1
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Sun H, Wang J, Wu H, Lin S, Chen J, Wei J, Lv S, Xiong Y, Wei DQ. A Multimodal Deep Learning Framework for Predicting PPI-Modulator Interactions. J Chem Inf Model 2023; 63:7363-7372. [PMID: 38037990 DOI: 10.1021/acs.jcim.3c01527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
Protein-protein interactions (PPIs) are essential for various biological processes and diseases. However, most existing computational methods for identifying PPI modulators require either target structure or reference modulators, which restricts their applicability to novel PPI targets. To address this challenge, we propose MultiPPIMI, a sequence-based deep learning framework that predicts the interaction between any given PPI target and modulator. MultiPPIMI integrates multimodal representations of PPI targets and modulators and uses a bilinear attention network to capture intermolecular interactions. Experimental results on our curated benchmark data set show that MultiPPIMI achieves an average AUROC of 0.837 in three cold-start scenarios and an AUROC of 0.994 in the random-split scenario. Furthermore, the case study shows that MultiPPIMI can assist molecular docking simulations in screening inhibitors of Keap1/Nrf2 PPI interactions. We believe that the proposed method provides a promising way to screen PPI-targeted modulators.
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Affiliation(s)
- Heqi Sun
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jianmin Wang
- The Interdisciplinary Graduate Program in Integrative Biotechnology and Translational Medicine, Yonsei University, Incheon 21983, Republic of Korea
| | - Hongyan Wu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Shenggeng Lin
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Junwei Chen
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jinghua Wei
- Department of Chemistry, University of Toronto, Toronto M5R 0A3, Canada
| | - Shuai Lv
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yi Xiong
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
| | - Dong-Qing Wei
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Peng Cheng National Laboratory, Shenzhen 518055, China
- Zhongjing Research and Industrialization Institute of Chinese Medicine, Nanyang 473006, China
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2
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Amoroso N, Gambacorta N, Mastrolorito F, Togo MV, Trisciuzzi D, Monaco A, Pantaleo E, Altomare CD, Ciriaco F, Nicolotti O. Making sense of chemical space network shows signs of criticality. Sci Rep 2023; 13:21335. [PMID: 38049451 PMCID: PMC10696027 DOI: 10.1038/s41598-023-48107-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/22/2023] [Indexed: 12/06/2023] Open
Abstract
Chemical space modelling has great importance in unveiling and visualising latent information, which is critical in predictive toxicology related to drug discovery process. While the use of traditional molecular descriptors and fingerprints may suffer from the so-called curse of dimensionality, complex networks are devoid of the typical drawbacks of coordinate-based representations. Herein, we use chemical space networks (CSNs) to analyse the case of the developmental toxicity (Dev Tox), which remains a challenging endpoint for the difficulty of gathering enough reliable data despite very important for the protection of the maternal and child health. Our study proved that the Dev Tox CSN has a complex non-random organisation and can thus provide a wealth of meaningful information also for predictive purposes. At a phase transition, chemical similarities highlight well-established toxicophores, such as aryl derivatives, mostly neurotoxic hydantoins, barbiturates and amino alcohols, steroids, and volatile organic compounds ether-like chemicals, which are strongly suspected of the Dev Tox onset and can thus be employed as effective alerts for prioritising chemicals before testing.
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Affiliation(s)
- Nicola Amoroso
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli studi di Bari Aldo Moro, via E. Orabona, 4, 70125, Bari, Italy.
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, via E. Orabona, 4, 70125, Bari, Italy.
| | - Nicola Gambacorta
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli studi di Bari Aldo Moro, via E. Orabona, 4, 70125, Bari, Italy
- Division of Medical Genetics, Fondazione IRCCS-Casa Sollievo della Sofferenza, San Giovanni Rotondo (Foggia), Italy
| | - Fabrizio Mastrolorito
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli studi di Bari Aldo Moro, via E. Orabona, 4, 70125, Bari, Italy
| | - Maria Vittoria Togo
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli studi di Bari Aldo Moro, via E. Orabona, 4, 70125, Bari, Italy
| | - Daniela Trisciuzzi
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli studi di Bari Aldo Moro, via E. Orabona, 4, 70125, Bari, Italy
| | - Alfonso Monaco
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, via E. Orabona, 4, 70125, Bari, Italy
- Dipartimento Interateneo di Fisica "M. Merlin", Università degli studi di Bari Aldo Moro, Via Giovanni Amendola, 173, 70125, Bari, Italy
| | - Ester Pantaleo
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, via E. Orabona, 4, 70125, Bari, Italy
- Dipartimento Interateneo di Fisica "M. Merlin", Università degli studi di Bari Aldo Moro, Via Giovanni Amendola, 173, 70125, Bari, Italy
| | - Cosimo Damiano Altomare
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli studi di Bari Aldo Moro, via E. Orabona, 4, 70125, Bari, Italy
| | - Fulvio Ciriaco
- Dipartimento di Chimica, Università degli studi di Bari Aldo Moro, via E. Orabona, 4, 70125, Bari, Italy.
| | - Orazio Nicolotti
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli studi di Bari Aldo Moro, via E. Orabona, 4, 70125, Bari, Italy
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3
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Rinotas V, Liepouri F, Ouzouni MD, Chalkidi N, Papaneophytou C, Lampropoulou M, Vidali VP, Kontopidis G, Couladouros E, Eliopoulos E, Papakyriakou A, Douni E. Structure-Based Discovery of Receptor Activator of Nuclear Factor-κB Ligand (RANKL)-Induced Osteoclastogenesis Inhibitors. Int J Mol Sci 2023; 24:11290. [PMID: 37511048 PMCID: PMC10379842 DOI: 10.3390/ijms241411290] [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: 06/22/2023] [Revised: 07/07/2023] [Accepted: 07/08/2023] [Indexed: 07/30/2023] Open
Abstract
Receptor activator of nuclear factor-κB ligand (RANKL) has been actively pursued as a therapeutic target for osteoporosis, given that RANKL is the master mediator of bone resorption as it promotes osteoclast differentiation, activity and survival. We employed a structure-based virtual screening approach comprising two stages of experimental evaluation and identified 11 commercially available compounds that displayed dose-dependent inhibition of osteoclastogenesis. Their inhibitory effects were quantified through TRAP activity at the low micromolar range (IC50 < 5 μΜ), but more importantly, 3 compounds displayed very low toxicity (LC50 > 100 μΜ). We also assessed the potential of an N-(1-aryl-1H-indol-5-yl)aryl-sulfonamide scaffold that was based on the structure of a hit compound, through synthesis of 30 derivatives. Their evaluation revealed 4 additional hits that inhibited osteoclastogenesis at low micromolar concentrations; however, cellular toxicity concerns preclude their further development. Taken together with the structure-activity relationships provided by the hit compounds, our study revealed potent inhibitors of RANKL-induced osteoclastogenesis of high therapeutic index, which bear diverse scaffolds that can be employed in hit-to-lead optimization for the development of therapeutics against osteolytic diseases.
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Affiliation(s)
- Vagelis Rinotas
- Institute for Bioinnovation, Biomedical Sciences Research Center "Alexander Fleming", 34 Fleming Street, 16672 Vari, Greece
| | | | - Maria-Dimitra Ouzouni
- Laboratory of General Chemistry, Department of Food Science and Human Nutrition, Agricultural University of Athens, 75 Iera Odos, 11855 Athens, Greece
| | - Niki Chalkidi
- Institute for Bioinnovation, Biomedical Sciences Research Center "Alexander Fleming", 34 Fleming Street, 16672 Vari, Greece
| | - Christos Papaneophytou
- Department of Biochemistry, Veterinary School, University of Thessaly, 224 Trikalon, 43131 Karditsa, Greece
- Department of Life Sciences, School of Life and Health Sciences, University of Nicosia, 46 Makedonitissas Avenue, 2417 Nicosia, Cyprus
| | | | - Veroniki P Vidali
- Institute of Nanoscience and Nanotechnology, National Centre for Scientific Research "Demokritos", Patr. Gregoriou E & 27 Neapoleos Str, 15341 Athens, Greece
| | - George Kontopidis
- Department of Biochemistry, Veterinary School, University of Thessaly, 224 Trikalon, 43131 Karditsa, Greece
| | - Elias Couladouros
- proACTINA SA, 20 Delfon Street, 15125 Athens, Greece
- Laboratory of General Chemistry, Department of Food Science and Human Nutrition, Agricultural University of Athens, 75 Iera Odos, 11855 Athens, Greece
| | - Elias Eliopoulos
- Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, 75 Iera Odos, 11855 Athens, Greece
| | - Athanasios Papakyriakou
- Institute of Biosciences and Applications, National Centre for Scientific Research "Demokritos", Patr. Gregoriou E & 27 Neapoleos Str, 15341 Athens, Greece
| | - Eleni Douni
- Institute for Bioinnovation, Biomedical Sciences Research Center "Alexander Fleming", 34 Fleming Street, 16672 Vari, Greece
- Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, 75 Iera Odos, 11855 Athens, Greece
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4
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Vaaltyn MC, Mateos‐Jimenez M, Müller R, Mackay CL, Edkins AL, Clarke DJ, Veale CGL. Native Mass Spectrometry-Guided Screening Identifies Hit Fragments for HOP-HSP90 PPI Inhibition. Chembiochem 2022; 23:e202200322. [PMID: 36017658 PMCID: PMC9826382 DOI: 10.1002/cbic.202200322] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/25/2022] [Indexed: 01/11/2023]
Abstract
Contemporary medicinal chemistry considers fragment-based drug discovery (FBDD) and inhibition of protein-protein interactions (PPI) as important means of expanding the volume of druggable chemical space. However, the ability to robustly identify valid fragments and PPI inhibitors is an enormous challenge, requiring the application of sensitive biophysical methodology. Accordingly, in this study, we exploited the speed and sensitivity of nanoelectrospray (nano-ESI) native mass spectrometry to identify a small collection of fragments which bind to the TPR2AB domain of HOP. Follow-up biophysical assessment of a small selection of binding fragments confirmed binding to the single TPR2A domain, and that this binding translated into PPI inhibitory activity between TPR2A and the HSP90 C-terminal domain. An in-silico assessment of binding fragments at the PPI interfacial region, provided valuable structural insight for future fragment elaboration strategies, including the identification of losartan as a weak, albeit dose-dependent inhibitor of the target PPI.
