Structure-based virtual screening for fragment-like ligands of the G protein-coupled histamine H4 receptor

We have explored the possibilities and challenges of structure-based virtual screening (SBVS) against the human histamine H4 receptor (H4R), a key player in inflammatory responses. Several SBVS strategies, employing different H4R ligand conformations, were validated and optimized with respect to their ability to discriminate small fragment-like H4R ligands from true inactive fragments, and compared to ligand-based virtual screening (LBVS) approaches. SBVS studies with a molecular interaction fingerprint (IFP) scoring method enabled the identification of H4R ligands that were not identified in LBVS runs, demonstrating the scaffold hopping potential of combining molecular docking and IFP scoring. Retrospective VS evaluations against H4R homology models based on the histamine H1 receptor (H1R) crystal structure did not give higher enrichments of H4R ligands than H4R models based on the beta-2 adrenergic receptor (β2R). Complementary prospective SBVS studies against β2R-based and H1R-based H4R homology models led to the discovery of different new fragment-like H4R ligand chemotypes. Of the 37 tested compounds, 9 fragments (representing 5 different scaffolds) had affinities between 0.14 and 6.3 μM at the H4R.

[1]  Christopher W Murray,et al.  Experiences in fragment-based drug discovery. , 2012, Trends in pharmacological sciences.

[2]  John P. Overington,et al.  ChEMBL: a large-scale bioactivity database for drug discovery , 2011, Nucleic Acids Res..

[3]  R. Stevens,et al.  Crystal structure-based virtual screening for fragment-like ligands of the human histamine H(1) receptor. , 2011, Journal of medicinal chemistry.

[4]  O. Zuiderveld,et al.  Combining Quantum Mechanical Ligand Conformation Analysis and Protein Modeling to Elucidate GPCR–Ligand Binding Modes , 2013, ChemMedChem.

[5]  Xueliang Fang,et al.  Molecular modeling of the three-dimensional structure of dopamine 3 (D3) subtype receptor: discovery of novel and potent D3 ligands through a hybrid pharmacophore- and structure-based database searching approach. , 2003, Journal of medicinal chemistry.

[6]  J. Ballesteros,et al.  [19] Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptors , 1995 .

[7]  C. de Graaf,et al.  The Receptor Concept in 3D: From Hypothesis and Metaphor to GPCR–Ligand Structures , 2014, Neurochemical Research.

[8]  G. Schneider,et al.  Homology Model Adjustment and Ligand Screening with a Pseudoreceptor of the Human Histamine H4 Receptor , 2009, ChemMedChem.

[9]  Ruben Abagyan,et al.  Status of GPCR modeling and docking as reflected by community-wide GPCR Dock 2010 assessment. , 2011, Structure.

[10]  Gebhard F. X. Schertler,et al.  Structure of a β1-adrenergic G-protein-coupled receptor , 2008, Nature.

[11]  T. O'Brien,et al.  Fragment-based drug discovery. , 2004, Journal of medicinal chemistry.

[12]  Didier Rognan,et al.  Fragment-based approaches and computer-aided drug discovery. , 2012, Topics in current chemistry.

[13]  Brian K. Shoichet,et al.  ZINC - A Free Database of Commercially Available Compounds for Virtual Screening , 2005, J. Chem. Inf. Model..

[14]  Peter Willett,et al.  Heuristics for Similarity Searching of Chemical Graphs Using a Maximum Common Edge Subgraph Algorithm , 2002, J. Chem. Inf. Comput. Sci..

[15]  Jonathan A. Javitch,et al.  Structure of the Human Dopamine D3 Receptor in Complex with a D2/D3 Selective Antagonist , 2010, Science.

[16]  Béla Noszál,et al.  Discovery of novel human histamine H4 receptor ligands by large-scale structure-based virtual screening. , 2008, Journal of medicinal chemistry.

[17]  R. Smits,et al.  Fragment library screening reveals remarkable similarities between the G protein-coupled receptor histamine H4 and the ion channel serotonin 5-HT3A , 2011, Bioorganic & medicinal chemistry letters.

[18]  D. E. Clark,et al.  Identification and hit-to-lead exploration of a novel series of histamine H4 receptor inverse agonists. , 2010, Bioorganic & medicinal chemistry letters.

[19]  Hualiang Jiang,et al.  Structural Basis for Molecular Recognition at Serotonin Receptors , 2013, Science.

[20]  Dennis M. Krüger,et al.  Comparison of Structure‐ and Ligand‐Based Virtual Screening Protocols Considering Hit List Complementarity and Enrichment Factors , 2010, ChemMedChem.

[21]  R. Smits,et al.  The emerging role of the histamine H4 receptor in anti-inflammatory therapy. , 2006, Current topics in medicinal chemistry.

