What Can We Learn from Molecular Recognition in Protein–Ligand Complexes for the Design of New Drugs?

The understanding of noncovalent interactions in protein–ligand complexes is essential in modern biochemistry and should contribute toward the discovery of new drugs. In the present review, we summarize recent work aimed at a better understanding of the physical nature of molecular recognition in protein–ligand complexes and also at the development and application of new computational tools that exploit our current knowledge on structural and energetic aspects of protein–ligand interactions in the design of novel ligands. These approaches are based on the exponentially growing amount of information about the geometry of protein structures and the properties of small organic molecules exposed to a structured molecular environment. The various contributions that determine the binding affinity of ligands toward a particular receptor are discussed. Their putative binding site conformations are analyzed, and some predictions are attempted. The similarity of ligands is examined with respect to their recognition properties. This information is used to understand and propose binding modes. In addition, an overview of the existing methods for the design and selection of novel protein ligands is given.     

Live‐Cell‐Templated Dynamic Combinatorial Chemistry

Dynamic covalent chemistry combines in a single step the screening and synthesis of ligands for biomolecular recognition. In order to do that, a chemical entity is used as template within a dynamic combinatorial library of interconverting species, so that the stronger binders are amplified due to the efficient interaction with the target. Here we employed whole A549 living cells as template in a dynamic mixture of imines, for which amplification reflects the efficient and selective interaction with the corresponding extracellular matrix. The amplified polyamine showed strong interaction with the A549 extracellular matrix in on‐cell NMR experiments, while combination of NMR, SPR, and molecular dynamics simulations in model systems provided insights on the molecular recognition event. Notably, our work pioneers the use of whole living cells in dynamic combinatorial chemistry, which paves the way towards the discovery of new bioactive molecules in a more biorelevant environment.     

Live-Cell-Templated Dynamic Combinatorial Chemistry

Dynamic covalent chemistry combines in a single step the screening and synthesis of ligands for biomolecular recognition. In order to do that, a chemical entity is used as template within a dynamic combinatorial library of interconverting species, so that the stronger binders are amplified due to the efficient interaction with the target. Here we employed whole A549 living cells as template in a dynamic mixture of imines, for which amplification reflects the efficient and selective interaction with the corresponding extracellular matrix. The amplified polyamine showed strong interaction with the A549 extracellular matrix in on-cell NMR experiments, while combination of NMR, SPR, and molecular dynamics simulations in model systems provided insights on the molecular recognition event. Notably, our work pioneers the use of whole living cells in dynamic combinatorial chemistry, which paves the way towards the discovery of new bioactive molecules in a more biorelevant environment.     

Synthetic ligands discovered by in vitro selection

The recognition and catalytic properties of biopolymers derive from an elegant evolutionary mechanism, whereby the genetic material encoding molecules with superior functional attributes survives a selective pressure and is propagated to subsequent generations. This process is routinely mimicked in vitro to generate nucleic-acid or peptide ligands and catalysts. Recent advances in DNA-programmed organic synthesis have raised the possibility that evolutionary strategies could also be used for small-molecule discovery, but the idea remains unproven. Here, using DNA-programmed combinatorial chemistry, a collection of 100 million distinct compounds is synthesized and subjected to selection for binding to the N-terminal SH3 domain of the proto-oncogene Crk. Over six generations, the molecular population converges to a small number of novel SH3 domain ligands. Remarkably, the hits bind with affinities similar to those of peptide SH3 ligands isolated from phage libraries of comparable complexity. The evolutionary approach has the potential to drastically simplify and accelerate small-molecule discovery.     

Dynamic Combinatorial Chemistry: A New Methodology Comes of Age

Dynamic combinatorial chemistry (DCC) has repeatedly proven to be an effective approach to generate directed ligand libraries for macromolecular targets. In the absence of an external stimulus, a dynamic library forms from reversibly reacting building blocks and reaches a stable thermodynamic equilibrium. However, upon addition of a macromolecular host which can bind and stabilize certain components of the library, the equilibrium composition changes and induces an evolution-like selection and enrichment of high-affinity ligands. A valuable application of this so-called target-directed DCC (tdDCC) is the identification of potent ligands for pharmacologically relevant targets. Over time, the term tdDCC has been applied to describe a number of different experimental setups, leading to some ambiguity concerning its definition. This article systematically classifies known procedures for tdDCC and related approaches, with a special focus on the methods used for analysis and evaluation of experiments.     

