Protein. Targets of a Ligand. by Computer

Transcription

1 Finding Multiple Protein Targets of a Ligand by Computer Potential Application: Identification of unknown and secondary therapeutic targets of drugs, drug leads, natural products. Prediction of protein targets related to side effect and toxicity. Ligand-protein interactions in pathways etc. Methodology: Ligand-protein inverse docking

2 Why study protein targets of a molecule? I. Therapeutic Targets Nature 396, 15 (1998)

3 Why study protein targets of a molecule? II. Side effect and toxicity Abstract From Medline

4 Why study protein targets of a molecule? Detection of side effect and toxicity in early stages of drug discovery Most drug candidates fail to reach market Side effect and toxicity is an important reason. Money ($350 million per drug) and time (6-12 years for a drug) has been wasted on failed drugs. Drug Candidates in Different Stages of Development Majority of Them Fail to Reach Market Clin Pharmacol Ther. 1991; 50:471 Drug Discov Today 1997; 2:72

5 Why study protein targets of a molecule? III. Drugs from Natural Products From natural products to therapeutic drugs TIPS, May 1999, 20:190 Screening New drug design

6 Why study protein targets of a molecule? IV. Applications in pathways EGF Pathway From Signaling Pathway Database

7 Existing Methods: Given a Protein, Find Putative Binding Ligands From a Chemical Database Strategy New Method: Given a Ligand, Find Putative Protein Targets From a Protein Database Compound Database Compound 1... Compound n Protein Database Protein 1... Protein n Protein Ligand Successfully Docked Compounds as Putative Ligands Science 1992;257: 1078 Successfully Docked Proteins as Putative Targets

8 Feasibility Proteins Database: >12,000 3D structures in PDB. Protein diversity: 17% in PDB with unique sequence. Development of structural genomics: 10,000 unique proteins within 5 years. Ann. Rev. Biophys. Biomol. Struct. 1996; 25:113 Nature Struct. Biol. 1998; 5:1029 Method Ligand-protein docking docking algorithms capable of finding binding conformations. Proteins. 1999; 36:1 Computers Increasing performance (docking of 100,000 compounds in days). Decreasing cost (Linux PC, Multi-processor Machine)

9 How to Model Ligand-Protein Binding? Learn from the Mechanism of Ligand-Protein Binding

10 Ligand Binding Site

11 Ligand binding mechanism

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17 How to Check Chemical Complementarity? Potential Energy Description:

18 Optimization and Scoring Functions in Ligand-Protein Docking Potential Energy Description: Conformation change Low energy conformation

19 Energy Functions Chemical bonds Hydrogen bonding van der Waals interactions Electrostatic interactions Empirical solvation free energy V = V bonds + S H bonds [ V 0 (1-e -a(r-r0) ) 2 - V 0 ] + S non bonded [ A ij /r 12 ij - B ij /r ij6 + q i q j /e r r ij ] + S atoms i Ds i A i

20 Modeling Strategy for Ligand-Protein Docking Receptor Cavity Model Ligand-Protein Docking Algorithm Geometric considerations Docking Evaluation (Chemical Complementarity) Structure optimization to release bad contacts Evaluation of ligand-protein interaction energy Science 1992;257: 1078

21 Strategy for Ligand-Protein Inverse Docking Ligand Automated Process to inversely dock a ligand to each entry in a Built-In Biomolecular Cavity Database Successfully Docked Proteins and Nucleic Acids Putative Targets of Ligand Therapeutic Targets Side-Effect and toxicitytargets Metabolism, Signalling etc

22 Automated Protein Targets Identification Software INVDOCK Ligand \ / Step 1: Vector-based docking of a ligand to a cavity Step 2: Limited conformation optimization on the ligand and side chain of biomolecule Step 3: Energy minimization for all atom in the binding site Step 4: Docking evaluation by molecular mechanics energy functions and comparison with other ligands Automated Process to inversely dock the Lignad to each entry in a Built-In Biomolecular Cavity Database (10,000 Protein and Nucleic Acid Entries) \ / Successfully Docked Proteins and Nucleic Acids as Putative Targets of a Ligand \ / Protein function, Proteomics, Ligand transport, Metabolism Potential Applications: \ / Therapeutic Targets, Side-Effects, Metabolism, Toxicity Function in Pathways

23 INVDOCK Cavity Models HIV-1 Protease

24 Estrogen Receptor INVDOCK Cavity Models II

25 INVDOCK Testing Results The docked (blue) and crystal (yellow) structure of ligands in some PDB ligand-protein complexes. The PDB Id of each structure is shown.

