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GE Healthcare Life Sciences The importance of residence and recognition time of drug-target interactions in understanding efficacy and SAR Markku Hämäläinen, PhD Senior scientist in chemometrics Protein Analysis, R&D GE Healthcare Bio-Sciences AB Uppsala, Sweden 1 GE Title or job number 3/31/2014 GE Healthcare Life Sciences Without on you are off! With slow off you might still be on even when the drug is gone! Markku Hämäläinen, PhD Senior scientist in chemometrics Protein Analysis, R&D GE Healthcare Bio-Sciences AB Uppsala, Sweden 2 GE Title or job number 3/31/2014 1/ GE / Outline •Short overview on the use of SPR in drug discovery •Why binding kinetics is closely connected with PK/PD and therefore also efficacy •The value of residence/recognition time for Structure Kinetic Relations (SKR) •Q&A session 3 GE Title or job number 3/31/2014 SPR, ITC & DSC fits into the interface between different DD-disciplines Medicinal Chemistry • SAR and QSAR based on on/off/KD-maps & enthalpy • Direct binding gives pure interaction info • Fragment and focused libraries gives new scaffolds • Do not misuse your time with frequent hitters Screening • Improved quality on hit identification by elimination of promiscuous binders and false positive/negatives • Selectivity screening using panels of proteins • Binding site ranking using LF-competition assays • Intell. stepwise screening • Screening of fragment, target focused and diversity libraries Protein & Structural Chemistry Biophysical Chemistry • Primary screen of fragments before NMR/X-ray • Identify binding pockets with competition • DSC for QC • Validate mutations • Adds kinetic and thermodynamic resolution and throughput • Transition state thermodynamics Label-free Interaction Analysis Biology • Interaction proteomics • Protein panels for the understanding of binding/biological effect mechanism • Selectivity • Validate binding difference in animal disease models Computational Chemistry • Validate your virtual binding site model with pure binding data • 3D structure gives not on/only off, i.e. not equal to function/affinity/efficacy • LF-screening can feed insilico models ADME & Bioanalytical Chemistry • HSA/AGP-maps for ranking of plasma protein binding • Fa% from interaction analysis with liposomes • Compare binding with the serum albumin from disease model animals 4 2/ GE / Label-free biophysical screening in Drug Discovery Primary Screen Up to ~10 000 compounds: Fragment libraries Selected diversities Hits from HTS Directed libraries Content: Active to Hit Hit To Lead Lead Optimization CD Selection 100 1000 New compounds 1-5% 0.50% 5-x scaffolds ~ 10 scaffolds ~all Low 2-3 scaffolds Medium Binding: Intent: Yes/No Promiscuous? Covalent? False positive? Medium/High Ranking: KD or IC50 1:1 binding Binding site ID Technologies: High SAR: SAR: Full kinetic profile Full kinetic (kon, koff,KD) selectivity profile Target selectivity Thermodynamics Early ADME SPR and ITC X-ray/NMR In-silico 5 GE Title or job number 3/31/2014 What do Biacore™ instruments measure? Compound Immobilized target buffer sample buffer association Response (RU) Lead dissociation Sensorgram X Binding late report point Binding response Fragment Baseline Time 6 GE Title or job number 3/31/2014 3/ GE / Kinetic analysis of lmw drug-target interactions Fc=2 Spot=1-r corr Estrogen receptor Fc=1 Spot=1-r corr 6 6 Thrombin 5.3 5 4.6 4 3.9 CD80 Adenosine receptor A2a 3.2 3 2.5 2 1.8 1 1.1 0 0.4 -1 -0.3 -2 -100 -50 0 50 100 150 200 Carbonic anhydrase -1 -100 0 100 -60 400 500 600 700 800 900 DNA sequence -10 40 90 140 s Albumin 21 100 17 Response (RU) 300 CDK2 Kinase RU 16 14 12 10 8 6 4 2 0 -2 HIV protease 25 200 80 13 60 9 40 5 20 1 0 -3 900 1100 1300 1500 Time (s) 1700 1900 2100 0 10 20 30 40 s Increasing the number of targets!! 