Diffusion NMR spectroscopy in supramolecular and combinatorial chemistry: an old parameter--new insights

Intermolecular interactions in solution play an important role in molecular recognition, which lies at the heart of supramolecular and combinatorial chemistry. Diffusion NMR spectroscopy gives information over such interactions and has become the method of choice for simultaneously measuring diffusion coefficients of multicomponent systems. The diffusion coefficient reflects the effective size and shape of a molecular species. Applications of this technique include the estimation of association constants and mapping the intermolecular interactions in multicomponent systems as well as investigating aggregation, ion pairing, encapsulation, and the size and structure of labile systems. Diffusion NMR spectroscopy can also be used to virtually separate mixtures and screen for specific ligands of different receptors, and may assist in finding lead compounds.     

Experimental and Computational Models for Side Chain Discrimination in Peptide–Protein Interactions

A bis(18-crown-6) Tröger's base receptor and 4-substituted hepta-1,7-diyl bisammonium salt ligands have been used as a model system to study the interactions between non-polar side chains of peptides and an aromatic cavity of a protein. NMR titrations and NOESY/ROESY NMR spectroscopy were used to analyze the discrimination of the ligands by the receptor based on the substituent of the ligand, both quantitatively (free binding energies) and qualitatively (conformations). The analysis showed that an all-anti conformation of the heptane chain was preferred for most of the ligands, both free and when bound to the receptor, and that for all of the receptor-ligand complexes, the substituent was located inside or partly inside of the aromatic cavity of the receptor. We estimated the free binding energy of a methyl- and a phenyl group to an aromatic cavity, via CH-π, and combined aromatic CH-π and π-π interactions to be −1.7 and −3.3 kJ mol⁻¹, respectively. The experimental results were used to assess the accuracy of different computational methods, including molecular mechanics (MM) and density functional theory (DFT) methods, showing that MM was superior.     

Supramolecular approaches to generate libraries of chelating bidentate ligands for homogeneous catalysis

The process of catalyst discovery and development relying on combinatorial methods has suffered so far from the difficult access to structurally diverse and large libraries of ligands, in particular the structurally more complex class of bidentate ligands. A completely new approach to streamline the difficult ligand synthesis process is to use structurally less complex monodentate ligands that self-assemble in the coordination sphere of a metal center through noncovalent attractive ligand-ligand interactions to generate bidentate, chelating ligands. When complementary attractive ligand-ligand interactions are employed, it is even possible to generate libraries of defined chelate-ligand catalysts by simply mixing two different monomeric ligands. This Minireview summarizes the first approaches and results in this new field of combinatorial homogeneous catalysis.     

Probing the phosphopeptide specificities of protein tyrosine phosphatases,SH2 and PTB domains with combinatorial library methods

Protein tyrosine phosphatases, SH2 and PTB domains are crucial elements for cellular signal transduction and regulation. Much effort has been directed towards elucidating their specificity in the past decade using a variety of approaches. Combinatorial library methods have contributed significantly to the understanding of substrate and ligand specificity of phosphoprotein recognizing domains. This review gives a brief overview of the structural characteristics of protein tyrosine phosphatases, SH2 and PTB domains and their binding to phosphopeptides. The chemical synthesis of peptides containing phosphotyrosine or phosphotyrosine mimics and the various formats of synthesis and deconvolution of combinatorial libraries are explained in detail. Examples are given as how different combinatorial libraries have been used to study the interaction of phosphopeptides with SH2 domains and phosphatases. The intrinsic advantages and difficulties of library synthesis, screening and deconvolution are pointed out. Finally, some experimental results on the substrate specificity of protein tyrosine phosphatase 1B and the SH2 domain of the adaptor protein Grb-2 are summarized and discussed.     