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Affiliation(s)
- Michaelone C. Vaaltyn
- The Biomedical Biotechnology Research Unit (BioBRU) Department of Biochemistry and Microbiology DepartmentRhodes UniversityMakhanda6139South Africa
| | - Maria Mateos‐Jimenez
- EaStCHEM School of ChemistryJoseph Black Building, David Brewster RoadEdinburghEH93FJUK
| | - Ronel Müller
- School of Chemistry and PhysicsUniversity of KwaZulu-NatalScottsville3209South Africa
| | - C. Logan Mackay
- EaStCHEM School of ChemistryJoseph Black Building, David Brewster RoadEdinburghEH93FJUK
| | - Adrienne L. Edkins
- The Biomedical Biotechnology Research Unit (BioBRU) Department of Biochemistry and Microbiology DepartmentRhodes UniversityMakhanda6139South Africa
| | - David J. Clarke
- EaStCHEM School of ChemistryJoseph Black Building, David Brewster RoadEdinburghEH93FJUK
| | - Clinton G. L. Veale
- Department of ChemistryUniversity of Cape Town RondeboschCape Town7700South Africa
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5
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Mayol GF, Defelipe LA, Arcon JP, Turjanski AG, Marti MA. Solvent Sites Improve Docking Performance of Protein–Protein Complexes and Protein–Protein Interface-Targeted Drugs. J Chem Inf Model 2022; 62:3577-3588. [DOI: 10.1021/acs.jcim.2c00264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Gonzalo F. Mayol
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (FCEyN-UBA) e Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Pabellòn 2 de Ciudad Universitaria, Ciudad de Buenos Aires C1428EHA, Argentina
| | - Lucas A. Defelipe
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (FCEyN-UBA) e Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Pabellòn 2 de Ciudad Universitaria, Ciudad de Buenos Aires C1428EHA, Argentina
- European Molecular Biology Laboratory - Hamburg Unit, Notkestrasse 85, Hamburg 22607, Germany
| | - Juan Pablo Arcon
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (FCEyN-UBA) e Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Pabellòn 2 de Ciudad Universitaria, Ciudad de Buenos Aires C1428EHA, Argentina
- Institute for Research in Biomedicine (IRB), 08028 Barcelona, Spain
- The Barcelona Institute of Science and Technology, 08036 Barcelona, Spain
| | - Adrian G. Turjanski
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (FCEyN-UBA) e Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Pabellòn 2 de Ciudad Universitaria, Ciudad de Buenos Aires C1428EHA, Argentina
| | - Marcelo A. Marti
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (FCEyN-UBA) e Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Pabellòn 2 de Ciudad Universitaria, Ciudad de Buenos Aires C1428EHA, Argentina
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6
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Structure-based assessment and druggability classification of protein-protein interaction sites. Sci Rep 2022; 12:7975. [PMID: 35562538 PMCID: PMC9106675 DOI: 10.1038/s41598-022-12105-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 04/20/2022] [Indexed: 11/08/2022] Open
Abstract
The featureless interface formed by protein–protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap. After evaluating 320 crystal structures, we find that the PPI binding sites have a wide range of druggability scores. This can be attributed to the unique structural and physiochemical features that influence their ligand binding and concomitantly, their druggability predictions. We then use these features to propose a specific classification system suitable for assessing PPI targets based on their druggability scores and measured binding-affinity. Interestingly, this system was able to distinguish between different PPIs and correctly categorize them into four classes (i.e. very druggable, druggable, moderately druggable, and difficult). We also studied the effects of protein flexibility on the computed druggability scores and found that protein conformational changes accompanying ligand binding in ligand-bound structures result in higher protein druggability scores due to more favorable structural features. Finally, the drug-likeness of many published PPI inhibitors was studied where it was found that the vast majority of the 221 ligands considered here, including orally tested/marketed drugs, violate the currently acceptable limits of compound size and hydrophobicity parameters. This outcome, combined with the lack of correlation observed between druggability and drug-likeness, reinforces the need to redefine drug-likeness for PPI drugs. This work proposes a PPI-specific classification scheme that will assist researchers in assessing the druggability and identifying inhibitors of the PPI interface.
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7
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Muller C, Rabal O, Diaz Gonzalez C. Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2021; 2390:383-407. [PMID: 34731478 DOI: 10.1007/978-1-0716-1787-8_16] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The discovery and development of drugs is a long and expensive process with a high attrition rate. Computational drug discovery contributes to ligand discovery and optimization, by using models that describe the properties of ligands and their interactions with biological targets. In recent years, artificial intelligence (AI) has made remarkable modeling progress, driven by new algorithms and by the increase in computing power and storage capacities, which allow the processing of large amounts of data in a short time. This review provides the current state of the art of AI methods applied to drug discovery, with a focus on structure- and ligand-based virtual screening, library design and high-throughput analysis, drug repurposing and drug sensitivity, de novo design, chemical reactions and synthetic accessibility, ADMET, and quantum mechanics.
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Affiliation(s)
- Christophe Muller
- Evotec (France) SAS, Computational Drug Discovery, Integrated Drug Discovery, Toulouse, France
| | - Obdulia Rabal
- Evotec (France) SAS, Computational Drug Discovery, Integrated Drug Discovery, Toulouse, France
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8
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Veale CGL, Mateos-Jiménez M, Vaaltyn MC, Müller R, Makhubu MP, Alhassan M, de la Torre BG, Albericio F, Mackay CL, Edkins AL, Clarke DJ. A native mass spectrometry platform identifies HOP inhibitors that modulate the HSP90-HOP protein-protein interaction. Chem Commun (Camb) 2021; 57:10919-10922. [PMID: 34591048 DOI: 10.1039/d1cc04257b] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Herein we describe a native mass spectromery protein-peptide model as a competent surrogate for the HOP-HSP90 protein-protein interaction (PPI), application of which led to the qualititive identification of two new peptides capable of in vitro PPI disruption. This proof of concept study offers a viable alternative for PPI inhibitor screening.
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Affiliation(s)
- Clinton G L Veale
- FLAIR Research Fellow, School of Chemistry and Physics, Pietermaritzburg Campus, University of KwaZulu-Natal, Private Bag X01, Scottsville, 3209, South Africa.
| | - Maria Mateos-Jiménez
- EaStCHEM School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh EH93FJ, UK.
| | - Michaelone C Vaaltyn
- The Biomedical Biotechnology Research Unit (BioBRU), Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa
| | - Ronel Müller
- FLAIR Research Fellow, School of Chemistry and Physics, Pietermaritzburg Campus, University of KwaZulu-Natal, Private Bag X01, Scottsville, 3209, South Africa.
| | - Matodzi P Makhubu
- The Biomedical Biotechnology Research Unit (BioBRU), Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa
| | - Mahama Alhassan
- FLAIR Research Fellow, School of Chemistry and Physics, Pietermaritzburg Campus, University of KwaZulu-Natal, Private Bag X01, Scottsville, 3209, South Africa.
| | - Beatriz G de la Torre
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, South Africa
| | - Fernando Albericio
- FLAIR Research Fellow, School of Chemistry and Physics, Pietermaritzburg Campus, University of KwaZulu-Natal, Private Bag X01, Scottsville, 3209, South Africa.
| | - C Logan Mackay
- EaStCHEM School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh EH93FJ, UK.
| | - Adrienne L Edkins
- The Biomedical Biotechnology Research Unit (BioBRU), Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa
| | - David J Clarke
- EaStCHEM School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh EH93FJ, UK.
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9
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Exploring the chemical space of protein-protein interaction inhibitors through machine learning. Sci Rep 2021; 11:13369. [PMID: 34183730 PMCID: PMC8238997 DOI: 10.1038/s41598-021-92825-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 06/16/2021] [Indexed: 11/08/2022] Open
Abstract
Although protein-protein interactions (PPIs) have emerged as the basis of potential new therapeutic approaches, targeting intracellular PPIs with small molecule inhibitors is conventionally considered highly challenging. Driven by increasing research efforts, success rates have increased significantly in recent years. In this study, we analyze the physicochemical properties of 9351 non-redundant inhibitors present in the iPPI-DB and TIMBAL databases to define a computational model for active compounds acting against PPI targets. Principle component analysis (PCA) and k-means clustering were used to identify plausible PPI targets in regions of interest in the active group in the chemical space between active and inactive iPPI compounds. Notably, the uniquely defined active group exhibited distinct differences in activity compared with other active compounds. These results demonstrate that active compounds with regions of interest in the chemical space may be expected to provide insights into potential PPI inhibitors for particular protein targets.
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10
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Gupta P, Mohanty D. SMMPPI: a machine learning-based approach for prediction of modulators of protein-protein interactions and its application for identification of novel inhibitors for RBD:hACE2 interactions in SARS-CoV-2. Brief Bioinform 2021; 22:6220172. [PMID: 33839740 PMCID: PMC8083326 DOI: 10.1093/bib/bbab111] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 02/18/2021] [Accepted: 03/12/2021] [Indexed: 11/30/2022] Open
Abstract
Small molecule modulators of protein–protein interactions (PPIs) are being pursued as novel anticancer, antiviral and antimicrobial drug candidates. We have utilized a large data set of experimentally validated PPI modulators and developed machine learning classifiers for prediction of new small molecule modulators of PPI. Our analysis reveals that using random forest (RF) classifier, general PPI Modulators independent of PPI family can be predicted with ROC-AUC higher than 0.9, when training and test sets are generated by random split. The performance of the classifier on data sets very different from those used in training has also been estimated by using different state of the art protocols for removing various types of bias in division of data into training and test sets. The family-specific PPIM predictors developed in this work for 11 clinically important PPI families also have prediction accuracies of above 90% in majority of the cases. All these ML-based predictors have been implemented in a freely available software named SMMPPI for prediction of small molecule modulators for clinically relevant PPIs like RBD:hACE2, Bromodomain_Histone, BCL2-Like_BAX/BAK, LEDGF_IN, LFA_ICAM, MDM2-Like_P53, RAS_SOS1, XIAP_Smac, WDR5_MLL1, KEAP1_NRF2 and CD4_gp120. We have identified novel chemical scaffolds as inhibitors for RBD_hACE PPI involved in host cell entry of SARS-CoV-2. Docking studies for some of the compounds reveal that they can inhibit RBD_hACE2 interaction by high affinity binding to interaction hotspots on RBD. Some of these new scaffolds have also been found in SARS-CoV-2 viral growth inhibitors reported recently; however, it is not known if these molecules inhibit the entry phase.
