Luận án tiến sĩ: Small molecule-based approach to chemistry and biology: Synthesis, measurement, and analysis

NOTE TO USERS This reproduction is the best copy available. ® UMI HARVARD UNIVERSITY Graduate School of Arts and Sciences THESIS ACCEPTANCE CERTIFICATE The undersigned, appointed by the Department of Chemistry and Chemical Biology have examined a thesis entitled Small Molecule-Based Approach to Chemistry and Biology: Synthesis, Measurement, and Analysis presented by Young-kwon Kim candidate for the degree of Doctor of Philosophy and hereby Signature. Typed name: P Signature. Typed name: Prof.

David Liu Signature. D TSTee Typed name: Prof. Daniel Kahne Date: December 7, 2005 Small Molecule-Based Approach to Chemistry and Biology: Synthesis, Measurement, and Analysis A thesis presented by Young-kwon Kim to The Department of Chemistry and Chemical Biology in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Chemistry and Chemical Biology Harvard University Cambridge, Massachusetts December 2005 UMI Number: 3205917 Copyright 2005 by Kim, Young-kwon All rights reserved. INFORMATION TO USERS The quality of this reproduction is dependent upon the quality of the copy submitted.

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All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. ProQuest Information and Learning Company 300 North Zeeb Road P. Box 1346 Ann Arbor, MI 48106-1346 © 2005 —- Young-kwon Kim All rights reserved Small Molecule-Based Approach to Chemistry and Biology: Synthesis, Measurement, and Analysis Young-kwon Kim Professor Stuart L.

Schreiber 7 December 2005 Research Adviser Abstract Small molecules have long played important roles in the advancement of biology; however, little meta-insight has been gained during this period. This thesis presents two studies that aim to uncover the relationships between chemical space and biological measurement space. The first chapter comprises literature surveys of chemical descriptor space, biological measurement space (outputs), and analysis methods to link them. An emphasis on the role of diversity-oriented synthesis populating accessible chemical space (inputs) is offered.

The second chapter describes the methodology that uses well-defined inputs provided by diversity-oriented synthesis and robust readouts from a series of chemical genetic modifier screenings. Subsequent multidimensional data analysis confirms the intuition of the scientists yet adds methodical rigor, while simultaneously discovers novel patterns of biological activity that correlate with stereochemistry in a subtle and unexpected way. Significant variations in biological outcomes were found to result from the stereochemical and skeletal elements in small molecules. Such insights facilitate efficient searching and probing of chemical space.

The third chapter reports the development of analytical implements and illustrates that the relevance network is robust and flexible. The resulting analysis environment enables the visualization of significant associations between small molecules. A larger number of - iii - structurally and functionally heterogeneous inputs (small molecules) are efficiently examined based on a small-molecule annotation dataset and subsequently validated. Furthermore, novel hypotheses on the biological mechanisms of small molecules are proposed using already annotated small molecules.

-Ìv- Table of Contents L4. iii Abbr€ViatÏOTS. cu ng ng nee ene E nh TK ee cet nee ete eH tk km nà tà nh rà vi Dedication. EE EEE ERLE EE EEE eRe E EERE EEE EEE xi Chapter 1.

eee ĐH HE BE ĐK Ki Ko EEE Đi EEE 1 1.1, Chemical descriptor sDACG. ng TT nà nà kh nh TH bà ST 2 1. Biological measurement SDAC€. ch nh mm ene eed eee hà by 24 1.

Multidimensional data analySIS.- cọ nee eect BH TK nh vệ,49 1. Sampling chemical space by diversity-oriented syntheSis. cence ee eee nent Ko ĐK net Ee eee eee eee EEE EEE Bà ea 105 2. Relationship of skeletal and stereochemical diversity to cellular measurement space.

Supporting inÍOrmatiOn.‹ ác cóc ch ni KH ch TK Ki ĐK ki KÊU 119 Chapter 3. Case Study ÏÏ. cm ĐK kh nh 197 3. Construction and analysis of relevance network from small-molecule annotation.