[22]  Austin B. Yongye,et al.  Identification, structure-activity relationships and molecular modeling of potent triamine and piperazine opioid ligands. , 2009, Bioorganic & medicinal chemistry.

[23]  Agonist/antagonist modulation in a series of 2-aryl benzimidazole H4 receptor ligands. , 2010, Bioorganic & medicinal chemistry letters.

[24]  Richard J. Hall,et al.  Docking performance of fragments and druglike compounds. , 2011, Journal of medicinal chemistry.

[25]  Rob Leurs,et al.  Transforming fragments into candidates: small becomes big in medicinal chemistry. , 2009, Drug discovery today.

[26]  R. Stevens,et al.  High-Resolution Crystal Structure of an Engineered Human β2-Adrenergic G Protein–Coupled Receptor , 2007, Science.

[27]  E. Haaksma,et al.  Design and pharmacological characterization of VUF14480, a covalent partial agonist that interacts with cysteine 983.36 of the human histamine H4 receptor , 2013, British journal of pharmacology.

[28]  I. D. de Esch,et al.  Phenylalanine 169 in the Second Extracellular Loop of the Human Histamine H4 Receptor Is Responsible for the Difference in Agonist Binding between Human and Mouse H4 Receptors , 2008, Journal of Pharmacology and Experimental Therapeutics.

[29]  R. Smits,et al.  Major advances in the development of histamine H4 receptor ligands. , 2009, Drug discovery today.

[30]  R. Smits,et al.  Synthesis and QSAR of quinazoline sulfonamides as highly potent human histamine H4 receptor inverse agonists. , 2010, Journal of medicinal chemistry.

[31]  Marta Filizola,et al.  Modern homology modeling of G-protein coupled receptors: which structural template to use? , 2009, Journal of medicinal chemistry.

[32]  Ruben Abagyan,et al.  Structure-based discovery of novel chemotypes for adenosine A(2A) receptor antagonists. , 2010, Journal of medicinal chemistry.

[33]  Krzysztof Palczewski,et al.  The Significance of G Protein-Coupled Receptor Crystallography for Drug Discovery , 2011, Pharmacological Reviews.

[34]  Gilles Marcou,et al.  Optimizing Fragment and Scaffold Docking by Use of Molecular Interaction Fingerprints , 2007, J. Chem. Inf. Model..

[35]  György M. Keserü,et al.  The Impact of Molecular Dynamics Sampling on the Performance of Virtual Screening against GPCRs , 2013, J. Chem. Inf. Model..

[36]  M. Congreve,et al.  A 'rule of three' for fragment-based lead discovery? , 2003, Drug discovery today.

[37]  Rob Leurs,et al.  Evaluation of Histamine H1-, H2-, and H3-Receptor Ligands at the Human Histamine H4 Receptor: Identification of 4-Methylhistamine as the First Potent and Selective H4 Receptor Agonist , 2005, Journal of Pharmacology and Experimental Therapeutics.

[38]  Chris de Graaf,et al.  From three-dimensional GPCR structure to rational ligand discovery. , 2014, Advances in experimental medicine and biology.

[39]  Saskia Nijmeijer,et al.  Virtual Fragment Screening: Discovery of Histamine H3 Receptor Ligands Using Ligand-Based and Protein-Based Molecular Fingerprints , 2012, J. Chem. Inf. Model..

[40]  M. Babu,et al.  Molecular signatures of G-protein-coupled receptors , 2013, Nature.

[41]  G. Keserű,et al.  Fragment-based lead discovery on G-protein-coupled receptors , 2013, Expert opinion on drug discovery.

[42]  R. Abagyan,et al.  Conserved binding mode of human beta2 adrenergic receptor inverse agonists and antagonist revealed by X-ray crystallography. , 2010, Journal of the American Chemical Society.

[43]  R. Stevens,et al.  Structure-function of the G protein-coupled receptor superfamily. , 2013, Annual review of pharmacology and toxicology.

[44]  Claudio N. Cavasotto,et al.  Docking-based virtual screening for ligands of G protein-coupled receptors: not only crystal structures but also in silico models. , 2011, Journal of molecular graphics & modelling.

[45]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[46]  Gerhard Klebe,et al.  Comparison of Automatic Three-Dimensional Model Builders Using 639 X-ray Structures , 1994, J. Chem. Inf. Comput. Sci..

[47]  Ola Engkvist,et al.  Molecular modeling of the second extracellular loop of G‐protein coupled receptors and its implication on structure‐based virtual screening , 2008, Proteins.

[48]  Avner Schlessinger,et al.  Ligand Discovery from a Dopamine D3 Receptor Homology Model and Crystal Structure , 2011, Nature chemical biology.

[49]  Wen Jiang,et al.  Molecular Determinants of Ligand Binding to H4R Species Variants , 2010, Molecular Pharmacology.