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Affiliation(s)
| | - Debasisa Mohanty
- Bioinformatics & Computational Biology research group at NII, New Delhi 110067, India
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11
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Veale CGL. Into the Fray! A Beginner's Guide to Medicinal Chemistry. ChemMedChem 2021; 16:1199-1225. [PMID: 33591595 DOI: 10.1002/cmdc.202000929] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Indexed: 12/31/2022]
Abstract
Modern medicinal chemistry is a complex, multidimensional discipline that operates at the interface of the chemical and biological sciences. The medicinal chemistry contribution to drug discovery is typically described in the context of the well-recited linear progression of the drug discovery pipeline. However, compound optimization is idiosyncratic to each project, and clear definitions of hit and lead molecules and the subsequent progress along the pipeline becomes easily blurred. In addition, this description lacks insight into the entangled relationship between chemical and pharmacological properties, and thus provides limited guidance on how innovative medicinal chemistry strategies can be applied to solve optimization problems, regardless of the stage in the pipeline. Through discussion and illustrative examples, this article seeks to provide insights into the finesse of medicinal chemistry and the subtlety of balancing chemical properties pharmacology. In so doing, it aims to serve as an accessible and simple-to-digest guide for anyone who wishes to learn about the underlying principles of medicinal chemistry, in a context that has been decoupled from the pipeline description.
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Affiliation(s)
- Clinton G L Veale
- School of Chemistry and Physics, Pietermaritzburg Campus, University of KwaZulu-Natal, Private Bag X01, Pietermaritzburg, Scottsville, 3209, South Africa
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12
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Kieffer C, Jourdan JP, Jouanne M, Voisin-Chiret AS. Noncellular screening for the discovery of protein–protein interaction modulators. Drug Discov Today 2020; 25:1592-1603. [DOI: 10.1016/j.drudis.2020.07.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 06/24/2020] [Accepted: 07/13/2020] [Indexed: 12/31/2022]
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13
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Bosc N, Muller C, Hoffer L, Lagorce D, Bourg S, Derviaux C, Gourdel ME, Rain JC, Miller TW, Villoutreix BO, Miteva MA, Bonnet P, Morelli X, Sperandio O, Roche P. Fr-PPIChem: An Academic Compound Library Dedicated to Protein-Protein Interactions. ACS Chem Biol 2020; 15:1566-1574. [PMID: 32320205 PMCID: PMC7399473 DOI: 10.1021/acschembio.0c00179] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Protein-protein interactions (PPIs) mediate nearly every cellular process and represent attractive targets for modulating disease states but are challenging to target with small molecules. Despite this, several PPI inhibitors (iPPIs) have entered clinical trials, and a growing number of PPIs have become validated drug targets. However, high-throughput screening efforts still endure low hit rates mainly because of the use of unsuitable screening libraries. Here, we describe the collective effort of a French consortium to build, select, and store in plates a unique chemical library dedicated to the inhibition of PPIs. Using two independent predictive models and two updated databases of experimentally confirmed PPI inhibitors developed by members of the consortium, we built models based on different training sets, molecular descriptors, and machine learning methods. Independent statistical models were used to select putative PPI inhibitors from large commercial compound collections showing great complementarity. Medicinal chemistry filters were applied to remove undesirable structures from this set (such as PAINS, frequent hitters, and toxic compounds) and to improve drug likeness. The remaining compounds were subjected to a clustering procedure to reduce the final size of the library while maintaining its chemical diversity. In practice, the library showed a 46-fold activity rate enhancement when compared to a non-iPPI-enriched diversity library in high-throughput screening against the CD47-SIRPα PPI. The Fr-PPIChem library is plated in 384-well plates and will be distributed on demand to the scientific community as a powerful tool for discovering new chemical probes and early hits for the development of potential therapeutic drugs.
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Affiliation(s)
- Nicolas Bosc
- Inserm U973 MTi, 25 rue Hélène Brion 75013 Paris
- Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR3528, 28 rue du Dr Roux 75015 Paris
| | - Christophe Muller
- IPC Drug Discovery Platform, Institut Paoli-Calmettes, 232 Boulevard de Sainte-Marguerite, 13009, Marseille, France
| | - Laurent Hoffer
- CRCM, CNRS, INSERM, Institut Paoli-Calmettes, Aix-Marseille Univ, 13009 Marseille, France
| | - David Lagorce
- Université de Paris, INSERM US14, Plateforme Maladies Rares - Orphanet, 75014 Paris, France
| | - Stéphane Bourg
- Institut de Chimie Organique et Analytique (ICOA), Université d’Orléans, UMR CNRS 7311, BP 6759, 45067 Orléans. France
| | - Carine Derviaux
- IPC Drug Discovery Platform, Institut Paoli-Calmettes, 232 Boulevard de Sainte-Marguerite, 13009, Marseille, France
| | - Marie-Edith Gourdel
- Hybrigenics Services SAS, 1 rue Pierre Fontaine, 91000 Evry Courcouronnes, France
| | - Jean-Christophe Rain
- Hybrigenics Services SAS, 1 rue Pierre Fontaine, 91000 Evry Courcouronnes, France
| | - Thomas W. Miller
- IPC Drug Discovery Platform, Institut Paoli-Calmettes, 232 Boulevard de Sainte-Marguerite, 13009, Marseille, France
| | - Bruno O. Villoutreix
- Université de Lille, INSERM, Institut Pasteur de Lille, U1177 - Drugs and Molecules for living Systems, 59000 Lille, France
| | - Maria A. Miteva
- Inserm U1268 MCTR, CNRS UMR 8038 CiTCoM – Univ. De Paris, Faculté de Pharmacie de Paris, 75006 Paris, France
| | - Pascal Bonnet
- Institut de Chimie Organique et Analytique (ICOA), Université d’Orléans, UMR CNRS 7311, BP 6759, 45067 Orléans. France
| | - Xavier Morelli
- IPC Drug Discovery Platform, Institut Paoli-Calmettes, 232 Boulevard de Sainte-Marguerite, 13009, Marseille, France
- CRCM, CNRS, INSERM, Institut Paoli-Calmettes, Aix-Marseille Univ, 13009 Marseille, France
| | - Olivier Sperandio
- Inserm U973 MTi, 25 rue Hélène Brion 75013 Paris
- Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR3528, 28 rue du Dr Roux 75015 Paris
| | - Philippe Roche
- CRCM, CNRS, INSERM, Institut Paoli-Calmettes, Aix-Marseille Univ, 13009 Marseille, France
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14
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Shen L, Yuan Y, Guo Y, Li M, Li C, Pu X. Probing the Druggablility on the Interface of the Protein-Protein Interaction and Its Allosteric Regulation Mechanism on the Drug Screening for the CXCR4 Homodimer. Front Pharmacol 2019; 10:1310. [PMID: 31787895 PMCID: PMC6855241 DOI: 10.3389/fphar.2019.01310] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 10/15/2019] [Indexed: 12/19/2022] Open
Abstract
Modulating protein–protein interactions (PPIs) with small drug-like molecules targeting it exhibits great promise in modern drug discovery. G protein-coupled receptors (GPCRs) are the largest family of targeted proteins and could form dimers in living biological cells through PPIs. However, compared to drug development of the orthosteric site, there has been lack of investigations on the druggability of the PPI interface for GPCRs and its functional implication on experiments. Thus, in order to address these issues, we constructed a novel computational strategy, which involved in molecular dynamics simulation, virtual screening and protein structure network (PSN), to study one representative GPCR homodimer (CXCR4). One druggable pocket was identified in the PPI interface and one small molecule targeting it was screened, which could strengthen PPI mainly through hydrophobic interaction between the benzene rings of the PPI molecule and TM4 of the receptor. The PSN results further reveals that the PPI molecule could increase the number of the allosteric regulation pathways between the druggable pocket of the dimer interface to the orthostatic site for the subunit A but only play minor role for the other subunit B, leading to the asymmetric change in the volume of the binding pockets for the two subunits (increase for the subunit A and minor change for the subunit B). Consequently, the screening performance of the subunit A to the antagonists is enhanced while the subunit B is unchanged nearly, implying that the PPI molecule may be beneficial to enhance the drug efficacies of the antagonists. In addition, one main regulation pathway with the highest frequency was identified for the subunit A, which consists of Trp1955.34–Tyr190ECL2–Val1965.35–Gln2005.39–Asp2626.58–Cys28N-term, revealing their importance in the allosteric regulation from the PPI molecule. The observations from the work could provide valuable information for the development of the PPI drug-like molecule for GPCRs.
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Affiliation(s)
- Liting Shen
- College of Chemistry, Sichuan University, Chengdu, China
| | - Yuan Yuan
- College of Management, Southwest University for Nationalities, Chengdu, China
| | - Yanzhi Guo
- College of Chemistry, Sichuan University, Chengdu, China
| | - Menglong Li
- College of Chemistry, Sichuan University, Chengdu, China
| | - Chuan Li
- College of Computer Science, Sichuan University, Chengdu, China
| | - Xuemei Pu
- College of Chemistry, Sichuan University, Chengdu, China
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15
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Sartini S, Levati E, Maccesi M, Guerra M, Spadoni G, Bach S, Benincasa M, Scocchi M, Ottonello S, Rivara S, Montanini B. New Antimicrobials Targeting Bacterial RNA Polymerase Holoenzyme Assembly Identified with an in Vivo BRET-Based Discovery Platform. ACS Chem Biol 2019; 14:1727-1736. [PMID: 31310497 DOI: 10.1021/acschembio.9b00178] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Bacterial resistance represents a major health threat worldwide, and the development of new therapeutics, including innovative antibiotics, is urgently needed. We describe a discovery platform, centered on in silico screening and in vivo bioluminescence resonance energy transfer in yeast cells, for the identification of new antimicrobials that, by targeting the protein-protein interaction between the β'-subunit and the initiation factor σ70 of bacterial RNA polymerase, inhibit holoenzyme assembly and promoter-specific transcription. Out of 34 000 candidate compounds, we identified seven hits capable of interfering with this interaction. Two derivatives of one of these hits proved to be effective in inhibiting transcription in vitro and growth of the Gram-positive pathogens Staphylococcus aureus and Listeria monocytogenes. Upon supplementation of a permeability adjuvant, one derivative also effectively inhibited Escherichia coli growth. On the basis of the chemical structures of these inhibitors, we generated a ligand-based pharmacophore model that will guide the rational discovery of increasingly effective antibacterial agents.
