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Hsieh CJ, Giannakoulias S, Petersson EJ, Mach RH. Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development. Pharmaceuticals (Basel) 2023; 16:317. [PMID: 37259459 PMCID: PMC9964981 DOI: 10.3390/ph16020317] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 02/15/2023] [Accepted: 02/16/2023] [Indexed: 11/19/2023] Open
Abstract
The use of computer-aided drug design (CADD) for the identification of lead compounds in radiotracer development is steadily increasing. Traditional CADD methods, such as structure-based and ligand-based virtual screening and optimization, have been successfully utilized in many drug discovery programs and are highlighted throughout this review. First, we discuss the use of virtual screening for hit identification at the beginning of drug discovery programs. This is followed by an analysis of how the hits derived from virtual screening can be filtered and culled to highly probable candidates to test in in vitro assays. We then illustrate how CADD can be used to optimize the potency of experimentally validated hit compounds from virtual screening for use in positron emission tomography (PET). Finally, we conclude with a survey of the newest techniques in CADD employing machine learning (ML).
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Affiliation(s)
- Chia-Ju Hsieh
- Division of Nuclear Medicine and Clinical Molecular Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sam Giannakoulias
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - E. James Petersson
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Robert H. Mach
- Division of Nuclear Medicine and Clinical Molecular Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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2
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Nakano H, Miyao T. Visualization of Topological Pharmacophore Space with Graph Edit Distance. ACS OMEGA 2022; 7:14057-14068. [PMID: 35559135 PMCID: PMC9088954 DOI: 10.1021/acsomega.2c00173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 03/25/2022] [Indexed: 06/15/2023]
Abstract
A topological pharmacophore (TP) is a chemical graph-based pharmacophore representation, where nodes are pharmacophoric features (PF) and edges are topological distances between PFs. Previously proposed sparse pharmacophore graphs (SPhGs) for TPs were shown to be effective in identifying structurally different active compounds while maintaining the interpretability of the graphs. However, one limitation of using SPhGs as queries is that many structurally similar SPhGs can be identified from a set of active compounds, requiring the classification and visualization of SPhGs, followed by an understanding of the pharmacophore hypotheses. In this study, we propose a scheme for SPhG analysis based on dimensionality reduction techniques with the graph edit distance (GED) metric. This metric enables measuring similarities among SPhGs in a quantitative manner. The visualization of SPhGs, which themselves are the graphs shared by active compounds, can help us understand the pharmacophore hypotheses as well as the data set. As a proof-of-concept study, we generated two-dimensional SPhG-maps using three dimensionality reduction techniques for six biological targets. A comparison with other pharmacophore representations was also conducted. We demonstrated knowledge extraction (interpretation of the data set) from the generated maps. Our findings include a suitable mapping algorithm as well as a pharmacophore hypothesis analysis procedure using an SPhG-map.
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Affiliation(s)
- Hiroshi Nakano
- Graduate
School of Science and Technology, Nara Institute
of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
| | - Tomoyuki Miyao
- Graduate
School of Science and Technology, Nara Institute
of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
- Data
Science Center, Nara Institute of Science
and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
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3
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Nakano H, Miyao T, Swarit J, Funatsu K. Sparse Topological Pharmacophore Graphs for Interpretable Scaffold Hopping. J Chem Inf Model 2021; 61:3348-3360. [PMID: 34264667 DOI: 10.1021/acs.jcim.1c00409] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The aim of scaffold hopping (SH) is to find compounds consisting of different scaffolds from those in already known active compounds, giving an opportunity for unexplored regions of chemical space. We previously demonstrated the usefulness of pharmacophore graphs (PhGs) for this purpose through proof-of-concept virtual screening experiments. PhGs consist of nodes and edges corresponding to pharmacophoric features (PFs) and their topological distances. Although PhGs were effective in SH, they are hard to interpret as they are complete graphs. Herein, we introduce an intuitive representation of a molecule, termed as sparse pharmacophore graphs (SPhG) by keeping the topological distances among PFs as much as possible while reducing the number of edges in the graphs. Several benchmark calculations quantitatively confirmed the sparseness of the graphs and the preservation of topological distances among pharmacophoric points. As proof-of-concept applications, virtual screening (VS) trials for SH were conducted using active and inactive compounds from ChEMBL and PubChem databases for three biological targets: thrombin, tyrosine kinase ABL1, and κ-opioid receptor. The performances of VS were comparable with using fully connected PhGs. Furthermore, highly ranked SPhGs were interpretable for the three biological targets, in particular for thrombin, for which selected SPhGs were in agreement with the structure-based interpretation.
