Cl-pi interactions in protein-ligand complexes

During systematic analysis of nonbonded contacts in protein-ligand complexes derived from crystal structures in the Protein Data Bank, Cl-pi interactions have been found, not only in the well-documented serine proteases but also, to a lesser extent, in other proteins. From geometric analysis of such Cl-pi interactions in the crystal structures, two distinct geometries were found: the "edge-on" approach of a Cl atom to a ring atom or C-C bond and the "face-on" approach toward the ring centroid with an average interatomic distance of 3.6 A. High-level ab initio calculations using benzene-chlorohydrocarbon model systems elucidated that the calculated Cl-pi interaction energy is -2.01 kcal/mol, and the dispersion force is the major source of attraction. We also discussed the geometric flexibility in Cl-pi interactions and a relationship between the intensity of the pi density in an aromatic ring and the interaction position of the Cl atom.     

Extent of enthalpy-entropy compensation in protein-ligand interactions

The extent of enthalpy-entropy compensation in protein-ligand interactions has long been disputed because negatively correlated enthalpy (ΔH) and entropy (TΔS) changes can arise from constraints imposed by experimental and analytical procedures as well as through a physical compensation mechanism. To distinguish these possibilities, we have created quantitative models of the effects of experimental constraints on isothermal titration calorimetry (ITC) measurements. These constraints are found to obscure any compensation that may be present in common data representations and regression analyses (e.g., in ΔH vs. -TΔS plots). However, transforming the thermodynamic data into ΔΔ-plots of the differences between all pairs of ligands that bind each protein diminishes the influence of experimental constraints and representational bias. Statistical analysis of data from 32 diverse proteins shows a significant and widespread tendency to compensation. ΔΔH versus ΔΔG plots reveal a wide variation in the extent of compensation for different ligand modifications. While strong compensation (ΔΔH and -TΔΔS opposed and differing by < 20% in magnitude) is observed for 22% of modifications (twice that expected without compensation), 15% of modifications result in reinforcement (ΔΔH and -TΔΔS of the same sign). Because both enthalpy and entropy changes arise from changes to the distribution of energy states on binding, there is a general theoretical expectation of compensated behavior. However, prior theoretical studies have focussed on explaining a stronger tendency to compensation than actually found here. These results, showing strong but imperfect compensation, will act as a benchmark for future theoretical models of the thermodynamic consequences of ligand modification.     

Free energy calculations of protein-ligand interactions

In the calculation of free energies of binding for protein-ligand complexes, we distinguish endpoint methods, methods involving alchemical modifications and methods that physically displace the ligand from the protein. Most methodological advances seem to come from a clever combination of multiple existing methods to enhance the sampling or to utilize specific advantages of various approaches. The coupling parameters common in thermodynamic integration and in Hamiltonian replica exchange are for instance combined to yield replica exchange thermodynamic integration. As new methods mostly aim to improve efficiency or to attain more complete sampling, there are good prospects to understand and tackle the sampling problem better and to shift the focus towards the scoring problem in the context of more robust and accurate force fields.     

Mass spectrometry-based approaches to protein-ligand interactions

One of the greatest current challenges in proteomics is to develop an understanding of cellular communication and regulation processes, most of which involve noncovalent interactions of proteins with various binding partners. Mass spectrometry plays an important role in all aspects of these research efforts. This article provides a survey of mass spectrometry-based approaches for exploring protein-ligand interactions. A wide array of techniques is available, and the choice of method depends on the specific problem at hand. For example, the high-throughput screening of compound libraries for binding to a specific receptor requires different approaches than structural studies on multiprotein complexes. This review is directed to readers wishing to obtain a concise yet comprehensive overview of existing experimental techniques. Specific emphasis is placed on emerging methods that have been developed within the last few years.     