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Affiliation(s)
- Sara Sartini
- Laboratory of Biochemistry and Molecular Biology, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy
- Interdepartmental Research Centre Biopharmanet-Tec, University of Parma, 43124 Parma, Italy
| | - Elisabetta Levati
- Laboratory of Biochemistry and Molecular Biology, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy
| | - Martina Maccesi
- Department of Chemical and Pharmaceutical Sciences, University of Ferrara, 44121 Ferrara, Italy
| | - Matteo Guerra
- Laboratory of Biochemistry and Molecular Biology, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy
| | - Gilberto Spadoni
- Department of Biomolecular Sciences, University of Urbino “Carlo Bo”, 61029 Urbino, Italy
| | - Stéphane Bach
- Sorbonne Université, CNRS, UMR 8227, Integrative Biology of Marine Models, Team Physiology and Cell Fate, Station Biologique de Roscoff, CS 90074, 29688 Roscoff Cedex, France
| | - Monica Benincasa
- Department of Life Sciences, University of Trieste, 34128 Trieste, Italy
| | - Marco Scocchi
- Department of Life Sciences, University of Trieste, 34128 Trieste, Italy
| | - Simone Ottonello
- Laboratory of Biochemistry and Molecular Biology, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy
| | - Silvia Rivara
- Department of Food and Drug, University of Parma, 43124 Parma, Italy
| | - Barbara Montanini
- Laboratory of Biochemistry and Molecular Biology, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy
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16
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Analysis of solvent-exposed and buried co-crystallized ligands: a case study to support the design of novel protein–protein interaction inhibitors. Drug Discov Today 2019; 24:551-559. [DOI: 10.1016/j.drudis.2018.11.013] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 11/03/2018] [Accepted: 11/16/2018] [Indexed: 12/22/2022]
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17
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Mohammadi M, Mohammadiarani H, Shaw VS, Neubig RR, Vashisth H. Interplay of cysteine exposure and global protein dynamics in small-molecule recognition by a regulator of G-protein signaling protein. Proteins 2018; 87:146-156. [PMID: 30521141 DOI: 10.1002/prot.25642] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 11/07/2018] [Accepted: 11/29/2018] [Indexed: 02/06/2023]
Abstract
Regulator of G protein signaling (RGS) proteins play a pivotal role in regulation of G protein-coupled receptor (GPCR) signaling and are therefore becoming an increasingly important therapeutic target. Recently discovered thiadiazolidinone (TDZD) compounds that target cysteine residues have shown different levels of specificities and potencies for the RGS4 protein, thereby suggesting intrinsic differences in dynamics of this protein upon binding of these compounds. In this work, we investigated using atomistic molecular dynamics (MD) simulations the effect of binding of several small-molecule inhibitors on perturbations and dynamical motions in RGS4. Specifically, we studied two conformational models of RGS4 in which a buried cysteine residue is solvent-exposed due to side-chain motions or due to flexibility in neighboring helices. We found that TDZD compounds with aromatic functional groups perturb the RGS4 structure more than compounds with aliphatic functional groups. Moreover, small-molecules with aromatic functional groups but lacking sulfur atoms only transiently reside within the protein and spontaneously dissociate to the solvent. We further measured inhibitory effects of TDZD compounds using a protein-protein interaction assay on a single-cysteine RGS4 protein showing trends in potencies of compounds consistent with our simulation studies. Thermodynamic analyses of RGS4 conformations in the apo-state and on binding to TDZD compounds revealed links between both conformational models of RGS4. The exposure of cysteine side-chains appears to facilitate initial binding of TDZD compounds followed by migration of the compound into a bundle of four helices, thereby causing allosteric perturbations in the RGS/Gα protein-protein interface.
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Affiliation(s)
| | | | - Vincent S Shaw
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, Michigan
| | - Richard R Neubig
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, Michigan
| | - Harish Vashisth
- Department of Chemical Engineering, University of New Hampshire, Durham, New Hampshire
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18
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Macalino SJY, Basith S, Clavio NAB, Chang H, Kang S, Choi S. Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery. Molecules 2018; 23:E1963. [PMID: 30082644 PMCID: PMC6222862 DOI: 10.3390/molecules23081963] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 08/03/2018] [Accepted: 08/04/2018] [Indexed: 12/14/2022] Open
Abstract
The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their "undruggable" binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery.
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Affiliation(s)
- Stephani Joy Y Macalino
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Shaherin Basith
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Nina Abigail B Clavio
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Hyerim Chang
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Soosung Kang
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
| | - Sun Choi
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
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19
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Wu X, Ji H. Rhodium-Catalyzed [4 + 1] Cyclization via C-H Activation for the Synthesis of Divergent Heterocycles Bearing a Quaternary Carbon. J Org Chem 2018; 83:4650-4656. [PMID: 29608841 DOI: 10.1021/acs.joc.8b00397] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The development of an efficient approach to construct fused polycyclic systems bearing a quaternary carbon center represents a great challenge to synthetic chemistry. Herein, we report a Rh(III)-catalyzed [4 + 1] annulation of propargyl alcohols with various heterocyclic scaffolds under an air atmosphere. Diverse fused heterocycles containing a quaternary carbon center were obtained in moderate to good yields. Additionally, this method features a high atom-economy, metal oxidant free, simple operation, and compatibility with various functional groups.
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Affiliation(s)
- Xiaowei Wu
- Drug Discovery Department , H. Lee Moffitt Cancer Center and Research Institute , 12902 Magnolia Drive , Tampa , Florida 33612-9416 , United States
| | - Haitao Ji
- Drug Discovery Department , H. Lee Moffitt Cancer Center and Research Institute , 12902 Magnolia Drive , Tampa , Florida 33612-9416 , United States.,Departments of Oncologic Sciences and Chemistry , University of South Florida , Tampa , Florida 33612 , United States
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20
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Wang Z, Kang Y, Li D, Sun H, Dong X, Yao X, Xu L, Chang S, Li Y, Hou T. Benchmark Study Based on 2P2I DB to Gain Insights into the Discovery of Small-Molecule PPI Inhibitors. J Phys Chem B 2018; 122:2544-2555. [PMID: 29420886 DOI: 10.1021/acs.jpcb.7b12658] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Protein-protein interactions (PPIs) have been regarded as novel and highly promising drug targets in drug discovery. Numerous new experimental techniques and computational approaches have been developed to assist the design of PPI modulators during the past two decades. However, identification and optimization of small-molecule inhibitors targeting PPIs is still a particularly challenging task due to the "undruggable" profiles of PPI interfaces. Nowadays, in silico screening, especially docking-based virtual screening, has emerged as an effective method to complement experimental high-throughput screening in identifying novel and potent small-molecule PPI inhibitors. Here, on the basis of the 2P2IDB database, we explored the structural features of the known small-molecule PPI inhibitors and analyzed the characteristics of the PPI binding pockets. More importantly, we evaluated the sampling power and screening power of six popular docking programs for PPI targets. Our results indicate that the chlorinated conjugate group and amidelike linkage are two types of privileged fragments of PPI inhibitors; the average druggability of the binding sites of the PPI targets in 2P2IDB is slightly worse than that of traditional ones; both academic and commercial docking programs exhibit an acceptable accuracy on pose prediction for PPI inhibitors, but their screening powers for identifying PPI inhibitors are still not satisfactory. It is expected that our work can provide valuable guidance on the construction of PPI-focused library, the determination of druggable PPI binding pocket, and the selection of docking program for the screening of small-molecule PPI inhibitors.
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Affiliation(s)
- Zhe Wang
- College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , Zhejiang 310058 , China
| | - Yu Kang
- College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , Zhejiang 310058 , China
| | - Dan Li
- College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , Zhejiang 310058 , China
| | - Huiyong Sun
- College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , Zhejiang 310058 , China
| | - Xiaowu Dong
- College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , Zhejiang 310058 , China
| | - Xiaojun Yao
- State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health , Macau University of Science and Technology , Avenida Wai Long , Taipa , Macau (SAR) , China
| | - Lei Xu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering , Jiangsu University of Technology , Changzhou 213001 , China
| | - Shan Chang
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering , Jiangsu University of Technology , Changzhou 213001 , China
| | - Youyong Li
- Institute of Functional Nano and Soft Materials (FUNSOM) , Soochow University , Suzhou , Jiangsu 215123 , China
| | - Tingjun Hou
- College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , Zhejiang 310058 , China
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21
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Bosc N, Kuenemann MA, Bécot J, Vavrusa M, Cerdan AH, Sperandio O. Privileged Substructures to Modulate Protein-Protein Interactions. J Chem Inf Model 2017; 57:2448-2462. [PMID: 28922596 DOI: 10.1021/acs.jcim.7b00435] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Given the difficulties to identify chemical probes that can modulate protein-protein interactions (PPIs), actors in the field have started to agree on the necessity to use PPI-tailored screening chemical collections. However, which type of scaffolds may promote the binding of compounds to PPI targets remains unclear. In this big data analysis, we have identified a list of privileged chemical substructures that are most often observed within inhibitors of PPIs. Using molecular frameworks as a way to perceive chemical substructures with the combination of an experimental and a machine-learning based predicted data set of iPPI compounds, we propose a list of privileged substructures in the form of scaffolds and chemical moieties that can be substantially chemically functionalized and do not present any toxicophore nor pan-assay interference (PAINS) alerts. We think that such chemical guidance will be valuable for medicinal chemists in their attempt to identify initial quality chemical probes on PPI targets.
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Affiliation(s)
- Nicolas Bosc
- Inserm, U973 , Paris 75013, France.,Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm , Paris 75013, France.,Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, Institut Pasteur , 25-28 rue du Dr Roux, Paris 75015, France.,CNRS UMR3528, Institut Pasteur , 25-28 rue du Dr Roux, Paris 75015, France
| | - Mélaine A Kuenemann
- Inserm, U973 , Paris 75013, France.,Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm , Paris 75013, France
| | - Jerome Bécot
- Inserm, U973 , Paris 75013, France.,Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm , Paris 75013, France
| | - Marek Vavrusa
- Inserm, U973 , Paris 75013, France.,Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm , Paris 75013, France
| | - Adrien H Cerdan
- Inserm, U973 , Paris 75013, France.,Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm , Paris 75013, France
| | - Olivier Sperandio
- Inserm, U973 , Paris 75013, France.,Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm , Paris 75013, France.,Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, Institut Pasteur , 25-28 rue du Dr Roux, Paris 75015, France.,CNRS UMR3528, Institut Pasteur , 25-28 rue du Dr Roux, Paris 75015, France
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22
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Lagorce D, Douguet D, Miteva MA, Villoutreix BO. Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors. Sci Rep 2017; 7:46277. [PMID: 28397808 PMCID: PMC5387685 DOI: 10.1038/srep46277] [Citation(s) in RCA: 91] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Accepted: 03/13/2017] [Indexed: 12/18/2022] Open
Abstract
The modulation of PPIs by low molecular weight chemical compounds, particularly by orally bioavailable molecules, would be very valuable in numerous disease indications. However, it is known that PPI inhibitors (iPPIs) tend to have properties that are linked to poor Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and in some cases to poor clinical outcomes. Previously reported in silico analyses of iPPIs have essentially focused on physicochemical properties but several other ADMET parameters would be important to assess. In order to gain new insights into the ADMET properties of iPPIs, computations were carried out on eight datasets collected from several databases. These datasets involve compounds targeting enzymes, GPCRs, ion channels, nuclear receptors, allosteric modulators, oral marketed drugs, oral natural product-derived marketed drugs and iPPIs. Several trends are reported that should assist the design and optimization of future PPI inhibitors, either for drug discovery endeavors or for chemical biology projects.
