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Manen-Freixa L, Antolin AA. Polypharmacology prediction: the long road toward comprehensively anticipating small-molecule selectivity to de-risk drug discovery. Expert Opin Drug Discov 2024:1-27. [PMID: 39004919 DOI: 10.1080/17460441.2024.2376643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Accepted: 07/02/2024] [Indexed: 07/16/2024]
Abstract
INTRODUCTION Small molecules often bind to multiple targets, a behavior termed polypharmacology. Anticipating polypharmacology is essential for drug discovery since unknown off-targets can modulate safety and efficacy - profoundly affecting drug discovery success. Unfortunately, experimental methods to assess selectivity present significant limitations and drugs still fail in the clinic due to unanticipated off-targets. Computational methods are a cost-effective, complementary approach to predict polypharmacology. AREAS COVERED This review aims to provide a comprehensive overview of the state of polypharmacology prediction and discuss its strengths and limitations, covering both classical cheminformatics methods and bioinformatic approaches. The authors review available data sources, paying close attention to their different coverage. The authors then discuss major algorithms grouped by the types of data that they exploit using selected examples. EXPERT OPINION Polypharmacology prediction has made impressive progress over the last decades and contributed to identify many off-targets. However, data incompleteness currently limits most approaches to comprehensively predict selectivity. Moreover, our limited agreement on model assessment challenges the identification of the best algorithms - which at present show modest performance in prospective real-world applications. Despite these limitations, the exponential increase of multidisciplinary Big Data and AI hold much potential to better polypharmacology prediction and de-risk drug discovery.
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Affiliation(s)
- Leticia Manen-Freixa
- Oncobell Division, Bellvitge Biomedical Research Institute (IDIBELL) and ProCURE Department, Catalan Institute of Oncology (ICO), Barcelona, Spain
| | - Albert A Antolin
- Oncobell Division, Bellvitge Biomedical Research Institute (IDIBELL) and ProCURE Department, Catalan Institute of Oncology (ICO), Barcelona, Spain
- Center for Cancer Drug Discovery, The Division of Cancer Therapeutics, The Institute of Cancer Research, London, UK
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Fan FM, Fleishman JS, Chen J, Chen ZS, Dong HH. New insights into the mechanism of resistance to lenvatinib and strategies for lenvatinib sensitization in hepatocellular carcinoma. Drug Discov Today 2024; 29:104069. [PMID: 38936692 DOI: 10.1016/j.drudis.2024.104069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 05/04/2024] [Accepted: 06/21/2024] [Indexed: 06/29/2024]
Abstract
Lenvatinib is a multikinase inhibitor that suppresses vascular endothelial growth factor receptor (VEGFR), fibroblast growth factor receptor (FGFR), platelet-derived growth factor receptor α (PDGFRα), as well as the proto-oncogenes RET and KIT. Lenvatinib has been approved by the US Food and Drug Administration (FDA) for the first-line treatment of hepatocellular carcinoma (HCC) due to its superior efficacy when compared to sorafenib. Unfortunately, the development of drug resistance to lenvatinib is becoming increasingly common. Thus, there is an urgent need to identify the factors that lead to drug resistance and ways to mitigate it. We summarize the molecular mechanisms that lead to lenvatinib resistance (LR) in HCC, which involve programmed cell death (PCD), translocation processes, and changes in the tumor microenvironment (TME), and provide strategies to reverse resistance.
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Affiliation(s)
- Fei-Mu Fan
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China; Clinical Medicine Research Center for Hepatic Surgery of Hubei Province, Wuhan 430000, China
| | - Joshua S Fleishman
- College of Pharmacy and Health Sciences, St John's University, Queens, NY 11439, USA
| | - Jin Chen
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China; Clinical Medicine Research Center for Hepatic Surgery of Hubei Province, Wuhan 430000, China.
| | - Zhe-Sheng Chen
- College of Pharmacy and Health Sciences, St John's University, Queens, NY 11439, USA.
| | - Han-Hua Dong
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China; Clinical Medicine Research Center for Hepatic Surgery of Hubei Province, Wuhan 430000, China.
