Apr 05 AMJ Computational decision support for drug design

Apr 05/AMJ Computational decision support for drug design Profiling of small molecule compound libraries Anne Marie Munk Jørgensen

Lundbeck Apr 05/AMJ Lundbeck’s Vision is to become the world leader in psychiatry and neurology Focus solely on treatment of diseases in the central nervous system (CNS) • depression • Psychoses • Migraine • Alzheimer • Sleep disorders 5000 people worldwide – app 800 in R & D

Outline Apr 05/AMJ 1. What is a small molecule drug? 2. How can computational methods help during the drug discovery phase? 1. 2. 3. 4. Library profiling: overall characterisation of a large pool of structures. Prediction of more specific characteristics like biological activity and ADME properties Privileged structures….

A small molecule drug Apr 05/AMJ … is a compound (ligand) which binds to a protein, often a receptor and in this way either initiates a process (agonists) or inhibits the natural signal transmitters in binding (antagonists) The structure/conformation of the ligand is complementary to the space defined by the proteins active site The binding is caused by favourable interactions between the ligand the side chains of the amino acids in the active site. (Electrostatic interactions, hydrogen bonds, hydrophobic contacts…) The ligand binds in a low energy conformation < 3 kcal/mol

Binding site complementarity Apr 05/AMJ HIV-Portease inhibitor JACS, V. 16, pp 847 (1994) H-bond donating H-bond accepting Hydrophobic Flo 98, Colin Mc. Martin. J. Comp-Aided Mol. Design, V. 11, pp 333 -44 (1997)

Example of ligand binding Apr 05/AMJ 1 UVT, Trombin Inhibitor

No vacancy! Apr 05/AMJ

Molecular factors Apr 05/AMJ Conformation Intramolecular interactions Ionization Intermolecular forces Electronic distribution Solubility, Partitioning Carrupt P-A. , Testa B. , Gailard P. Boyd D. B. , Lipkowitz K. B. , Reviews in Computational Chemistry, Vol. 11, 1997, pp. 241 -304.

Compound library profiling Apr 05/AMJ Analyze a pool of structures to find out how attractive they are to us…. . • 10 years ago: Diversity + HTS • Now: very high focus on how biologically relevant the screening collection is. • Computational methods to predict drug likeness, CNS likeness…. High throughput is not enough … to get high output…. .

Compound analysis Apr 05/AMJ Ideal 50. 000 Structures: Chemical intuition

Choosing the right descriptors is difficult Wolfgang Sauer, SMI 2004 Apr 05/AMJ

How we describe the structures in the computer Apr 05/AMJ o Calculate a number of phys chem descriptors, like molecular weight, nhba, nhbd, log. P, SASA…. . o Describe the structures by keys….

Lipinski statistics Apr 05/AMJ Rule of 5 References (1) Lipinski, C. A. ; Lombardo, F. ; Dominy, B. W. ; Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev JID - 8710523 1997, 23, 3 -25.

Diversity and "Chemical Space" Apr 05/AMJ PCA

Chemical space navigator Apr 05/AMJ Global Positioning System (GPS) Chem GPS (Oprea & Gottfries, J. Comb. Chem 2001) We want to define the CNS ”world” – the space which is biologically relevant when considering CNS drugs

CNS model Apr 05/AMJ PCA 12 descriptors 3 components, R 2 X=0. 71 Blue dots define: : CNS drug space CNS ”World”

CNS ”world” sub classes Apr 05/AMJ

Model used to predict CNS-likeness Apr 05/AMJ

Structural clustering based on keys Apr 05/AMJ C-N 1 0. 349 3 6 13 19 26 31 38 1 … 0100110001…. C=O C=C Similarity by Tanimoto: Tc= Bc/(B 1 + B 2 – Bc) clust_benzo (order)

Structural analysis Apr 05/AMJ o Clustering o Virtual screening – looking for structural similar compounds in a large pool of structures…. .

Apr 05/AMJ I have talked about overall profiling of a large number of compounds…… in terms of CNS-likeness … now I will turn to talk about prediction of more specific characteristics like biological activity and ADME properties…. . Quantitative Structure Activity Relationship or Quantitative Structure Property Relationship

In house QSAR study Apr 05/AMJ Correlation between Glyt-1 inhibitor activity and pi (lipophilicity) and Sigma. P (electronic characteristics) for the R substituent

ADME property predictions Apr 05/AMJ Oral absorption …depends heavily on permeability and Solubility… high interest in predicting these things in silico… Other things: Blood-brain Barrier penetration, clearance, Metabolism, tox…. .