On‐Bead Screens Sample Narrower Affinity Ranges of Protein–Ligand Interactions Compared to Equivalent Solution Assays

Conceptually, on‐bead screening is one of the most efficient high‐throughput screening (HTS) methods. One of its inherent advantages is that the solid support has a dual function: it serves as a synthesis platform and as a screening compartment. Compound purification, cleavage and storage and extensive liquid handling are not necessary in bead‐based HTS. Since the establishment of one‐bead one‐compound library synthesis, the properties of polymer beads in chemical reactions have been thoroughly investigated. However, the characterization of the kinetics and thermodynamics of protein–ligand interactions on the beads used for screening has received much less attention. Consequently, the majority of reported on‐bead screens are based on empirically derived procedures, independent of measured equilibrium constants and rate constants of protein binding to ligands on beads. More often than not, on‐bead screens reveal apparent high affinity binders through strong protein complexation on the matrix of the solid support. After decoding, resynthesis, and solution testing the primary hits turn out to be unexpectedly weak binders, or may even fall out of the detection limit of the solution assay. Only a quantitative comparison of on‐bead binding and solution binding events will allow systematically investigating affinity differences as function of protein and small molecule properties. This will open up routes for optimized bead materials, blocking conditions and other improved assay procedures. By making use of the unique features of our previously introduced confocal nanoscanning (CONA) method, we investigated the kinetic and thermodynamic properties of protein–ligand interactions on TentaGel beads, a popular solid support for on‐bead screening. The data obtained from these experiments allowed us to determine dissociation constants for the interaction of bead‐immobilized ligands with soluble proteins. Our results therefore provide, for the first time, a comparison of on‐bead versus solution binding thermodynamics. Our data indicate that affinity ranges found in on‐bead screening are indeed narrower compared to equivalent interactions in homogeneous solution. A thorough physico‐chemical understanding of the molecular recognition between proteins and surface bound ligands will further strengthen the role of on‐bead screening as an ultimately cost‐effective method in hit and lead finding.     

Anticalins versus antibodies: made-to-order binding proteins for small molecules

Engineering proteins to bind small molecules presents a challenge as daunting as drug discovery, for both hinge upon our understanding of receptor-ligand molecular recognition. However, powerful techniques from combinatorial molecular biology can be used to rapidly select artificial receptors. While traditionally researchers have relied upon antibody technologies as a source of new binding proteins, the lipocalin scaffold has recently emerged as an adaptable receptor for small molecule binding. 'Anticalins', engineered lipocalin variants, offer some advantages over traditional antibody technology and illuminate features of molecular recognition between receptors and small molecule ligands.     

VoteDock: Consensus docking method for prediction of protein–ligand interactions

Molecular recognition plays a fundamental role in all biological processes, and that is why great efforts have been made to understand and predict protein–ligand interactions. Finding a molecule that can potentially bind to a target protein is particularly essential in drug discovery and still remains an expensive and time‐consuming task. In silico, tools are frequently used to screen molecular libraries to identify new lead compounds, and if protein structure is known, various protein–ligand docking programs can be used. The aim of docking procedure is to predict correct poses of ligand in the binding site of the protein as well as to score them according to the strength of interaction in a reasonable time frame. The purpose of our studies was to present the novel consensus approach to predict both protein–ligand complex structure and its corresponding binding affinity. Our method used as the input the results from seven docking programs (Surflex, LigandFit, Glide, GOLD, FlexX, eHiTS, and AutoDock) that are widely used for docking of ligands. We evaluated it on the extensive benchmark dataset of 1300 protein–ligands pairs from refined PDBbind database for which the structural and affinity data was available. We compared independently its ability of proper scoring and posing to the previously proposed methods. In most cases, our method is able to dock properly approximately 20% of pairs more than docking methods on average, and over 10% of pairs more than the best single program. The RMSD value of the predicted complex conformation versus its native one is reduced by a factor of 0.5 Å. Finally, we were able to increase the Pearson correlation of the predicted binding affinity in comparison with the experimental value up to 0.5. © 2010 Wiley Periodicals, Inc. J Comput Chem 32: 568–581, 2011     

NMR spectroscopy techniques for screening and identifying ligand binding to protein receptors

Binding events of ligands to receptors are the key for an understanding of biological processes. Gaining insight into protein-protein and protein-ligand interactions in solution has recently become possible on an atomic level by new NMR spectroscopic techniques. These experiments identify binding events either by looking at the resonance signals of the ligand or the protein. Ideally, both techniques together deliver a complete picture of ligand binding to a receptor. The approaches discussed in this review allow screening of compound libraries as well as a detailed identification of the groups involved in the binding events. Also, characterization of the binding strength and kinetics is possible, competitive binding as well as allosteric effects can be identified, and it has even been possible to identify ligand binding to intact viruses and membrane-bound proteins.     