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Haupenthal J, Rafehi M, Kany AM, Lespine A, Stefan K, Hirsch AKH, Stefan SM. Target repurposing unravels avermectins and derivatives as novel antibiotics inhibiting energy-coupling factor transporters (ECFTs). Arch Pharm (Weinheim) 2024:e2400267. [PMID: 38896404 DOI: 10.1002/ardp.202400267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 05/23/2024] [Accepted: 05/26/2024] [Indexed: 06/21/2024]
Abstract
Energy-coupling factor transporters (ECFTs) are membrane-bound ATP-binding cassette (ABC) transporters in prokaryotes that are found in pathogens against which novel antibiotics are urgently needed. To date, just 54 inhibitors of three molecular-structural classes with mostly weak inhibitory activity are known. Target repurposing is a strategy that transfers knowledge gained from a well-studied protein family to under-studied targets of phylogenetic relation. Forty-eight human ABC transporters are known that may harbor structural motifs similar to ECFTs to which particularly multitarget compounds may bind. We assessed 31 multitarget compounds which together target the entire druggable human ABC transporter proteome against ECFTs, of which nine showed inhibitory activity (hit rate 29.0%) and four demonstrated moderate to strong inhibition of an ECFT (IC50 values between 4.28 and 50.2 µM) as well as antibacterial activity against ECFT-expressing Streptococcus pneumoniae. Here, ivermectin was the most potent candidate (MIC95: 22.8 µM), and analysis of five ivermectin derivatives revealed moxidectin as one of the most potent ECFT-targeting antibacterial agents (IC50: 2.23 µM; MIC95: 2.91 µM). Distinct molecular-structural features of avermectins and derivatives as well as the differential biological response of the hit compounds in general provided first indications with respect to the structure-activity relationships and mode of action, respectively.
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Affiliation(s)
- Jörg Haupenthal
- Helmholtz Institute for Pharmaceutical Research Saarland (HIPS)-Helmholtz Centre for Infection Research (HZI), Saarland University, Saarbrücken, Germany
| | - Muhammad Rafehi
- Institute of Clinical Pharmacology, University Medical Center Göttingen, Göttingen, Germany
- Department of Medical Education Augsburg, Augsburg University Medicine, Augsburg, Germany
| | - Andreas M Kany
- Helmholtz Institute for Pharmaceutical Research Saarland (HIPS)-Helmholtz Centre for Infection Research (HZI), Saarland University, Saarbrücken, Germany
| | - Anne Lespine
- INTHERES, Université de Toulouse, INRAE, ENVT, Toulouse, France
| | - Katja Stefan
- Lübeck Institute of Experimental Dermatology, Medicinal Chemistry and Systems Polypharmacology, University of Lübeck and University Medical Center Schleswig-Holstein, Lübeck, Germany
| | - Anna K H Hirsch
- Helmholtz Institute for Pharmaceutical Research Saarland (HIPS)-Helmholtz Centre for Infection Research (HZI), Saarland University, Saarbrücken, Germany
- Department of Pharmacy, Saarland University, Saarbrücken, Germany
| | - Sven Marcel Stefan
- Lübeck Institute of Experimental Dermatology, Medicinal Chemistry and Systems Polypharmacology, University of Lübeck and University Medical Center Schleswig-Holstein, Lübeck, Germany
- Department of Biopharmacy, Medical University of Lublin, Lublin, Poland
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Stefan K, Namasivayam V, Stefan SM. Computer-aided pattern scoring - A multitarget dataset-driven workflow to predict ligands of orphan targets. Sci Data 2024; 11:530. [PMID: 38783061 PMCID: PMC11116543 DOI: 10.1038/s41597-024-03343-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 05/03/2024] [Indexed: 05/25/2024] Open
Abstract
The identification of lead molecules and the exploration of novel pharmacological drug targets are major challenges of medical life sciences today. Genome-wide association studies, multi-omics, and systems pharmacology steadily reveal new protein networks, extending the known and relevant disease-modifying proteome. Unfortunately, the vast majority of the disease-modifying proteome consists of 'orphan targets' of which intrinsic ligands/substrates, (patho)physiological roles, and/or modulators are unknown. Undruggability is a major challenge in drug development today, and medicinal chemistry efforts cannot keep up with hit identification and hit-to-lead optimization studies. New 'thinking-outside-the-box' approaches are necessary to identify structurally novel and functionally distinctive ligands for orphan targets. Here we present a unique dataset that includes critical information on the orphan target ABCA1, from which a novel cheminformatic workflow - computer-aided pattern scoring (C@PS) - for the identification of novel ligands was developed. Providing a hit rate of 95.5% and molecules with high potency and molecular-structural diversity, this dataset represents a suitable template for general deorphanization studies.