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Affiliation(s)
- Hiroshi Nakano
- Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
| | - Tomoyuki Miyao
- Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan.,Data Science Center, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
| | - Jasial Swarit
- Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan.,Data Science Center, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
| | - Kimito Funatsu
- Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan.,Data Science Center, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan.,Department of Chemical System Engineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
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4
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Nakano H, Miyao T, Funatsu K. Exploring Topological Pharmacophore Graphs for Scaffold Hopping. J Chem Inf Model 2020; 60:2073-2081. [DOI: 10.1021/acs.jcim.0c00098] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- Hiroshi Nakano
- Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
| | - Tomoyuki Miyao
- Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
- Data Science Center, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
| | - Kimito Funatsu
- Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
- Data Science Center, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan
- Department of Chemical System Engineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
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5
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6
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Jiang L, Li Y, Qiao L, Chen X, He Y, Zhang Y, Li G. Discovery of potential negative allosteric modulators of mGluR5 from natural products using pharmacophore modeling, molecular docking, and molecular dynamics simulation studies. CAN J CHEM 2015. [DOI: 10.1139/cjc-2015-0197] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
mGluR5, which belongs to the G-protein-coupled receptor superfamily, is believed to be associated with many human diseases, such as a wide range of neurological disorders, gastroesophageal reflux disease, and cancer. Comparing with compounds that target on the orthosteric binding site, significant roles have been established for mGluR5 negative allosteric modulators (NAMs) due to their higher subtype selectivity and more suitable pharmacokinetic profiles. Nevertheless, to date, none of them have come to market for various reasons. In this study, a 3D quantitative pharmacophore model was generated by using the HypoGen module in Discovery Studio 4.0. With several validation methods ultilized, the optimal pharmacophore model Hypo2 was selected to discover potential mGluR5 NAMs from natural products. Two hundred and seventeen potential NAMs were obtained after being filtered by Lipinski’s rule (≥4). Then, molecular docking was used to refine the pharmacophore-based screening results and analyze the binding mode of NAMs and mGluR5. Three compounds, aglaiduline, 5-O-ethyl-hirsutanonol, and yakuchinone A, with good ADMET properties, acceptable Fit value and estimated value, and high docking score, were reserved for a molecular dynamics simulation study. All of them have stability of ligand binding. From our computational results, there might exhibit drug-like negative allosteric moderating effects on mGluR5 in these natural products. This work provides a reliable method for discovering mGluR5 NAMs from natural products.
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Affiliation(s)
- Ludi Jiang
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Yong Li
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Liansheng Qiao
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Xi Chen
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Yusu He
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Yanling Zhang
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Gongyu Li
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
- School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China
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7
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Feng Z, Hu G, Ma S, Xie XQ. Computational Advances for the Development of Allosteric Modulators and Bitopic Ligands in G Protein-Coupled Receptors. AAPS JOURNAL 2015; 17:1080-95. [PMID: 25940084 DOI: 10.1208/s12248-015-9776-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Accepted: 04/21/2015] [Indexed: 12/14/2022]
Abstract
Allosteric modulators of G protein-coupled receptors (GPCRs), which target at allosteric sites, have significant advantages against the corresponding orthosteric compounds including higher selectivity, improved chemical tractability or physicochemical properties, and reduced risk of receptor oversensitization. Bitopic ligands of GPCRs target both orthosteric and allosteric sites. Bitopic ligands can improve binding affinity, enhance subtype selectivity, stabilize receptors, and reduce side effects. Discovering allosteric modulators or bitopic ligands for GPCRs has become an emerging research area, in which the design of allosteric modulators is a key step in the detection of bitopic ligands. Radioligand binding and functional assays ([(35)S]GTPγS and ERK1/2 phosphorylation) are used to test the effects for potential modulators or bitopic ligands. High-throughput screening (HTS) in combination with disulfide trapping and fragment-based screening are used to aid the discovery of the allosteric modulators or bitopic ligands of GPCRs. When used alone, these methods are costly and can often result in too many potential drug targets, including false positives. Alternatively, low-cost and efficient computational approaches are useful in drug discovery of novel allosteric modulators and bitopic ligands to help refine the number of targets and reduce the false-positive rates. This review summarizes the state-of-the-art computational methods for the discovery of modulators and bitopic ligands. The challenges and opportunities for future drug discovery are also discussed.
