1
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Henry C, Kruell JA, Wilson RM, Chang CF, Woo CM, Koehler AN. A Versatile Isocyanate-Mediated Strategy for Appending Chemical Tags onto Drug-Like Small Molecules. Bioconjug Chem 2023; 34:2181-2186. [PMID: 38052453 PMCID: PMC10739574 DOI: 10.1021/acs.bioconjchem.3c00352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Revised: 10/09/2023] [Accepted: 10/23/2023] [Indexed: 12/07/2023]
Abstract
Target identification studies are a major hurdle in probe and drug discovery pipelines due to the need to chemically modify small molecules of interest, which can be time intensive and have low throughput. Here, we describe a versatile and scalable method for attaching chemical moieties to a small molecule, isocyanate-mediated chemical tagging (IMCT). By preparation of a template resin with an isocyanate capture group and a cleavable linker, nucleophilic groups on small molecules can be modified with an enforced one-to-one stoichiometry. We demonstrate a small molecule substrate scope that includes primary and secondary amines, thiols, phenols, benzyl alcohols, and primary alcohols. Cheminformatic analyses predict that IMCT is reactive with more than 25% of lead-like compounds in publicly available databases. To demonstrate that the method can produce biologically active molecules, we generated FKBP12 photoaffinity labeling (PAL) compounds with a wide range of affinities and showed that purified and crude cleavage products can bind to and label FKBP12. This method could be used to rapidly modify small molecules for many applications, including the synthesis of PAL probes, fluorescence polarization probes, pull-down probes, and degraders.
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Affiliation(s)
- Catherine
C. Henry
- David
H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, United States
- MIT
Center for Precision Cancer Medicine, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
- Broad
Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
- Department
of Biological Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
| | - Jasmin A. Kruell
- David
H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, United States
- MIT
Center for Precision Cancer Medicine, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
- Broad
Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
| | - Robert M. Wilson
- David
H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, United States
- MIT
Center for Precision Cancer Medicine, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
- Broad
Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
- Department
of Biological Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
| | - Chia-Fu Chang
- Chemistry
and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Christina M. Woo
- Chemistry
and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Angela N. Koehler
- David
H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, United States
- MIT
Center for Precision Cancer Medicine, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
- Broad
Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
- Department
of Biological Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
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2
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Brulet JW, Ciancone AM, Yuan K, Hsu K. Advances in Activity‐Based Protein Profiling of Functional Tyrosines in Proteomes. Isr J Chem 2023. [DOI: 10.1002/ijch.202300001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Affiliation(s)
- Jeffrey W. Brulet
- Department of Chemistry University of Virginia Charlottesville Virginia 22904 United States (K.-L.H
| | - Anthony M. Ciancone
- Department of Chemistry University of Virginia Charlottesville Virginia 22904 United States (K.-L.H
| | - Kun Yuan
- Department of Chemistry University of Virginia Charlottesville Virginia 22904 United States (K.-L.H
| | - Ku‐Lung Hsu
- Department of Chemistry University of Virginia Charlottesville Virginia 22904 United States (K.-L.H
- Department of Pharmacology University of Virginia School of Medicine Charlottesville Virginia 22908 United States
- Department of Molecular Physiology and Biological Physics University of Virginia Charlottesville Virginia 22908 United States
- University of Virginia Cancer Center University of Virginia Charlottesville VA 22903 USA
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3
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Licciardello MP, Workman P. The era of high-quality chemical probes. RSC Med Chem 2022; 13:1446-1459. [PMID: 36545432 PMCID: PMC9749956 DOI: 10.1039/d2md00291d] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 11/11/2022] [Indexed: 11/29/2022] Open
Abstract
Small-molecule chemical probes are among the most important tools to study the function of proteins in cells and organisms. Regrettably, the use of weak and non-selective small molecules has generated an abundance of erroneous conclusions in the scientific literature. More recently, minimal criteria have been outlined for investigational compounds, encouraging the selection and use of high-quality chemical probes. Here, we briefly recall the milestones and key initiatives that have paved the way to this new era, illustrate examples of recent high-quality chemical probes and provide our perspective on future challenges and developments.
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Affiliation(s)
- Marco P. Licciardello
- Centre for Cancer Drug Discovery, Division of Cancer Therapeutics, The Institute of Cancer ResearchLondonUK
| | - Paul Workman
- Centre for Cancer Drug Discovery, Division of Cancer Therapeutics, The Institute of Cancer ResearchLondonUK,The Chemical Probes PortalUK
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4
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Janin YL. On drug discovery against infectious diseases and academic medicinal chemistry contributions. Beilstein J Org Chem 2022; 18:1355-1378. [PMID: 36247982 PMCID: PMC9531561 DOI: 10.3762/bjoc.18.141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 09/21/2022] [Indexed: 11/23/2022] Open
Abstract
This perspective is an attempt to document the problems that medicinal chemists are facing in drug discovery. It is also trying to identify relevant/possible, research areas in which academics can have an impact and should thus be the subject of grant calls. Accordingly, it describes how hit discovery happens, how compounds to be screened are selected from available chemicals and the possible reasons for the recurrent paucity of useful/exploitable results reported. This is followed by the successful hit to lead stories leading to recent and original antibacterials which are, or about to be, used in human medicine. Then, illustrated considerations and suggestions are made on the possible inputs of academic medicinal chemists. This starts with the observation that discovering a “good” hit in the course of a screening campaign still rely on a lot of luck – which is within the reach of academics –, that the hit to lead process requires a lot of chemistry and that if public–private partnerships can be important throughout these stages, they are absolute requirements for clinical trials. Concerning suggestions to improve the current hit success rate, one academic input in organic chemistry would be to identify new and pertinent chemical space, design synthetic accesses to reach these and prepare the corresponding chemical libraries. Concerning hit to lead programs on a given target, if no new hits are available, previously reported leads along with new structural data can be pertinent starting points to design, prepare and assay original analogues. In conclusion, this text is an actual plea illustrating that, in many countries, academic research in medicinal chemistry should be more funded, especially in the therapeutic area neglected by the industry. At the least, such funds would provide the intensive to secure series of hopefully relevant chemical entities which appears to often lack when considering the results of academic as well as industrial screening campaigns.
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Affiliation(s)
- Yves L Janin
- Structure et Instabilité des Génomes (StrInG), Muséum National d'Histoire Naturelle, INSERM, CNRS, Alliance Sorbonne Université, 75005 Paris, France
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5
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Škuta C, Southan C, Bartůněk P. Will the chemical probes please stand up? RSC Med Chem 2021; 12:1428-1441. [PMID: 34447939 PMCID: PMC8372204 DOI: 10.1039/d1md00138h] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/28/2021] [Indexed: 12/22/2022] Open
Abstract
In 2005, the NIH Molecular Libraries Program (MLP) undertook the identification of tool compounds to expand biological insights, now termed small-molecule chemical probes. This inspired other organisations to initiate similar efforts from 2010 onwards. As a central focus of the Probes & Drugs portal (P&D), we have standardised, integrated and compared sets of declared probe compounds harvested from 12 different sources. This turned out to be challenging and revealed unexpected anomalies. Results in this work address key questions including; a) individual and total structure counts, b) overlaps between sources, c) comparisons with selected PubChem sources and d) investigating the probe coverage of druggable targets. In addition, we developed new high-level scoring schemes to filter collections down to probes of higher quality. This generated 548 high-quality chemical probes (HQCP) covering 447 distinct protein targets. This HQCP collection has been added to the P&D portal and will be regularly updated as established sources expand and new ones release data.
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Affiliation(s)
- Ctibor Škuta
- CZ-OPENSCREEN, National Infrastructure for Chemical Biology, Institute of Molecular Genetics of the Czech Academy of Sciences Vídeňská 1083 142 20 Prague 4 Czech Republic
| | - Christopher Southan
- Deanery of Biomedical Sciences, University of Edinburgh Edinburgh EH8 9XD UK
| | - Petr Bartůněk
- CZ-OPENSCREEN, National Infrastructure for Chemical Biology, Institute of Molecular Genetics of the Czech Academy of Sciences Vídeňská 1083 142 20 Prague 4 Czech Republic
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6
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Antolin AA, Workman P, Al-Lazikani B. Public resources for chemical probes: the journey so far and the road ahead. Future Med Chem 2021; 13:731-747. [PMID: 31778323 DOI: 10.4155/fmc-2019-0231] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
High-quality small molecule chemical probes are extremely valuable for biological research and target validation. However, frequent use of flawed small-molecule inhibitors produces misleading results and diminishes the robustness of biomedical research. Several public resources are available to facilitate assessment and selection of better chemical probes for specific protein targets. Here, we review chemical probe resources, discuss their current strengths and limitations, and make recommendations for further improvements. Expert review resources provide in-depth analysis but currently cover only a limited portion of the liganded proteome. Computational resources encompass more proteins and are regularly updated, but have limitations in data availability and curation. We show how biomedical scientists may use these resources to choose the best available chemical probes for their research.
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Affiliation(s)
- Albert A Antolin
- The Department of Data Science, The Institute of Cancer Research, London, SM2 5NG, UK
- CRUK Cancer Therapeutics Unit, The Institute of Cancer Research, London, SM2 5NG, UK
- CRUK ICR/Imperial Convergence Science Centre, London, SM2 5NG, UK
| | - Paul Workman
- CRUK Cancer Therapeutics Unit, The Institute of Cancer Research, London, SM2 5NG, UK
- CRUK ICR/Imperial Convergence Science Centre, London, SM2 5NG, UK
| | - Bissan Al-Lazikani
- The Department of Data Science, The Institute of Cancer Research, London, SM2 5NG, UK
- CRUK Cancer Therapeutics Unit, The Institute of Cancer Research, London, SM2 5NG, UK
- CRUK ICR/Imperial Convergence Science Centre, London, SM2 5NG, UK
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7
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Canham SM, Wang Y, Cornett A, Auld DS, Baeschlin DK, Patoor M, Skaanderup PR, Honda A, Llamas L, Wendel G, Mapa FA, Aspesi P, Labbé-Giguère N, Gamber GG, Palacios DS, Schuffenhauer A, Deng Z, Nigsch F, Frederiksen M, Bushell SM, Rothman D, Jain RK, Hemmerle H, Briner K, Porter JA, Tallarico JA, Jenkins JL. Systematic Chemogenetic Library Assembly. Cell Chem Biol 2020; 27:1124-1129. [PMID: 32707038 DOI: 10.1016/j.chembiol.2020.07.004] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 06/03/2020] [Accepted: 07/02/2020] [Indexed: 12/22/2022]
Abstract
Chemogenetic libraries, collections of well-defined chemical probes, provide tremendous value to biomedical research but require substantial effort to ensure diversity as well as quality of the contents. We have assembled a chemogenetic library by data mining and crowdsourcing institutional expertise. We are sharing our approach, lessons learned, and disclosing our current collection of 4,185 compounds with their primary annotated gene targets (https://github.com/Novartis/MoaBox). This physical collection is regularly updated and used broadly both within Novartis and in collaboration with external partners.