Grafting and thermal stripping of organo-bimetallic clusters on AU surfaces: toward controlled CO/RU aggregates

The controlled stoichiometry of heterometallic carbonyl clusters make them attractive precursors for the stabilization of bare metal alloy clusters for magnetic applications. The mixed-metal molecular cluster [RuCo3(H)(CO)12] has been functionalized with the phosphane-thiol ligand Ph2PCH2CH2SH to allow subsequent anchoring on a gold surface. The resulting tetrahedral cluster [RuCo3(H)(CO)11(Ph2PCH2CH2SH)] (1) has been characterized by X-ray diffraction and the P-monodentate ligand is axially bound to a cobalt center and trans to the ruthenium cap. This synthesis also yielded the product of oxidative coupling, in which two SH groups were coupled intermolecularly to give a disulfide ligand that links two tetrahedral cluster units in [{RuCo3(H)(CO)11(Ph2PCH2CH2S)}2] (2). This cluster has also been characterized by X-ray diffractions studies. After deposition of 1 on a Au(111) surface by self-assembly, the carbonyl ligands were stripped off by thermal annealing in ultra-high vacuum (UHV) to form a metallic species. X-ray photoelectron spectroscopic measurements performed as a function of the annealing temperature show that the cobalt and ruthenium centers converge towards metallic character and that the stoichiometry of the alloy is retained during the annealing process. Preliminary X-ray absorption spectroscopy (XAS) synchrotron experiments indicate that clusters 1 and 2 behave similarly, which is consistent with the retention of their tetrahedral units on the gold surface after transformation of the thiol function or breaking of the disulfide bond to form Au--S bonds, respectively, has occurred.     

Multi‐Objective Molecular De Novo Design by Adaptive Fragment Prioritization

We present the development and application of a computational molecular de novo design method for obtaining bioactive compounds with desired on‐ and off‐target binding. The approach translates the nature‐inspired concept of ant colony optimization to combinatorial building block selection. By relying on publicly available structure–activity data, we developed a predictive quantitative polypharmacology model for 640 human drug targets. By taking reductive amination as an example of a privileged reaction, we obtained novel subtype‐selective and multitarget‐modulating dopamine D₄ antagonists, as well as ligands selective for the sigma‐1 receptor with accurately predicted affinities. The nanomolar potencies of the hits obtained, their high ligand efficiencies, and an overall success rate of 90 % demonstrate that this ligand‐based computer‐aided molecular design method may guide target‐focused combinatorial chemistry.     

Synthesis of 5-, 6- and 7-substituted-2-aminoquinolines as SH3 domain ligands

The Src homology 3 (SH3) domains are small protein-protein interaction domains that mediate a range of important biological processes and are considered valuable targets for the development of therapeutic agents. We have been developing 2-aminoquinolines as ligands for SH3 domains--so far the only reported examples of entirely small-molecule ligands for the SH3 domains. The highest affinity 2-aminoquinolines so far identified are 6-substituted compounds. In this article, the synthesis of several new 2-aminoquinolines, including 5-, 6- and 7-substituted compounds, for Tec SH3 domain ligand binding studies is presented. As a part of the synthetic investigation, the utility of different methods for the synthesis of 2-aminoquinolines was explored and potentially powerful methods were identified for the synthesis of 2-aminoquinolines with diverse functionality. Of the compounds prepared, the 5-substituted-2-aminoquinolines generally bound with similar affinities to unsubstituted 2-aminoquinoline, whilst the 7-substituted compounds generally bound with similar or lower affinity than unsubstituted 2-aminoquinoline. However, the 6-substituted-2-aminoquinolines generally bound with significantly higher affinity than unsubstituted 2-aminoquinoline. In addition, one 6-substituted-N-benzylated-2-aminoquinoline was also tested for SH3 binding and some evidence for the formation of additional contacts at other regions of the SH3 domain was found. These results provide new and useful SAR information that should greatly assist with the challenge of developing high affinity small-molecule ligands for the SH3 domains.     

