1
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Balaji S. Metabophore-mediated retro-metabolic ('MeMeReMe') approach in drug design. Drug Discov Today 2023; 28:103736. [PMID: 37586644 DOI: 10.1016/j.drudis.2023.103736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 06/13/2023] [Accepted: 08/09/2023] [Indexed: 08/18/2023]
Abstract
Preclinical toxicity assessments of new drugs require the use of in silico prediction techniques as ethics, cost, time, and complexity limit in vitro and in vivo methods. This review discusses the fundamental concepts of biophores especially toxicophores and their detection methodologies, tools and techniques, as well as ongoing challenges, and methods for overcoming them. This will guide the design community in manipulating lead compounds via a pre-determined pathway based on the MeMeReMe approach. The ideas discussed will be useful both for predicting toxicity and for de-risking leads through optimization.
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Affiliation(s)
- Seetharaman Balaji
- Department of Biotechnology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka 57614, India.
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2
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Moquin SA, Simon O, Karuna R, Lakshminarayana SB, Yokokawa F, Wang F, Saravanan C, Zhang J, Day CW, Chan K, Wang QY, Lu S, Dong H, Wan KF, Lim SP, Liu W, Seh CC, Chen YL, Xu H, Barkan DT, Kounde CS, Sim WLS, Wang G, Yeo HQ, Zou B, Chan WL, Ding M, Song JG, Li M, Osborne C, Blasco F, Sarko C, Beer D, Bonamy GMC, Sasseville VG, Shi PY, Diagana TT, Yeung BKS, Gu F. NITD-688, a pan-serotype inhibitor of the dengue virus NS4B protein, shows favorable pharmacokinetics and efficacy in preclinical animal models. Sci Transl Med 2021; 13:13/579/eabb2181. [PMID: 33536278 DOI: 10.1126/scitranslmed.abb2181] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 01/13/2021] [Indexed: 12/12/2022]
Abstract
Dengue virus (DENV) is a mosquito-borne flavivirus that poses a threat to public health, yet no antiviral drug is available. We performed a high-throughput phenotypic screen using the Novartis compound library and identified candidate chemical inhibitors of DENV. This chemical series was optimized to improve properties such as anti-DENV potency and solubility. The lead compound, NITD-688, showed strong potency against all four serotypes of DENV and demonstrated excellent oral efficacy in infected AG129 mice. There was a 1.44-log reduction in viremia when mice were treated orally at 30 milligrams per kilogram twice daily for 3 days starting at the time of infection. NITD-688 treatment also resulted in a 1.16-log reduction in viremia when mice were treated 48 hours after infection. Selection of resistance mutations and binding studies with recombinant proteins indicated that the nonstructural protein 4B is the target of NITD-688. Pharmacokinetic studies in rats and dogs showed a long elimination half-life and good oral bioavailability. Extensive in vitro safety profiling along with exploratory rat and dog toxicology studies showed that NITD-688 was well tolerated after 7-day repeat dosing, demonstrating that NITD-688 may be a promising preclinical candidate for the treatment of dengue.
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Affiliation(s)
- Stephanie A Moquin
- Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA.,Novartis Institute for Tropical Diseases, Emeryville, CA 94608, USA
| | - Oliver Simon
- Novartis (Singapore) Pte Ltd, Singapore 117432, Singapore
| | - Ratna Karuna
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | | | - Fumiaki Yokokawa
- Novartis Institute for Tropical Diseases, Emeryville, CA 94608, USA
| | - Feng Wang
- Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA
| | - Chandra Saravanan
- Novartis Institutes for Biomedical Research, Translational Medicine: Preclinical Safety, Cambridge, MA 02139, USA
| | - Jin Zhang
- Novartis Institutes for Biomedical Research, Translational Medicine: Pharmacokinetics, East Hanover, NJ 07936, USA
| | - Craig W Day
- Institute for Antiviral Research, Utah State University, Logan, UT 84322, USA
| | - Katherine Chan
- Novartis Institute for Tropical Diseases, Emeryville, CA 94608, USA
| | - Qing-Yin Wang
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Siyan Lu
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Hongping Dong
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Kah Fei Wan
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Siew Pheng Lim
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Wei Liu
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Cheah Chen Seh
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Yen-Liang Chen
- Novartis Institute for Tropical Diseases, Emeryville, CA 94608, USA
| | - Haoying Xu
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - David T Barkan
- Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA
| | - Cyrille S Kounde
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | | | - Gang Wang
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Hui-Quan Yeo
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Bin Zou
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Wai Ling Chan
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Mei Ding
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | - Jae-Geun Song
- Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA
| | - Min Li
- Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA
| | - Colin Osborne
- Novartis Institute for Tropical Diseases, Emeryville, CA 94608, USA
| | - Francesca Blasco
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | | | - David Beer
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | | | - Vito G Sasseville
- Novartis Institutes for Biomedical Research, Translational Medicine: Preclinical Safety, Cambridge, MA 02139, USA
| | - Pei-Yong Shi
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore
| | | | - Bryan K S Yeung
- Novartis Institute for Tropical Diseases, Singapore 138670, Singapore.
