MULTITARGET DOCKING WITH DYNAMICS

1. MULTITARGET DOCKING WITH DYNAMICS COMPOUND SELECTION Compound database (~300,000) Multiple disease related proteins DRUG-LIKE (~5000 from FDA) Compound library Computational docking with dynamics High throughput screen Computational docking Experimental verificationSuccess rate +Time .Cost $$$$$ Initial candidates Initial candidates Experimental verificationSuccess rate ++Time .Cost $$$ Experimental verificationSuccess rate +++++Time .Cost $ Disease &target identification NOVEL FRAGMENT BASED TRADITIONAL SINGLE MULTITARGET SCREENING TARGET SCREENING Single disease related protein

2. SHOTGUN MULTITARGET DOCKING WITH DYNAMICS ALL KNOWN DRUGS (~5,000 FROM FDA) FRAGMENT BASED DOCKING WITH DYNAMICS (~50,000,000) PRIORITISED HITS DISSOCIATION CONSTANTS (KD) (~300-500) + ALL TARGETS WITH KNOWN STRUCTURE (~5,000-10,000) IN VITRO STUDIES INITIAL CLINICAL TRIALS IN VIVO STUDIES CLINICAL STUDIES/APPLICATION

3. DENGUE INHIBITOR DISCOVERY prediction #1 Costin, Jenwitheesuk, …, Samudrala, Michael, PLoS Negl Trop Dis, 2010

4. MALARIA INHIBITOR DISCOVERY Predicted inhibitory constant 10-13 10-12 10-11 10-10 10-9 10-8 10-7 None Jenwitheesuk, Horst, Rivas, Van Voorhis, Samudrala, Trends in Pharm Sci, 2008

5. Horst, Laurenzi, Samudrala, PolyPharmacology Hoffmann-La Roche, 2011

6. G-protein coupled receptor A2α adenosine receptor 2.1 Å CαRMSD (CASP GPCR/3eml) Horst, Roy, Bernard, Zhang, Samudrala, in: Michino et al., Nat Rev Drug Disco, 2009

7. G-protein coupled Receptor A2a Horst, Roy, Bernard, Iyer

8. What MFS can do

9. What MFS can do • How clear • can it be? Ornithine Decarboxylase+Pyridoxal-5’-PO4 (1ord) Wang, Horst, Cheng, Nickle, Samudrala, PLoS CompBio, 2008

10. PROTEIN INHIBITOR DOCKING WITH DYNAMICS 1.0 0.5 with MD without MD Correlation coefficient ps 0 0.2 0.4 0.6 0.8 1.0 MD simulation time HIV protease Jenwitheesuk & Samudrala, AIDS, 2005