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Computer-Aided Discovery of New HIV-1 Integrase Inhibitors (ISTC/BTEP Project # 3197/111) Vladimir Poroikov Laboratory for Structure-Function Based Drug.

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Presentation on theme: "Computer-Aided Discovery of New HIV-1 Integrase Inhibitors (ISTC/BTEP Project # 3197/111) Vladimir Poroikov Laboratory for Structure-Function Based Drug."— Presentation transcript:

1 Computer-Aided Discovery of New HIV-1 Integrase Inhibitors (ISTC/BTEP Project # 3197/111) Vladimir Poroikov Laboratory for Structure-Function Based Drug Design, Institute of Biomedical Chemistry of Rus. Acad. Med. Sci.

2 Slovenja: The Land of Many Dreams

3 Acquired immunodeficiency syndrome (AIDS), which is caused by HIV, is an immunosuppressive disease that results in life-threatening opportunistic infections and malignancies. First reported in 1981 in the United States, AIDS has become a major worldwide epidemic. The United Nations Program on AIDS (UNAIDS) estimates that at the end of 2002 nearly 42 million will have died of AIDS. During 2002, about 3 million people became infected. AIDS is presently the leading cause of death in Africa and the fourth leading cause of death worldwide. Cos P. et al. J. Nat. Prod., 2004, 67, 284-293. HIV/AIDS as a Global Threat

4 HIV-1 Replication Cycle HAART – Highly Active AntiRetroviral Therapy

5 Problems with the Current Therapy: - Adverse/Toxic effects. - High cost of treatment. - Multiple drug resistance.

6 Post-integration processing U5 Cellular DNA R U3 U5 U3 U5 3’-end processing integrase integrase HIV-1 DNA R 5’ACTGGAA 3’TGACCTT TAGCAGT 3’ ATCGTCA 5’ R U3 gag pol env U3U5 Strand transfer cytoplasm nucleus R 5’ACTGGAA 3’ ACCTT TAGCA 3’ ATCGTCA 5’ R U3 gag pol env U3U5 Mechanism of HIV-1 DNA integration into a cellular DNA

7 HIV-1 integrase: Catalyzes one of the crucial step of HIV replication. Has no cellular analogs. All retroviral integrases have a conservative structure. Is a prospective target for treating HIV infection and preventing AIDS. HIV-1 Integrase as Anti-HIV Target

8 ISTC/BTEP Project # 3197/111 The purpose of the project is to find new efficient inhibitors of HIV-1 integrase on the basis of the latest technologies in bioinformatics and computer-aided drug discovery. Duration: April 1, 2005 – March 31, 2008

9 First Approval of HIV-1 Integrase Inhibitor

10 Problems with Finding of HIV-1 Integrase Inhibitors Viral strains resistant to HIV-1 integrase inhibitors have been already identified. Conformation of integrase is rather flexible, it is stabilized in the pre-integration complex. Three-dimensional structure of full-length integrase as well as the structure of integrase complex with viral DNA are not known.

11 Participating Institutions Institute of Biomedical Chemistry of RAMS (IBMC), Moscow (leading organization – computer-aided drug discovery) Institute of Organic Chemistry of RAS (IOC), Moscow (chemical synthesis of potential compounds) Institute of Physical-Chemical Biology of MSU (IPCB), Moscow (testing of potential compounds in vitro) National Cancer Institute, NIH, Frederick, MD (molecular modelling, testing in cell culture)

12 ISTC/BTEP Project # 3197/111 Svyatoslav Shevelev IOC RAS (FWS) Marina Gottikh IPCB MSU Vladimir Poroikov IBMC RAMS HIV/AIDS Computer-assisted discovery of new HIV-1 integrase inhibitors Marc Nicklaus NCI/NIH

13 PASS: Prediction of Activity Spectra for Substances

14 What is the Biological Activity Spectrum? Biological Activity Spectrum is the “intrinsic” property of the compound that reflects all kinds of its biological activity, which can be found in the compound’s interaction with biological entity. Poroikov V. and Filimonov D. In: Predictive Toxicology. Ed. by Christoph Helma. Taylor & Francis, 2005, 459-478.

15 Biological Activity Spectrum Represents 3300 kinds of biological activity (PASS 2007), including: 374 pharmacotherapeutic effects, e.g. Alzheimer's disease treatment Anabolic Analgesic Angiogenesis inhibitor Angiogenesis stimulant Antiarrhythmic Antiarrhythmic Class III Antiarthritic Antibacterial...

16 Biological Activity Spectrum Represents 3300 kinds of biological activity (PASS 2007), including: 2755 biochemical mechanisms, e.g. 5 Alpha reductase inhibitor 5 Hydroxytryptamine 1 agonist 5 Hydroxytryptamine 1A antagonist 5 Hydroxytryptamine 1B agonist 5 Lipoxygenase inhibitor 5-Phytase inhibitor 6 Phosphofructokinase inhibitor Acetaldehyde dehydrogenase inhibitor Acetate kinase inhibitor Acetate-CoA ligase inhibitor...