7 GE Title or job number 3/31/2014 Binding kinetics data to understand drug efficacy 4/ GE / Affinity – Kinetics - Thermodynamics Transition state SPR/Biacore™ KD = koff/kon Lead series Affinity 1*106 ka 100 pM 1 nM 10 nM 7 100 nM 6 1 µM log (ka ) 100pM 1nM 10nM 100nM 1M 10M 100M 1 mM kathermodynamics (M-1s-1) 1*107 Kinetics 5 10 µM 4 100 µM 3 1 mM 2 -4 -3 -2 -1 1*105 0.1 kd 0 log (kd) Equilibrium How strong? 275 Vary temperature Rates of complex formation and dissociation How fast? 285 295 305 Temp (K) kd s-1 0.01 0.001 275 285 295 305 Temp (K) Why that fast? All affinities and rate constants are apparent Ki vs. KD shows “good” correlation 1000.0 Large differences at high affinities 100.0 Ki (nM) Buffer differences 10.0 Ki=PBS, pH 5.5, 1M NaCl. KD= HBS pH 7.4, 0.15M NaCl 1.0 0.1 0.1 1.0 10.0 100.0 KD (nM) Clinically used drugs 1000.0 10000.0 1.0e5 10 GE Title or job number 3/31/2014 5/ GE / Affinity – Kinetics - Thermodynamics Lead series SPR/Biacore™ KD = koff/kon KD 100 pM 1 nM 10 nM ∆G = ∆H - T∆S KD 7 100 nM 6 1 µM 5 10 µM log kon (M-1s-1) Kinetics ∆G =RTlnKD 5 0 Thermo- 4 100 µM 3 1 mM 2 -4 10 -3 -2 -1 kcal/mole Affinity 100 pM 1 nM 10 nM 100 nM 1 M 10 M 100 M 1 mM ITC/MicroCal™ -10 dynamics -15 A,B,C 0 log koff (s-1) -5 -20 A Rates of complex formation and dissociation How fast? Equilibrium How strong? B C ∆ G - Gibbs free energy ∆H - Enthalpy T∆S - Entropy Why that strong? Complementary information Kinetics On-off rate map Thermodynamics Ethoxzolamide log kon (M-1s-1) KD 7 Entropy-Enthalpy map TS (kcal mol-1) KD 5 3 6 1 -1 5 -3 -5 4 -7 3 -3 -2 -1 log koff (s-1) -9 -18 -16 -14 -12 -10 -8 -6 H (kcal mol-1) Furosemide 6/ GE / 100 times higher affinity but lower efficacy Both drugs with identical and rapid clearance (short plasma half-life) Concentration 1 M 0 M 100 % occupied 92 % occupied koff 10-2 10-3 10-4 10-5 10-6 87 % occupied Residence time - t½ (s-1) KD = 10 nM kon = 103 (M-1s-1) koff = 10-5 (s-1) = 2 minutes = 19 minutes = 2 hours = 19 hours = 8 days KD = 100 pM kon = 107 (M-1s-1) koff = 10-3 (s-1) 0 % occupied 1 Time (h) 2 Higher affinity is not always better! 13 GE Title or job number 3/31/2014 Binding site occupancy (%) at different on/off/KD-values at 10/100 nM after 1h of interaction and 1h of dissociation Rapid off-rate limited efficacy kon (M-1s-1) koff (s-1) A 90 C B D 95 99 90 99 0 0 90 0 99 0 90 0 99 0 70 70 92 Slow off-rate protected efficacy 14 GE Title or job number 3/31/2014 7/ GE / Summary – the 4 areas Ancient medicinal chemistry knowledge! Affinity limited efficacy High affinity do not help if clearance is rapid! Rapid off-rate limited efficacy koff (s-1) kon (M-1s-1) 0/0 99/0 100/100 30/30 Slow off-rate enhanced efficacy Slow on-rate limited efficacy Without on you are off! With slow off you might still be on even when the drug is ”gone”! 15 GE Title or job number 3/31/2014 When is short residence time better? Short in relation to the effect wanted: e.g. Sleeping pills with very long residence time is very bad business ”For pharmacological mechanism requiring the endogenous ligand to perform routine fysiological functions a fast binding exogenous ligand displaying short lived interventions might be advisable.”1 Ion-channel antagonism: Ketamine and MK-801 gives mechanism based adverse effect probably due to strong and slowly dissociation binding to NMDA2 Dopamin receptor antagonism Cyclooxygenase inhibitors: naproxen and ibuprofen sometimes better due to rapid reversible contra aspirin which binds covalently and gives side effects 1)Sara Núňez et al. DDT (2012) 17:1/2:pp10-22 receptor 2)N-methyl-D-aspartate 16 GE Title or job number 3/31/2014 8/ GE / Lead optimization based on Residence and recognition time to understand SAR Overview of the spread in on/off-rates KD HIV-1 Protease inhibitors 7 7 DPP-IV inhibitors 7 Log (kon) Scaffolds cluster in on/off/KDspace 2 -4 Log (koff ) 0 7 6 0 2 -4 0 Ago Anta 3 0 -2 Carbonic anhydrase inhibitors -4 0 7 DC BA E 3 2 0 -5 0 -4 Estrogen