Analysis of protein-ligand interactions by fluorescence polarization

Quantification of the associations between biomolecules is required both to predict and understand the interactions that underpin all biological activity. Fluorescence polarization (FP) provides a nondisruptive means of measuring the association of a fluorescent ligand with a larger molecule. We describe an FP assay in which binding of fluorescein-labeled inositol 1,4,5-trisphosphate (IP(3)) to N-terminal fragments of IP(3) receptors can be characterized at different temperatures and in competition with other ligands. The assay allows the standard Gibbs free energy (ΔG°), enthalpy (ΔH°) and entropy (ΔS°) changes of ligand binding to be determined. The method is applicable to any purified ligand-binding site for which an appropriate fluorescent ligand is available. FP can be used to measure low-affinity interactions in real time without the use of radioactive materials, it is nondestructive and, with appropriate care, it can resolve ΔH° and ΔS°. The first part of the protocol, protein preparation, may take several weeks, whereas the FP measurements, once they have been optimized, would normally take 1-6 h.     

Screening of protein-ligand interactions by affinity chromatography

This paper examines affinity chromatography (AC) as an alternative tool for the determination of protein-ligand interactions for the particular case in which the ligand is the same protein. The methodology is less labor-intensive and more sample-efficient than traditional methods used to measure the second virial coefficient (B(22)), a parameter commonly used to evaluate protein-protein interactions. The chromatographic capacity factor (k') was studied for lysozyme and equine serum albumin for a wide range of experimental solution conditions such as crystallizing agent concentration, protein concentration and pH. Parallel experiments using AC to determine k' and static light scattering (SLS) to determine B(22) showed that the two parameters were highly correlated. Two different column volumes ( approximately 1 and approximately 0.1 mL) were tested and gave essentially the same values for k', showing the feasibility of miniaturization.     

Simplified proteomics approach to discover protein-ligand interactions

Identifying targets of biologically active small molecules is an essential but still challenging task in drug research and chemical genetics. Energetics-based target identification is an approach that utilizes the change in the conformational stabilities of proteins upon ligand binding in order to identify target proteins. Different from traditional affinity-based capture approaches, energetics-based methods do not require any labeling or immobilization of the test molecule. Here, we report a surprisingly simple version of energetics-based target identification, which only requires ion exchange chromatography, SDS PAGE, and minimal use of mass spectrometry. The complexity of a proteome is reduced through fractionation by ion exchange chromatography. Urea-induced unfolding of proteins in each fraction is then monitored by the significant increase in proteolytic susceptibility upon unfolding in the presence and the absence of a ligand. Proteins showing a different degree of unfolding with the ligand are identified by SDS PAGE followed by mass spectrometry. Using this approach, we identified ATP-binding proteins in the Escherichia coli proteome. In addition to known ATP-binding proteins, we also identified a number of proteins that were not previously known to interact with ATP. To validate one such finding, we cloned and purified phosphoglyceromutase, which was not previously known to bind ATP, and confirmed that ATP indeed stabilizes this protein. The combination of fractionation and pulse proteolysis offers an opportunity to investigate protein-drug or protein-metabolite interactions on a proteomic scale with minimal instrumentation and without modification of a molecule of interest.     

Knowledge-based scoring function to predict protein-ligand interactions

The development and validation of a new knowledge-based scoring function (DrugScore) to describe the binding geometry of ligands in proteins is presented. It discriminates efficiently between well-docked ligand binding modes (root-mean-square deviation <2.0 A with respect to a crystallographically determined reference complex) and those largely deviating from the native structure, e.g. generated by computer docking programs. Structural information is extracted from crystallographically determined protein-ligand complexes using ReLiBase and converted into distance-dependent pair-preferences and solvent-accessible surface (SAS) dependent singlet preferences for protein and ligand atoms. Definition of an appropriate reference state and accounting for inaccuracies inherently present in experimental data is required to achieve good predictive power. The sum of the pair preferences and the singlet preferences is calculated based on the 3D structure of protein-ligand binding modes generated by docking tools. For two test sets of 91 and 68 protein-ligand complexes, taken from the Protein Data Bank (PDB), the calculated score recognizes poses generated by FlexX deviating <2 A from the crystal structure on rank 1 in three quarters of all possible cases. Compared to FlexX, this is a substantial improvement. For ligand geometries generated by DOCK, DrugScore is superior to the "chemical scoring" implemented into this tool, while comparable results are obtained using the "energy scoring" in DOCK. None of the presently known scoring functions achieves comparable power to extract binding modes in agreement with experiment. It is fast to compute, regards implicitly solvation and entropy contributions and produces correctly the geometry of directional interactions. Small deviations in the 3D structure are tolerated and, since only contacts to non-hydrogen atoms are regarded, it is independent from assumptions of protonation states.     