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Affiliation(s)
- Stephen M Canham
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA.
| | - Yuan Wang
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Allen Cornett
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Douglas S Auld
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA.
| | - Daniel K Baeschlin
- Novartis Institute for BioMedical Research, Novartis Pharma AG, Forum 1 Novartis Campus, 4056 Basel, Switzerland
| | - Maude Patoor
- Novartis Institute for BioMedical Research, Novartis Pharma AG, Forum 1 Novartis Campus, 4056 Basel, Switzerland
| | - Philip R Skaanderup
- Novartis Institute for BioMedical Research, Novartis Pharma AG, Forum 1 Novartis Campus, 4056 Basel, Switzerland
| | - Ayako Honda
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Luis Llamas
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Greg Wendel
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Felipa A Mapa
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Peter Aspesi
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Nancy Labbé-Giguère
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Gabriel G Gamber
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Daniel S Palacios
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Ansgar Schuffenhauer
- Novartis Institute for BioMedical Research, Novartis Pharma AG, Forum 1 Novartis Campus, 4056 Basel, Switzerland
| | - Zhan Deng
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Florian Nigsch
- Novartis Institute for BioMedical Research, Novartis Pharma AG, Forum 1 Novartis Campus, 4056 Basel, Switzerland
| | - Mathias Frederiksen
- Novartis Institute for BioMedical Research, Novartis Pharma AG, Forum 1 Novartis Campus, 4056 Basel, Switzerland
| | - Simon M Bushell
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Deborah Rothman
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Rishi K Jain
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Horst Hemmerle
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Karin Briner
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Jeffery A Porter
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - John A Tallarico
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Jeremy L Jenkins
- Novartis Institute for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA.
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8
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Abstract
Drug design needs high-quality chemical probes for target validation, but the demands on chemical probes are largely different than those on drugs. Whereas therapeutic value and safety are main criteria for a drug evaluation, the chemical probe is influencing a biological target in a well-characterized way. Affinity, efficacy, selectivity and versatility in different read-outs are main criteria for chemical probes to test biochemical hypothesis and verify targets for new therapeutic approaches.
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Affiliation(s)
- Holger Stark
- Heinrich Heine University Düsseldorf, Institut fuer Pharmazeutische und Medizinische Chemie , Duesseldorf, Germany
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9
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Clegg MA, Bamborough P, Chung CW, Craggs PD, Gordon L, Grandi P, Leveridge M, Lindon M, Liwicki GM, Michon AM, Molnar J, Rioja I, Soden PE, Theodoulou NH, Werner T, Tomkinson NCO, Prinjha RK, Humphreys PG. Application of Atypical Acetyl-lysine Methyl Mimetics in the Development of Selective Inhibitors of the Bromodomain-Containing Protein 7 (BRD7)/Bromodomain-Containing Protein 9 (BRD9) Bromodomains. J Med Chem 2020; 63:5816-5840. [PMID: 32410449 DOI: 10.1021/acs.jmedchem.0c00075] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Non-BET bromodomain-containing proteins have become attractive targets for the development of novel therapeutics targeting epigenetic pathways. To help facilitate the target validation of this class of proteins, structurally diverse small-molecule ligands and methodologies to produce selective inhibitors in a predictable fashion are in high demand. Herein, we report the development and application of atypical acetyl-lysine (KAc) methyl mimetics to take advantage of the differential stability of conserved water molecules in the bromodomain binding site. Discovery of the n-butyl group as an atypical KAc methyl mimetic allowed generation of 31 (GSK6776) as a soluble, permeable, and selective BRD7/9 inhibitor from a pyridazinone template. The n-butyl group was then used to enhance the bromodomain selectivity of an existing BRD9 inhibitor and to transform pan-bromodomain inhibitors into BRD7/9 selective compounds. Finally, a solvent-exposed vector was defined from the pyridazinone template to enable bifunctional molecule synthesis, and affinity enrichment chemoproteomic experiments were used to confirm several of the endogenous protein partners of BRD7 and BRD9, which form part of the chromatin remodeling PBAF and BAF complexes, respectively.
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Affiliation(s)
- Michael A Clegg
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom.,WestCHEM, Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, 295 Cathedral Street, Glasgow G1 1XL, United Kingdom
| | - Paul Bamborough
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Chun-Wa Chung
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Peter D Craggs
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Laurie Gordon
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Paola Grandi
- Cellzome GmbH, R&D MST GlaxoSmithKline, Meyerhofstrasse 1 69117 Heidelberg, Germany
| | - Melanie Leveridge
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Matthew Lindon
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Gemma M Liwicki
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Anne-Marie Michon
- Cellzome GmbH, R&D MST GlaxoSmithKline, Meyerhofstrasse 1 69117 Heidelberg, Germany
| | - Judit Molnar
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Inmaculada Rioja
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Peter E Soden
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
| | - Natalie H Theodoulou
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom.,WestCHEM, Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, 295 Cathedral Street, Glasgow G1 1XL, United Kingdom
| | - Thilo Werner
- Cellzome GmbH, R&D MST GlaxoSmithKline, Meyerhofstrasse 1 69117 Heidelberg, Germany
| | - Nicholas C O Tomkinson
- WestCHEM, Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, 295 Cathedral Street, Glasgow G1 1XL, United Kingdom
| | - Rab K Prinjha
- GlaxoSmithKline R&D, Stevenage SG1 2NY, Hertfordshire, United Kingdom
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10
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Pacureanu L, Avram S, Crisan L. Comprehensive investigation of selectivity landscape of glycogen synthase kinase-3 inhibitors. J Biomol Struct Dyn 2020; 39:2318-2337. [PMID: 32216607 DOI: 10.1080/07391102.2020.1747544] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Interaction signatures of drug candidates are characteristic to off-target (neutral) and antitarget (negative) effects, inferring reduced efficiency, side-effects and high attrition rate. Today's retroactive scaled-down virtual screening (VS) experiments relying on benchmarking datasets are extensively involved to assess ligand enrichment in the real-world problem. In recent years, unbiased benchmarking sets turned into a tremendous need to assist virtual screening methodologies for emerging drug targets. To date, the benchmarking datasets are quite limited, whereas glycogen synthase kinase-3 (GSK-3) is not included into directories of benchmarking datasets such as DUD-e, MUV, etc. Herein we introduced our in-house algorithm to build an unbiased benchmarking dataset, including highly selective, moderately selective and nonselective inhibitors for a significant therapeutic target - GSK-3, suitable for both ligand-based and structure-based VS approaches. These datasets are unbiased in terms of physico-chemical properties and topological descriptors, as resulted from mean(ROC-AUC) leave-one-out cross-validation (LOO CV). and additional 2 D similarity search. Moreover, we investigated the gradual selectivity dataset by application of multiple 2 D similarity coefficients and distances, 3 D similarity and docking. Besides the resulted links between the enrichment of selective GSK-3 inhibitors and their chemical structures, a database of compounds and their 3 D similarity signatures including cut-off thresholds for enhanced selectivity was generated. 2 D similarity space analysis revealed that selectivity problem cannot be evaluated appropriately with 2 D similarity searching alone. The current analysis provided useful, comprehensive insights, which may facilitate the knowledge-based identification of novel selective GSK-3 inhibitors.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Liliana Pacureanu
- "Coriolan Dragulescu" Institute of Chemistry, Romanian Academy, Timisoara, Romania
| | - Sorin Avram
- "Coriolan Dragulescu" Institute of Chemistry, Romanian Academy, Timisoara, Romania
| | - Luminita Crisan
- "Coriolan Dragulescu" Institute of Chemistry, Romanian Academy, Timisoara, Romania
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11
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Clegg MA, Tomkinson NCO, Prinjha RK, Humphreys PG. Advancements in the Development of non-BET Bromodomain Chemical Probes. ChemMedChem 2019; 14:362-385. [PMID: 30624862 DOI: 10.1002/cmdc.201800738] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Indexed: 01/07/2023]
Abstract
The bromodomain and extra terminal (BET) family of bromodomain-containing proteins (BCPs) have been the subject of extensive research over the past decade, resulting in a plethora of high-quality chemical probes for their tandem bromodomains. In turn, these chemical probes have helped reveal the profound biological role of the BET bromodomains and their role in disease, ultimately leading to a number of molecules in active clinical development. However, the BET subfamily represents just 8/61 of the known human bromodomains, and attention has now expanded to the biological role of the remaining 53 non-BET bromodomains. Rapid growth of this research area has been accompanied by a greater understanding of the requirements for an effective bromodomain chemical probe and has led to a number of new non-BET bromodomain chemical probes being developed. Advances since December 2015 are discussed, highlighting the strengths/caveats of each molecule, and the value they add toward validating the non-BET bromodomains as tractable therapeutic targets.
