In Silico Veritas: The Pitfalls and Challenges of Predicting GPCR-Ligand Interactions

Tetrahydroisoquinoline CXCR4 Antagonists Adopt a Hybrid Binding Mode within the Peptide Subpocket of the CXCR4 Receptor

The rationale for the structural and mechanistic basis of a tetrahydroisoquinoline (THIQ) based series of CXCR4 antagonists is presented. Using the previously reported crystal structures which reveal two distinct binding sites of CXCR4 defined as the small molecule (IT1t or minor) binding pocket and peptide (CVX15 or major) binding pocket, we hypothesized our THIQ small molecule series could bind like either molecule in these respective receptor configurations (IT1t versus CVX15 based poses). To this end, a thorough investigation was performed through a combination of receptor mutation studies, medicinal chemistry, biological testing, conformational analysis, and flexible docking. Our findings showed that the CVX15 peptide-based CXCR4 receptor complexes (red pose) were consistently favored over the small molecule IT1t based CXCR4 receptor configurations (blue pose) to correctly explain the computational and mutational studies as well as key structural components of activity for these small molecules.

Aminergic GPCR-Ligand Interactions: A Chemical and Structural Map of Receptor Mutation Data

The aminergic family of G protein-coupled receptors (GPCRs) plays an important role in various diseases and represents a major drug discovery target class. Structure determination of all major aminergic subfamilies has enabled structure-based ligand design for these receptors. Site-directed mutagenesis data provides an invaluable complementary source of information for elucidating the structural determinants of binding of different ligand chemotypes. The current study provides a comparative analysis of 6692 mutation data points on 34 aminergic GPCR subtypes, covering the chemical space of 540 unique ligands from mutagenesis experiments and information from experimentally determined structures of 52 distinct aminergic receptor-ligand complexes. The integrated analysis enables detailed investigation of structural receptor-ligand interactions and assessment of the transferability of combined binding mode and mutation data across ligand chemotypes and receptor subtypes. An overview is provided of the possibilities and limitations of using mutation data to guide the design of novel aminergic receptor ligands.

Structural Analysis of Chemokine Receptor-Ligand Interactions

This review focuses on the construction and application of structural chemokine receptor models for the elucidation of molecular determinants of chemokine receptor modulation and the structure-based discovery and design of chemokine receptor ligands. A comparative analysis of ligand binding pockets in chemokine receptors is presented, including a detailed description of the CXCR4, CCR2, CCR5, CCR9, and US28 X-ray structures, and their implication for modeling molecular interactions of chemokine receptors with small-molecule ligands, peptide ligands, and large antibodies and chemokines. These studies demonstrate how the integration of new structural information on chemokine receptors with extensive structure–activity relationship and site-directed mutagenesis data facilitates the prediction of the structure of chemokine receptor–ligand complexes that have not been crystallized. Finally, a review of structure-based ligand discovery and design studies based on chemokine receptor crystal structures and homology models illustrates the possibilities and challenges to find novel ligands for chemokine receptors.

A Molecular Pharmacologist's Guide to G Protein-Coupled Receptor Crystallography

G protein-coupled receptor (GPCR) structural biology has progressed dramatically in the last decade. There are now over 120 GPCR crystal structures deposited in the Protein Data Bank of 32 different receptors from families scattered across the phylogenetic tree, including class B, C, and Frizzled GPCRs. These structures have been obtained in combination with a wide variety of ligands and captured in a range of conformational states. This surge in structural knowledge has enlightened research into the molecular recognition of biologically active molecules, the mechanisms of receptor activation, the dynamics of functional selectivity, and fueled structure-based drug design efforts for GPCRs. Here we summarize the innovations in both protein engineering/molecular biology and crystallography techniques that have led to these advances in GPCR structural biology and discuss how they may influence the resulting structural models. We also provide a brief molecular pharmacologist's guide to GPCR X-ray crystallography, outlining some key aspects in the process of structure determination, with the goal to encourage noncrystallographers to interrogate structures at the molecular level. Finally, we show how chemogenomics approaches can be used to marry the wealth of existing receptor pharmacology data with the expanding repertoire of structures, providing a deeper understanding of the mechanistic details of GPCR function.

Generic GPCR residue numbers - aligning topology maps while minding the gaps

Generic residue numbers facilitate comparisons of, for example, mutational effects, ligand interactions, and structural motifs. The numbering scheme by Ballesteros and Weinstein for residues within the class A GPCRs (G protein-coupled receptors) has more than 1100 citations, and the recent crystal structures for classes B, C, and F now call for a community consensus in residue numbering within and across these classes. Furthermore, the structural era has uncovered helix bulges and constrictions that offset the generic residue numbers. The use of generic residue numbers depends on convenient access by pharmacologists, chemists, and structural biologists. We review the generic residue numbering schemes for each GPCR class, as well as a complementary structure-based scheme, and provide illustrative examples and GPCR database (GPCRDB) web tools to number any receptor sequence or structure.