Computational combinatorial ligand design: Application to human α-thrombin

Summary A new method is presented for computer-aided ligand design by combinatorial selection of fragments that bind favorably to a macromolecular target of known three-dimensional structure. Firstly, the multiple-copy simultaneous-search procedure (MCSS) is used to exhaustively search for optimal positions and orientations of functional groups on the surface of the macromolecule (enzyme or receptor fragment). The MCSS minima are then sorted according to an approximated binding free energy, whose solvation component is expressed as a sum of separate electrostatic and nonpolar contributions. The electrostatic solvation energy is calculated by the numerical solution of the linearized Poisson-Boltzmann equation, while the nonpolar contribution to the binding free energy is assumed to be proportional to the loss in solvent-accessible surface area. The program developed for computational combinatorial ligand design (CCLD) allows the fast and automatic generation of a multitude of highly diverse compounds, by connecting in a combinatorial fashion the functional groups in their minimized positions. The fragments are linked as two atoms may be either fused, or connected by a covalent bond or a small linker unit. To avoid the combinatorial explosion problem, pruning of the growing ligand is performed according to the average value of the approximated binding free energy of its fragments. The method is illustrated here by constructing candidate ligands for the active site of human -thrombin. The MCSS minima with favorable binding free energy reproduce the interaction patterns of known inhibitors. Starting from these fragments, CCLD generates a set of compounds that are closely related to high-affinity thrombin inhibitors. In addition, putative ligands with novel binding motifs are suggested. Probable implications of the MCSS-CCLD approach for the evolving scenario of drug discovery are discussed.     

Site‐Specific Investigation of the Steady‐State Kinetics and Dynamics of the Multistep Binding of Bile Acid Molecules to a Lipid Carrier Protein

The investigation of multi‐site ligand–protein binding and multi‐step mechanisms is highly demanding. In this work, advanced NMR methodologies such as 2D ¹H–¹⁵N line‐shape analysis, which allows a reliable investigation of ligand binding occurring on micro‐ to millisecond timescales, have been extended to model a two‐step binding mechanism. The molecular recognition and complex uptake mechanism of two bile salt molecules by lipid carriers is an interesting example that shows that protein dynamics has the potential to modulate the macromolecule–ligand encounter. Kinetic analysis supports a conformational selection model as the initial recognition process in which the dynamics observed in the apo form is essential for ligand uptake, leading to conformations with improved access to the binding cavity. Subsequent multi‐step events could be modelled, for several residues, with a two‐step binding mechanism. The protein in the ligand‐bound state still exhibits a conformational rearrangement that occurs on a very slow timescale, as observed for other proteins of the family. A global mechanism suggesting how bile acids access the macromolecular cavity is thus proposed.     

On the Role of Flexibility in Protein–Ligand Interactions: the Example of p53 Tetramerization Domain

The recognition of protein surfaces by designed ligands has become an attractive approach in drug discovery. However, the variable nature and irregular behavior of protein surfaces defy this new area of research. The easy to understand “lock‐and‐key” model is far from being the ideal paradigm in biomolecular interactions and, hence, any new finding on how proteins and ligands behave in recognition events paves a step of the way. Herein, we illustrate a clear example on how an increase in flexibility of both protein and ligand can result in an increase in the stability of the macromolecular complex. The biophysical study of the interaction between a designed flexible tetraguanidinium‐calix[4]arene and the tetramerization domain of protein p53 (p53TD) and its natural mutant p53TD‐R337H shows how the floppy mutant domain interacts more tightly with the ligand than the well‐packed wild‐type protein. Moreover, the flexible calixarene ligand interacts with higher affinity to both wild‐type and mutated protein domains than a conformationally rigid calixarene analog previously reported. These findings underscore the crucial role of flexibility in molecular recognition processes, for both small ligands and large biomolecular surfaces.     

Utilization of self-sorting processes to generate dynamic combinatorial libraries with new network topologies

The synthesis of water-soluble, organometallic macrocycles is described. They were obtained by self-assembly in reactions of the half-sandwich complexes [[Ru(C6H5Me)Cl2]2], [[Ru(p-cymene)Cl2]2], [[Rh(Cp)Cl2]2], and [[Ir(Cp*)Cl2]2] with the ligand 5-dimethylaminomethyl-3-hydroxy-2-methyl-4-(1H)-pyridone in buffered aqueous solution at pH 8. The structure of the Ru-(p-cymene) complex was determined by single-crystal X-ray crystallography. Upon mixing, these complexes undergo scrambling reactions to give dynamic combinatorial libraries. In combination with structurally related complexes based on amino-methylated 3-hydroxy-2-(1H)-pyridone ligands, an exchange of metal fragments but no mixing of ligands was observed. This self-sorting behavior was used to construct dynamic combinatorial libraries of macrocycles, in which two four-component sub-libraries are connected by two common building blocks. This type of network topology influences the adaptive behavior of the library as demonstrated in selection experiments with lithium ions as the target.