no HH ener eee eee EERE Ee een ti nền nà EEE EE EERE 215 Abbreviations Ac acetyl ACD available chemical directory Ach acetylcholinesterase AcOH acetic acid AD activation domain AML acute myelogenous leukemia AT angiotensin ATP adenosine 5’-triphosphate BD binding domain BB building block BrdU 5-bromo-2’deoxyuridine cAMP adenosine 3’,5’-cyclic monophosphate Cal-AM calcein-acetoxymethylesters CAN ceric ammonium nitrate CCK cholecystokinin receptor CHCl, methylene chloride CH3CN acetonitrile CHCl chloroform ChemGPS chemical global positioning system CI-MS chemical ionization-mass spectrometry CMC comprehensive medicinal chemistry CNS central nervous system CoMFA comparative molecular field analysis DCM dichloromethane -Vi- DIC 1,3-diisopropylcarbodiimide DIPEA N,N-diisopropylethylamine DM data mining DMAP 4-(dimethylamino)pyridine DMF N,N-dimethylamino)pyridine DMSO dimethylsulfoxide DNA deoxyribonucleic acid DOS diversity-oriented synthesis ECs effective concentration of half-maximal effect EDC 1- ethyl-3-(3’-dimethylaminopropyl)carbodiimide hydrochloride EI-MS electron impact-mass spectrometry ELISA enzyme-linked immunosorbent assay EM expectation-maximization EtO diethyl ether EtOAc ethyl acetate Et ethyl ES-MS electrospray-mass spectrometry FAB-MS fast atom bombardment-mass spectrometry FTIR Fourier transform infrared spectrometry GA genetic algorithm GE-HTS gene expression-based high-throughput screening GPCR G protein coupled receptor GRIND grid-independent descriptors h hours HCS high-content screening HDAC histone deacetylase - Vii- HF hydrogen fluoride HRMS high-resolution mass spectrometry HSD hydroxysteroid dehydrogenase HT hydroxytryptamine HTS high-throughput screening Hz Hertz HPLC high-pressure liquid chromatography HSCS highest scoring common substructure i-PrOH iso-propylalcohol KDD knowledge discovery in database KEGG Kyoto encyclopedia of genes and genomes LC-MS tandem liquid chromatography-mass spectrometry MAS-NMR magic angle spinning nuclear magnetic resonance spectroscopy MCR multi-component reaction MDS multidimensional scaling Me methyl Mes 2,4,6-trimethylphenyl MeOH methanol MHz megahertz min minutes Mg;SO¿ magnesium sulfate MS mass spectrometry MDDR MACCS-II drug data report MTT (3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyltetrazoliumbromide) Na,SO, sodium sulfate NMR nuclear magnetic resonance spectroscopy - VI - NR nuclear receptor PCA principal component analysis PCR polymerase chain reaction PEG polyethylene glycol P-gp P-glycoprotein Ph phenyl PhH benzene Pd(PPha) tetrakis(triphenylphosphine) palladium(0) PS polystyrene PSA polar surface area p-TsOH para-toluenesulfonic acid PyBOP bezotriazol-1-yloxytripyrrolidinophosphonium hexafluorophosphate pybox pyridine-bis(oxazoline) PyBroP bromotripyrrolidinophosphonium hexafluorophophate pyr pyridine QSAR quantitative structure activity relationship QUINAP [1-(2-diphenylphosphino-1-naphthy])isoquinoline] RNA ribonucleic acid RNAi RNA interference ROF rule-of-five SMILES simplified molecular input line entry specification SMM small-molecule microarray SOM self-organizing map SOSA ‘selective optimization of side activities TBS tert-butyldimethylsily! TES triethylsilyl -iX- TfOH trifluoromethanesulfonic acid THF tetrahydrofuran TIPS triisopropylsilyl TLC thin-layer chromatography TMS trimethylsilyl] TMSOEt ethoxytrimethylsilane tol toluene TOS target-oriented synthesis UV ultraviolet WDI world drug index WT wild-type Y2H yeast two-hybrid Y3H yeast three-hybrid [M] Macrobeads Silyl y functionalized, 500-600 um PS, 1% cross-linked by y divinylbenzene y To my parents -Xi- Chapter 1. Chemical descriptor space 1. Biological measurement space 24 1. Multidimensional data analysis 49 1.

Sampling chemical space by diversity-oriented synthesis 67 1. Chemical descriptor space 1. Chemical (descriptor) space Frequently, the term “chemical space” is used as a colloquialism referring to a conceptual framework for formulating relations between molecular structures and/or properties. Chemical space, which encompasses all possible small organic molecules, has no theoretical limit, but can be reduced according to practical concerns: synthetic feasibility, user accessibility, drug-like properties, and the ability to modulate biological processes.' chemical space in silico data mining and analysis computational scientist ¬ feasible chemical space in cerebro strategy and methodology synthetic chemist /_.* accessible chemical space in vivo, in vitro x assay measurements chemical biologist Figure 1.