General and targeted statistical potentials for protein-ligand interactions

We present a novel atom-atom potential derived from a database of protein-ligand complexes. First, we clarify the similarities and differences between two statistical potentials described in the literature, PMF and Drugscore. We highlight shortcomings caused by an important factor unaccounted for in their reference states, and describe a new potential, which we name the Astex Statistical Potential (ASP). ASP's reference state considers the difference in exposure of protein atom types towards ligand binding sites. We show that this new potential predicts binding affinities with an accuracy similar to that of Goldscore and Chemscore. We investigate the influence of the choice of reference state by constructing two additional statistical potentials that differ from ASP only in this respect. The reference states in these two potentials are defined along the lines of Drugscore and PMF. In docking experiments, the potential using the new reference state proposed for ASP gives better success rates than when these literature reference states were used; a success rate similar to the established scoring functions Goldscore and Chemscore is achieved with ASP. This is the case both for a large, general validation set of protein-ligand structures and for small test sets of actives against four pharmaceutically relevant targets. Virtual screening experiments for these targets show less discrimination between the different reference states in terms of enrichment. In addition, we describe how statistical potentials can be used in the construction of targeted scoring functions. Examples are given for cdk2, using four different targeted scoring functions, biased towards increasingly large target-specific databases. Using these targeted scoring functions, docking success rates as well as enrichments are significantly better than for the general ASP scoring function. Results improve with the number of structures used in the construction of the target scoring functions, thus illustrating that these targeted ASP potentials can be continuously improved as new structural data become available.     

The contribution of halogen atoms to protein-ligand interactions.

The three-dimensional structure of para-fluoro-D-phenylalanine (PFF) in its complex with the zinc protease carboxypeptidase A (CPA) has been determined at 2.0 A resolution by X-ray crystallographic methods. The structure reveals that the para-fluorobenzyl side chain of the inhibitor is buried in the S'1 hydrophobic pocket of the enzyme. Intriguingly, this ligand molecule inhibits CPA better than its amino acid analogues D-phenylalanine (D-Phe) and D-tyrosine (D-Tyr) by factors of 4 and 5, respectively. Moreover, the para-fluoro derivative is a better inhibitor than para-chloro- or para-bromo-D-phenylalanine by nearly a factor of 50. This result is consistent with binding enhancements realized in other protein complexes involving halogenated ligand molecules, regardless of whether the carbon-halogen group of the ligand makes specific polar interactions or non-specific hydrophobic interactions with its protein host. In the CPA-PFF complex, the fluorine atom of PFF does not make any direct polar contact with the enzyme, and the contact surface area of the protein-ligand interface is only slightly greater, although more hydrophobic, than that of D-Phe and D-Tyr. Therefore, we conclude that the slight binding enhancement measured for PFF relative to D-Phe and D-Tyr arises predominantly from increasing the hydrophobic character of the protein-ligand interface, and not solely from increasing the degree of protein-ligand contact.     