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Affiliation(s)
- Michael A Clegg
- Epigenetics Discovery Performance Unit, GlaxoSmithKline R&D, Stevenage, Hertfordshire, SG1 2NY, UK.,WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, 295 Cathedral Street, Thomas Graham Building, Glasgow, G1 1XL, UK
| | - Nicholas C O Tomkinson
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, 295 Cathedral Street, Thomas Graham Building, Glasgow, G1 1XL, UK
| | - Rab K Prinjha
- Epigenetics Discovery Performance Unit, GlaxoSmithKline R&D, Stevenage, Hertfordshire, SG1 2NY, UK
| | - Philip G Humphreys
- Epigenetics Discovery Performance Unit, GlaxoSmithKline R&D, Stevenage, Hertfordshire, SG1 2NY, UK
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12
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Ichiishi N, Moore KP, Wassermann AM, Wolkenberg SE, Krska SW. Reducing Limitation in Probe Design: The Development of a Diazirine-Compatible Suzuki-Miyaura Cross Coupling Reaction. ACS Med Chem Lett 2019; 10:56-61. [PMID: 30655947 DOI: 10.1021/acsmedchemlett.8b00403] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2018] [Accepted: 12/06/2018] [Indexed: 12/17/2022] Open
Abstract
Access to high quality photoaffinity probe molecules is often constrained by synthetic limitations related to diazirine installation. A survey of recently published photoaffinity probe syntheses identified the Suzuki-Miyaura (S-M) coupling reaction, ubiquitous in drug discovery, as being underutilized to incorporate diazirines. To test whether advances in modern cross-coupling catalysis might enable efficient S-M couplings tolerant of the diazirine moiety, a fragment-based screening approach was employed. A model S-M coupling reaction was screened under various conditions in the presence of an aromatic diazirine fragment. This screen identified reaction conditions that gave good yields of S-M coupling product while minimally perturbing the diazirine reporter fragment. These conditions were found to be highly scalable and exhibited broad scope when applied to a chemistry informer library of 24 pharmaceutically relevant aryl boron pinacol esters. Furthermore, these conditions were used to synthesize a known diazirine-containing probe molecule with improved synthetic efficiency.
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Affiliation(s)
- Naoko Ichiishi
- Merck & Co., Inc., Discovery Chemistry, HTE and Lead Discovery Capabilities, Kenilworth, New Jersey 07033, United States
| | - Keith P. Moore
- Merck & Co., Inc., Discovery Chemistry, Chemical Biology, West Point, Pennsylvania 19486, United States
| | - Anne Mai Wassermann
- Merck & Co., Inc., Discovery Chemistry, Chemistry Informatics, Boston, Massachusetts 02115, United States
| | - Scott E. Wolkenberg
- Merck & Co., Inc., Discovery Chemistry, Chemical Biology, West Point, Pennsylvania 19486, United States
| | - Shane W. Krska
- Merck & Co., Inc., Discovery Chemistry, HTE and Lead Discovery Capabilities, Kenilworth, New Jersey 07033, United States
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13
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Bologa CG, Ursu O, Oprea TI. How to Prepare a Compound Collection Prior to Virtual Screening. Methods Mol Biol 2019; 1939:119-138. [PMID: 30848459 DOI: 10.1007/978-1-4939-9089-4_7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Virtual screening is a well-established technique that has proven to be successful in the identification of novel biologically active molecules, including drug repurposing. Whether for ligand-based or for structure-based virtual screening, a chemical collection needs to be properly processed prior to in silico evaluation. Here we describe our step-by-step procedure for handling very large collections (up to billions) of compounds prior to virtual screening.
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Affiliation(s)
- Cristian G Bologa
- Division of Translational Informatics, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Oleg Ursu
- Merck Research Laboratories, Boston, MA, USA.,Division of Translational Informatics, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Tudor I Oprea
- Division of Translational Informatics, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA.
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14
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Affiliation(s)
- Kamal Kumar
- Max-Planck-Institut für molekulare PhysiologieAbteilung Chemische Biologie Otto-Hahn Str. 11 44227- Dortmund Germany
| | - Herbert Waldmann
- Max-Planck-Institut für molekulare PhysiologieAbteilung Chemische Biologie Otto-Hahn Str. 11 44227- Dortmund Germany
- Technische Universität DortmundFakultät Chemie, Chemische Biologie Otto-Hahn-Straße 6 Dortmund 44221 Germany
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15
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Saha A, Varghese T, Liu A, Allen SJ, Mirzadegan T, Hack MD. An Analysis of Different Components of a High-Throughput Screening Library. J Chem Inf Model 2018; 58:2057-2068. [PMID: 30204440 DOI: 10.1021/acs.jcim.8b00258] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Since many projects at pharmaceutical organizations get their start from a high-throughput screening (HTS) campaign, improving the quality of the HTS deck can improve the likelihood of discovering a high-quality lead molecule that can be progressed to a drug candidate. Over the past decade, Janssen has implemented several strategies for external compound acquisition to augment the screening deck beyond the chemical space and number of molecules synthesized for internal projects. In this report, we analyzed the performance of each of those compound collections in the screening campaigns performed internally within Janssen during the last five years. We classified the screening library into two broad categories: Internal and External. The comparison of the performance of these sets of libraries was done by considering the primary, confirmation, and dose response hit rates. Our analysis revealed that Internal compounds (resulting from numerous medicinal chemistry efforts against diverse protein targets) have higher average confirmation hit rates than External ones; however, actives from both categories show similar probabilities of hitting multiple distinct targets. We also investigated the property landscape of both sets of libraries to identify the key elements which make a difference in these categories of compounds. From this analysis, Janssen aims to understand the descriptor landscape of the compounds with the highest hit rates and to use them for improving its future acquisition strategies as well as to inform our plating strategy.
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Affiliation(s)
- Arjun Saha
- Janssen Pharmaceutical Research and Development , 3210 Merryfield Row , La Jolla , California 92121 , United States
| | - Teena Varghese
- Janssen Pharmaceutical Research and Development , 3210 Merryfield Row , La Jolla , California 92121 , United States
| | - Annie Liu
- Janssen Pharmaceutical Research and Development , 3210 Merryfield Row , La Jolla , California 92121 , United States
| | - Samantha J Allen
- Janssen Pharmaceutical Research and Development , 3210 Merryfield Row , La Jolla , California 92121 , United States
| | - Taraneh Mirzadegan
- Janssen Pharmaceutical Research and Development , 3210 Merryfield Row , La Jolla , California 92121 , United States
| | - Michael D Hack
- Janssen Pharmaceutical Research and Development , 3210 Merryfield Row , La Jolla , California 92121 , United States
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16
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Cheminformatics in the Service of GPCR Drug Discovery. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2018; 1705:395-411. [PMID: 29188575 DOI: 10.1007/978-1-4939-7465-8_20] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Cheminformatics is a broad discipline covering a wide range of computational approaches, including the characterization of molecular similarity, pattern recognition, and predictive modeling. The unifying theme that these apparently disparate methods have in common is the aim of extracting useable information from the increasing amounts of data that are associated with contemporary drug discovery projects. Both proprietary and publically available data can be exploited to help inform and improve the process of developing novel therapeutic molecules targeting the GPCR family of proteins.
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17
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Antolin AA, Tym JE, Komianou A, Collins I, Workman P, Al-Lazikani B. Objective, Quantitative, Data-Driven Assessment of Chemical Probes. Cell Chem Biol 2018; 25:194-205.e5. [PMID: 29249694 PMCID: PMC5814752 DOI: 10.1016/j.chembiol.2017.11.004] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 09/22/2017] [Accepted: 11/14/2017] [Indexed: 12/21/2022]
Abstract
Chemical probes are essential tools for understanding biological systems and for target validation, yet selecting probes for biomedical research is rarely based on objective assessment of all potential compounds. Here, we describe the Probe Miner: Chemical Probes Objective Assessment resource, capitalizing on the plethora of public medicinal chemistry data to empower quantitative, objective, data-driven evaluation of chemical probes. We assess >1.8 million compounds for their suitability as chemical tools against 2,220 human targets and dissect the biases and limitations encountered. Probe Miner represents a valuable resource to aid the identification of potential chemical probes, particularly when used alongside expert curation.
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Affiliation(s)
- Albert A Antolin
- Cancer Research UK Cancer Therapeutics Unit, Division of Cancer Therapeutics, The Institute of Cancer Research, 15 Cotswold Road, London SM2 5NG, UK; Department of Data Science, The Institute of Cancer Research, 15 Cotswold Road, London SM2 5NG, UK
| | - Joseph E Tym
- Department of Data Science, The Institute of Cancer Research, 15 Cotswold Road, London SM2 5NG, UK
| | - Angeliki Komianou
- Department of Data Science, The Institute of Cancer Research, 15 Cotswold Road, London SM2 5NG, UK
| | - Ian Collins
- Cancer Research UK Cancer Therapeutics Unit, Division of Cancer Therapeutics, The Institute of Cancer Research, 15 Cotswold Road, London SM2 5NG, UK
| | - Paul Workman
- Cancer Research UK Cancer Therapeutics Unit, Division of Cancer Therapeutics, The Institute of Cancer Research, 15 Cotswold Road, London SM2 5NG, UK.
| | - Bissan Al-Lazikani
- Cancer Research UK Cancer Therapeutics Unit, Division of Cancer Therapeutics, The Institute of Cancer Research, 15 Cotswold Road, London SM2 5NG, UK; Department of Data Science, The Institute of Cancer Research, 15 Cotswold Road, London SM2 5NG, UK.
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18
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Baba Y, Isomura T, Kashima H. Wisdom of crowds for synthetic accessibility evaluation. J Mol Graph Model 2018; 80:217-223. [PMID: 29414041 DOI: 10.1016/j.jmgm.2018.01.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Revised: 01/14/2018] [Accepted: 01/15/2018] [Indexed: 11/15/2022]
Abstract
Synthetic accessibility evaluation is a process to assess the ease of synthesis of compounds. A rapid method for the assessment of synthetic accessibility for a vast number of chemical compounds is expected to bring about a breakthrough in the drug discovery. Although several computational methods have been proposed, the compound evaluation has still been processed by medicinal chemists; however, the low throughput of the human evaluation due to the lack of chemists is a critical issue for handling a large number of compounds. We propose the use of crowdsourcing for addressing this problem, and we conducted experiments to investigate the feasibility of incorporating semi-experts and a statistical aggregation method into the synthetic accessibility evaluation. Our experimental results show that we can obtain accurate synthetic accessibility scores through the statistical aggregation of judgments from semi-experts.
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Affiliation(s)
- Yukino Baba
- Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan.
| | - Tetsu Isomura
- Mitsubishi Chemical Holdings Corporation, 1-1, Marunouchi 1-chome, Chiyoda-ku, Tokyo 100-8251, Japan.
| | - Hisashi Kashima
- Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan.