26 INVDOCK Testing Results II Comparison of docked structure of 4H-tamoxifen (blue ball-and-stick structure) with the crystal structure of estrogen (yellow stick structure) in protein estrogen receptor (PDB Id: 1a52). For comparison, the docked structure of estrogen (red line-drawing structure) is also included.

27 INVDOCK Testing Results III Molecule Docked Protein PDB Id RMSD Description of Docking Quality Energy Indinavir HIV-1 Protease 1hsg 1.38 Match Xk263 Of Dupont Merck HIV-1 Protease 1hvr 2.05 Match Vac HIV-1 Protease 4phv 0.80 Match Folate Dihydrofolate Reductase 1dhf 6.55 One end match, the other in different orientation Deazafolate Dihydrofolate Reductase 2dhf 1.48 Match Estrogen Estrogen Receptor 1a Match Complete overlap, flipped along

28 INVDOCK Testing Results IV (a) Tamoxifen is a famous anticancer drug for treatment of breast cancer. It was approved by FDA in 1998 as the 1st cancer preventive drug. 30 million people are expected to use it. Vitamin E is a widely used supplement. Many experimental studies have indicated its therapeutic effect to a number of diseases.

29 INVDOCK Testing Results IV (b) Aspirin is a famous antiinflammatory drug. It is called as a wonder drug because of its multiple therapeutic effects. Vitamin C is a widely used supplement. Many experimental studies have indicated its therapeutic effect to a number of diseases.

30 INVDOCK Identified Protein Targets For an Anticancer Drug Tamoxifen PDB Id Protein Experimental Findings 1a25 Protein Kinase C Secondary Target 1a52 Estrogen Receptor Drug Target 1bhs 17beta Hydroxysteroid dehydragenase Inhibitor 1bld Basic Fibroblast Growth Factor Inhibitor 1cpt Cytochrome P450-TERP Metabolism 1dmo Calmodulin Secondary Target Tamoxifen is a famous anticancer drug for treatment of breast cancer. It was approved by FDA in 1998 as the 1st cancer preventive drug. 30 million people are expected to use it.

31 INVDOCK Testing Results: putative targets of 4H-tamoxifen PDB Putative Protein Target Experimental Finding Target Status Clinical Implication Ref 1a52 Estrogen Receptor Drug target Confirmed Treatment of breast cancer 36 1akz Uracil-DNA Glycosylase 1ayk Collagenase Inhibited activity Confirmed Tumor cell invasion and cancer metastasis 38 1az1 Aldose Reductase 1bnt Carbonic Anhydrase 1boz Dihydrofolate Reductase Decreased level Combination therapy for cancer 43

32 INVDOCK Testing Results: putative targets of vitamin E PDB Putative Protein Target Experimental Finding Target Status Clinical Implication 1a27 17β-Hydroxysteroid-Dehydrogenase Stimulated Activity Testicular Steroidogenesis 1az1 Aldose Reductase Increased Level Treatment Of Cataract Development 1bm k Map Kinase P38 1crr C-H-Ras P21 Protein Decreased H-Ras Expression Improved Cancer Therapy

33 INVDOCK Testing Results V Compound Putative Targets Identified Experimentally Confirmed Experimentally Implicated 4H-Tamoxifen Aspirin Vitamin C Vitamin E

34 INVDOCK Testing Results VI Chinese Natural Product Compound Putative Cancer- Related Targets Identified Experimentally Confirmed or Implicated Acronycine 12 3 Allicin 15 2 Baicalin 17 3 Catechin 16 3 Emodin 9 4

35 Conclusions Ligand-protein inverse docking is useful in probing putative targets of a molecule. Potential applications in identification of therapeutic, side effect, toxicity targets of drugs, drug leads, natural products; and in determination of pathways. Application potentials increase with advances in structural and functional genomics.