[50]  Thomas Stützle,et al.  An ant colony optimization approach to flexible protein–ligand docking , 2007, Swarm Intelligence.

[51]  Didier Rognan,et al.  Customizing G Protein-coupled receptor models for structure-based virtual screening. , 2009, Current pharmaceutical design.

[52]  G. Hessler,et al.  The scaffold hopping potential of pharmacophores. , 2010, Drug discovery today. Technologies.

[53]  R. Leurs,et al.  Detailed analysis of biased histamine H4 receptor signalling by JNJ 7777120 analogues , 2013, British journal of pharmacology.

[54]  A. Strasser,et al.  Paradoxical Stimulatory Effects of the “Standard” Histamine H4-Receptor Antagonist JNJ7777120: the H4 Receptor Joins the Club of 7 Transmembrane Domain Receptors Exhibiting Functional Selectivity , 2011, Molecular Pharmacology.

[55]  Ajay N. Jain,et al.  Recommendations for evaluation of computational methods , 2008, J. Comput. Aided Mol. Des..

[56]  Saskia Nijmeijer,et al.  Small and colorful stones make beautiful mosaics: fragment-based chemogenomics. , 2013, Drug Discovery Today.

[57]  Anna Whyatt,et al.  Notes and references , 1984, International Journal of Legal Information : Official Publication.

[58]  Márton Vass,et al.  Virtual fragment screening on GPCRs: a case study on dopamine D3 and histamine H4 receptors. , 2014, European journal of medicinal chemistry.

[59]  Ruben Abagyan,et al.  Structure of the human histamine H1 receptor complex with doxepin , 2011, Nature.

[60]  Iwan J. P. de Esch,et al.  Delineation of Agonist Binding to the Human Histamine H4 Receptor Using Mutational Analysis, Homology Modeling, and ab Initio Calculations , 2008, J. Chem. Inf. Model..

[61]  K. Jacobson,et al.  New Insights for Drug Design from the X-Ray Crystallographic Structures of G-Protein-Coupled Receptors , 2012, Molecular Pharmacology.

[62]  A. Leach,et al.  Molecular complexity and fragment-based drug discovery: ten years on. , 2011, Current opinion in chemical biology.

[63]  Chris de Graaf,et al.  From heptahelical bundle to hits from the Haystack: structure-based virtual screening for GPCR ligands. , 2013, Methods in enzymology.

[64]  R. Leurs,et al.  A structural chemogenomics analysis of aminergic GPCRs: lessons for histamine receptor ligand design , 2013, British journal of pharmacology.

[65]  Gregg Siegal,et al.  Fragment screening of stabilized G-protein-coupled receptors using biophysical methods. , 2011, Methods in enzymology.

[66]  Maria F. Sassano,et al.  Conformation Guides Molecular Efficacy in Docking Screens of Activated β-2 Adrenergic G Protein Coupled Receptor , 2013, ACS chemical biology.

[67]  Michael M. Mysinger,et al.  Structure-based ligand discovery for the protein–protein interface of chemokine receptor CXCR4 , 2012, Proceedings of the National Academy of Sciences.

[68]  S. Charlton,et al.  Agonist-Biased Signaling at the Histamine H4 Receptor: JNJ7777120 Recruits β-Arrestin without Activating G Proteins , 2011, Molecular Pharmacology.

[69]  S. P. Andrews,et al.  Structure‐Based and Fragment‐Based GPCR Drug Discovery , 2014, ChemMedChem.

[70]  Saskia Nijmeijer,et al.  Combinatorial Consensus Scoring for Ligand-Based Virtual Fragment Screening: A Comparative Case Study for Serotonin 5-HT3A, Histamine H1, and Histamine H4 Receptors , 2015, J. Chem. Inf. Model..

[71]  Y. Cheng,et al.  Relationship between the inhibition constant (K1) and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an enzymatic reaction. , 1973, Biochemical pharmacology.

[72]  Miles Congreve,et al.  Structure-based drug design for G protein-coupled receptors. , 2014, Progress in medicinal chemistry.

[73]  I. D. de Esch,et al.  En route to new blockbuster anti-histamines: surveying the offspring of the expanding histamine receptor family. , 2011, Trends in pharmacological sciences.

[74]  David Rodríguez,et al.  Structure-based discovery of selective serotonin 5-HT(1B) receptor ligands. , 2014, Structure.

[75]  Thomas Stützle,et al.  Empirical Scoring Functions for Advanced Protein-Ligand Docking with PLANTS , 2009, J. Chem. Inf. Model..

[76]  Tudor I. Oprea,et al.  Property distribution of drug-related chemical databases* , 2000, J. Comput. Aided Mol. Des..