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Affiliation(s)
- Zhiwei Feng
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, 3501 Terrace Street, 529 Salk Hall, Pittsburgh, Pennsylvania, 15261, USA
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Kooistra AJ, Roumen L, Leurs R, de Esch IJ, de Graaf C. From Heptahelical Bundle to Hits from the Haystack. Methods Enzymol 2013; 522:279-336. [DOI: 10.1016/b978-0-12-407865-9.00015-7] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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9
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Langdon SR, Ertl P, Brown N. Bioisosteric Replacement and Scaffold Hopping in Lead Generation and Optimization. Mol Inform 2010; 29:366-85. [PMID: 27463193 DOI: 10.1002/minf.201000019] [Citation(s) in RCA: 145] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2010] [Accepted: 04/01/2010] [Indexed: 11/09/2022]
Abstract
Bioisosteric replacement and scaffold hopping are twin methods used in drug design to improve the synthetic accessibility, potency and drug like properties of a compound and to move into novel chemical space. Bioisosteric replacement involves swapping functional groups of a molecule with other functional groups that have similar biological properties. Scaffold hopping is the replacement of the core framework of a molecule with another scaffold that will improve the properties of the molecule or to find similar potent compounds that exist in novel chemical space. This review outlines the key concepts, importance and challenges of both methods using examples and comparisons of techniques available for finding bioisosteric replacements and scaffold hops. There are many methods available for bioisosteric replacement and scaffold hopping, all with their own advantages and disadvantages. Drug design projects would benefit from a combination of these methods to retrieve diverse and complimentary results. Continuing progress in these fields will allow further validation of both methods as well as the accumulation of knowledge on bioisosteres and possible scaffold replacements.
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Affiliation(s)
- Sarah R Langdon
- In Silico Medicinal Chemistry, Cancer Research UK Centre for Cancer Therapeutics, The Institute of Cancer Research, 15 Cotswold Road, Sutton, SM2 5NG, UK phone/fax: +44 (0) 20 8722 4033/+44 (0) 20 8722 4205
| | - Peter Ertl
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Nathan Brown
- In Silico Medicinal Chemistry, Cancer Research UK Centre for Cancer Therapeutics, The Institute of Cancer Research, 15 Cotswold Road, Sutton, SM2 5NG, UK phone/fax: +44 (0) 20 8722 4033/+44 (0) 20 8722 4205.
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10
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Consonni V, Todeschini R. Molecular Descriptors. CHALLENGES AND ADVANCES IN COMPUTATIONAL CHEMISTRY AND PHYSICS 2010. [DOI: 10.1007/978-1-4020-9783-6_3] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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11
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Sato T, Honma T, Yokoyama S. Combining Machine Learning and Pharmacophore-Based Interaction Fingerprint for in Silico Screening. J Chem Inf Model 2009; 50:170-85. [PMID: 20038188 DOI: 10.1021/ci900382e] [Citation(s) in RCA: 82] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Affiliation(s)
- Tomohiro Sato
- Department of Biophysics and Biochemistry, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan, and RIKEN Systems and Structural Biology Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Teruki Honma
- Department of Biophysics and Biochemistry, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan, and RIKEN Systems and Structural Biology Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Shigeyuki Yokoyama
- Department of Biophysics and Biochemistry, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan, and RIKEN Systems and Structural Biology Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
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12
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Noeske T, Trifanova D, Kauss V, Renner S, Parsons CG, Schneider G, Weil T. Synergism of virtual screening and medicinal chemistry: identification and optimization of allosteric antagonists of metabotropic glutamate receptor 1. Bioorg Med Chem 2009; 17:5708-15. [PMID: 19574055 DOI: 10.1016/j.bmc.2009.05.072] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2008] [Revised: 05/27/2009] [Accepted: 05/28/2009] [Indexed: 11/26/2022]
Abstract
We report the identification of novel potent and selective metabotropic glutamate receptor 1 (mGluR1) antagonists by virtual screening and subsequent hit optimization. For ligand-based virtual screening, molecules were represented by a topological pharmacophore descriptor (CATS-2D) and clustered by a self-organizing map (SOM). The most promising compounds were tested in mGluR1 functional and binding assays. We identified a potent chemotype exhibiting selective antagonistic activity at mGluR1 (functional IC(50)=0.74+/-0.29 microM). Hit optimization yielded lead structure 16 with an affinity of K(i)=0.024+/-0.001 microM and greater than 1000-fold selectivity for mGluR1 versus mGluR5. Homology-based receptor modelling suggests a binding site compatible with previously reported mutation studies. Our study demonstrates the usefulness of ligand-based virtual screening for scaffold-hopping and rapid lead structure identification in early drug discovery projects.