| | - Feng Gu
- Novartis Institute for Tropical Diseases, Emeryville, CA 94608, USA.
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3
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Arvidsson McShane S, Ahlberg E, Noeske T, Spjuth O. Machine Learning Strategies When Transitioning between Biological Assays. J Chem Inf Model 2021; 61:3722-3733. [PMID: 34152755 PMCID: PMC8317157 DOI: 10.1021/acs.jcim.1c00293] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Machine learning is widely used in drug development to predict activity in biological assays based on chemical structure. However, the process of transitioning from one experimental setup to another for the same biological endpoint has not been extensively studied. In a retrospective study, we here explore different modeling strategies of how to combine data from the old and new assays when training conformal prediction models using data from hERG and NaV assays. We suggest to continuously monitor the validity and efficiency of models as more data is accumulated from the new assay and select a modeling strategy based on these metrics. In order to maximize the utility of data from the old assay, we propose a strategy that augments the proper training set of an inductive conformal predictor by adding data from the old assay but only having data from the new assay in the calibration set, which results in valid (well-calibrated) models with improved efficiency compared to other strategies. We study the results for varying sizes of new and old assays, allowing for discussion of different practical scenarios. We also conclude that our proposed assay transition strategy is more beneficial, and the value of data from the new assay is higher, for the harder case of regression compared to classification problems.
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Affiliation(s)
- Staffan Arvidsson McShane
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, 751 24 Uppsala, Sweden
| | - Ernst Ahlberg
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, 751 24 Uppsala, Sweden.,Stena Line Scandinavia AB, AI & Data, 405 19 Gothenburg, Sweden.,Predictive Compound ADME & Safety, Drug Safety & Metabolism, AstraZeneca IMED Biotech Unit, 431 50 Gothenburg, Sweden
| | - Tobias Noeske
- Imaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, 431 50 Gothenburg, Sweden
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, 751 24 Uppsala, Sweden
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4
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Schoepfer J, Jahnke W, Berellini G, Buonamici S, Cotesta S, Cowan-Jacob SW, Dodd S, Drueckes P, Fabbro D, Gabriel T, Groell JM, Grotzfeld RM, Hassan AQ, Henry C, Iyer V, Jones D, Lombardo F, Loo A, Manley PW, Pellé X, Rummel G, Salem B, Warmuth M, Wylie AA, Zoller T, Marzinzik AL, Furet P. Discovery of Asciminib (ABL001), an Allosteric Inhibitor of the Tyrosine Kinase Activity of BCR-ABL1. J Med Chem 2018; 61:8120-8135. [DOI: 10.1021/acs.jmedchem.8b01040] [Citation(s) in RCA: 175] [Impact Index Per Article: 29.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Joseph Schoepfer
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Wolfgang Jahnke
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | | | | | - Simona Cotesta
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Sandra W. Cowan-Jacob
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Stephanie Dodd
- Novartis Institutes for BioMedical Research, 250 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Peter Drueckes
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | | | - Tobias Gabriel
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Jean-Marc Groell
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Robert M. Grotzfeld
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | | | - Chrystèle Henry
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | | | - Darryl Jones
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | | | - Alice Loo
- Novartis Institutes for BioMedical Research, 250 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Paul W. Manley
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Xavier Pellé
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Gabriele Rummel
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Bahaa Salem
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | | | | | - Thomas Zoller
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Andreas L. Marzinzik
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
| | - Pascal Furet
- Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland
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5
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Manjunatha UH, Vinayak S, Zambriski JA, Chao AT, Sy T, Noble CG, Bonamy GMC, Kondreddi RR, Zou B, Gedeck P, Brooks CF, Herbert GT, Sateriale A, Tandel J, Noh S, Lakshminarayana SB, Lim SH, Goodman LB, Bodenreider C, Feng G, Zhang L, Blasco F, Wagner J, Leong FJ, Striepen B, Diagana TT. A Cryptosporidium PI(4)K inhibitor is a drug candidate for cryptosporidiosis. Nature 2017; 546:376-380. [PMID: 28562588 PMCID: PMC5473467 DOI: 10.1038/nature22337] [Citation(s) in RCA: 120] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2016] [Accepted: 03/31/2017] [Indexed: 01/02/2023]
