Drug Design 2. Overview. Drug Discovery Pipeline. Drug Design. Oliver Kohlbacher Winter 2009/ Success Stories

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1 Drug Design 2 Oliver Kohlbacher Winter 2009/ Success Stories Abt. Simulation biologischer Systeme WSI/ZBIT, Eberhard Karls Universität Tübingen Overview Drug Discovery Pipeline reloaded Successful rational design some examples Structure-based/de novo design Thymidylate synthetase inhibitors Similarity/Pharmacophores Dopamine agonists General design principles Endothelin Drug Discovery Pipeline Drug Design Accelerated by Bioinformatics/Cheminformatics 1

2 Pipeline Biological Data Selection of indication/disease to target (mostly economic aspects) Collection of all available biological and clinical data Ideal case: animal disease model available, otherwise try to develop an animal model Pipeline Target Identification (Target ID) Target Discovery Search for possible molecular targets, i.e., molecules involved in the disease Identify the corresponding gene and protein Target Validation Verify that the target is truly suitable as a target Is the protein expressed in the tissues in question? Does a knock-out show an effect in the animal model? Pipeline Lead Structure Identification (Lead ID) Search for a lead structure (lead), i.e. a small molecule binding to the selected target Methods: High-throughput Screening (HTS) Combinatorial Chemistry (Combichem) Virtual Screening (vhts) Also test some antitargets, i.e targets that should not be affected by the lead (remember ASA and COX-1/COX-2!) 2

3 Design Strategies Drug Design 2 No target structure No known ligands Combichem, HTS No target structure Ligands Pharmacophores, Similarity, QSAR Ligand-Based Target structure No known ligands De Novo Design Target structure Ligands Structure-Based Design Drug Design 1 Structure-Based After: H. Kubinyi, Vorlesung Drug-Design Pipeline Lead Optimization Optimize lead to obtain a drug candidate Improve response (µm! nm) Reduce side effects Improve pharmacokinetics Simplify synthesis Ensure patentability/absence of other IP Pipeline Testing/Trials Preclinical studies Pharmcokinetics, pharmacodynamics (in animals) Phase I clinical trials First testing in (healthy) human subjects Phase II clinical trials patients Phase III clinical trials patients Phase IV clinical trials Long-term trials after approval 3

4 Pipeline Development of one new drug: Cost: $800 mio. (numbers from 2001) Duration: years ) Drug companies focus on block busters Pharma industry limits research on areas with high economic potential Less promising areas (tropical medicine, parasitology) have been reduced drastically over the last two decades (lack of market potential) Successes in Rational Design Rational design of drugs has of course been used a lot in pharmaceutical industry Purely rational design a drug candidate found using computational methods only is still not possible Internal details of the steps involved in drug design are hard to figure out There are a few published success stories from the 90s General design principles Structure-based/de novo design Receptor agonist/antagonist design Example: Endothelin Endothelin is a highly potent vasoconstrictor (discovered in 1988) Endothelin is a short peptide (21 aa) There are several homolog proteins with similar effect Initially, endothelin was described as a substance raising blood pressure It is involved in many diseases, though It is thus an interesting structure to pharma industry 4

5 Endothelin Receptors Endothelin receptors were identified shortly after endothelin Two subtypes ET A receptor: mainly on smooth muscles and blood vessels ET B receptor: common throughout the body Stimulation of ET A increases blood pressure Identification of endothelin and its receptor enables the search for small-molecule antagonists Two strategies were applied in parallel Peptidomimetics Screening of large structure databases Peptidomimetics Step-wise replacement by Ala ( alanine scanning ): C-terminal end is most important for binding Removal of C-terminal Trp leads to complete loss of activity Last 6 amino acids of the des C-terminal end still bind with IC 50 = 44µM Sequence: His-Leu-Asp-Ile-Ile-Trp First step: sytematic modification to increase affinity Modification of Sequence Replacing L-His by D-His leads to a drastic increase in affinity The resulting peptide binds with IC 50 = 35 nm to ET A receptor Final sequence after modifications: Ac-D-Dip-Leu- Asp-Ile-Ile-Trp (Dip = diphenylalanine) Despite an intensive search, no way to further decrease the size of the peptide could be found 5