[77]  R. Smits,et al.  Discovery of quinazolines as histamine H4 receptor inverse agonists using a scaffold hopping approach. , 2008, Journal of medicinal chemistry.

[78]  Gerrit Groenhof,et al.  GROMACS: Fast, flexible, and free , 2005, J. Comput. Chem..

[79]  F. Monsma,et al.  Molecular modeling and site-specific mutagenesis of the histamine-binding site of the histamine H4 receptor. , 2002, Molecular pharmacology.

[80]  Gregg Siegal,et al.  Fragment screening of GPCRs using biophysical methods: identification of ligands of the adenosine A(2A) receptor with novel biological activity. , 2012, ACS chemical biology.

[81]  Sid Topiol,et al.  Use of the X-ray structure of the Beta2-adrenergic receptor for drug discovery. , 2008, Bioorganic & medicinal chemistry letters.

[82]  David Rogers,et al.  Extended-Connectivity Fingerprints , 2010, J. Chem. Inf. Model..

[83]  Cathy H. Wu,et al.  The Universal Protein Resource (UniProt): an expanding universe of protein information , 2005, Nucleic Acids Res..

[84]  I. D. de Esch,et al.  Molecular determinants of selective agonist and antagonist binding to the histamine H₄ receptor. , 2011, Current topics in medicinal chemistry.

[85]  R. Leurs,et al.  Analysis of Multiple Histamine H4 Receptor Compound Classes Uncovers Gαi Protein- and β-Arrestin2-Biased Ligands , 2012, Molecular Pharmacology.

[86]  Saskia Nijmeijer,et al.  Mapping histamine H4 receptor–ligand binding modes , 2013 .

[87]  Thierry Kogej,et al.  Comparison of Molecular Fingerprint Methods on the Basis of Biological Profile Data , 2009, J. Chem. Inf. Model..

[88]  Leonardo Pardo,et al.  An Activation Switch in the Rhodopsin Family of G Protein-coupled Receptors , 2005, Journal of Biological Chemistry.

[89]  A. Kruse,et al.  Structure of the human M2 muscarinic acetylcholine receptor bound to an antagonist , 2011, Nature.

[90]  M. Zweig,et al.  Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. , 1993, Clinical chemistry.

[91]  I. D. de Esch,et al.  A chemical switch for the modulation of the functional activity of higher homologues of histamine on the human histamine H3 receptor: effect of various substitutions at the primary amino function. , 2006, Journal of medicinal chemistry.

[92]  T. Klabunde,et al.  Structure-based drug discovery using GPCR homology modeling: successful virtual screening for antagonists of the alpha1A adrenergic receptor. , 2005, Journal of medicinal chemistry.

[93]  Chris G. Kruse,et al.  Assessment of scaffold hopping efficiency by use of molecular interaction fingerprints. , 2008, Journal of medicinal chemistry.

[94]  Adriaan P. IJzerman,et al.  Complementarity between in Silico and Biophysical Screening Approaches in Fragment-Based Lead Discovery against the A2A Adenosine Receptor , 2013, J. Chem. Inf. Model..

[95]  Saskia Nijmeijer,et al.  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. , 2011, Journal of medicinal chemistry.

[96]  A. Strasser,et al.  Molecular determinants for the high constitutive activity of the human histamine H4 receptor: functional studies on orthologues and mutants , 2015, British journal of pharmacology.

[97]  Susan M. Boyd,et al.  Fragment library design: efficiently hunting drugs in chemical space. , 2010, Drug discovery today. Technologies.

[98]  Albert C. Pan,et al.  Structure and Dynamics of the M3 Muscarinic Acetylcholine Receptor , 2012, Nature.

[99]  Ruben Abagyan,et al.  Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: meeting new challenges. , 2014, Structure.

[100]  Saskia Nijmeijer,et al.  Triazole ligands reveal distinct molecular features that induce histamine H4 receptor affinity and subtly govern H4/H3 subtype selectivity. , 2011, Journal of medicinal chemistry.

[101]  Xavier Robin,et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves , 2011, BMC Bioinformatics.

[102]  Woody Sherman,et al.  Computational approaches for fragment-based and de novo design. , 2010, Current topics in medicinal chemistry.

[103]  Brian K. Shoichet,et al.  Structure-Based Discovery of A2A Adenosine Receptor Ligands , 2010, Journal of medicinal chemistry.

[104]  J. A. Jablonowski,et al.  The first potent and selective non-imidazole human histamine H4 receptor antagonists. , 2003, Journal of medicinal chemistry.

[105]  Christopher G. Tate,et al.  Biophysical Fragment Screening of the β1-Adrenergic Receptor: Identification of High Affinity Arylpiperazine Leads Using Structure-Based Drug Design , 2013, Journal of medicinal chemistry.