Aqueous Solubility Apr 05/AMJ QSRP model n=775, R 2=0. 84, Q 2=0. 83 8 2 D descriptors, Cerius 2 Most important descriptors: log. P, hba*hbd, hba, hbd Drugs: – 6 < log. S < 0; If error of 1 log unit is OK model predicts 60 -80% of the compounds correctly Journal of Medicinal Chemistry, 2003, Vol. 46, No. 17

Permeability Apr 05/AMJ QSRP N= 13 R 2=0. 93 Q 2= 0. 83 Key descriptors: PSA> Odbl >N-H >. . NPSA >SA Polar descriptors important and size matters…. Simple Rule: PSA < 120 Å2 Journal of Medicinal Chemistry, 2003, Vol. 46, No. 4

Pharmacophore modelling Apr 05/AMJ …. . Another method of biological activity prediction… Observations that modification of some parts of a ligand results in minor changes of activity, whereas modifications of other parts of the ligand result in large change of activity. Pharmacophore element: Atom or functional group essential for biological activity 3 D Pharmacophore mode: Collection of pharmacophore elements including their relative position in space

From TCAs to SSRIs and Beyond Selective Serotonin Reuptake Inhibitors (SSRIs) zimelidine citalopram cipramil/celexa fluoxetine prozac/fontex 28. 04. 1971 14. 1. 1976 10. 1. 1974 First synt. Aug 1972 First synt. May 1972 indalpine 12. 1975 sertraline zoloft 1. 1979 paroxetine paxil/seroxat fluvoxamine fevarin 30. 1. 1973 20. 3. 1975

The mechanism of SSRI’s Apr 05/AMJ

Pharmacophore modelling example Apr 05/AMJ Fluoxetine Paroxetine Citalopram Chapter 13. Pharmacophore Modeling by Automated Methods: Possibilities and Limitations M. Langgård, B. Bjørnholm, K. Gundertofte In "Pharmacophore Perception, Development, and use in Drug Design". Edited by Osman F. Güne International University Line (2000) Sertraline

Privileged structures Apr 05/AMJ ……. are ligand substructures that can provide high-affinity ligands for more than one target…. .

Privileged structures Apr 05/AMJ ”A single ring system, the 5 -phenyl-1, 4 -benzodiazepine ring, provides ligands for a surprisingly diverse collection of receptors…. . ” Evans et al. , J. Med. Chem 1988, 31, 2235 -2246

G-protein coupled receptors Apr 05/AMJ • 7 TM • Example: dopamine, serotonine, muscarinic, histamine, neurokinin • Family A, B, C, A = Rhodopsin like • In general low sequence homology even within each family, but highly conserved residues in the TM regions • Small molecule ligands bind wholly or partly within the transmembrane region mainly in the region flanked by helix 3, 5, 6 and 7 • From site-directed mutagenesis studies, side chains involved in binding has been characterised Chem. Bio. Chem 2002, 3, 928 -944

GPCR Privileged structures type of receptor Apr 05/AMJ J. Med. Chem. , 47 (4), 888 -899, 2004

Amino acid ”hot spots” Apr 05/AMJ Priviledged sub structure for target T 1 and T 2 Align T 1 and T 2 Look for these in other GPCR’s Examine which amino acids are conserved in binding pocket for T 1 and T 2 Amino acid ”HOT SPOTS” Linking target and ligand side…. . Didier Rognan at the 5 ht international workshop in New Approaches In drug design & discovery, Marburg 21 -24 marts 2005

Fluoxetine scaffold common for SERT and GLYT-1 Apr 05/AMJ Gibson et al, Biorg. Med. Chem Letters 2001 (11), 2007 -2009 Atkinson et al, Mol. Pharm. 2001 (60), 1414 -1420

Comparison between SERT and GLYT-1 Apr 05/AMJ Y 102 F 288 Y 310 GLYT 1 sequence; RED: conserved residues GREY: conservative mutations SERT model From Na+/H+ antiporter, J. Pharmacol & Exp Therapeutics, 307, 34 -41

Resume Apr 05/AMJ Computational methods for o Compound library profiling, Chem GPS o activity QSAR prediction and pharmacophore modelling o Solubility and permeability QSPR prediction o Privileged structures of GPCR’s

”Hit finding” Apr 05/AMJ Drug discovery ~ Looking for a needle in a haystack Filtering of compounds ~ remove some of the hay

Serendipity Apr 05/AMJ “To look for the needle in the haystack and coming out with the farmer’s daughter” Arvid Carlsson