Abstract
Diarrhoeal disease is responsible for 8.6% of global child mortality. Recent epidemiological studies found the protozoan parasite Cryptosporidium to be a leading cause of paediatric diarrhoea, with particularly grave impact on infants and immunocompromised individuals. There is neither a vaccine nor an effective treatment. Here we establish a drug discovery process built on scalable phenotypic assays and mouse models that take advantage of transgenic parasites. Screening a library of compounds with anti-parasitic activity, we identify pyrazolopyridines as inhibitors of Cryptosporidium parvum and Cryptosporidium hominis. Oral treatment with the pyrazolopyridine KDU731 results in a potent reduction in intestinal infection of immunocompromised mice. Treatment also leads to rapid resolution of diarrhoea and dehydration in neonatal calves, a clinical model of cryptosporidiosis that closely resembles human infection. Our results suggest that the Cryptosporidium lipid kinase PI(4)K (phosphatidylinositol-4-OH kinase) is a target for pyrazolopyridines and that KDU731 warrants further preclinical evaluation as a drug candidate for the treatment of cryptosporidiosis. The establishment of a drug-discovery screening pipeline for cryptosporidiosis, and identification of pyrazolopyridines as selective ATP-competitive inhibitors of the Cryptosporidium lipid kinase PI(4)K. The apicomplexan parasite Cryptosporidium is a leading cause of paediatric diarrhoea, with high mortality in infants and individuals with weak immune systems. Here, the authors report the establishment of a drug discovery screening pipeline for cryptosporidiosis, and identify pyrazolopyridines as selective ATP-competitive inhibitors of the Cryptosporidium lipid kinase PI(4)K. The lead candidate, KDU731, inhibits growth of C. parvum and C. hominis in vitro, and demonstrated in vivo efficacy in immunocompromised mice and neonatal calves (a clinical model of human disease). Moreover, KDU731 meets a broad range of safety and pharmacology criteria, and has potential as a much-needed therapeutic for treatment of cryptosporidiosis.
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Affiliation(s)
| | - Sumiti Vinayak
- Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA, USA
| | - Jennifer A Zambriski
- Washington State University, College of Veterinary Medicine, Paul G. Allen School for Global Animal Health, Pullman, WA, USA
| | | | - Tracy Sy
- Washington State University, College of Veterinary Medicine, Paul G. Allen School for Global Animal Health, Pullman, WA, USA
| | | | | | | | - Bin Zou
- Novartis Institute for Tropical Diseases, Singapore 138670
| | - Peter Gedeck
- Novartis Institute for Tropical Diseases, Singapore 138670
| | - Carrie F Brooks
- Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA, USA
| | - Gillian T Herbert
- Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA, USA
| | - Adam Sateriale
- Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA, USA
| | - Jayesh Tandel
- Department of Cellular Biology, University of Georgia, Athens, GA, USA
| | - Susan Noh
- Washington State University, College of Veterinary Medicine, Paul G. Allen School for Global Animal Health, Pullman, WA, USA.,USDA-Agricultural Research Service, Animal Disease Research Unit and Washington State University, Department of Veterinary Microbiology and Pathology, Washington Animal Disease Diagnostic Laboratory, Pullman, WA, USA
| | | | - Siau H Lim
- Novartis Institute for Tropical Diseases, Singapore 138670
| | - Laura B Goodman
- Cornell University, College of Veterinary Medicine, Department of Population Medicine and Diagnostic Sciences, Ithaca, NY, USA
| | | | - Gu Feng
- Novartis Institute for Tropical Diseases, Singapore 138670
| | - Lijun Zhang
- China Novartis Institute for Biomedical Research, Shanghai 201203, China
| | | | - Juergen Wagner
- Novartis Institute for Tropical Diseases, Singapore 138670
| | - F Joel Leong
- Novartis Institute for Tropical Diseases, Singapore 138670
| | - Boris Striepen
- Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA, USA.,Department of Cellular Biology, University of Georgia, Athens, GA, USA
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6
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Ahmed A, Sandler SI. Predictions of the physicochemical properties of amino acid side chain analogs using molecular simulation. Phys Chem Chem Phys 2016; 18:6559-68. [DOI: 10.1039/c5cp05393e] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
A candidate drug compound is released for clinical trails (in vivo activity) only if its physicochemical properties meet desirable bioavailability and partitioning criteria.