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19
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Ekins S, Clark AM, Dole K, Gregory K, Mcnutt AM, Spektor AC, Weatherall C, Litterman NK, Bunin BA. Data Mining and Computational Modeling of High-Throughput Screening Datasets. Methods Mol Biol 2018; 1755:197-221. [PMID: 29671272 DOI: 10.1007/978-1-4939-7724-6_14] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
We are now seeing the benefit of investments made over the last decade in high-throughput screening (HTS) that is resulting in large structure activity datasets entering public and open databases such as ChEMBL and PubChem. The growth of academic HTS screening centers and the increasing move to academia for early stage drug discovery suggests a great need for the informatics tools and methods to mine such data and learn from it. Collaborative Drug Discovery, Inc. (CDD) has developed a number of tools for storing, mining, securely and selectively sharing, as well as learning from such HTS data. We present a new web based data mining and visualization module directly within the CDD Vault platform for high-throughput drug discovery data that makes use of a novel technology stack following modern reactive design principles. We also describe CDD Models within the CDD Vault platform that enables researchers to share models, share predictions from models, and create models from distributed, heterogeneous data. Our system is built on top of the Collaborative Drug Discovery Vault Activity and Registration data repository ecosystem which allows users to manipulate and visualize thousands of molecules in real time. This can be performed in any browser on any platform. In this chapter we present examples of its use with public datasets in CDD Vault. Such approaches can complement other cheminformatics tools, whether open source or commercial, in providing approaches for data mining and modeling of HTS data.
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Affiliation(s)
- Sean Ekins
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, NC, 27606, USA.
| | - Alex M Clark
- Collaborative Drug Discovery, Inc., Burlingame, CA, USA
- Molecular Materials Informatics, Inc., Montreal, QC, Canada
| | - Krishna Dole
- Collaborative Drug Discovery, Inc., Burlingame, CA, USA
| | | | | | | | | | | | - Barry A Bunin
- Collaborative Drug Discovery, Inc., Burlingame, CA, USA
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20
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Coussens NP, Braisted JC, Peryea T, Sittampalam GS, Simeonov A, Hall MD. Small-Molecule Screens: A Gateway to Cancer Therapeutic Agents with Case Studies of Food and Drug Administration-Approved Drugs. Pharmacol Rev 2017; 69:479-496. [PMID: 28931623 DOI: 10.1124/pr.117.013755] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
High-throughput screening (HTS) of small-molecule libraries accelerates the discovery of chemical leads to serve as starting points for probe or therapeutic development. With this approach, thousands of unique small molecules, representing a diverse chemical space, can be rapidly evaluated by biologically and physiologically relevant assays. The origins of numerous United States Food and Drug Administration-approved cancer drugs are linked to HTS, which emphasizes the value in this methodology. The National Institutes of Health Molecular Libraries Program made HTS accessible to the public sector, enabling the development of chemical probes and drug-repurposing initiatives. In this work, the impact of HTS in the field of oncology is considered among both private and public sectors. Examples are given for the discovery and development of approved cancer drugs. The importance of target validation is discussed, and common assay approaches for screening are reviewed. A rigorous examination of the PubChem database demonstrates that public screening centers are contributing to early-stage drug discovery in oncology by focusing on new targets and developing chemical probes. Several case studies highlight the value of different screening strategies and the potential for drug repurposing.
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Affiliation(s)
- Nathan P Coussens
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland
| | - John C Braisted
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland
| | - Tyler Peryea
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland
| | - G Sitta Sittampalam
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland
| | - Anton Simeonov
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland
| | - Matthew D Hall
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland
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21
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Butler KV, MacDonald IA, Hathaway NA, Jin J. Report and Application of a Tool Compound Data Set. J Chem Inf Model 2017; 57:2699-2706. [PMID: 29035535 PMCID: PMC5705340 DOI: 10.1021/acs.jcim.7b00343] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
![]()
Small molecule tool compounds have
enabled profound advances in
life science research. These chemicals are potent, cell active, and
selective, and, thus, are suitable for interrogating biological processes.
For these chemicals to be useful they must be correctly characterized
and researchers must be aware of them. We mined the ChEMBL bioactivity
database to identify high quality tool compounds in an unbiased way.
We identified 407 best-in-class compounds for 278 protein targets,
and these are reported in an annotated data set. Additionally, we
developed informatics functions and a web application for data visualization
and automated pharmacological hypothesis generation. These functions
were used to predict inhibitors of the Chromobox Protein Homologue
5 (CBX5) mediated gene repression pathway that currently lacks appropriate
inhibitors. The predictions were subsequently validated by a highly
specific cell based assay, revealing new chemical modulators of CBX5-mediated
heterochromatin formation. This data set and associated functions
will help researchers make the best use of these valuable compounds.
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Affiliation(s)
- Kyle V Butler
- Center for Chemical Biology and Drug Discovery, Departments of Pharmacological Sciences and Oncological Sciences, Icahn School of Medicine at Mount Sinai , New York, New York 10029, United States
| | - Ian A MacDonald
- Division of Chemical Biology and Medicinal Chemistry, Center for Integrative Chemical Biology and Drug Discovery, UNC Eshelman School of Pharmacy , Chapel Hill, North Carolina 27599, United States.,Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina 27599, United States
| | - Nathaniel A Hathaway
- Division of Chemical Biology and Medicinal Chemistry, Center for Integrative Chemical Biology and Drug Discovery, UNC Eshelman School of Pharmacy , Chapel Hill, North Carolina 27599, United States.,Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina 27599, United States
| | - Jian Jin
- Center for Chemical Biology and Drug Discovery, Departments of Pharmacological Sciences and Oncological Sciences, Icahn School of Medicine at Mount Sinai , New York, New York 10029, United States
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22
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Nie Y, Littleton B, Kavanagh T, Abbate V, Bansal SS, Richards D, Hylands P, Stürzenbaum SR. Proanthocyanidin trimer gallate modulates lipid deposition and fatty acid desaturation in
Caenorhabditis elegans. FASEB J 2017; 31:4891-4902. [DOI: 10.1096/fj.201700438r] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Accepted: 07/05/2017] [Indexed: 12/14/2022]
Affiliation(s)
- Yu Nie
- Analytical and Environmental Sciences DivisionFaculty of Life Sciences and Medicine
| | - Brad Littleton
- Department of PhysicsFaculty of Natural and Mathematical SciencesKing’s College LondonLondonUnited Kingdom
| | - Thomas Kavanagh
- Department of PhysicsFaculty of Natural and Mathematical SciencesKing’s College LondonLondonUnited Kingdom
| | - Vincenzo Abbate
- Institute of Pharmaceutical ScienceFaculty of Life Sciences and Medicine
| | | | - David Richards
- Department of PhysicsFaculty of Natural and Mathematical SciencesKing’s College LondonLondonUnited Kingdom
| | - Peter Hylands
- Institute of Pharmaceutical ScienceFaculty of Life Sciences and Medicine
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23
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Blagg J, Workman P. Choose and Use Your Chemical Probe Wisely to Explore Cancer Biology. Cancer Cell 2017; 32:9-25. [PMID: 28697345 PMCID: PMC5511331 DOI: 10.1016/j.ccell.2017.06.005] [Citation(s) in RCA: 121] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Revised: 05/31/2017] [Accepted: 06/09/2017] [Indexed: 01/15/2023]
Abstract
Small-molecule chemical probes or tools have become progressively more important in recent years as valuable reagents to investigate fundamental biological mechanisms and processes causing disease, including cancer. Chemical probes have also achieved greater prominence alongside complementary biological reagents for target validation in drug discovery. However, there is evidence of widespread continuing misuse and promulgation of poor-quality and insufficiently selective chemical probes, perpetuating a worrisome and misleading pollution of the scientific literature. We discuss current challenges with the selection and use of chemical probes, and suggest how biologists can and should be more discriminating in the probes they employ.
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Affiliation(s)
- Julian Blagg
- Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London SM2 5NG, UK.
| | - Paul Workman
- Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London SM2 5NG, UK.
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24
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Prelec D, Seung HS, McCoy J. A solution to the single-question crowd wisdom problem. Nature 2017; 541:532-535. [PMID: 28128245 DOI: 10.1038/nature21054] [Citation(s) in RCA: 115] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2016] [Accepted: 12/09/2016] [Indexed: 11/09/2022]
Abstract
Once considered provocative, the notion that the wisdom of the crowd is superior to any individual has become itself a piece of crowd wisdom, leading to speculation that online voting may soon put credentialed experts out of business. Recent applications include political and economic forecasting, evaluating nuclear safety, public policy, the quality of chemical probes, and possible responses to a restless volcano. Algorithms for extracting wisdom from the crowd are typically based on a democratic voting procedure. They are simple to apply and preserve the independence of personal judgment. However, democratic methods have serious limitations. They are biased for shallow, lowest common denominator information, at the expense of novel or specialized knowledge that is not widely shared. Adjustments based on measuring confidence do not solve this problem reliably. Here we propose the following alternative to a democratic vote: select the answer that is more popular than people predict. We show that this principle yields the best answer under reasonable assumptions about voter behaviour, while the standard 'most popular' or 'most confident' principles fail under exactly those same assumptions. Like traditional voting, the principle accepts unique problems, such as panel decisions about scientific or artistic merit, and legal or historical disputes. The potential application domain is thus broader than that covered by machine learning and psychometric methods, which require data across multiple questions.
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Affiliation(s)
- Dražen Prelec
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.,Department of Economics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.,Department of Brain &Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - H Sebastian Seung
- Princeton Neuroscience Institute and Computer Science Department, Princeton University, Princeton, New Jersey 08544, USA
| | - John McCoy
- Department of Brain &Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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25
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Abstract
Collective intelligence is the ability of a group to perform more effectively than any individual alone. Diversity among group members is a key condition for the emergence of collective intelligence, but maintaining diversity is challenging in the face of social pressure to imitate one's peers. Through an evolutionary game-theoretic model of collective prediction, we investigate the role that incentives may play in maintaining useful diversity. We show that market-based incentive systems produce herding effects, reduce information available to the group, and restrain collective intelligence. Therefore, we propose an incentive scheme that rewards accurate minority predictions and show that this produces optimal diversity and collective predictive accuracy. We conclude that real world systems should reward those who have shown accuracy when the majority opinion has been in error.