Strategies for improved modeling of GPCR-drug complexes: blind predictions of serotonin receptors bound to ergotamine

The recent increase in the number of atomic-resolution structures of G protein-coupled receptors (GPCRs) has contributed to a deeper understanding of ligand binding to several important drug targets. However, reliable modeling of GPCR-ligand complexes for the vast majority of receptors with unknown structure remains to be one of the most challenging goals for computer-aided drug design. The GPCR Dock 2013 assessment, in which researchers were challenged to predict the crystallographic structures of serotonin 5-HT(1B) and 5-HT(2B) receptors bound to ergotamine, provided an excellent opportunity to benchmark the current state of this field. Our contributions to GPCR Dock 2013 accurately predicted the binding mode of ergotamine with RMSDs below 1.8 Å for both receptors, which included the best submissions for the 5-HT(1B) complex. Our models also had the most accurate description of the binding sites and receptor-ligand contacts. These results were obtained using a ligand-guided homology modeling approach, which combines extensive molecular docking screening with incorporation of information from multiple crystal structures and experimentally derived restraints. In this work, we retrospectively analyzed thousands of structures that were generated during the assessment to evaluate our modeling strategies. Major contributors to accuracy were found to be improved modeling of extracellular loop two in combination with the use of molecular docking to optimize the binding site for ligand recognition. Our results suggest that modeling of GPCR-drug complexes has reached a level of accuracy at which structure-based drug design could be applied to a large number of pharmaceutically relevant targets.

C(X)CR in silico: Computer-aided prediction of chemokine receptor-ligand interactions

This review will focus on the construction, refinement, and validation of chemokine receptor models for the purpose of structure-based virtual screening and ligand design. The review will present a comparative analysis of ligand binding pockets in chemokine receptors, including a review of the recently released CXCR4 X-ray structures, and their implication on chemokine receptor (homology) modeling. The recommended protein-ligand modeling procedure as well as the use of experimental anchors to steer the modeling procedure is discussed and an overview of several successful structure-based ligand discovery and design studies is provided. This review shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands for chemokine receptors.:

Current progress in Structure-Based Rational Drug Design marks a new mindset in drug discovery

The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented.

Flexible protein-ligand docking using the Fleksy protocol

Considering protein plasticity is important in accurately predicting the three-dimensional geometry of protein-ligand complexes. Here, we present the first public release of our flexible docking tool Fleksy, which is able to consider both ligand and protein flexibility in the docking process. We describe the workflow and different features of the software and present its performance on two cross-docking benchmark datasets.

Structure-based ligand discovery for the protein-protein interface of chemokine receptor CXCR4

G-protein-coupled receptors (GPCRs) are key signaling molecules and are intensely studied. Whereas GPCRs recognizing small-molecules have been successfully targeted for drug discovery, protein-recognizing GPCRs, such as the chemokine receptors, claim few drugs or even useful small molecule reagents. This reflects both the difficulties that attend protein-protein interface inhibitor discovery, and the lack of structures for these targets. Imminent structure determination of chemokine receptor CXCR4 motivated docking screens for new ligands against a homology model and subsequently the crystal structure. More than 3 million molecules were docked against the model and then against the crystal structure; 24 and 23 high-scoring compounds from the respective screens were tested experimentally. Docking against the model yielded only one antagonist, which resembled known ligands and lacked specificity, whereas the crystal structure docking yielded four that were dissimilar to previously known scaffolds and apparently specific. Intriguingly, several were potent and relatively small, with IC(50) values as low as 306 nM, ligand efficiencies as high as 0.36, and with efficacy in cellular chemotaxis. The potency and efficiency of these molecules has few precedents among protein-protein interface inhibitors, and supports structure-based efforts to discover leads for chemokine GPCRs.

Drug design for ever, from hype to hope

In its first 25 years JCAMD has been disseminating a large number of techniques aimed at finding better medicines faster. These include genetic algorithms, COMFA, QSAR, structure based techniques, homology modelling, high throughput screening, combichem, and dozens more that were a hype in their time and that now are just a useful addition to the drug-designers toolbox. Despite massive efforts throughout academic and industrial drug design research departments, the number of FDA-approved new molecular entities per year stagnates, and the pharmaceutical industry is reorganising accordingly. The recent spate of industrial consolidations and the concomitant move towards outsourcing of research activities requires better integration of all activities along the chain from bench to bedside. The next 25 years will undoubtedly show a series of translational science activities that are aimed at a better communication between all parties involved, from quantum chemistry to bedside and from academia to industry. This will above all include understanding the underlying biological problem and optimal use of all available data.

Molecular determinants of ligand binding modes in the histamine H(4) receptor: linking ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR) models to in silico guided receptor mutagenesis studies

The histamine H(4) receptor (H(4)R) is a G protein-coupled receptor (GPCR) that plays an important role in inflammation. Similar to the homologous histamine H(3) receptor (H(3)R), two acidic residues in the H(4)R binding pocket, D(3.32) and E(5.46), act as essential hydrogen bond acceptors of positively ionizable hydrogen bond donors in H(4)R ligands. Given the symmetric distribution of these complementary pharmacophore features in H(4)R and its ligands, different alternative ligand binding mode hypotheses have been proposed. The current study focuses on the elucidation of the molecular determinants of H(4)R-ligand binding modes by combining (3D) quantitative structure-activity relationship (QSAR), protein homology modeling, molecular dynamics simulations, and site-directed mutagenesis studies. We have designed and synthesized a series of clobenpropit (N-(4-chlorobenzyl)-S-[3-(4(5)-imidazolyl)propyl]isothiourea) derivatives to investigate H(4)R-ligand interactions and ligand binding orientations. Interestingly, our studies indicate that clobenpropit (2) itself can bind to H(4)R in two distinct binding modes, while the addition of a cyclohexyl group to the clobenpropit isothiourea moiety allows VUF5228 (5) to adopt only one specific binding mode in the H(4)R binding pocket. Our ligand-steered, experimentally supported protein modeling method gives new insights into ligand recognition by H(4)R and can be used as a general approach to elucidate the structure of protein-ligand complexes.