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Affiliation(s)
- David Lagorce
- INSERM, U973, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Dominique Douguet
- CNRS UMR7275, Institut de Pharmacologie Moléculaire et Cellulaire, Université Côte d’Azur, Valbonne, France
| | - Maria A. Miteva
- INSERM, U973, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
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23
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Murakami Y, Tripathi LP, Prathipati P, Mizuguchi K. Network analysis and in silico prediction of protein-protein interactions with applications in drug discovery. Curr Opin Struct Biol 2017; 44:134-142. [PMID: 28364585 DOI: 10.1016/j.sbi.2017.02.005] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2016] [Revised: 02/05/2017] [Accepted: 02/23/2017] [Indexed: 11/29/2022]
Abstract
Protein-protein interactions (PPIs) are vital to maintaining cellular homeostasis. Several PPI dysregulations have been implicated in the etiology of various diseases and hence PPIs have emerged as promising targets for drug discovery. Surface residues and hotspot residues at the interface of PPIs form the core regions, which play a key role in modulating cellular processes such as signal transduction and are used as starting points for drug design. In this review, we briefly discuss how PPI networks (PPINs) inferred from experimentally characterized PPI data have been utilized for knowledge discovery and how in silico approaches to PPI characterization can contribute to PPIN-based biological research. Next, we describe the principles of in silico PPI prediction and survey the existing PPI and PPI site prediction servers that are useful for drug discovery. Finally, we discuss the potential of in silico PPI prediction in drug discovery.
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Affiliation(s)
- Yoichi Murakami
- National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8 Saito Asagi, Ibaraki, Osaka 567-0085, Japan.
| | - Lokesh P Tripathi
- National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8 Saito Asagi, Ibaraki, Osaka 567-0085, Japan.
| | - Philip Prathipati
- National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8 Saito Asagi, Ibaraki, Osaka 567-0085, Japan
| | - Kenji Mizuguchi
- National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8 Saito Asagi, Ibaraki, Osaka 567-0085, Japan.
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24
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Choi S, Choi KY. Screening-based approaches to identify small molecules that inhibit protein–protein interactions. Expert Opin Drug Discov 2017; 12:293-303. [DOI: 10.1080/17460441.2017.1280456] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Sehee Choi
- Translational Research Center for Protein Function Control, Yonsei University, Seoul, Korea
- Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea
| | - Kang-Yell Choi
- Translational Research Center for Protein Function Control, Yonsei University, Seoul, Korea
- Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea
- CK Biotechnology Inc., 416 Advanced Science and Technology Center, 50 Yonsei-ro, Seoul, Korea
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25
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Ivan T, Enkvist E, Viira B, Manoharan GB, Raidaru G, Pflug A, Alam KA, Zaccolo M, Engh RA, Uri A. Bifunctional Ligands for Inhibition of Tight-Binding Protein-Protein Interactions. Bioconjug Chem 2016; 27:1900-10. [PMID: 27389935 DOI: 10.1021/acs.bioconjchem.6b00293] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The acknowledged potential of small-molecule therapeutics targeting disease-related protein-protein interactions (PPIs) has promoted active research in this field. The strategy of using small molecule inhibitors (SMIs) to fight strong (tight-binding) PPIs tends to fall short due to the flat and wide interfaces of PPIs. Here we propose a biligand approach for disruption of strong PPIs. The potential of this approach was realized for disruption of the tight-binding (KD = 100 pM) tetrameric holoenzyme of cAMP-dependent protein kinase (PKA). Supported by X-ray analysis of cocrystals, bifunctional inhibitors (ARC-inhibitors) were constructed that simultaneously associated with both the ATP-pocket and the PPI interface area of the catalytic subunit of PKA (PKAc). Bifunctional inhibitor ARC-1411, possessing a KD value of 3 pM toward PKAc, induced the dissociation of the PKA holoenzyme with a low-nanomolar IC50, whereas the ATP-competitive inhibitor H89 bound to the PKA holoenzyme without disruption of the protein tetramer.
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Affiliation(s)
- Taavi Ivan
- Institute of Chemistry, University of Tartu , 50410 Tartu, Estonia
| | - Erki Enkvist
- Institute of Chemistry, University of Tartu , 50410 Tartu, Estonia
| | - Birgit Viira
- Institute of Chemistry, University of Tartu , 50410 Tartu, Estonia
| | | | - Gerda Raidaru
- Institute of Chemistry, University of Tartu , 50410 Tartu, Estonia
| | - Alexander Pflug
- The Norwegian Structural Biology Centre, Department of Chemistry, University of Tromsø , N-9019 Tromsø, Norway
| | - Kazi Asraful Alam
- The Norwegian Structural Biology Centre, Department of Chemistry, University of Tromsø , N-9019 Tromsø, Norway
| | - Manuela Zaccolo
- Department of Physiology, Anatomy and Genetics, University of Oxford , OX1 3QX Oxford, United Kingdom
| | - Richard Alan Engh
- The Norwegian Structural Biology Centre, Department of Chemistry, University of Tromsø , N-9019 Tromsø, Norway
| | - Asko Uri
- Institute of Chemistry, University of Tartu , 50410 Tartu, Estonia
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26
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Lipinski CA. Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions. Adv Drug Deliv Rev 2016; 101:34-41. [PMID: 27154268 DOI: 10.1016/j.addr.2016.04.029] [Citation(s) in RCA: 268] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2015] [Revised: 04/22/2016] [Accepted: 04/27/2016] [Indexed: 12/13/2022]
Abstract
The rule of five (Ro5), based on physicochemical profiles of phase II drugs, is consistent with structural limitations in protein targets and the drug target ligands. Three of four parameters in Ro5 are fundamental to the structure of both target and drug binding sites. The chemical structure of the drug ligand depends on the ligand chemistry and design philosophy. Two extremes of chemical structure and design philosophy exist; ligands constructed in the medicinal chemistry synthesis laboratory without input from natural selection and natural product (NP) metabolites biosynthesized based on evolutionary selection. Exceptions to Ro5 are found mostly among NPs. Chemistry chameleon-like behavior of some NPs due to intra-molecular hydrogen bonding as exemplified by cyclosporine A is a strong contributor to NP Ro5 outliers. The fragment derived, drug Navitoclax is an example of the extensive expertise, resources, time and key decisions required for the rare discovery of a non-NP Ro5 outlier.
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27
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Imbalance in chemical space: How to facilitate the identification of protein-protein interaction inhibitors. Sci Rep 2016; 6:23815. [PMID: 27034268 PMCID: PMC4817116 DOI: 10.1038/srep23815] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Accepted: 03/15/2016] [Indexed: 02/03/2023] Open
Abstract
Protein-protein interactions (PPIs) play vital roles in life and provide new opportunities for therapeutic interventions. In this large data analysis, 3,300 inhibitors of PPIs (iPPIs) were compared to 17 reference datasets of collectively ~566,000 compounds (including natural compounds, existing drugs, active compounds on conventional targets, etc.) using a chemoinformatics approach. Using this procedure, we showed that comparable classes of PPI targets can be formed using either the similarity of their ligands or the shared properties of their binding cavities, constituting a proof-of-concept that not only can binding pockets be used to group PPI targets, but that these pockets certainly condition the properties of their corresponding ligands. These results demonstrate that matching regions in both chemical space and target space can be found. Such identified classes of targets could lead to the design of PPI-class-specific chemical libraries and therefore facilitate the development of iPPIs to the stage of drug candidates.
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Affiliation(s)
- Raphael M. Franzini
- Department
of Medicinal Chemistry,
College of Pharmacy, University of Utah, 30 S 2000 E, Salt Lake City, Utah 84112, United States
| | - Cassie Randolph
- Department
of Medicinal Chemistry,
College of Pharmacy, University of Utah, 30 S 2000 E, Salt Lake City, Utah 84112, United States
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29
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Hauser AS, Windshügel B. LEADS-PEP: A Benchmark Data Set for Assessment of Peptide Docking Performance. J Chem Inf Model 2016; 56:188-200. [PMID: 26651532 DOI: 10.1021/acs.jcim.5b00234] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
With increasing interest in peptide-based therapeutics also the application of computational approaches such as peptide docking has gained more and more attention. In order to assess the suitability of docking programs for peptide placement and to support the development of peptide-specific docking tools, an independently constructed benchmark data set is urgently needed. Here we present the LEADS-PEP benchmark data set for assessing peptide docking performance. Using a rational and unbiased workflow, 53 protein-peptide complexes with peptide lengths ranging from 3 to 12 residues were selected. The data set is publicly accessible at www.leads-x.org . In a second step we evaluated several small molecule docking programs for their potential to reproduce peptide conformations as present in LEADS-PEP. While most tested programs were capable to generate native-like binding modes of small peptides, only Surflex-Dock and AutoDock Vina performed reasonably well for peptides consisting of more than five residues. Rescoring of docking poses with scoring functions ChemPLP, ChemScore, and ASP further increased the number of top-ranked near-native conformations. Our results suggest that small molecule docking programs are a good and fast alternative to specialized peptide docking programs.
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Affiliation(s)
- Alexander Sebastian Hauser
- Fraunhofer Institute for Molecular Biology and Applied Ecology IME , Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Björn Windshügel
- Fraunhofer Institute for Molecular Biology and Applied Ecology IME , Schnackenburgallee 114, 22525 Hamburg, Germany
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30
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Abstract
Modulation of protein-protein interactions (PPIs) is becoming increasingly important in drug discovery and chemical biology. While a few years ago this 'target class' was deemed to be largely undruggable an impressing number of publications and success stories now show that targeting PPIs with small, drug-like molecules indeed is a feasible approach. Here, we summarize the current state of small-molecule inhibition and stabilization of PPIs and review the active molecules from a structural and medicinal chemistry angle, especially focusing on the key examples of iNOS, LFA-1 and 14-3-3.