Reduction of chemical space. Based on the feasibility of practical synthesis, chemical space is reduced to “feasible chemical space” (blue circle), which is then reduced into a number of “accessible chemical spaces”. Accessible chemical space is the collection of small molecules ready for the perturbation ofbiological systems by a chemical biologist (e., amount, purity, explicit/implicit structural information, e/c. However, for synthetic chemists, accessible chemical space is defined by the collection of commercially available reagents.

Based on synthetic feasibility, chemical space is reduced to “feasible chemical space”. Feasible chemical space can also be defined in various ways, even without real synthetic considerations. For example, # silico combinatorial enumerations of common appendages and core skeletons in chemical databases delineate the boundary of a chemical space.” Further reduction to “accessible chemical space” can be primarily based on scientific demands. For example, accessible chemical space for the chemical biologist is populated by ! (a) Dobson, C.

-2- natural products, commercially available compounds, and libraries derived from diversity- oriented synthesis, each ready for interrogating biological systems of interest. These compounds should be of sufficient quantity, purity, and with adequate explicit/implicit structural information. For synthetic chemists, the development of novel synthetic strategies and methodologies might expand feasible chemical space significantly; indeed, the execution of diversity-oriented synthesis can populate extensively the accessible chemical space. Chemical descriptor space: mathematical definition The definition of chemical descriptor space is a vector (metric) space defined by a number of chemical descriptors for each small molecule.

In general, each ofø selected chemical descriptors adds a dimension to an n-dimensional vector space, and each small molecule is assigned to coordinates in this vector space according to the scaled values of its chemical descriptors (Figure 1. For visualization, an n-dimensional chemical-descriptor space can be projected onto fewer dimensions by a variety of dimensionality reduction methods. As shown in Figure 1.2b, each axis is replaced by a latent variable from the original descriptor set. Sometimes chemical space is partitioned by a number of binned descriptors, represented by a number of cells shown in Figure 1.’ (a) descriptor 3 (b) : (e) 3 descriptor 4 SM %iXapXajp r4 Z e tr ⁄⁄ J) s | ‘ descriptor 2 oom, AV i + at * descriptor & X SN K, raw aK? X; descriptor 1 descriptorn 4 n-dimensional chemical deacriptor space Reduced space by latent variables 18 cells divided by 5 partitioning Figure 1.

Chemical descriptor space. (a) n-dimensional chemical descriptor space (b) For visualization, n-dimensional chemical descriptor space can be reduced into two or three-dimensional space using proper dimensionality reduction methods. Each axis is represented by a latent variable from the original descriptor set. Chemoinformatics: a textbook (Wiley-VCH, Weinheim, 2003), pp 15-268.

-3- Role of chemical descriptor space The role of chemical descriptor space is divided into two elements: storage and retrieval of chemical information related to large compound collections in databases, and rigorous analysis of the properties (i., measurement space) of small molecules associated with their structural features encoded by chemical descriptors. The process of assigning each small molecule in feasible (F) or accessible chemical space (A) to chemical descriptor space based on its chemical descriptors can be referred to as “representation” (Figure 1.3)? On the other hand, analysis of chemical descriptor space and measurement space can generate a number of hypothetical models to be tested. These models are testing-grounds for the practical significance of chemical descriptor space as a valid method for linking chemical space and measurement space.” Moreover, the construction of chemical descriptor space is much cheaper, more consistent than both empirical synthesis and biological testing. Therefore, chemical descriptor space might make possible valid predictions of routes between accessible to feasible chemical spaces.

For example, thoughtful extension of validated models from the analysis of accessible chemical space and measurement space might provide guidelines for a second-phase synthesis directed at molecules with improved measured outcomes. ` Mm ee ` * model | Chemical descriptor epece | representation model representation a Figure 1. Role of chemical descriptor space. (a) Each molecule is processed mathematically to represent structures for storage and further analysis (representation); data analysis of measurement space with respect to chemical descriptor space might yield predictive and descriptive models characterizing the relationships (b) Chemical descriptor space representing overall feasible chemical space (F) utilizes the models constructed to guide synthesis, i., actualization of accessible chemical space (A).

In short, dynamic integration of synthetic chemistry, assay measurements, and data analysis might enable us to constantly evaluate overall processes in order to provide probabilistic, statistically significant predictions. Chemical descriptors Representation: search and retrieval Molecular structures are usually represented, manipulated, and stored as molecular graphs.