receptor inhibitors CD80/CD28 inhibitors Range in kon 2-5 orders of magnitude Range in koff 2-5 orders in magnitude Leads with slowest offrates – all with scaffold E had highest biological potency 18 GE Title or job number 3/31/2014 Also shown in poster 9/ GE / The rate of association of the inhibitor to thrombin is of crucial importance for its in vivo effect The slope in the dose response curves from the rat arterial thrombosis model is related with the k on efegatran Thrombin is the key enzyme in the coagulation process and converts fibrinogen into clottable fibrin. slope AT rate 6 CH 1091 4 PPACK 2 melagatran An intensive effort in several pharmaceutical companies has lead to the development of many potent and selective thrombin inhibitors with distinct advantages over heparin and warfarin. argatroban inogatran hirulog 0 1 10 100 The choice of thrombin inhibitors as antithrombotic drugs depends a.o. on their affinity for the target and on their rate of binding. kon (/µM.s) from: Elg M, Gustafsson D, Deinum J: The importance of enzyme inhibition kinetics for the effect of thrombin inhibitors in a rat model of arterial thrombosis, Thrombosis and Haemostasis 78 (1997) 1286-1292 19 GE Title or job number 3/31/2014 Structure kinetic relations (SKR) of P38 map kinase inhibitors R1 BIRB 796O O N N N N H H N O Former BI drug candidate for inflammatoric and auto-immune diseases The t-Bu induce rearrangement of activation loop and fills the formed lipofilic pocket KD R2 107 1 pM 10 pM 100 pM 1 nM 100 nM 106 kon (M-1s-1) 10 nM 105 1 M 104 10 M 103 100 M ATP 10-6 10-5 10-4 10-3 10-2 10-1 koff (s-1) 1.) J. Regan, C.A. Pargellis, et. al. (2003) Bioorg. Med.. Chem. Letters 13, 3101-3104. 20 GE Title or job number 3/31/2014 10 / GE / SKR of P38 inhibitors R1 BIRB 796O O N N N N H H Some of the first tool compounds show rapidon/rapid-off type of binding SB 203580 N O R2 1 pM 10 pM 100 pM 1 nM 107 -OH -NO2 100 nM 106 kon (M-1s-1) KD 10 nM 105 1 M 104 10 M 103 100 M ATP 10-6 10-5 10-4 10-3 10-2 10-1 koff (s-1) 21 GE Title or job number 3/31/2014 1.) J. Regan, C.A. Pargellis, et. al. (2003) Bioorg. Med.. Chem. Letters 13, 3101-3104. SKR of P38 inhibitors R1 BIRB 796O O N N N N H H The ”formation” and filling of the pocket increase the complex stability longer residence time N O R2 107 1 pM 10 pM 100 pM 1 nM 100 nM R1= -tBu kon (M-1s-1) 106 R2= KD 10 nM 105 1 M 104 10 M 103 100 M -iPr -H 10-6 10-5 10-4 koff 10-3 10-2 10-1 (s-1) 22 1.) J. Regan, C.A. Pargellis, et. al. (2003) Bioorg. Med.. Chem. Letters 13, 3101-3104. 11 / GE / Phenyl and tolyl identical affinity but tolyl better efficacy due to longer residence time SKR of P38 inhibitors R1 BIRB 796O O N N N N H H R2 = Phenyl koff = 1.5*10-5 s-1 ; t1/2 = 13h N O R1=tBu R2 = Tolyl -6 -1 -Me koff = 8.3*10 s ; t1/2 = 23h KD R2= R2 Me 1 pM 10 pM 100 pM 1 nM 107 100 nM 106 kon (M-1s-1) 10 nM 105 1 M 104 10 M 103 100 M 10-6 10-5 10-4 10-3 10-2 10-1 koff (s-1) 23 SKR of P38 inhibitors R1 BIRB 796O O N N N N H H N O R2= R1=tBu N Me Me 107 Me NMe2 Me -Me CO2H NMe2 1 pM 10 pM 100 pM 1 nM KD 10 nM 100 nM 106 kon (M-1s-1) R2 Polar R2 gives slower onrates 105 1 M 104 10 M 103 100 M 10-6 10-5 10-4 koff 10-3 10-2 10-1 (s-1) 24 1.) J. Regan, C.A. Pargellis, et. al. (2003) Bioorg. Med.. Chem. Letters 13, 3101-3104. 12 / GE / HIV1-protease inhibitors: on-off rate map Ritonavir 10 pM 100 pM 1 nM XM232 A008 3.8 nM 7 nM Cyclic urea KD 10 nM B376 27 nM O 100 nM N HO O U75875 107 B369 Ind 106 Nelf Saq B440 B408 B409 B429 B412 kon (M-1s-1) B388 Rit Amp A037 105 B268 B439 B435 10 M O N HO O A017 B249 103 102 0.0001 0.001 N H O P1´ B268 O H N 0.1 OH O Symmetric B268 TS-analoges P2 0.01 N OH AHA-021 1 mM A016 O S HO 100 M B347 B277 O Cyclic sulfonamides A015 A038 104 OH OH AHA-008 1 M B322 B355 B425 A021 B295 A030 A045 A024 A018 B365 A047 A023 Drugs Cyclic urea Cyclic sulfonamides B268 analogues P1/P1´ - modified P2/P2´- modified