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31
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Cierpicki T, Grembecka J. Targeting protein-protein interactions in hematologic malignancies: still a challenge or a great opportunity for future therapies? Immunol Rev 2015; 263:279-301. [PMID: 25510283 DOI: 10.1111/imr.12244] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Over the past several years, there has been an increasing research effort focused on inhibition of protein-protein interactions (PPIs) to develop novel therapeutic approaches for cancer, including hematologic malignancies. These efforts have led to development of small molecule inhibitors of PPIs, some of which already advanced to the stage of clinical trials while others are at different stages of preclinical optimization, emphasizing PPIs as an emerging and attractive class of drug targets. Here, we review several examples of recently developed inhibitors of PPIs highly relevant to hematologic cancers. We address the existing skepticism about feasibility of targeting PPIs and emphasize potential therapeutic benefit from blocking PPIs in hematologic malignancies. We then use these examples to discuss the approaches for successful identification of PPI inhibitors and provide analysis of the protein-protein interfaces, with the goal to address 'druggability' of new PPIs relevant to hematology. We discuss lessons learned to improve the success of targeting new PPIs and evaluate prospects and limits of the research in this field. We conclude that not all PPIs are equally tractable for blocking by small molecules, and detailed analysis of PPI interfaces is critical for selection of those with the highest chance of success. Together, our analysis uncovers patterns that should help to advance drug discovery in hematologic malignancies by successful targeting of new PPIs.
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Affiliation(s)
- Tomasz Cierpicki
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
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32
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Sheng C, Dong G, Miao Z, Zhang W, Wang W. State-of-the-art strategies for targeting protein-protein interactions by small-molecule inhibitors. Chem Soc Rev 2015; 44:8238-59. [PMID: 26248294 DOI: 10.1039/c5cs00252d] [Citation(s) in RCA: 106] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Targeting protein-protein interactions (PPIs) has emerged as a viable approach in modern drug discovery. However, the identification of small molecules enabling us to effectively interrupt their interactions presents significant challenges. In the recent past, significant advances have been made in the development of new biological and chemical strategies to facilitate the discovery process of small-molecule PPI inhibitors. This review aims to highlight the state-of-the-art technologies and the achievements made recently in this field. The "hot spots" of PPIs have been proved to be critical for small molecules to bind. Three strategies including screening, designing, and synthetic approaches have been explored for discovering PPI inhibitors by targeting the "hot spots". Although the classic high throughput screening approach can be used, fragment screening, fragment-based drug design and newly improved virtual screening are demonstrated to be more effective in the discovery of PPI inhibitors. In addition to screening approaches, design strategies including anchor-based and small molecule mimetics of secondary structures involved in PPIs have become powerful tools as well. Finally, constructing new chemically spaced libraries with high diversity and complexity is becoming an important area of interest for PPI inhibitors. The successful cases from the recent five year studies are used to illustrate how these approaches are implemented to uncover and optimize small molecule PPI inhibitors and notably some of them have become promising therapeutics.
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Affiliation(s)
- Chunquan Sheng
- Department of Medicinal Chemistry, School of Pharmacy, Second Military Medical University, 325 Guohe Road, Shanghai 200433, P. R. China.
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33
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Blazer LL, Storaska AJ, Jutkiewicz EM, Turner EM, Calcagno M, Wade SM, Wang Q, Huang XP, Traynor JR, Husbands SM, Morari M, Neubig RR. Selectivity and anti-Parkinson's potential of thiadiazolidinone RGS4 inhibitors. ACS Chem Neurosci 2015; 6:911-9. [PMID: 25844489 DOI: 10.1021/acschemneuro.5b00063] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Many current therapies target G protein coupled receptors (GPCR), transporters, or ion channels. In addition to directly targeting these proteins, disrupting the protein-protein interactions that localize or regulate their function could enhance selectivity and provide unique pharmacologic actions. Regulators of G protein signaling (RGS) proteins, especially RGS4, play significant roles in epilepsy and Parkinson's disease. Thiadiazolidinone (TDZD) inhibitors of RGS4 are nanomolar potency blockers of the biochemical actions of RGS4 in vitro. Here, we demonstrate the substantial selectivity (8- to >5000-fold) of CCG-203769 for RGS4 over other RGS proteins. It is also 300-fold selective for RGS4 over GSK-3β, another target of this class of chemical scaffolds. It does not inhibit the cysteine protease papain at 100 μM. CCG-203769 enhances Gαq-dependent cellular Ca(2+) signaling in an RGS4-dependent manner. TDZD inhibitors also enhance Gαi-dependent δ-OR inhibition of cAMP production in SH-SY-5Y cells, which express endogenous receptors and RGS4. Importantly, CCG-203769 potentiates the known RGS4 mechanism of Gαi-dependent muscarinic bradycardia in vivo. Furthermore, it reverses raclopride-induced akinesia and bradykinesia in mice, a model of some aspects of the movement disorder in Parkinson's disease. A broad assessment of compound effects revealed minimal off-target effects at concentrations necessary for cellular RGS4 inhibition. These results expand our understanding of the mechanism and specificity of TDZD RGS inhibitors and support the potential for therapeutic targeting of RGS proteins in Parkinson's disease and other neural disorders.
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Affiliation(s)
- Levi L. Blazer
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan 48109, United States,
| | - Andrew J. Storaska
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan 48109, United States,
- Department of Pharmacology and Toxicology, Michigan State University, East
Lansing, Michigan 48824, United States
| | - Emily M. Jutkiewicz
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan 48109, United States,
| | - Emma M. Turner
- Department of Pharmacy and Pharmacology, University of Bath, Bath, U.K
| | - Mariangela Calcagno
- Section of Pharmacology, Department of
Medical Science, University of Ferrara, Ferrara, Italy 44121
| | - Susan M. Wade
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan 48109, United States,
| | - Qin Wang
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan 48109, United States,
| | - Xi-Ping Huang
- National Institute of Mental Health Psychoactive Drug
Screening Program (NIMH PDSP), Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina 27599, United States
| | - John R. Traynor
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan 48109, United States,
| | | | - Michele Morari
- Section of Pharmacology, Department of
Medical Science, University of Ferrara, Ferrara, Italy 44121
| | - Richard R. Neubig
- Department of Pharmacology and Toxicology, Michigan State University, East
Lansing, Michigan 48824, United States
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34
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Sperandio O, Villoutreix BO, Morelli X, Roche P. [Chemical libraries dedicated to protein-protein interactions]. Med Sci (Paris) 2015; 31:312-9. [PMID: 25855285 DOI: 10.1051/medsci/20153103017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
The identification of complete networks of protein-protein interactions (PPI) within a cell has contributed to major breakthroughs in understanding biological pathways, host-pathogen interactions and cancer development. As a consequence, PPI have emerged as a new class of promising therapeutic targets. However, they are still considered as a challenging class of targets for drug discovery programs. Recent successes have allowed the characterization of structural and physicochemical properties of protein-protein interfaces leading to a better understanding of how they can be disrupted with small molecule compounds. In addition, characterization of the profiles of PPI inhibitors has allowed the development of PPI-focused libraries. In this review, we present the current efforts at developing chemical libraries dedicated to these innovative targets.
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Affiliation(s)
- Olivier Sperandio
- Molécules thérapeutiques in silico (MTi), université Paris Diderot, Inserm UMR-S973, 35, rue Hélène Brion, 75205 Paris Cedex 13, France
| | - Bruno O Villoutreix
- Molécules thérapeutiques in silico (MTi), université Paris Diderot, Inserm UMR-S973, 35, rue Hélène Brion, 75205 Paris Cedex 13, France
| | - Xavier Morelli
- Centre de recherche en cancérologie de Marseille (CRCM), CNRS UMR7258 ; Inserm U1068 ; institut Paoli-Calmettes ; université d'Aix-Marseille UM105, 27, boulevard Lei Roure,13009, Marseille, France
| | - Philippe Roche
- Centre de recherche en cancérologie de Marseille (CRCM), CNRS UMR7258 ; Inserm U1068 ; institut Paoli-Calmettes ; université d'Aix-Marseille UM105, 27, boulevard Lei Roure,13009, Marseille, France
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35
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Levoin N, Vo DD, Gautier F, Barillé-Nion S, Juin P, Tasseau O, Grée R. A combination of in silico and SAR studies to identify binding hot spots of Bcl-xL inhibitors. Bioorg Med Chem 2015; 23:1747-57. [DOI: 10.1016/j.bmc.2015.02.060] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Accepted: 02/18/2015] [Indexed: 01/01/2023]
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36
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Yuriev E, Holien J, Ramsland PA. Improvements, trends, and new ideas in molecular docking: 2012-2013 in review. J Mol Recognit 2015; 28:581-604. [PMID: 25808539 DOI: 10.1002/jmr.2471] [Citation(s) in RCA: 159] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2014] [Revised: 01/16/2015] [Accepted: 02/05/2015] [Indexed: 12/11/2022]
Abstract
Molecular docking is a computational method for predicting the placement of ligands in the binding sites of their receptor(s). In this review, we discuss the methodological developments that occurred in the docking field in 2012 and 2013, with a particular focus on the more difficult aspects of this computational discipline. The main challenges and therefore focal points for developments in docking, covered in this review, are receptor flexibility, solvation, scoring, and virtual screening. We specifically deal with such aspects of molecular docking and its applications as selection criteria for constructing receptor ensembles, target dependence of scoring functions, integration of higher-level theory into scoring, implicit and explicit handling of solvation in the binding process, and comparison and evaluation of docking and scoring methods.
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Affiliation(s)
- Elizabeth Yuriev
- Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Jessica Holien
- ACRF Rational Drug Discovery Centre and Structural Biology Laboratory, St. Vincent's Institute of Medical Research, Fitzroy, Victoria, 3065, Australia
| | - Paul A Ramsland
- Centre for Biomedical Research, Burnet Institute, Melbourne, Victoria, 3004, Australia.,Department of Surgery Austin Health, University of Melbourne, Melbourne, Victoria, 3084, Australia.,Department of Immunology, Monash University, Alfred Medical Research and Education Precinct, Melbourne, Victoria, 3004, Australia.,School of Biomedical Sciences, CHIRI Biosciences, Curtin University, Perth, Western Australia, 6845, Australia
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37
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Kuenemann MA, Sperandio O, Labbé CM, Lagorce D, Miteva MA, Villoutreix BO. In silico design of low molecular weight protein-protein interaction inhibitors: Overall concept and recent advances. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2015; 119:20-32. [PMID: 25748546 DOI: 10.1016/j.pbiomolbio.2015.02.006] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2014] [Revised: 02/18/2015] [Accepted: 02/24/2015] [Indexed: 12/22/2022]
Abstract
Protein-protein interactions (PPIs) are carrying out diverse functions in living systems and are playing a major role in the health and disease states. Low molecular weight (LMW) "drug-like" inhibitors of PPIs would be very valuable not only to enhance our understanding over physiological processes but also for drug discovery endeavors. However, PPIs were deemed intractable by LMW chemicals during many years. But today, with the new experimental and in silico technologies that have been developed, about 50 PPIs have already been inhibited by LMW molecules. Here, we first focus on general concepts about protein-protein interactions, present a consensual view about ligandable pockets at the protein interfaces and the possibilities of using fast and cost effective structure-based virtual screening methods to identify PPI hits. We then discuss the design of compound collections dedicated to PPIs. Recent financial analyses of the field suggest that LMW PPI modulators could be gaining momentum over biologics in the coming years supporting further research in this area.