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26
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Chen L, Wilson K, Goldlust I, Mott BT, Eastman R, Davis MI, Zhang X, McKnight C, Klumpp-Thomas C, Shinn P, Simmons J, Gormally M, Michael S, Thomas CJ, Ferrer M, Guha R. mQC: A Heuristic Quality-Control Metric for High-Throughput Drug Combination Screening. Sci Rep 2016; 6:37741. [PMID: 27883049 PMCID: PMC5121902 DOI: 10.1038/srep37741] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Accepted: 11/01/2016] [Indexed: 11/09/2022] Open
Abstract
Quality control (QC) metrics are critical in high throughput screening (HTS) platforms to ensure reliability and confidence in assay data and downstream analyses. Most reported HTS QC metrics are designed for plate level or single well level analysis. With the advent of high throughput combination screening there is a need for QC metrics that quantify the quality of combination response matrices. We introduce a predictive, interpretable, matrix-level QC metric, mQC, based on a mix of data-derived and heuristic features. mQC accurately reproduces the expert assessment of combination response quality and correctly identifies unreliable response matrices that can lead to erroneous or misleading characterization of synergy. When combined with the plate-level QC metric, Z', mQC provides a more appropriate determination of the quality of a drug combination screen. Retrospective analysis on a number of completed combination screens further shows that mQC is able to identify problematic screens whereas plate-level QC was not able to. In conclusion, our data indicates that mQC is a reliable QC filter that can be used to identify problematic drug combinations matrices and prevent further analysis on erroneously active combinations as well as for troubleshooting failed screens. The R source code of mQC is available at http://matrix.ncats.nih.gov/mQC.
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Affiliation(s)
- Lu Chen
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Kelli Wilson
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Ian Goldlust
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Bryan T. Mott
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Richard Eastman
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Mindy I. Davis
- National Institute of Allergy and Infectious Diseases (NIAID), Rockville, MD 20852, USA
| | - Xiaohu Zhang
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Crystal McKnight
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Carleen Klumpp-Thomas
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Paul Shinn
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - John Simmons
- Laboratory of Cancer Biology and Genetics, National Cancer Institute (NCI), Bethesda, MD 20892, USA
| | - Mike Gormally
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Sam Michael
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Craig J. Thomas
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Marc Ferrer
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
| | - Rajarshi Guha
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences (NCATS), Rockville, MD 20850, USA
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27
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Yang JJ, Ursu O, Lipinski CA, Sklar LA, Oprea TI, Bologa CG. Badapple: promiscuity patterns from noisy evidence. J Cheminform 2016; 8:29. [PMID: 27239230 PMCID: PMC4884375 DOI: 10.1186/s13321-016-0137-3] [Citation(s) in RCA: 76] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 04/26/2016] [Indexed: 01/01/2023] Open
Abstract
Background Bioassay data analysis continues to be an essential, routine, yet challenging task in modern drug discovery and chemical biology research. The challenge is to infer reliable knowledge from big and noisy data. Some aspects of this problem are general with solutions informed by existing and emerging data science best practices. Some aspects are domain specific, and rely on expertise in bioassay methodology and chemical biology. Testing compounds for biological activity requires complex and innovative methodology, producing results varying widely in accuracy, precision, and information content. Hit selection criteria involve optimizing such that the overall probability of success in a project is maximized, and resource-wasteful “false trails” are avoided. This “fail-early” approach is embraced both in pharmaceutical and academic drug discovery, since follow-up capacity is resource-limited. Thus, early identification of likely promiscuous compounds has practical value. Results Here we describe an algorithm for identifying likely promiscuous compounds via associated scaffolds which combines general and domain-specific features to assist and accelerate drug discovery informatics, called Badapple: bioassay-data associative promiscuity pattern learning engine. Results are described from an analysis using data from MLP assays via the BioAssay Research Database (BARD) http://bard.nih.gov. Specific examples are analyzed in the context of medicinal chemistry, to illustrate associations with mechanisms of promiscuity. Badapple has been developed at UNM, released and deployed for public use two ways: (1) BARD plugin, integrated into the public BARD REST API and BARD web client; and (2) public web app hosted at UNM. Conclusions Badapple is a method for rapidly identifying likely promiscuous compounds via associated scaffolds. Badapple generates a score associated with a pragmatic, empirical definition of promiscuity, with the overall goal to identify “false trails” and streamline workflows. Unlike methods reliant on expert curation of chemical substructure patterns, Badapple is fully evidence-driven, automated, self-improving via integration of additional data, and focused on scaffolds. Badapple is robust with respect to noise and errors, and skeptical of scanty evidence. Electronic supplementary material The online version of this article (doi:10.1186/s13321-016-0137-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jeremy J Yang
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM 87131 USA
| | - Oleg Ursu
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM 87131 USA
| | | | - Larry A Sklar
- Department of Pathology, Center for Molecular Discovery, University of New Mexico School of Medicine, Albuquerque, NM 87131 USA
| | - Tudor I Oprea
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM 87131 USA
| | - Cristian G Bologa
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM 87131 USA
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28
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Chen S, Zhang P, Liu X, Qin C, Tao L, Zhang C, Yang SY, Chen YZ, Chui WK. Towards cheminformatics-based estimation of drug therapeutic index: Predicting the protective index of anticonvulsants using a new quantitative structure-index relationship approach. J Mol Graph Model 2016; 67:102-10. [PMID: 27262528 DOI: 10.1016/j.jmgm.2016.05.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Revised: 05/17/2016] [Accepted: 05/18/2016] [Indexed: 02/05/2023]
Abstract
The overall efficacy and safety profile of a new drug is partially evaluated by the therapeutic index in clinical studies and by the protective index (PI) in preclinical studies. In-silico predictive methods may facilitate the assessment of these indicators. Although QSAR and QSTR models can be used for predicting PI, their predictive capability has not been evaluated. To test this capability, we developed QSAR and QSTR models for predicting the activity and toxicity of anticonvulsants at accuracy levels above the literature-reported threshold (LT) of good QSAR models as tested by both the internal 5-fold cross validation and external validation method. These models showed significantly compromised PI predictive capability due to the cumulative errors of the QSAR and QSTR models. Therefore, in this investigation a new quantitative structure-index relationship (QSIR) model was devised and it showed improved PI predictive capability that superseded the LT of good QSAR models. The QSAR, QSTR and QSIR models were developed using support vector regression (SVR) method with the parameters optimized by using the greedy search method. The molecular descriptors relevant to the prediction of anticonvulsant activities, toxicities and PIs were analyzed by a recursive feature elimination method. The selected molecular descriptors are primarily associated with the drug-like, pharmacological and toxicological features and those used in the published anticonvulsant QSAR and QSTR models. This study suggested that QSIR is useful for estimating the therapeutic index of drug candidates.
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Affiliation(s)
- Shangying Chen
- Department of Pharmacy, National University of Singapore, 18 Science Drive 4, Singapore 117543, Singapore
| | - Peng Zhang
- Department of Pharmacy, National University of Singapore, 18 Science Drive 4, Singapore 117543, Singapore
| | - Xin Liu
- Shanghai Applied Protein Technology Co. Ltd, Research Center for Proteome Analysis, Institute of Biochemistry and cell Biology, Shanghai Institutes for Biological Sciences, Shanghai, 200233, China
| | - Chu Qin
- Department of Pharmacy, National University of Singapore, 18 Science Drive 4, Singapore 117543, Singapore
| | - Lin Tao
- Department of Pharmacy, National University of Singapore, 18 Science Drive 4, Singapore 117543, Singapore
| | - Cheng Zhang
- Department of Pharmacy, National University of Singapore, 18 Science Drive 4, Singapore 117543, Singapore
| | - Sheng Yong Yang
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, West China Medical School, Sichuan University, Sichuan, China
| | - Yu Zong Chen
- Department of Pharmacy, National University of Singapore, 18 Science Drive 4, Singapore 117543, Singapore.
| | - Wai Keung Chui
- Department of Pharmacy, National University of Singapore, 18 Science Drive 4, Singapore 117543, Singapore.
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29
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Dark chemical matter as a promising starting point for drug lead discovery. Nat Chem Biol 2015; 11:958-66. [DOI: 10.1038/nchembio.1936] [Citation(s) in RCA: 95] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2015] [Accepted: 09/10/2015] [Indexed: 11/08/2022]
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30
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Patridge EV, Gareiss PC, Kinch MS, Hoyer DW. An analysis of original research contributions toward FDA-approved drugs. Drug Discov Today 2015; 20:1182-7. [DOI: 10.1016/j.drudis.2015.06.006] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Revised: 06/09/2015] [Accepted: 06/12/2015] [Indexed: 12/12/2022]
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31
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Abstract
INTRODUCTION The contraction in pharmaceutical drug discovery operations in the past decade has been counter-balanced by a significant rise in the number of academic drug discovery groups. In addition, pharmaceutical companies that used to operate in completely independent, vertically integrated operations for drug discovery, are now collaborating more with each other, and with academic groups. We are in a new era of drug discovery. AREAS COVERED This review provides an overview of the current status of academic drug discovery groups, their achievements and the challenges they face, together with perspectives on ways to achieve improved outcomes. EXPERT OPINION Academic groups have made important contributions to drug discovery, from its earliest days and continue to do so today. However, modern drug discovery and development is exceedingly complex, and has high failure rates, principally because human biology is complex and poorly understood. Academic drug discovery groups need to play to their strengths and not just copy what has gone before. However, there are lessons to be learnt from the experiences of the industrial drug discoverers and four areas are highlighted for attention: i) increased validation of targets; ii) elimination of false hits from high throughput screening (HTS); iii) increasing the quality of molecular probes; and iv) investing in a high-quality informatics infrastructure.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Research Group, University of Greenwich, Chatham Maritime , Kent, ME4 4TB , UK
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32
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Schreiber SL, Kotz JD, Li M, Aubé J, Austin CP, Reed JC, Rosen H, White EL, Sklar LA, Lindsley CW, Alexander BR, Bittker JA, Clemons PA, de Souza A, Foley MA, Palmer M, Shamji AF, Wawer MJ, McManus O, Wu M, Zou B, Yu H, Golden JE, Schoenen FJ, Simeonov A, Jadhav A, Jackson MR, Pinkerton AB, Chung TDY, Griffin PR, Cravatt BF, Hodder PS, Roush WR, Roberts E, Chung DH, Jonsson CB, Noah JW, Severson WE, Ananthan S, Edwards B, Oprea TI, Conn PJ, Hopkins CR, Wood MR, Stauffer SR, Emmitte KA. Advancing Biological Understanding and Therapeutics Discovery with Small-Molecule Probes. Cell 2015; 161:1252-65. [PMID: 26046436 PMCID: PMC4564295 DOI: 10.1016/j.cell.2015.05.023] [Citation(s) in RCA: 121] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Indexed: 02/06/2023]
Abstract
Small-molecule probes can illuminate biological processes and aid in the assessment of emerging therapeutic targets by perturbing biological systems in a manner distinct from other experimental approaches. Despite the tremendous promise of chemical tools for investigating biology and disease, small-molecule probes were unavailable for most targets and pathways as recently as a decade ago. In 2005, the NIH launched the decade-long Molecular Libraries Program with the intent of innovating in and broadening access to small-molecule science. This Perspective describes how novel small-molecule probes identified through the program are enabling the exploration of biological pathways and therapeutic hypotheses not otherwise testable. These experiences illustrate how small-molecule probes can help bridge the chasm between biological research and the development of medicines but also highlight the need to innovate the science of therapeutic discovery.