17 50 adverse effects & toxicity, e.g. Arrhythmogenic Carcinogenic Cardiotoxic Cytotoxic DNA damaging Embryotoxic Eye irritation, corrasive Hematotoxic Hyperglycemic... Biological Activity Spectrum Represents 3300 kinds of biological activity (PASS 2007), including:

18 CYP2 substrate CYP24 substrate CYP27 substrate CYP2A substrate CYP2A1 substrate CYP2A10 substrate CYP2A3 substrate CYP2A6 substrate... 121 metabolic terms, e.g. Biological Activity Spectrum Represents 3300 kinds of biological activity (PASS 2007), including:

19 How Biological Activity Spectrum Is Predicted? Structure of new compound Anxiolytic Sedative 5HT1A Inhibitor Carcinogen... Estimating the probability that it has a particular biological activity Pa Pi for Activity: 0.853 0.020 Anxiolytic 0.694 0.035 Sedative... Predicted biological activity spectrum

20 Some Examples of PASS INet ( Predictions, Confirmed by the Experiments Chemical classBiological activityReference MethoxyacridinesAntileishmanial Di Giorgio et al., 2003. QuinazolinesAnxiolytic Goel et al., 2005. BenzimidazolesAntihypertensive Estrada-Soto et al., 2006. PolyketidesPhosphatase inhibitor Seibert et al., 2006. Cyclic nitronesNootropic Marwaha et al., 2007. Geronikaki A. et al. Prediction of biological activity via Internet. Medicinal chemist's point of view. SAR & QSAR Environ. Res., 2007, 19, 27-38.

21 Lab. Med. Chem.,Lab. Str.-Funct. Based NCI, NIH Drug Des., IBMC, RAMS Computer-assisted mechanism-of-action analysis of large databases including 250,000 chemical compounds registered by NCI Former Collaboration (CRDF Grant RC1-2064)

22 More than 64 million PASS predictions included. More than 700 activities available. Predictions separately searchable by probabilities of activity and inactivity. Both types combinable by logical AND. Predictions searchable by probability ranges (in subintervals of 0.0 – 1.0). PASS searches combinable with any other search criteria. PASS Predictions Searchable in NCI DB Browser (

23 Based on PASS predictions, a fraction of “active” compounds can be increased significantly: Poroikov et al. J. Chem. Inf. Comput. Sci., 2003, 43, 228-236.

24 15 10 5 Idea Medicine year s Creating New Medicines Is a High Risk Journey 3D-TI Conference, Dec. 10-11, 2007

25 General Scheme of Search for New HIV-1 Inhibitors Computer Screening of Diverse Databases Development of New Synthetic Routes, Chemical Synthesis Improvement of PASS Training Set Molecular Modelling (Target Based Design) In Vitro Testing Hits Testing in Cell Culture Leads O P T I M I Z A T I O N

26 HIV-1 IN Inhibitors Database Prepared for Input to PASS Training Set

27 3D Model of HIV-1 Integrase (Karki R. et al. JCAMD, 2004, 18: 739.

28 Example of HIV-1 Inhibitors Pharmacophore

29 Optimization of the Specialized PASS Training Set 2205 compounds 2006 260 compounds 2008 - Publications - Patents - NIAID HIV Therapeutics Database - Publications (only with Mg 2+ ) - Tested in NCI - Tested in IPCB Name Exp. IC 50,  M Predictions (2006 database)Predictions (2008 database) 3’-pST3’-pST3’-pST L-870,8100.0850.0150.5890.6390.6890,765 GS 9137 0.0072 0.4850,3630,898 S-1360 0.530.1930.19 0,511 L-870,812 0.04 0,2180,724 MK-0518 0.007 0,806

30 From Hits to Leads: Structure Optimization GS 9137MK-0518 IOCh-18-76 IC 50 : 3’-P = 80  M, ST = 80  M IOCh-18-47 IOCh-18-74 IC 50 : 3’-P = 0.2  M, ST = 20  M IC 50 : 3’-P = 0.3  M, ST = 0.5  M

31 Strand Transfer Inhibition by Compounds IOCh-18-47, IOCh-18-74 and IOCh-18-92

32 3’-Processing Inhibition by Compounds IOCh-18-47, IOCh-18-74 and IOCh-18-92

33 198 compounds were selected as hits, synthesized (or purchased from vendors of commercially available samples) 176 compounds were tested in vitro on inhibition for strand transfer and 32 compounds were tested on inhibition for 3’-processing. 15 compounds were identified as HIV-1 integrase inhibiting agents with IC 50 values in the micromolar and sub-micromolar range. For 4 most active compounds results were further confirmed by in vitro testing at NCI. The discovered compounds belong to the chemical series where this activity was unknown (NCEs). Summary of the Results

34 Some Prospects for a Near Future (BII Supported?) 1.Synthesis and biological testing of additional rationally designed derivatives from the same chemical series, to increase potency and decrease toxicity. 2.Detailed study the mechanism of binding, specificity, etc. for this classes of compounds. 3.Preparation and submission of patent(s). 4.Negotiations with pharmaceutical companies about possibilities of commercialization.

35 Acknowledgements IBMC Tamara Fedoronchuk Dmitry Filimonov Tatyana Gloriozova Dmitry Druzhilovsky Alexey Lagunin Alexander Shkrob Alexander Veselovsky Elena Shilova Antonina Boudunova IOC Svyatoslav Shevelev & Associates IPCB Marina Gottikh & Associates NCI Marc Nicklaus & Associates Winay Pattak & Associates Financial support: ISTC/BTEP Project # 3197/111

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