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Affiliation(s)
- Mélaine A Kuenemann
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France
| | - Olivier Sperandio
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France; CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse, 59000 Lille, France
| | - Céline M Labbé
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France; CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse, 59000 Lille, France
| | - David Lagorce
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France
| | - Maria A Miteva
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France
| | - Bruno O Villoutreix
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France; CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse, 59000 Lille, France.
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38
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Peyressatre M, Prével C, Pellerano M, Morris MC. Targeting cyclin-dependent kinases in human cancers: from small molecules to Peptide inhibitors. Cancers (Basel) 2015; 7:179-237. [PMID: 25625291 PMCID: PMC4381256 DOI: 10.3390/cancers7010179] [Citation(s) in RCA: 219] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2014] [Accepted: 01/12/2015] [Indexed: 12/12/2022] Open
Abstract
Cyclin-dependent kinases (CDK/Cyclins) form a family of heterodimeric kinases that play central roles in regulation of cell cycle progression, transcription and other major biological processes including neuronal differentiation and metabolism. Constitutive or deregulated hyperactivity of these kinases due to amplification, overexpression or mutation of cyclins or CDK, contributes to proliferation of cancer cells, and aberrant activity of these kinases has been reported in a wide variety of human cancers. These kinases therefore constitute biomarkers of proliferation and attractive pharmacological targets for development of anticancer therapeutics. The structural features of several of these kinases have been elucidated and their molecular mechanisms of regulation characterized in depth, providing clues for development of drugs and inhibitors to disrupt their function. However, like most other kinases, they constitute a challenging class of therapeutic targets due to their highly conserved structural features and ATP-binding pocket. Notwithstanding, several classes of inhibitors have been discovered from natural sources, and small molecule derivatives have been synthesized through rational, structure-guided approaches or identified in high throughput screens. The larger part of these inhibitors target ATP pockets, but a growing number of peptides targeting protein/protein interfaces are being proposed, and a small number of compounds targeting allosteric sites have been reported.
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Affiliation(s)
- Marion Peyressatre
- Institut des Biomolécules Max Mousseron, IBMM-CNRS-UMR5247, 15 Av. Charles Flahault, 34093 Montpellier, France.
| | - Camille Prével
- Institut des Biomolécules Max Mousseron, IBMM-CNRS-UMR5247, 15 Av. Charles Flahault, 34093 Montpellier, France.
| | - Morgan Pellerano
- Institut des Biomolécules Max Mousseron, IBMM-CNRS-UMR5247, 15 Av. Charles Flahault, 34093 Montpellier, France.
| | - May C Morris
- Institut des Biomolécules Max Mousseron, IBMM-CNRS-UMR5247, 15 Av. Charles Flahault, 34093 Montpellier, France.
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Cukuroglu E, Engin HB, Gursoy A, Keskin O. Hot spots in protein–protein interfaces: Towards drug discovery. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2014; 116:165-73. [DOI: 10.1016/j.pbiomolbio.2014.06.003] [Citation(s) in RCA: 113] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2014] [Revised: 05/30/2014] [Accepted: 06/12/2014] [Indexed: 11/16/2022]
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40
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Kuenemann MA, Bourbon LML, Labbé CM, Villoutreix BO, Sperandio O. Which three-dimensional characteristics make efficient inhibitors of protein-protein interactions? J Chem Inf Model 2014; 54:3067-79. [PMID: 25285479 DOI: 10.1021/ci500487q] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
The specific properties of protein-protein interactions (PPI) (flat, large and hydrophobic) make them harder to tackle with low-molecular-weight compounds. Learning from the properties of successful examples of PPI interface inhibitors (iPPI) at earlier stages of developments, has been pinpointed as a powerful strategy to circumvent this trend. To this end, we have computationally analyzed the bioactive conformations of iPPI and those of inhibitors of conventional targets (e.g enzymes) to highlight putative iPPI 3D characteristics. Most noticeably, the essential property revealed by this study illustrates how efficiently iPPI manages to bind to the hydrophobic patch often present at the core of protein interfaces. The newly identified properties were further confirmed as characteristics of iPPI using much larger data sets (e.g iPPI-DB, www.ippidb.cdithem.fr ). Interestingly, the absence of correlation of such properties with the hydrophobicity and the size of the compounds opens new ways to design potent iPPI with better pharmacokinetic features.
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Affiliation(s)
- Mélaine A Kuenemann
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm , Paris 75013, France
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41
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Fluorescent biosensors for drug discovery new tools for old targets--screening for inhibitors of cyclin-dependent kinases. Eur J Med Chem 2014; 88:74-88. [PMID: 25314935 DOI: 10.1016/j.ejmech.2014.10.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2014] [Revised: 09/29/2014] [Accepted: 10/01/2014] [Indexed: 12/12/2022]
Abstract
Cyclin-dependent kinases play central roles in regulation of cell cycle progression, transcriptional regulation and other major biological processes such as neuronal differentiation and metabolism. These kinases are hyperactivated in most human cancers and constitute attractive pharmacological targets. A large number of ATP-competitive inhibitors of CDKs have been identified from natural substances, in high throughput screening assays, or through structure-guided approaches. Alternative strategies have been explored to target essential protein/protein interfaces and screen for allosteric inhibitors that trap inactive intermediates or prevent conformational activation. However this remains a major challenge given the highly conserved structural features of these kinases, and calls for new and alternative screening technologies. Fluorescent biosensors constitute powerful tools for the detection of biomolecules in complex biological samples, and are well suited to study dynamic processes and highlight molecular alterations associated with pathological disorders. They further constitute sensitive and selective tools which can be readily implemented to high throughput and high content screens in drug discovery programmes. Our group has developed fluorescent biosensors to probe cyclin-dependent kinases and gain insight into their molecular behaviour in vitro and in living cells. These tools provide a means of monitoring subtle alterations in the abundance and activity of CDK/Cyclins and can respond to compounds that interfere with the conformational dynamics of these kinases. In this review we discuss the different strategies which have been devised to target CDK/Cyclins, and describe the implementation of our CDK/Cyclin biosensors to develop HTS/HCS assays in view of identifying new classes of inhibitors for cancer therapeutics.
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42
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Ma Y, Nagamune T, Kawahara M. Split focal adhesion kinase for probing protein–protein interactions. Biochem Eng J 2014. [DOI: 10.1016/j.bej.2014.06.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Villoutreix BO, Kuenemann MA, Poyet JL, Bruzzoni-Giovanelli H, Labbé C, Lagorce D, Sperandio O, Miteva MA. Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology. Mol Inform 2014; 33:414-437. [PMID: 25254076 PMCID: PMC4160817 DOI: 10.1002/minf.201400040] [Citation(s) in RCA: 84] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Accepted: 04/21/2014] [Indexed: 12/13/2022]
Abstract
[Formula: see text] Fundamental processes in living cells are largely controlled by macromolecular interactions and among them, protein-protein interactions (PPIs) have a critical role while their dysregulations can contribute to the pathogenesis of numerous diseases. Although PPIs were considered as attractive pharmaceutical targets already some years ago, they have been thus far largely unexploited for therapeutic interventions with low molecular weight compounds. Several limiting factors, from technological hurdles to conceptual barriers, are known, which, taken together, explain why research in this area has been relatively slow. However, this last decade, the scientific community has challenged the dogma and became more enthusiastic about the modulation of PPIs with small drug-like molecules. In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www.vls3d.com). We first introduce the field of protein-protein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators.
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Affiliation(s)
- Bruno O Villoutreix
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
- CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse59000 Lille, France
| | - Melaine A Kuenemann
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
| | - Jean-Luc Poyet
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
- IUH, Hôpital Saint-LouisParis, France
- CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse59000 Lille, France
| | - Heriberto Bruzzoni-Giovanelli
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
- CIC, Clinical investigation center, Hôpital Saint-LouisParis, France
| | - Céline Labbé
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
| | - David Lagorce
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
| | - Olivier Sperandio
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
- CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse59000 Lille, France
| | - Maria A Miteva
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
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Mathieu AL, Sperandio O, Pottiez V, Balzarin S, Herlédan A, Elkaïm JO, Fogeron ML, Piveteau C, Dassonneville S, Deprez B, Villoutreix BO, Bonnefoy N, Leroux F. Identification of Small Inhibitory Molecules Targeting the Bfl-1 Anti-Apoptotic Protein That Alleviates Resistance to ABT-737. ACTA ACUST UNITED AC 2014; 19:1035-46. [PMID: 24809353 DOI: 10.1177/1087057114534070] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2014] [Accepted: 04/10/2014] [Indexed: 11/15/2022]
Abstract
One approach currently being developed in anticancer drug discovery is to search for small compounds capable of occupying and blocking the hydrophobic pocket of anti-apoptotic Bcl-2 family members necessary for interacting with pro-apoptotic proteins. Such an approach led to the discovery of several compounds, such as ABT-737 (which interacts with Bcl-2, Bcl-xl, and Bcl-w) or the latest one, ABT-199, that selectively targets Bcl-2 protein. The efficacy of those compounds is, however, limited by the expression of two other anti-apoptotic Bcl-2 members, Mcl-1 and Bfl-1. Based on the role of Bfl-1 in cancer, especially in chemoresistance associated with its overexpression in B-cell malignancies, we searched for modulators of protein-protein interaction through a high-throughput screening of a designed chemical library with relaxed drug-like properties to identify small molecules targeting Bfl-1 anti-apoptotic protein. We found two compounds that display electrophilic functions, interact with Bfl-1, inhibit Bfl-1 protective activity, and promote cell death of malignant B cells. Of particular interest, we observed a synergistic effect of those compounds with ABT-737 in Bfl-1 overexpressing lymphoma cell lines. Our results provide the basis for the development of Bfl-1 specific antagonists for antitumor therapies.