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Affiliation(s)
- Stuart L Schreiber
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Howard Hughes Medical Institute, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
| | - Joanne D Kotz
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
| | - Min Li
- Johns Hopkins School of Medicine Ion Channel Center, Baltimore, MD 21205, USA
| | - Jeffrey Aubé
- University of Kansas Specialized Chemistry Center, Lawrence, KS 66045, USA; Department of Medicinal Chemistry, University of Kansas, Lawrence, KS, 66045, USA
| | - Christopher P Austin
- NIH Chemical Genomics Center, National Institutes of Health, Rockville, MD 20850, USA; National Center for Advancing Translational Sciences, Bethesda, MD 20892, USA
| | - John C Reed
- Conrad Prebys Center for Chemical Genomics, Sanford-Burnham Medical Research Institute, La Jolla, CA 92037, and Lake Nona, FL 32827, USA
| | - Hugh Rosen
- Molecular Screening Center, The Scripps Research Institute, La Jolla, CA 92037, and Jupiter, FL 33458, USA; Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - E Lucile White
- Southern Research Specialized Biocontainment Screening Center, Southern Research Institute, Birmingham, AL 35205, USA
| | - Larry A Sklar
- University of New Mexico Center for Molecular Discovery, Albuquerque, NM 87131, USA; Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, 87131, USA
| | - Craig W Lindsley
- The Vanderbilt Specialized Chemistry Center for Accelerated Probe Development, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Vanderbilt Center for Neuroscience Drug Discovery, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Benjamin R Alexander
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Joshua A Bittker
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Center for the Development of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Paul A Clemons
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Andrea de Souza
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Michael A Foley
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Michelle Palmer
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Alykhan F Shamji
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Mathias J Wawer
- Probe Development Center, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Owen McManus
- Johns Hopkins School of Medicine Ion Channel Center, Baltimore, MD 21205, USA
| | - Meng Wu
- Johns Hopkins School of Medicine Ion Channel Center, Baltimore, MD 21205, USA
| | - Beiyan Zou
- Johns Hopkins School of Medicine Ion Channel Center, Baltimore, MD 21205, USA
| | - Haibo Yu
- Johns Hopkins School of Medicine Ion Channel Center, Baltimore, MD 21205, USA
| | - Jennifer E Golden
- University of Kansas Specialized Chemistry Center, Lawrence, KS 66045, USA
| | - Frank J Schoenen
- University of Kansas Specialized Chemistry Center, Lawrence, KS 66045, USA
| | - Anton Simeonov
- NIH Chemical Genomics Center, National Institutes of Health, Rockville, MD 20850, USA; National Center for Advancing Translational Sciences, Bethesda, MD 20892, USA
| | - Ajit Jadhav
- NIH Chemical Genomics Center, National Institutes of Health, Rockville, MD 20850, USA; National Center for Advancing Translational Sciences, Bethesda, MD 20892, USA
| | - Michael R Jackson
- Conrad Prebys Center for Chemical Genomics, Sanford-Burnham Medical Research Institute, La Jolla, CA 92037, and Lake Nona, FL 32827, USA
| | - Anthony B Pinkerton
- Conrad Prebys Center for Chemical Genomics, Sanford-Burnham Medical Research Institute, La Jolla, CA 92037, and Lake Nona, FL 32827, USA
| | - Thomas D Y Chung
- Conrad Prebys Center for Chemical Genomics, Sanford-Burnham Medical Research Institute, La Jolla, CA 92037, and Lake Nona, FL 32827, USA
| | - Patrick R Griffin
- Molecular Screening Center, The Scripps Research Institute, La Jolla, CA 92037, and Jupiter, FL 33458, USA; Department of Molecular Therapeutics, The Scripps Research Institute, Jupiter, FL, 33458, USA
| | - Benjamin F Cravatt
- Molecular Screening Center, The Scripps Research Institute, La Jolla, CA 92037, and Jupiter, FL 33458, USA; Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Peter S Hodder
- Molecular Screening Center, The Scripps Research Institute, La Jolla, CA 92037, and Jupiter, FL 33458, USA
| | - William R Roush
- Molecular Screening Center, The Scripps Research Institute, La Jolla, CA 92037, and Jupiter, FL 33458, USA; Department of Chemistry, The Scripps Research Institute, Jupiter, FL, 33458, USA
| | - Edward Roberts
- Molecular Screening Center, The Scripps Research Institute, La Jolla, CA 92037, and Jupiter, FL 33458, USA
| | - Dong-Hoon Chung
- Southern Research Specialized Biocontainment Screening Center, Southern Research Institute, Birmingham, AL 35205, USA
| | - Colleen B Jonsson
- Southern Research Specialized Biocontainment Screening Center, Southern Research Institute, Birmingham, AL 35205, USA
| | - James W Noah
- Southern Research Specialized Biocontainment Screening Center, Southern Research Institute, Birmingham, AL 35205, USA
| | - William E Severson
- Southern Research Specialized Biocontainment Screening Center, Southern Research Institute, Birmingham, AL 35205, USA
| | - Subramaniam Ananthan
- Southern Research Specialized Biocontainment Screening Center, Southern Research Institute, Birmingham, AL 35205, USA
| | - Bruce Edwards
- University of New Mexico Center for Molecular Discovery, Albuquerque, NM 87131, USA; Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, 87131, USA
| | - Tudor I Oprea
- University of New Mexico Center for Molecular Discovery, Albuquerque, NM 87131, USA; Department of Internal Medicine, University of New Mexico, Albuquerque, NM, 87131, USA
| | - P Jeffrey Conn
- The Vanderbilt Specialized Chemistry Center for Accelerated Probe Development, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Vanderbilt Center for Neuroscience Drug Discovery, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Corey R Hopkins
- The Vanderbilt Specialized Chemistry Center for Accelerated Probe Development, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Vanderbilt Center for Neuroscience Drug Discovery, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Michael R Wood
- The Vanderbilt Specialized Chemistry Center for Accelerated Probe Development, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Vanderbilt Center for Neuroscience Drug Discovery, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Shaun R Stauffer
- The Vanderbilt Specialized Chemistry Center for Accelerated Probe Development, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Kyle A Emmitte
- The Vanderbilt Specialized Chemistry Center for Accelerated Probe Development, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Vanderbilt Center for Neuroscience Drug Discovery, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
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Abstract
Small molecules are essential tool compounds to probe the role of proteins in biology and advance toward more efficient therapeutics. However, they are used without a complete knowledge of their selectivity across the entire proteome, at risk of confounding their effects due to unknown off-target interactions. Current state-of-the-art computational approaches to predicting the affinity profile of small molecules offer a means to anticipate potential nonobvious selectivity liabilities of chemical probes. The application of in silico target profiling on the full set of chemical probes from the NIH Molecular Libraries Program (MLP) resulted in the identification of biologically relevant in vitro affinities for proteins distantly related to the primary targets of ML006, ML123, ML141, and ML204, helping to lower the risk of their further use in chemical biology.
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Affiliation(s)
- Albert A. Antolín
- Systems
Pharmacology, Research Program on Biomedical Informatics, IMIM Hospital del Mar Medical Research Institute and Universitat Pompeu Fabra, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - Jordi Mestres
- Systems
Pharmacology, Research Program on Biomedical Informatics, IMIM Hospital del Mar Medical Research Institute and Universitat Pompeu Fabra, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain
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Lipinski CA, Litterman NK, Southan C, Williams AJ, Clark AM, Ekins S. Parallel worlds of public and commercial bioactive chemistry data. J Med Chem 2014; 58:2068-76. [PMID: 25415348 PMCID: PMC4360371 DOI: 10.1021/jm5011308] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
![]()
The
availability of structures and linked bioactivity data in databases
is powerfully enabling for drug discovery and chemical biology. However,
we now review some confounding issues with the divergent expansions
of public and commercial sources of chemical structures. These are
associated with not only expanding patent extraction but also increasingly
large vendor collections amassed via different selection criteria
between SciFinder from Chemical Abstracts Service (CAS) and major
public sources such as PubChem, ChemSpider, UniChem, and others. These
increasingly massive collections may include both real and virtual
compounds, as well as so-called prophetic compounds from patents.
We address a range of issues raised by the challenges faced resolving
the NIH probe compounds. In addition we highlight the confounding
of prior-art searching by virtual compounds that could impact the
composition of matter patentability of a new medicinal chemistry lead.
Finally, we propose some potential solutions.
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Affiliation(s)
- Christopher A Lipinski
- Christopher A. Lipinski, Ph.D., LLC , 10 Connshire Drive, Waterford, Connecticut 06385-4122, United States
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Litterman NK, Lipinski CA, Bunin BA, Ekins S. Computational prediction and validation of an expert's evaluation of chemical probes. J Chem Inf Model 2014; 54:2996-3004. [PMID: 25244007 DOI: 10.1021/ci500445u] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
In a decade with over half a billion dollars of investment, more than 300 chemical probes have been identified to have biological activity through NIH funded screening efforts. We have collected the evaluations of an experienced medicinal chemist on the likely chemistry quality of these probes based on a number of criteria including literature related to the probe and potential chemical reactivity. Over 20% of these probes were found to be undesirable. Analysis of the molecular properties of these compounds scored as desirable suggested higher pKa, molecular weight, heavy atom count, and rotatable bond number. We were particularly interested whether the human evaluation aspect of medicinal chemistry due diligence could be computationally predicted. We used a process of sequential Bayesian model building and iterative testing as we included additional probes. Following external validation of these methods and comparing different machine learning methods, we identified Bayesian models with accuracy comparable to other measures of drug-likeness and filtering rules created to date.
