of sorting molecules on the basis of biospectra similarity but also of predicting simultaneous interactions of new molecules with multiple proteins.

Role of solution conformation and flexibility of short peptide ligands that bind to the p56(lck) SH2 domain

A general approach in drug design is making ligands more rigid in order to avoid loss in conformational entropy (deltaS(conf)) upon receptor binding. We hypothesized that in the high affinity binding of pYEEI peptide ligands to the p56(lck) SH2 domain this loss in deltaS(conf) might be diminished due to preorganization of the fourfold negatively charged pYEEI peptide in the bound, extended, conformation. A thermodynamic analysis was performed on the peptides Ac-pYEEI-NH(2), Ac-pYAAI-NH(2) and Ac-pYGGI-NH(2) using surface plasmon resonance (SPR) competition experiments to assay affinity constants at different temperatures. To study the effect of solution conformation and flexibility a computational conformation analysis was performed from which low energy conformations in solution were calculated, and S(conf) estimated. It was found that the calculated low energy conformations for especially the pYE moiety in solution resemble that in the bound state. In the calculated minimum energy conformation in solution isoleucine is bent towards the pY aromatic ring, the occurrence of such conformation is experimentally confirmed by NMR. The estimated values for S(conf) of the EE- and AA-peptide were similar, suggesting no predominant role of preorganization of the solution conformation due to electrostatic repulsion. Apparently the thermodynamics obey the same entropy-enthalpy compensation relationship, which also was found to hold for other peptides and peptidomimetics binding to p60(src) family SH2 domains. The implications of the results for drug design are discussed.