Other N HO OH O O O H N OH N H O P2´ 1 koff (s-1) P1 25 / Markku Hämäläinen, Orion Finland Sep 2007 / HIV1-protease inhibitors – SKR 10 pM 100 pM 1 nM XM232 A008 3.8 nM 7 nM 10 nM B376 27 nM KD 100 nM U75875 107 B369 Rit Amp kon (M-1s-1) 106 105 B268 B425 A021 B439 B435 OH O H N N H O P2 End amid ester B249 100 M Chirality of dihydroxy S,S R,R 1 mM A038 B347 104 103 P1/P1´ Bz i-Pr B277 102 0.0001 O Di- Mono-hydroxy 10 M B365 B409 B429 B412 A037 O 1 M B322 B408 N H P1 OH O O B388 Ind Nelf Saq B440 B268 H N 0.001 0.01 koff (s-1) 0.1 1 Higher rotational freedom - ~1000 times slower on-rate 26 / Markku Hämäläinen, Orion Finland Sep 2007 / 13 / GE / HIV1 protease inhibitors: COMFA-QSAR 38 Inhibitors (22 in the training set, 16 in the test set) from 5 different scaffolds and the clinically used drugs. • The structures were aligned and 3D-CoMFA was used for obtaining a QSAR model describing on-rates and off-rates. Predicted pkoff • Observed pkoff Predictive COMFA-QSAR model only for offrate - not for on-rate nor affinity 27 / Markku Hämäläinen, Orion Finland Sep 2007 / 28 / Markku Hämäläinen, Orion Finland Sep 2007 / 14 / GE / Qualitative chemodynamics: HIV-p 100 pM 1 nM 10 nM 107 Indinavir A = pH 7.4 B = pH 5.1 C = pH 4.1 B A C 106 B B Scaffold 1 Scaffold 2 A kon 100 nM C A 1 M C B 105 A peptide 0.001 0.010 koff 29 20110303 0.100 The “unknown binding site/binder situation” Remedy - label-free/in-silico combination Hit identification and validation 1. Label free selectivity screening – 1-50k compounds 4. LF-competition screen – b.sites Scaffolds identification 2. Target 3. Structure feeds selective hits in-silico selection Binding site classification 5. Binding site selective hits 6. B-site classes feeds in-silico Lead identification and optimization Co-cryst. Xray Kinetic charact. Kinetic screening Lead identification & Thermodyn. optimization. charact. Early ADME CADD SAR/QSAR Cell based assays Animal models Candidate Drug 30 GE Title or job number 3/31/2014 15 / GE / Conclusions 1. Binding kinetics resolve affinity into ”new” more ”close to efficacy” type of data 2. Residence time/off-rate of slowly dissociating compounds often dominates the binding site occupancy over time and cannot be neglected when judging the quality of a lead 3. Compounds with slow off-rates need only a peak in bioavailable concentration to have a broader therapeutic window 4. You cannot properly judge pharmacokinetic data without knowing the binding kinetics of the interaction 5. High residence time selectivity is important to minimize side effects 6. The “slowness” of the off-rate should be judged in relation to the time constant of the biological system and the effect wanted 7. Rapid on-rate is important if the bioavailability is low or if a rapid effect is needed 8. There is also a wealth of other information in the Biacore™/MicroCal™ measurements which can be used for identification of ”good/bad” binders: (on/off-rates, enthalpy/entropy, stoichiometry, selectivity, ”shape”, affinity, specificity) 9. Label-free screening, binding kinetics and thermodynamics are now on the way of being fully integrated into the DD-process of most pharma/biotec companies 31 GE Title or job number 3/31/2014 GE, imagination at work and GE monogram are trademarks of General Electric Company. Biacore and MicroCal are trademarks of GE Healthcare companies. All third party trademarks are the property of their respective owners. All goods and services are sold subject to the terms and conditions of sale of the company within GE Healthcare which supplies them. A copy of these terms and conditions is available on request. Contact your local GE Healthcare representative for the most current information. © 2013 General Electric Company – All rights reserved. GE Healthcare Bio-Sciences AB, a General Electric Company. GE Healthcare Bio-Sciences AB, Björkgatan 30, SE-751 84 Uppsala, Sweden. 16 / GE /