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Affiliation(s)
- Nadia K Litterman
- Collaborative Drug Discovery, Inc. , 1633 Bayshore Highway, Suite 342, Burlingame, California 94010, United States
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Eskiocak B, Ali A, White MA. The estrogen-related receptor α inverse agonist XCT 790 is a nanomolar mitochondrial uncoupler. Biochemistry 2014; 53:4839-46. [PMID: 24999922 PMCID: PMC4116149 DOI: 10.1021/bi500737n] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Revised: 07/07/2014] [Indexed: 01/23/2023]
Abstract
XCT 790 is widely used to inhibit estrogen-related receptor α (ERRα) activity as an inverse agonist. Here, we report that XCT 790 potently activates AMP kinase (AMPK) in a dose-dependent and ERRα-independent manner, with active concentrations more than 25-fold below those typically used to perturb ERRα. AMPK activation is secondary to inhibition of energy production as XCT 790 rapidly depletes the pool of cellular ATP. A concomitant increase in oxygen consumption rates suggests uncoupling of the mitochondrial electron transport chain. Consistent with this, XCT 790 decreased mitochondrial membrane potential without affecting mitochondrial mass. Therefore, XCT 790 is a potent, fast-acting, mitochondrial uncoupler independent of its inhibition of ERRα. The biological activity together with structural features in common with the chemical uncouplers FCCP and CCCP indicates likely mode of action as a proton ionophore.
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Affiliation(s)
- Banu Eskiocak
- Department
of Cell Biology, University of Texas Southwestern
Medical Center, Dallas, Texas 75390, United
States
| | - Aktar Ali
- Department
of Internal Medicine, Touchstone Diabetes Center, University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Michael A. White
- Department
of Cell Biology, University of Texas Southwestern
Medical Center, Dallas, Texas 75390, United
States
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37
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Dahlin JL, Walters MA. The essential roles of chemistry in high-throughput screening triage. Future Med Chem 2014; 6:1265-90. [PMID: 25163000 PMCID: PMC4465542 DOI: 10.4155/fmc.14.60] [Citation(s) in RCA: 95] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
It is increasingly clear that academic high-throughput screening (HTS) and virtual HTS triage suffers from a lack of scientists trained in the art and science of early drug discovery chemistry. Many recent publications report the discovery of compounds by screening that are most likely artifacts or promiscuous bioactive compounds, and these results are not placed into the context of previous studies. For HTS to be most successful, it is our contention that there must exist an early partnership between biologists and medicinal chemists. Their combined skill sets are necessary to design robust assays and efficient workflows that will weed out assay artifacts, false positives, promiscuous bioactive compounds and intractable screening hits, efforts that ultimately give projects a better chance at identifying truly useful chemical matter. Expertise in medicinal chemistry, cheminformatics and purification sciences (analytical chemistry) can enhance the post-HTS triage process by quickly removing these problematic chemotypes from consideration, while simultaneously prioritizing the more promising chemical matter for follow-up testing. It is only when biologists and chemists collaborate effectively that HTS can manifest its full promise.
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Affiliation(s)
- Jayme L Dahlin
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA
- Medical Scientist Training Program, Mayo Clinic College of Medicine, Rochester, MN 55905, USA
| | - Michael A Walters
- Institute for Therapeutics Discovery & Development, University of Minnesota, Minneapolis, MN 55414, USA
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38
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Drug discovery and human African trypanosomiasis: a disease less neglected? Future Med Chem 2014; 5:1801-41. [PMID: 24144414 DOI: 10.4155/fmc.13.162] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Human African trypanosomiasis (HAT) has been neglected for a long time. The most recent drug to treat this disease, eflornithine, was approved by the US FDA in 2000. Current treatments exhibit numerous problematic side effects and are often ineffective against the debilitating CNS resident stage of the disease. Fortunately, several partnerships and initiatives have been formed over the last 20 years in an effort to eradicate HAT, along with a number of other neglected diseases. This has led to an increasing number of foundations and research institutions that are currently working on the development of new drugs for HAT and tools with which to diagnose and treat patients. New biochemical pathways as therapeutic targets are emerging, accompanied by increasing numbers of new antitrypanosomal compound classes. The future looks promising that this collaborative approach will facilitate eagerly awaited breakthroughs in the treatment of HAT.
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Curpăn R, Avram S, Vianello R, Bologa C. Exploring the biological promiscuity of high-throughput screening hits through DFT calculations. Bioorg Med Chem 2014; 22:2461-8. [PMID: 24656802 DOI: 10.1016/j.bmc.2014.02.055] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Revised: 02/20/2014] [Accepted: 02/28/2014] [Indexed: 11/28/2022]
Abstract
The goal of this study is the understanding of biologically promiscuous compounds (frequent hitters) in HTS outcomes through their chemical behavior estimated via reactivity descriptors. Chemical reactivity is often an undesirable property due to the lack in biological selectivity of compounds comprised in HTS libraries. In this study the reactivity indexes have been computed within the DFT formalism, at different levels of theory, for two classes of representative compounds compiled from PubChem database, one comprising frequent hitters and the second one comprising rare hitters (biologically more selective compounds). We found that frequent hitters exert increased reactivity, mainly due to their electrophilic character, compared to the more selective class of compounds.
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Affiliation(s)
- Ramona Curpăn
- Department of Computational Chemistry, Institute of Chemistry Timisoara of Romanian Academy, 24 Mihai Viteazul, Timisoara 300223, Romania.
| | - Sorin Avram
- Department of Computational Chemistry, Institute of Chemistry Timisoara of Romanian Academy, 24 Mihai Viteazul, Timisoara 300223, Romania
| | - Robert Vianello
- Quantum Organic Chemistry Group, Ruđer Bošković Institute, Bijenička cesta 54, Zagreb HR-10000, Croatia
| | - Cristian Bologa
- Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
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40
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Franco P, Porta N, Holliday JD, Willett P. The use of 2D fingerprint methods to support the assessment of structural similarity in orphan drug legislation. J Cheminform 2014; 6:5. [PMID: 24485002 PMCID: PMC3923256 DOI: 10.1186/1758-2946-6-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2013] [Accepted: 01/02/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In the European Union, medicines are authorised for some rare disease only if they are judged to be dissimilar to authorised orphan drugs for that disease. This paper describes the use of 2D fingerprints to show the extent of the relationship between computed levels of structural similarity for pairs of molecules and expert judgments of the similarities of those pairs. The resulting relationship can be used to provide input to the assessment of new active compounds for which orphan drug authorisation is being sought. RESULTS 143 experts provided judgments of the similarity or dissimilarity of 100 pairs of drug-like molecules from the DrugBank 3.0 database. The similarities of these pairs were also computed using BCI, Daylight, ECFC4, ECFP4, MDL and Unity 2D fingerprints. Logistic regression analyses demonstrated a strong relationship between the human and computed similarity assessments, with the resulting regression models having significant predictive power in experiments using data from submissions of orphan drug medicines to the European Medicines Agency. The BCI fingerprints performed best overall on the DrugBank dataset while the BCI, Daylight, ECFP4 and Unity fingerprints performed comparably on the European Medicines Agency dataset. CONCLUSIONS Measures of structural similarity based on 2D fingerprints can provide a useful source of information for the assessment of orphan drug status by regulatory authorities.
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Affiliation(s)
| | | | | | - Peter Willett
- Information School, University of Sheffield, 211 Portobello Street, Sheffield S1 4DP, UK.
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41
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Cumming JG, Davis AM, Muresan S, Haeberlein M, Chen H. Chemical predictive modelling to improve compound quality. Nat Rev Drug Discov 2014; 12:948-62. [PMID: 24287782 DOI: 10.1038/nrd4128] [Citation(s) in RCA: 156] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The 'quality' of small-molecule drug candidates, encompassing aspects including their potency, selectivity and ADMET (absorption, distribution, metabolism, excretion and toxicity) characteristics, is a key factor influencing the chances of success in clinical trials. Importantly, such characteristics are under the control of chemists during the identification and optimization of lead compounds. Here, we discuss the application of computational methods, particularly quantitative structure-activity relationships (QSARs), in guiding the selection of higher-quality drug candidates, as well as cultural factors that may have affected their use and impact.
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Affiliation(s)
- John G Cumming
- Chemistry Innovation Centre, Discovery Sciences, AstraZeneca R&D, Alderley Park, Macclesfield SK10 4TG, UK
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42
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43
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44
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Abstract
Virtual screening is an established technique that has successfully been deployed in the identification of novel biologically active molecules. Whether for ligand-based or for structure-based virtual screening, a chemical collection needs to be properly processed prior to in silico evaluation. Here we describe our step-by-step procedure for handling large collections of compounds prior to virtual screening.
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Affiliation(s)
- Cristian G Bologa
- Department of Biochemistry and Molecular Biology, University of New Mexico School of Medicine, Albuquerque, NM, USA
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45
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Bajorath J. A Perspective on Computational Chemogenomics. Mol Inform 2013; 32:1025-8. [PMID: 27481147 DOI: 10.1002/minf.201300034] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2013] [Accepted: 05/16/2013] [Indexed: 01/12/2023]
Affiliation(s)
- Jürgen Bajorath
- Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Dahlmannstr. 2, D-53113 Bonn phone/fax: +49-228-2699-306/341.