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Affiliation(s)
- Alauddin Ahmed
- Center for Molecular and Engineering Thermodynamics
- Department of Chemical and Biomolecular Engineering
- University of Delaware
- Newark
- USA
| | - Stanley I. Sandler
- Center for Molecular and Engineering Thermodynamics
- Department of Chemical and Biomolecular Engineering
- University of Delaware
- Newark
- USA
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7
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Manjunatha UH, S Rao SP, Kondreddi RR, Noble CG, Camacho LR, Tan BH, Ng SH, Ng PS, Ma NL, Lakshminarayana SB, Herve M, Barnes SW, Yu W, Kuhen K, Blasco F, Beer D, Walker JR, Tonge PJ, Glynne R, Smith PW, Diagana TT. Direct inhibitors of InhA are active against Mycobacterium tuberculosis. Sci Transl Med 2015; 7:269ra3. [PMID: 25568071 DOI: 10.1126/scitranslmed.3010597] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
New chemotherapeutic agents are urgently required to combat the global spread of multidrug-resistant tuberculosis (MDR-TB). The mycobacterial enoyl reductase InhA is one of the few clinically validated targets in tuberculosis drug discovery. We report the identification of a new class of direct InhA inhibitors, the 4-hydroxy-2-pyridones, using phenotypic high-throughput whole-cell screening. This class of orally active compounds showed potent bactericidal activity against common isoniazid-resistant TB clinical isolates. Biophysical studies revealed that 4-hydroxy-2-pyridones bound specifically to InhA in an NADH (reduced form of nicotinamide adenine dinucleotide)-dependent manner and blocked the enoyl substrate-binding pocket. The lead compound NITD-916 directly blocked InhA in a dose-dependent manner and showed in vivo efficacy in acute and established mouse models of Mycobacterium tuberculosis infection. Collectively, our structural and biochemical data open up new avenues for rational structure-guided optimization of the 4-hydroxy-2-pyridone class of compounds for the treatment of MDR-TB.
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Affiliation(s)
- Ujjini H Manjunatha
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore. Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore, Singapore.
| | - Srinivasa P S Rao
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | | | - Christian G Noble
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | - Luis R Camacho
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | - Bee H Tan
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | - Seow H Ng
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | - Pearly Shuyi Ng
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | - Ng L Ma
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | | | - Maxime Herve
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | - Susan W Barnes
- Genomics Institute of the Novartis Research Foundation, San Diego, CA 92121, USA
| | - Weixuan Yu
- Institute of Chemical Biology & Drug Discovery, Stony Brook University, Stony Brook, NY 11794-3400, USA
| | - Kelli Kuhen
- Genomics Institute of the Novartis Research Foundation, San Diego, CA 92121, USA
| | - Francesca Blasco
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | - David Beer
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | - John R Walker
- Genomics Institute of the Novartis Research Foundation, San Diego, CA 92121, USA
| | - Peter J Tonge
- Institute of Chemical Biology & Drug Discovery, Stony Brook University, Stony Brook, NY 11794-3400, USA
| | - Richard Glynne
- Genomics Institute of the Novartis Research Foundation, San Diego, CA 92121, USA
| | - Paul W Smith
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore
| | - Thierry T Diagana
- Novartis Institute for Tropical Diseases, 138670 Singapore, Singapore. Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore, Singapore.