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Affiliation(s)
- Anne-Laure Mathieu
- CIRI, Université de Lyon, France; INSERM, U1111, Ecole Normale Supérieure de Lyon, Lyon, France
| | - Olivier Sperandio
- CDithem. Faculté de Pharmacie, Lille, France; www.CDithem.com Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques in silico, France INSERM UMR-S 973, Paris Cedex 13, France
| | - Virginie Pottiez
- CDithem. Faculté de Pharmacie, Lille, France; www.CDithem.com INSERM U761, Biostructures and Drug Discovery, Université de Lille, Institut Pasteur de Lille, IFR 142, PRIM, Lille, France
| | - Sophie Balzarin
- IRCM, Institut de Recherche en Cancérologie de Montpellier; INSERM, U896; Université Montpellier1; Institut Régional du Cancer de Montpellier, Montpellier, France
| | - Adrien Herlédan
- CDithem. Faculté de Pharmacie, Lille, France; www.CDithem.com INSERM U761, Biostructures and Drug Discovery, Université de Lille, Institut Pasteur de Lille, IFR 142, PRIM, Lille, France
| | - Judith O Elkaïm
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques in silico, France INSERM UMR-S 973, Paris Cedex 13, France
| | - Marie-Laure Fogeron
- Université Lyon 1, Univ Lyon, CNRS, UMR5086, Bases Moléculaires et Structurales des Systèmes Infectieux, France
| | - Catherine Piveteau
- CDithem. Faculté de Pharmacie, Lille, France; www.CDithem.com INSERM U761, Biostructures and Drug Discovery, Université de Lille, Institut Pasteur de Lille, IFR 142, PRIM, Lille, France
| | - Sandrine Dassonneville
- CDithem. Faculté de Pharmacie, Lille, France; www.CDithem.com INSERM U761, Biostructures and Drug Discovery, Université de Lille, Institut Pasteur de Lille, IFR 142, PRIM, Lille, France
| | - Benoit Deprez
- CDithem. Faculté de Pharmacie, Lille, France; www.CDithem.com INSERM U761, Biostructures and Drug Discovery, Université de Lille, Institut Pasteur de Lille, IFR 142, PRIM, Lille, France
| | - Bruno O Villoutreix
- CDithem. Faculté de Pharmacie, Lille, France; www.CDithem.com Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques in silico, France INSERM UMR-S 973, Paris Cedex 13, France
| | - Nathalie Bonnefoy
- CIRI, Université de Lyon, France; INSERM, U1111, Ecole Normale Supérieure de Lyon, Lyon, France IRCM, Institut de Recherche en Cancérologie de Montpellier; INSERM, U896; Université Montpellier1; Institut Régional du Cancer de Montpellier, Montpellier, France
| | - Florence Leroux
- CDithem. Faculté de Pharmacie, Lille, France; www.CDithem.com INSERM U761, Biostructures and Drug Discovery, Université de Lille, Institut Pasteur de Lille, IFR 142, PRIM, Lille, France
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Focused chemical libraries--design and enrichment: an example of protein-protein interaction chemical space. Future Med Chem 2014; 6:1291-307. [PMID: 24773599 DOI: 10.4155/fmc.14.57] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
One of the many obstacles in the development of new drugs lies in the limited number of therapeutic targets and in the quality of screening collections of compounds. In this review, we present general strategies for building target-focused chemical libraries with a particular emphasis on protein-protein interactions (PPIs). We describe the chemical spaces spanned by nine commercially available PPI-focused libraries and compare them to our 2P2I3D academic library, dedicated to orthosteric PPI modulators. We show that although PPI-focused libraries have been designed using different strategies, they share common subspaces. PPI inhibitors are larger and more hydrophobic than standard drugs; however, an effort has been made to improve the drug-likeness of focused chemical libraries dedicated to this challenging class of targets.
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Nero TL, Morton CJ, Holien JK, Wielens J, Parker MW. Oncogenic protein interfaces: small molecules, big challenges. Nat Rev Cancer 2014; 14:248-62. [PMID: 24622521 DOI: 10.1038/nrc3690] [Citation(s) in RCA: 206] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Historically, targeting protein-protein interactions with small molecules was not thought possible because the corresponding interfaces were considered mostly flat and featureless and therefore 'undruggable'. Instead, such interactions were targeted with larger molecules, such as peptides and antibodies. However, the past decade has seen encouraging breakthroughs through the refinement of existing techniques and the development of new ones, together with the identification and exploitation of unexpected aspects of protein-protein interaction surfaces. In this Review, we describe some of the latest techniques to discover modulators of protein-protein interactions and how current drug discovery approaches have been adapted to successfully target these interfaces.
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Affiliation(s)
- Tracy L Nero
- Australian Cancer Research Foundation Rational Drug Discovery Centre and Biota Structural Biology Laboratory, St. Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, Victoria 3065, Australia
| | - Craig J Morton
- Australian Cancer Research Foundation Rational Drug Discovery Centre and Biota Structural Biology Laboratory, St. Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, Victoria 3065, Australia
| | - Jessica K Holien
- Australian Cancer Research Foundation Rational Drug Discovery Centre and Biota Structural Biology Laboratory, St. Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, Victoria 3065, Australia
| | - Jerome Wielens
- 1] Australian Cancer Research Foundation Rational Drug Discovery Centre and Biota Structural Biology Laboratory, St. Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, Victoria 3065, Australia. [2] Department of Medicine, University of Melbourne, 41 Victoria Parade, Fitzroy, Victoria 3065, Australia
| | - Michael W Parker
- 1] Australian Cancer Research Foundation Rational Drug Discovery Centre and Biota Structural Biology Laboratory, St. Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, Victoria 3065, Australia. [2] Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3052, Australia
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Kastritis PL, Rodrigues JPGLM, Bonvin AMJJ. HADDOCK(2P2I): a biophysical model for predicting the binding affinity of protein-protein interaction inhibitors. J Chem Inf Model 2014; 54:826-36. [PMID: 24521147 PMCID: PMC3966529 DOI: 10.1021/ci4005332] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The HADDOCK score, a scoring function for both protein-protein and protein-nucleic acid modeling, has been successful in selecting near-native docking poses in a variety of cases, including those of the CAPRI blind prediction experiment. However, it has yet to be optimized for small molecules, and in particular inhibitors of protein-protein interactions, that constitute an "unmined gold reserve" for drug design ventures. We describe here HADDOCK(2P2I), a biophysical model capable of predicting the binding affinity of protein-protein complex inhibitors close to experimental error (~2-fold larger). The algorithm was trained and 4-fold cross-validated against experimental data for 27 inhibitors targeting 7 protein-protein complexes of various functions and tested on an independent set of 24 different inhibitors for which K(d)/IC50 data are available. In addition, two popular ligand topology generation and parametrization methods (ACPYPE and PRODRG) were assessed. The resulting HADDOCK(2P2I) model, derived from the original HADDOCK score, provides insights into inhibition determinants: while the role of electrostatics and desolvation energies is case-dependent, the interface area plays a more critical role compared to protein-protein interactions.
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Affiliation(s)
- Panagiotis L Kastritis
- Bijvoet Center for Biomolecular Research, Faculty of Science/Chemistry, Utrecht University , Utrecht, 3584CH, the Netherlands
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Hamon V, Bourgeas R, Ducrot P, Theret I, Xuereb L, Basse MJ, Brunel JM, Combes S, Morelli X, Roche P. 2P2I HUNTER: a tool for filtering orthosteric protein-protein interaction modulators via a dedicated support vector machine. J R Soc Interface 2013; 11:20130860. [PMID: 24196694 DOI: 10.1098/rsif.2013.0860] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Over the last 10 years, protein-protein interactions (PPIs) have shown increasing potential as new therapeutic targets. As a consequence, PPIs are today the most screened target class in high-throughput screening (HTS). The development of broad chemical libraries dedicated to these particular targets is essential; however, the chemical space associated with this 'high-hanging fruit' is still under debate. Here, we analyse the properties of 40 non-redundant small molecules present in the 2P2I database (http://2p2idb.cnrs-mrs.fr/) to define a general profile of orthosteric inhibitors and propose an original protocol to filter general screening libraries using a support vector machine (SVM) with 11 standard Dragon molecular descriptors. The filtering protocol has been validated using external datasets from PubChem BioAssay and results from in-house screening campaigns. This external blind validation demonstrated the ability of the SVM model to reduce the size of the filtered chemical library by eliminating up to 96% of the compounds as well as enhancing the proportion of active compounds by up to a factor of 8. We believe that the resulting chemical space identified in this paper will provide the scientific community with a concrete support to search for PPI inhibitors during HTS campaigns.
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Affiliation(s)
- Véronique Hamon
- Laboratory of integrative Structural and Chemical Biology (iSCB), Centre de Recherche en Cancérologie de Marseille (CRCM); CNRS UMR 7258, INSERM U 1068, Institut Paoli-Calmettes; and Aix-Marseille Universités, , Marseille 13009, France
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49
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Coarse-grain modelling of protein-protein interactions. Curr Opin Struct Biol 2013; 23:878-86. [PMID: 24172141 DOI: 10.1016/j.sbi.2013.09.004] [Citation(s) in RCA: 103] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2013] [Revised: 08/29/2013] [Accepted: 09/17/2013] [Indexed: 11/24/2022]
Abstract
Here, we review recent advances towards the modelling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behaviour. PPI models of soluble proteins and membrane proteins are separately described, but we note the parallel development that is present in both research fields with three important themes: firstly, combining CG modelling with knowledge-based approaches to predict and refine protein-protein complexes; secondly, using physics-based CG models for de novo prediction of protein-protein complexes; and thirdly modelling of large scale protein aggregates.
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50
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Electrostatic similarities between protein and small molecule ligands facilitate the design of protein-protein interaction inhibitors. PLoS One 2013; 8:e75762. [PMID: 24130741 PMCID: PMC3794991 DOI: 10.1371/journal.pone.0075762] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2013] [Accepted: 08/19/2013] [Indexed: 12/26/2022] Open
Abstract
One of the underlying principles in drug discovery is that a biologically active compound is complimentary in shape and molecular recognition features to its receptor. This principle infers that molecules binding to the same receptor may share some common features. Here, we have investigated whether the electrostatic similarity can be used for the discovery of small molecule protein-protein interaction inhibitors (SMPPIIs). We have developed a method that can be used to evaluate the similarity of electrostatic potentials between small molecules and known protein ligands. This method was implemented in a software called EleKit. Analyses of all available (at the time of research) SMPPII structures indicate that SMPPIIs bear some similarities of electrostatic potential with the ligand proteins of the same receptor. This is especially true for the more polar SMPPIIs. Retrospective analysis of several successful SMPPIIs has shown the applicability of EleKit in the design of new SMPPIIs.
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