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Weber GM, Kohane IS. Extracting physician group intelligence from electronic health records to support evidence based medicine. PLoS One 2013; 8:e64933. [PMID: 23734227 PMCID: PMC3666978 DOI: 10.1371/journal.pone.0064933] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2011] [Accepted: 04/22/2013] [Indexed: 11/18/2022] Open
Abstract
Evidence-based medicine employs expert opinion and clinical data to inform clinical decision making. The objective of this study is to determine whether it is possible to complement these sources of evidence with information about physician "group intelligence" that exists in electronic health records. Specifically, we measured laboratory test "repeat intervals", defined as the amount of time it takes for a physician to repeat a test that was previously ordered for the same patient. Our assumption is that while the result of a test is a direct measure of one marker of a patient's health, the physician's decision to order the test is based on multiple factors including past experience, available treatment options, and information about the patient that might not be coded in the electronic health record. By examining repeat intervals in aggregate over large numbers of patients, we show that it is possible to 1) determine what laboratory test results physicians consider "normal", 2) identify subpopulations of patients that deviate from the norm, and 3) identify situations where laboratory tests are over-ordered. We used laboratory tests as just one example of how physician group intelligence can be used to support evidence based medicine in a way that is automated and continually updated.
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Affiliation(s)
- Griffin M Weber
- Information Technology, Harvard Medical School, Boston, Massachusetts, USA.
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Peng Z, Gillespie P, Weisel M, So SS, So WV, Kondru R, Narayanan A, Hermann JC. A Crowd-Based Process and Tool for HTS Hit Triage. Mol Inform 2013; 32:337-45. [PMID: 27481590 DOI: 10.1002/minf.201200154] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2012] [Accepted: 03/02/2012] [Indexed: 11/06/2022]
Affiliation(s)
- Zhengwei Peng
- pRED Informatics, Hoffmann-La Roche Inc. 340 Kingsland Street, Nutley, New Jersey 07110, USA.
| | - Paul Gillespie
- pRED Discovery Chemistry, Hoffmann-La Roche Inc. 340 Kingsland Street, Nutley, New Jersey 07110, USA
| | - Martin Weisel
- pRED Discovery Chemistry, Hoffmann-La Roche Inc. 340 Kingsland Street, Nutley, New Jersey 07110, USA
| | - Sung-Sau So
- pRED Discovery Chemistry, Hoffmann-La Roche Inc. 340 Kingsland Street, Nutley, New Jersey 07110, USA
| | - W Venus So
- pRED Informatics, Hoffmann-La Roche Inc. 340 Kingsland Street, Nutley, New Jersey 07110, USA
| | - Rama Kondru
- pRED Discovery Chemistry, Hoffmann-La Roche Inc. 340 Kingsland Street, Nutley, New Jersey 07110, USA
| | - Arjun Narayanan
- pRED Discovery Chemistry, Hoffmann-La Roche Inc. 340 Kingsland Street, Nutley, New Jersey 07110, USA
| | - Johannes C Hermann
- pRED Discovery Chemistry, Hoffmann-La Roche Inc. 340 Kingsland Street, Nutley, New Jersey 07110, USA
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Zhang J, Jia J, Zhu F, Ma X, Han B, Wei X, Tan C, Jiang Y, Chen Y. Analysis of bypass signaling in EGFR pathway and profiling of bypass genes for predicting response to anticancer EGFR tyrosine kinase inhibitors. MOLECULAR BIOSYSTEMS 2013; 8:2645-56. [PMID: 22833077 DOI: 10.1039/c2mb25165e] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Some drugs, such as anticancer EGFR tyrosine kinase inhibitors, elicit markedly different clinical response rates due to differences in drug bypass signaling as well as genetic variations of drug target and downstream drug-resistant genes. The profiles of these bypass signaling are expected to be useful for improved drug response prediction, which have not been systematically explored previously. In this work, we searched and analyzed 16 literature-reported EGFR tyrosine kinase inhibitor bypass signaling routes in the EGFR pathway, which include 5 compensatory routes of EGFR transactivation by another receptor, and 11 alternative routes activated by another receptor. These 16 routes are reportedly regulated by 11 bypass genes. Their expression profiles together with the mutational, amplification and expression profiles of EGFR and 4 downstream drug-resistant genes, were used as new sets of biomarkers for identifying 53 NSCLC cell-lines sensitive or resistant to EGFR tyrosine kinase inhibitors gefitinib, erlotinib and lapatinib. The collective profiles of all 16 genes distinguish sensitive and resistant cell-lines are better than those of individual genes and the combined EGFR and downstream drug resistant genes, and their derived cell-line response rates are consistent with the reported clinical response rates of the three drugs. The usefulness of cell-line data for drug response studies was further analyzed by comparing the expression profiles of EGFR and bypass genes in NSCLC cell-lines and patient samples, and by using a machine learning feature selection method for selecting drug response biomarkers. Our study suggested that the profiles of drug bypass signaling are highly useful for improved drug response prediction.
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Affiliation(s)
- Jingxian Zhang
- The Guangdong Provincial Key Laboratory of Chemical Biology, The Graduate School at Shenzhen, Tsinghua University, Shenzhen, China
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Antolín AA, Jalencas X, Yélamos J, Mestres J. Identification of pim kinases as novel targets for PJ34 with confounding effects in PARP biology. ACS Chem Biol 2012; 7:1962-7. [PMID: 23025350 DOI: 10.1021/cb300317y] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Small molecules are widely used in chemical biology without complete knowledge of their target profile, at risk of deriving conclusions that ignore potential confounding effects from unknown off-target interactions. The prediction and further experimental confirmation of novel affinities for PJ34 on Pim1 (IC(50) = 3.7 μM) and Pim2 (IC(50) = 16 μM) serine/threonine kinases, together with their involvement in many of the processes relevant to PARP biology, questions the appropriateness of using PJ34 as a chemical tool to probe the biological role of PARP1 and PARP2 at the high micromolar concentrations applied in most studies.
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Affiliation(s)
- Albert A. Antolín
- Chemogenomics
Laboratory, Research Program on Biomedical Informatics and ‡Department of
Immunology, Research Program on Cancer, IMIM Hospital del Mar Research Institute and Universitat Pompeu Fabra, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - Xavier Jalencas
- Chemogenomics
Laboratory, Research Program on Biomedical Informatics and ‡Department of
Immunology, Research Program on Cancer, IMIM Hospital del Mar Research Institute and Universitat Pompeu Fabra, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - José Yélamos
- Chemogenomics
Laboratory, Research Program on Biomedical Informatics and ‡Department of
Immunology, Research Program on Cancer, IMIM Hospital del Mar Research Institute and Universitat Pompeu Fabra, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - Jordi Mestres
- Chemogenomics
Laboratory, Research Program on Biomedical Informatics and ‡Department of
Immunology, Research Program on Cancer, IMIM Hospital del Mar Research Institute and Universitat Pompeu Fabra, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain
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Qin C, Tan KL, Zhang CL, Tan CY, Chen YZ, Jiang YY. What does it take to synergistically combine sub-potent natural products into drug-level potent combinations? PLoS One 2012; 7:e49969. [PMID: 23209627 PMCID: PMC3509152 DOI: 10.1371/journal.pone.0049969] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2012] [Accepted: 10/17/2012] [Indexed: 12/26/2022] Open
Abstract
There have been renewed interests in natural products as drug discovery sources. In particular, natural product combinations have been extensively studied, clinically tested, and widely used in traditional, folk and alternative medicines. But opinions about their therapeutic efficacies vary from placebo to synergistic effects. The important questions are whether synergistic effects can sufficiently elevate therapeutic potencies to drug levels, and by what mechanisms and at what odds such combinations can be assembled. We studied these questions by analyzing literature-reported cell-based potencies of 190 approved anticancer and antimicrobial drugs, 1378 anticancer and antimicrobial natural products, 99 natural product extracts, 124 synergistic natural product combinations, and 122 molecular interaction profiles of the 19 natural product combinations with collective potency enhanced to drug level or by >10-fold. Most of the evaluated natural products and combinations are sub-potent to drugs. Sub-potent natural products can be assembled into combinations of drug level potency at low probabilities by distinguished multi-target modes modulating primary targets, their regulators and effectors, and intracellular bioavailability of the active natural products.
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Affiliation(s)
- Chu Qin
- Department of Pharmacology and Pharmaceutical Sciences, School of Medicine, Tsinghua University, Beijing, P. R. China
- The Ministry-Province Jointly Constructed Base for State Key Lab-Shenzhen Key Laboratory of Chemical Biology, the Graduate School at Shenzhen, Tsinghua University, Shenzhen, P. R. China
- Bioinformatics and Drug Design Group, Department of Pharmacy, and Center for Computational Science and Engineering, National University of Singapore, Singapore,Singapore
- NUS Graduate School for Integrative Sciences and Engineering, Singapore, Singapore
| | - Kai Leng Tan
- Bioinformatics and Drug Design Group, Department of Pharmacy, and Center for Computational Science and Engineering, National University of Singapore, Singapore,Singapore
| | - Cun Long Zhang
- Department of Pharmacology and Pharmaceutical Sciences, School of Medicine, Tsinghua University, Beijing, P. R. China
- The Ministry-Province Jointly Constructed Base for State Key Lab-Shenzhen Key Laboratory of Chemical Biology, the Graduate School at Shenzhen, Tsinghua University, Shenzhen, P. R. China
| | - Chun Yan Tan
- Department of Pharmacology and Pharmaceutical Sciences, School of Medicine, Tsinghua University, Beijing, P. R. China
- The Ministry-Province Jointly Constructed Base for State Key Lab-Shenzhen Key Laboratory of Chemical Biology, the Graduate School at Shenzhen, Tsinghua University, Shenzhen, P. R. China
| | - Yu Zong Chen
- Department of Pharmacology and Pharmaceutical Sciences, School of Medicine, Tsinghua University, Beijing, P. R. China
- The Ministry-Province Jointly Constructed Base for State Key Lab-Shenzhen Key Laboratory of Chemical Biology, the Graduate School at Shenzhen, Tsinghua University, Shenzhen, P. R. China
- Bioinformatics and Drug Design Group, Department of Pharmacy, and Center for Computational Science and Engineering, National University of Singapore, Singapore,Singapore
- * E-mail: (YZC); (YYJ)
| | - Yu Yang Jiang
- Department of Pharmacology and Pharmaceutical Sciences, School of Medicine, Tsinghua University, Beijing, P. R. China
- The Ministry-Province Jointly Constructed Base for State Key Lab-Shenzhen Key Laboratory of Chemical Biology, the Graduate School at Shenzhen, Tsinghua University, Shenzhen, P. R. China
- * E-mail: (YZC); (YYJ)
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