Correction for light absorption in fluorescence studies of protein-ligand interactions

It is shown that absorption of the excitation light can lead to substantial systematic errors in fluorescence measurements of equilibrium constants for formation of protein-ligand complexes. The assumptions about the optical arrangement of the fluorescence spectrometer involved in the calculation of the correction of this absorption are discussed. A general semiempirical correction procedure which can be used for (calculated) absorbance values as high as 5 is described. The importance of choosing the excitation wavelength so as to minimize the necessity for these corrections is emphasized.     

Energetics-based discovery of protein-ligand interactions on a proteomic scale

Biochemical functions of proteins in cells frequently involve interactions with various ligands. Proteomic methods for the identification of proteins that interact with specific ligands such as metabolites, signaling molecules, and drugs are valuable in investigating the regulatory mechanisms of cellular metabolism, annotating proteins with unknown functions, and elucidating pharmacological mechanisms. Here we report an energetics-based target identification method in which target proteins in a cell lysate are identified by exploiting the effect of ligand binding on their stabilities. Urea-induced unfolding of proteins in cell lysates is probed by a short pulse of proteolysis, and the effect of a ligand on the amount of folded protein remaining is monitored on a proteomic scale. As proof of principle, we identified proteins that interact with ATP in the Escherichia coli proteome. Literature and database mining confirmed that a majority of the identified proteins are indeed ATP-binding proteins. Four identified proteins that were previously not known to interact with ATP were cloned and expressed to validate the result. Except for one protein, the effects of ATP on urea-induced unfolding were confirmed. Analyses of the protein sequences and structure models were also employed to predict potential ATP binding sites in the identified proteins. Our results demonstrate that this energetics-based target identification approach is a facile method to identify proteins that interact with specific ligands on a proteomic scale.     

Understanding protein-ligand interactions: the price of protein flexibility

In order to design selective, high-affinity ligands to a target protein, it is advantageous to understand the structural determinants for protein-ligand complex formation at the atomic level. In a model system, we have successively mapped the factor Xa binding site onto trypsin, showing that certain mutations influence both protein structure and inhibitor specificity. Our previous studies have shown that introduction of the 172SSFI175 sequence of factor Xa into rat or bovine trypsin results in the destabilisation of the intermediate helix with burial of Phe174 (the down conformation). Surface exposure of the latter residue (the up conformation) is critical for the correct formation of the aromatic box found in factor Xa-ligand complexes. In the present study, we investigate the influence of aromatic residues in position 174. Replacement with the bulky tryptophan (SSWI) shows reduced affinity for benzamidine-based inhibitors (1) and (4), whereas removal of the side-chain (alanine, SSAI) or exchange with a hydrophilic residue (arginine, SSRI) leads to a significant loss in affinity for all inhibitors studied. The variants could be crystallised in the presence of different inhibitors in multiple crystal forms. Structural characterisation of the variants revealed three different conformations of the intermediate helix and 175 loop in SSAI (down, up and super-up), as well as a complete disorder of this region in one crystal form of SSRI, suggesting that the compromised affinity of these variants is related to conformational flexibility. The influence of Glu217, peripheral to the ligand-binding site in factor Xa, was investigated. Introduction of Glu217 into trypsin variants containing the SSFI sequence exhibited enhanced affinity for the factor Xa ligands (2) and (3). The crystal structures of these variants also exhibited the down and super-up conformations, the latter of which could be converted to up upon soaking and binding of inhibitor (2). The improved affinity of the Glu217-containing variants appears to be due to a shift towards the up conformation. Thus, the reduction in affinity caused by conformational variability of the protein target can be partially or wholly offset by compensatory binding to the up conformation. The insights provided by these studies will be helpful in improving our understanding of ligand binding for the drug design process.     

Protein-protein and protein-ligand interactions studied by electrospray-ionization mass spectrometry

Preservation of non-covalent interactions in biopolymer mass spectrometry offers new approaches to binding analysis. Recent work from our laboratory is reviewed here and discussed with reference to recent literature in the field. Three issues are considered in particular: hydrophobically stabilized complexes, pH-dependent transitions, and linked protein-ligand and protein-protein binding equilibria.