6 Peptide Screening First antagonist found in a systematic screening: cyclo-(d-glu-ala-allo-d I le-leu-d T rp) Structural optimization led to cyclo-(d-asp-pro-d-val-lez-d-trp) internal name: BQ-123 Binds with IC 50 = 22 nm to ET A Affinity to ET B approx times weaker No oral bioavailability Very short half-life in vivo Solution: Non-Peptide Candidates Screening of the internal compound library of Bristol-Myers Squibb for ET A inhibitors Yields sulfathiazole (weakly active) A more detailed screening of similar compounds identifies sulfisoxazole as a better binder Known antibiotic This is being used as a lead sulfathiazole sulfisoxazole Solution: Non-Peptide Candidates Systematic variation of sude chains leads to ET A - selective antagonist (BMS , IC 50 = 0.15 µm) VMS is orally available in animal models, lowers blood pressure and has a long in vivo half life BMS

7 Solution: Nonpeptidic Ligands Screening Screening of related structures Lead Optimization Sulfathiazol IC 50 = 69µM Sulfisoxazol IC 50 = 0,78µM BMS IC 50 = 0,15µM Thymidylate Synthetase Inhibitors Thymidylate synthetase (TS) is a key enzyme in the biosynthesis of thymine Thymine is an essential nucleotide of DANN and thus needed during cell division If cell proliferation is out of control (cancer), more thymine is required Inhibition of TS is thus a possible mechanism in tumor therapy Thymine Biosynthesis Stryer, Biochemistry [ 7

8 Thymidylate Synthetase TS methylates deoxyuridylate to desoxythymidylate Precursor to thymine Methyl group is transferred from cofactor methylene tetrahydrofolate Two major options for inhibition Substrate competition by analogous binding to substrate binding site Blocking of cofactor binding site Known Inhibitors 5-flourodeoxyuridylate (F-dUMP) inhibits substrate binding irreversibly by covalent binding to Cys 146 Structurally similar compound CB3717 binds at the cofactor binding site instead 5-flourodeoxyuridylate Known Inhibitors N10-propargyl-5,8-deazofolate (CB3717) binds competitively to cofactor binding site Poor solubility Poor absorption Kidney toxicity Clinical study was aborted CB 3717 (R = NH 2 ) 8

9 Search for Alternatives There are alternative variants of the structure with lower toxicity In the end, they did not yield viable alternatives, though Other, novel, derivatives were thus needed with better physicochemical, toxicological and pharmacokinetic properties Structure-Based Design Initially, only the crystal structure of TS from Escherichia coli was known The binding geometry of CB3717 in the binding pocket was studied extensively Chinazoline scaffold binds to the protein through a network of hydrogen bonds Hydrophobic interaction with a narrow channel in the binding site Later on, crystal structures of TS with novel derivatives of CB3717 were obtained to confirm the binding modes of these compounds PDB: 2G8O (blue: UMP, red: CB3717) 9

10 PDB: 2G8O (blue: UMP, red: CB3717) Abbildung H-Brücken Systematic Modification Starting point: 2methyl derivative of CB 3717 Removal of glutamate side chain Causes major loss of affinity (two orders of magnitude) How to compensate for that? 10

11 Systematic Modification Tests of different substituents, taking into consideration the structural environment Lipophilic pocket formed by Leu 172 and Val 262 lipophilic substituent in meta position of the phenyl rest favorable Electron donor close to the para substitutent Use suitable electron acceptors Favorable contact to Phe 176 by attaching another aromatic ring Using an indoyl rest increases hydrophobic contact surface Systematic Modification Nr R 1 R 2 5 H H 6 CF 3 H 7 H Cl 8 H NO 2 9 H CN 10 H SO 2 NH 2 11 H SO 2 CF 3 12 H CO-Phe 13 H SO 2 -Phe 14 H SO 2 -Indol Structur-Based Design vs. de novo Structure-based design yields a soluble inhibitor with high receptor affinity So far only the substituents have been modified, the scaffold remains unchanged These modifications were inspired by the known structural properties of the binding mode Can the scaffold be replaced as well? ) This scaffold hopping can be achieved using de novo techniques 11

12 Scaffold Design Binding mode from XRD defines constraints on hydrogen bond networks for the scaffold Ligand needs to be H-bond donor for carboxylate group of Asp 169 Ligand needs ot be H-bond acceptor for Trp 430 We need a scaffold that can acceptor and donor for closely neighboring H bonds cis-amides imidazoles Angle between HBs: 120 Imidazoles are a promising start Scaffold Design Analyze the binding site using GRID Close to Trp 80, Trp 83 and Phe 176 methyl groups would be favorable (lipophilic region) Imidazole can be extended to an imidazole tetrahydrochinoline Piperidine ring fills the lipophilic pocket N serves as an achiral anchor for a side chain sticking out into the solvent Scaffold Design Side chain based on phenylsulfonyl fits into the binding channel pretty well (according to models) Good complementarity to the receptor Terminal piperazine ring interacts with the solvent This compound was synthesized and turned out to be a micromolar inhibitor Crystal structure confirms the predicted binding mode 12