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Affiliation(s)
- Tobias Noeske
- Merz Pharmaceuticals GmbH, Altenhöfer Allee 3, D-60438 Frankfurt, Germany
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13
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Tsunoyama K, Amini A, Sternberg MJE, Muggleton SH. Scaffold hopping in drug discovery using inductive logic programming. J Chem Inf Model 2008; 48:949-57. [PMID: 18457387 DOI: 10.1021/ci700418f] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
In chemoinformatics, searching for compounds which are structurally diverse and share a biological activity is called scaffold hopping. Scaffold hopping is important since it can be used to obtain alternative structures when the compound under development has unexpected side-effects. Pharmaceutical companies use scaffold hopping when they wish to circumvent prior patents for targets of interest. We propose a new method for scaffold hopping using inductive logic programming (ILP). ILP uses the observed spatial relationships between pharmacophore types in pretested active and inactive compounds and learns human-readable rules describing the diverse structures of active compounds. The ILP-based scaffold hopping method is compared to two previous algorithms (chemically advanced template search, CATS, and CATS3D) on 10 data sets with diverse scaffolds. The comparison shows that the ILP-based method is significantly better than random selection while the other two algorithms are not. In addition, the ILP-based method retrieves new active scaffolds which were not found by CATS and CATS3D. The results show that the ILP-based method is at least as good as the other methods in this study. ILP produces human-readable rules, which makes it possible to identify the three-dimensional features that lead to scaffold hopping. A minor variant of a rule learnt by ILP for scaffold hopping was subsequently found to cover an inhibitor identified by an independent study. This provides a successful result in a blind trial of the effectiveness of ILP to generate rules for scaffold hopping. We conclude that ILP provides a valuable new approach for scaffold hopping.
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Affiliation(s)
- Kazuhisa Tsunoyama
- Computational Bioinformatics Laboratory, Department of Computing, Imperial College London, 180 Queen's Gate, London SW7 2AZ, United Kingdom
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Weil T, Renner S. Homology Model-Based Virtual Screening for GPCR Ligands Using Docking and Target-Biased Scoring. J Chem Inf Model 2008; 48:1104-17. [DOI: 10.1021/ci8000265] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Tanja Weil
- Chemical R&D, Merz Pharmaceuticals GmbH, Eckenheimer Landstrasse 100, D-60318 Frankfurt am Main, Germany
| | - Steffen Renner
- Chemical R&D, Merz Pharmaceuticals GmbH, Eckenheimer Landstrasse 100, D-60318 Frankfurt am Main, Germany
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15
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Renner S, Hechenberger M, Noeske T, Böcker A, Jatzke C, Schmuker M, Parsons C, Weil T, Schneider G. Suche nach Wirkstoff-Grundgerüsten mit 3D-Pharmakophorhypothesen und Ensembles neuronaler Netze. Angew Chem Int Ed Engl 2007. [DOI: 10.1002/ange.200604125] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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16
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Renner S, Hechenberger M, Noeske T, Böcker A, Jatzke C, Schmuker M, Parsons CG, Weil T, Schneider G. Searching for Drug Scaffolds with 3D Pharmacophores and Neural Network Ensembles. Angew Chem Int Ed Engl 2007; 46:5336-9. [PMID: 17604383 DOI: 10.1002/anie.200604125] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Affiliation(s)
- Steffen Renner
- Chemical R&D, Medicinal Chemistry/Cheminformatics, Merz Pharmaceuticals GmbH, Eckenheimer Landstrasse 100, 60318 Frankfurt am Main, Germany
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18
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Affiliation(s)
- Steffen Renner
- Institute of Organic Chemistry & Chemical Biology, Johann Wolfgang Goethe University, Siesmayerstrasse 70, 60323 Frankfurt, Germany
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20
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Bach P, Nilsson K, Wållberg A, Bauer U, Hammerland LG, Peterson A, Svensson T, Osterlund K, Karis D, Boije M, Wensbo D. A new series of pyridinyl-alkynes as antagonists of the metabotropic glutamate receptor 5 (mGluR5). Bioorg Med Chem Lett 2006; 16:4792-5. [PMID: 16839764 DOI: 10.1016/j.bmcl.2006.06.079] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2006] [Revised: 06/21/2006] [Accepted: 06/24/2006] [Indexed: 11/25/2022]
Abstract
Synthesis and some structure-activity relationships for a new series of propargyl ethers as mGluR5 antagonists are reported.
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Affiliation(s)
- Peter Bach
- Department of Medicinal Chemistry, AstraZeneca R&D Mölndal, Pepparedsleden 1, S-431 83 Mölndal, Sweden.
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