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8
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Liu T, Altman RB. Relating Essential Proteins to Drug Side-Effects Using Canonical Component Analysis: A Structure-Based Approach. J Chem Inf Model 2015; 55:1483-94. [PMID: 26121262 DOI: 10.1021/acs.jcim.5b00030] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The molecular mechanism of many drug side-effects is unknown and difficult to predict. Previous methods for explaining side-effects have focused on known drug targets and their pathways. However, low affinity binding to proteins that are not usually considered drug targets may also drive side-effects. In order to assess these alternative targets, we used the 3D structures of 563 essential human proteins systematically to predict binding to 216 drugs. We first benchmarked our affinity predictions with available experimental data. We then combined singular value decomposition and canonical component analysis (SVD-CCA) to predict side-effects based on these novel target profiles. Our method predicts side-effects with good accuracy (average AUC: 0.82 for side effects present in <50% of drug labels). We also noted that side-effect frequency is the most important feature for prediction and can confound efforts at elucidating mechanism; our method allows us to remove the contribution of frequency and isolate novel biological signals. In particular, our analysis produces 2768 triplet associations between 50 essential proteins, 99 drugs, and 77 side-effects. Although experimental validation is difficult because many of our essential proteins do not have validated assays, we nevertheless attempted to validate a subset of these associations using experimental assay data. Our focus on essential proteins allows us to find potential associations that would likely be missed if we used recognized drug targets. Our associations provide novel insights about the molecular mechanisms of drug side-effects and highlight the need for expanded experimental efforts to investigate drug binding to proteins more broadly.
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Affiliation(s)
- Tianyun Liu
- †Department of Genetics, Stanford University, Stanford, California 94305, United States
| | - Russ B Altman
- ‡Department of Genetics and Department of Bioengineering, Stanford University, Stanford, California 94305, United States
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9
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Rao SPS, Lakshminarayana SB, Kondreddi RR, Herve M, Camacho LR, Bifani P, Kalapala SK, Jiricek J, Ma NL, Tan BH, Ng SH, Nanjundappa M, Ravindran S, Seah PG, Thayalan P, Lim SH, Lee BH, Goh A, Barnes WS, Chen Z, Gagaring K, Chatterjee AK, Pethe K, Kuhen K, Walker J, Feng G, Babu S, Zhang L, Blasco F, Beer D, Weaver M, Dartois V, Glynne R, Dick T, Smith PW, Diagana TT, Manjunatha UH. Indolcarboxamide Is a Preclinical Candidate for Treating Multidrug-Resistant Tuberculosis. Sci Transl Med 2013; 5:214ra168. [DOI: 10.1126/scitranslmed.3007355] [Citation(s) in RCA: 111] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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10
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Muthas D, Boyer S, Hasselgren C. A critical assessment of modeling safety-related drug attrition. MEDCHEMCOMM 2013. [DOI: 10.1039/c3md00072a] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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11
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Ewart L, Gallacher DJ, Gintant G, Guillon JM, Leishman D, Levesque P, McMahon N, Mylecraine L, Sanders M, Suter W, Wallis R, Valentin JP. How do the top 12 pharmaceutical companies operate safety pharmacology? J Pharmacol Toxicol Methods 2012; 66:66-70. [DOI: 10.1016/j.vascn.2012.03.004] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2012] [Revised: 03/05/2012] [Accepted: 03/23/2012] [Indexed: 12/20/2022]
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12
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Zhang L, Cvijic ME, Lippy J, Myslik J, Brenner SL, Binnie A, Houston JG. Case study: technology initiative led to advanced lead optimization screening processes at Bristol-Myers Squibb, 2004–2009. Drug Discov Today 2012; 17:733-40. [DOI: 10.1016/j.drudis.2012.02.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2011] [Revised: 01/10/2012] [Accepted: 02/27/2012] [Indexed: 12/21/2022]
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13
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Luo X, Krumrine JR, Shenvi AB, Pierson ME, Bernstein PR. Calculation and application of activity discriminants in lead optimization. J Mol Graph Model 2010; 29:372-81. [PMID: 20800520 DOI: 10.1016/j.jmgm.2010.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2010] [Revised: 07/10/2010] [Accepted: 07/14/2010] [Indexed: 11/18/2022]
Abstract
We present a technique for computing activity discriminants of in vitro (pharmacological, DMPK, and safety) assays and the application to the prediction of in vitro activities of proposed synthetic targets during the lead optimization phase of drug discovery projects. This technique emulates how medicinal chemists perform SAR analysis and activity prediction. The activity discriminants that are functions of 6 commonly used medicinal chemistry descriptors can be interpreted easily by medicinal chemists. Further, visualization with Spotfire allows medicinal chemists to analyze how the query molecule is related to compounds tested previously, and to evaluate easily the relevance of the activity discriminants to the activities of the query molecule. Validation with all compounds synthesized and tested in AstraZeneca Wilmington since 2006 demonstrates that this approach is useful for prioritizing new synthetic targets for synthesis.