13 Scaffold Design Further modification based on GRID analysis and crystal structures Transport properties have been optimized by replacing the solvent-exposed residue Resulting structure binds with K i = 60 nm New inhibitor based on de novo design! Nolatrexed Several drug inhibiting TS (and/or dihydrofolate reductase) are on the market as cancer drugs One is Nolatrexed (Tradename: Thymitaq) Nolatrexed is being used for treatment of liver cancer It binds to the folate binding pocket of TS Nolatrexed Pemetrexed Pemetrexed (tradename: Alimta) is being used to treat lung cancer (among others) The drug was developed by Edward C. Taylor in Princeton It inhibits both TS and DHFR 13

14 Ligand-Based Design G-protein coupled receptors (GPCRs) are an important class of drug targets Only of two GPCRs the crystal structure is known today There are no crystal structures of pharmaceutically relevant GPCRs How to design a drug in this case? Two key options: Build a model of the structure (structure prediction) and use that for structure-based drug design (risky models are generally poor!) Ligand-based design Example: Dopamine-D 1 Agonists Dopamine is an important neurotransmitter Closely linked to Parkinson s disease L-dopa is a common treatment for Parkinson s In contrast to dopamine, it is transported across the bloodbrain barrier In the brain it is metabolized to dopamine (prodrug concept: administer something that is turned into the real drug in the body) Dopamine L-DOPA Search for Dopamine Agonists L-DOPA has numerous side effects Agonists binding selectively to the D 1 receptor could alleviate this problem The search for such agonists sketched here was conducted at Abbott between 1988 and 1991 using computer-aided drug design It demonstrates how new leads can be discovered without the aid of a 3D structure of the receptor 14

15 Analysis of the Binding Mode Essential: information on the binding mode of an agonist Difficult without a crystal structure Starting point: known inhibitor SKF It was well-known from prior studies that amino and hydroxyl groups are essential for the activity Dopamin SKF BKK S. 536ff Analysis of the Binding Mode Replacing the phenyl group by H reduced affinity to D 1, not to D 2 Conclusion: phenyl group fits into the binding pocket of D 1 receptor This pocket does not exist (at least with that size) in the D 2 receptor R K i (D 1 ) K i (D 2 ) Phenyl (SKF 38393) H K i in nm Analysis of the Binding Mode What s the position of the phenyl rest with respect to the NH and OH groups? Conformation analysis Result: two different energetically favorable conformations: Phenyl ring in the same plane as the bicylic rings system Phenyl ring above the 7-ring The first conformation turns out to be the biologically active one 15

16 Other Agonists At the same time another unspecific dopamine agonist was discovered (right) Substitution of R with a phenyl group high selectivity for D 1 Similar affinity as SKF SKF 38393, but stronger D 1 selectivity Good structure, however, very hard to synthesize! R K i (D 1 ) K i (D 2 ) H Phenyl 63 > Database Search 3D database search using ALADDIN in all structures of the internal Abbott database ALADDIN is a tool for strucutre design and 3D pharmacophore search Considers geometric an steric properties Can also be used for substructure search Develoepd 1989 at Abbott (internal code) (Van Drije et al.; JCAMD 3(3): , 1998) A Lead from the Database Database search revealed the structure on the right It was shown to bind to D 1 receptor Substitution of R with a phenyl group again results in higher affinity This scaffold was used as a lead and further modified R K i (D 1 ) K i (D 2 ) H 1600 > Phenyl

17 Result Result of the modification is a highly effective, D 1 - selective agonist This compound had the highest known activity then R K i (D 1 ) K i (D 2 ) Phenyl Important Factors for Success 1. Rational approach Understanding the ligand-receptor interaction either from the crystal structure or from ligand structures and SARs Construction of models explaining the experiemental data 2. Close interaction between modelers and medicinal chemists Validation of computational models, understanding of a model s implications for a structure Construction of new hypotheses based on the models Adaptation of the model to new data 3. Understanding of experimental and computational methods Understanding of the methods (experimental and computational), their limitations and potential error sources Respect the methods of the other side, but also a healthy mistrust against absolute statements References Books [BKK] Böhm, Klebe, Kubinyi: Wirkstoffdesign, Spektrum