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Affiliation(s)
- Katja Stefan
- University of Oslo and Oslo University Hospital, Department of Pathology, Rikshospitalet, Sognsvannsveien 20, 0372, Oslo, Norway
- University of Lübeck and University Medical Center Schleswig-Holstein, Lübeck Institute of Experimental Dermatology, Medical Systems Biology Division, Medicinal Chemistry and Systems Polypharmacology, Ratzeburger Allee 160, 23538, Lübeck, Germany
| | - Vigneshwaran Namasivayam
- University of Lübeck and University Medical Center Schleswig-Holstein, Lübeck Institute of Experimental Dermatology, Medical Systems Biology Division, Medicinal Chemistry and Systems Polypharmacology, Ratzeburger Allee 160, 23538, Lübeck, Germany.
- University of Bonn, Pharmaceutical Institute, Department of Pharmaceutical and Cellbiological Chemistry, An der Immenburg 4, 53121, Bonn, Germany.
| | - Sven Marcel Stefan
- University of Oslo and Oslo University Hospital, Department of Pathology, Rikshospitalet, Sognsvannsveien 20, 0372, Oslo, Norway.
- University of Lübeck and University Medical Center Schleswig-Holstein, Lübeck Institute of Experimental Dermatology, Medical Systems Biology Division, Medicinal Chemistry and Systems Polypharmacology, Ratzeburger Allee 160, 23538, Lübeck, Germany.
- Medical University of Lublin, Department of Biopharmacy, Chodzki 4a, 20-093, Lublin, Poland.
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Stefan SM, Rafehi M. Medicinal polypharmacology: Exploration and exploitation of the polypharmacolome in modern drug development. Drug Dev Res 2024; 85:e22125. [PMID: 37920929 DOI: 10.1002/ddr.22125] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 09/23/2023] [Accepted: 10/12/2023] [Indexed: 11/04/2023]
Abstract
At the core of complex and multifactorial human diseases, such as cancer, metabolic syndrome, or neurodegeneration, are multiple players that cross-talk in robust biological networks which are intrinsically resilient to alterations. These multifactorial diseases are characterized by sophisticated feedback mechanisms which manifest cellular imbalance and resistance to drug therapy. By adhering to the specificity paradigm ("one target-one drug concept"), research focused for many years on drugs with very narrow mechanisms of action. This narrow focus promoted therapy ineffectiveness and resistance. However, modern drug discovery has evolved over the last years, increasingly emphasizing integral strategies for the development of clinically effective drugs. These integral strategies include the controlled engagement of multiple targets to overcome therapy resistance. Apart from the additive or even synergistic effects in therapy, multitarget drugs harbor molecular-structural attributes to explore orphan targets of which intrinsic substrates/physiological role(s) and/or modulators are unknown for future therapy purposes. We designated this multidisciplinary and translational research field between medicinal chemistry, chemical biology, and molecular pharmacology as 'medicinal polypharmacology'. Medicinal polypharmacology emerged as alternative approach to common single-targeted pharmacology stretching from basic drug and target identification processes to clinical evaluation of multitarget drugs, and the exploration and exploitation of the 'polypharmacolome' is at the forefront of modern drug development research.
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Affiliation(s)
- Sven Marcel Stefan
- Drug Development and Chemical Biology, Lübeck Institute of Experimental Dermatology (LIED), University of Lübeck and University Medical Center Schleswig-Holstein, Lübeck, Germany
- Translational Neurodegeneration Research and Neuropathology Lab, Department of Pathology, Section of Neuropathology and Oslo University Hospital, University of Oslo, Oslo, Norway
- School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia
| | - Muhammad Rafehi
- Department of Medical Education, Augsburg University Medicine, Augsburg, Germany
- Institute of Clinical Pharmacology, University Medical Center Göttingen, Göttingen, Germany
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