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Affiliation(s)
- Xincai Luo
- Department of Chemistry, AstraZeneca Pharmaceuticals, 1800 Concord Pike, Wilmington, DE 19850, USA.
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14
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Jahnke W, Rondeau JM, Cotesta S, Marzinzik A, Pellé X, Geiser M, Strauss A, Götte M, Bitsch F, Hemmig R, Henry C, Lehmann S, Glickman JF, Roddy TP, Stout SJ, Green JR. Allosteric non-bisphosphonate FPPS inhibitors identified by fragment-based discovery. Nat Chem Biol 2010; 6:660-6. [DOI: 10.1038/nchembio.421] [Citation(s) in RCA: 105] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2010] [Accepted: 07/12/2010] [Indexed: 12/31/2022]
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15
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Wang J, Skolnik S. Recent advances in physicochemical and ADMET profiling in drug discovery. Chem Biodivers 2010; 6:1887-99. [PMID: 19937823 DOI: 10.1002/cbdv.200900117] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The drastic increase in the cost for discovering and developing a new drug along with the high attrition rate of development candidates led to shifting drug-discovery strategy to parallel assessment of comprehensive drug physicochemical, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties alongside efficacy. With the proposal of a profiling paradigm and utilization of integrated risk assessment, one can exponentially enhance the predictive power of in vitro tools by taking into consideration the interplay among profiling parameters. In particular, this article will review recent advances in accurate assessment of solubility and other physicochemical parameters. The proper interpretation of these experimental data is crucial for rapid and meaningful risk assessment and rational optimization of drug candidates in drug discovery. The impact of these tools on assisting drug-discovery teams in establishing in vitro-in vivo correlation (IVIVC) as well as structure-property relationship (SPR) will be presented.
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Affiliation(s)
- Jianling Wang
- ADME Profiling Cambridge, Metabolism and Pharmacokinetics, Novartis Institute for Biomedical Research, 250 Mass Ave, Cambridge, MA 02139, USA.
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Krämer S, Lombardi D, Primorac A, Thomae A, Wunderli-Allenspach H. Lipid-Bilayer Permeation of Drug-Like Compounds. Chem Biodivers 2009; 6:1900-16. [DOI: 10.1002/cbdv.200900122] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Redfern WS, Waldron G, Winter MJ, Butler P, Holbrook M, Wallis R, Valentin JP. Zebrafish assays as early safety pharmacology screens: Paradigm shift or red herring? J Pharmacol Toxicol Methods 2008; 58:110-7. [DOI: 10.1016/j.vascn.2008.05.006] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2008] [Accepted: 05/08/2008] [Indexed: 12/22/2022]
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Baillie TA. Metabolism and Toxicity of Drugs. Two Decades of Progress in Industrial Drug Metabolism. Chem Res Toxicol 2007; 21:129-37. [DOI: 10.1021/tx7002273] [Citation(s) in RCA: 158] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
- Thomas A. Baillie
- Merck Research Laboratories, Department of Drug Metabolism and Pharmacokinetics WP75B-330, Sumneytown Pike, West Point, Pennsylvania 19486-0004
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Wang J, Urban L, Bojanic D. Maximising use ofin vitroADMET tools to predictin vivobioavailability and safety. Expert Opin Drug Metab Toxicol 2007; 3:641-65. [DOI: 10.1517/17425255.3.5.641] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
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Chapter 29 Computational Models for ADME. ANNUAL REPORTS IN MEDICINAL CHEMISTRY 2007. [DOI: 10.1016/s0065-7743(07)42029-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register]
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