1
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Ayoub N, Gedeon A, Munier-Lehmann H. A journey into the regulatory secrets of the de novo purine nucleotide biosynthesis. Front Pharmacol 2024; 15:1329011. [PMID: 38444943 PMCID: PMC10912719 DOI: 10.3389/fphar.2024.1329011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 02/01/2024] [Indexed: 03/07/2024] Open
Abstract
De novo purine nucleotide biosynthesis (DNPNB) consists of sequential reactions that are majorly conserved in living organisms. Several regulation events take place to maintain physiological concentrations of adenylate and guanylate nucleotides in cells and to fine-tune the production of purine nucleotides in response to changing cellular demands. Recent years have seen a renewed interest in the DNPNB enzymes, with some being highlighted as promising targets for therapeutic molecules. Herein, a review of two newly revealed modes of regulation of the DNPNB pathway has been carried out: i) the unprecedent allosteric regulation of one of the limiting enzymes of the pathway named inosine 5'-monophosphate dehydrogenase (IMPDH), and ii) the supramolecular assembly of DNPNB enzymes. Moreover, recent advances that revealed the therapeutic potential of DNPNB enzymes in bacteria could open the road for the pharmacological development of novel antibiotics.
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Affiliation(s)
- Nour Ayoub
- Institut Pasteur, Université Paris Cité, INSERM UMRS-1124, Paris, France
| | - Antoine Gedeon
- Sorbonne Université, École Normale Supérieure, Université PSL, CNRS UMR7203, Laboratoire des Biomolécules, LBM, Paris, France
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2
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Olmedo DA, Durant-Archibold AA, López-Pérez JL, Medina-Franco JL. Design and Diversity Analysis of Chemical Libraries in Drug Discovery. Comb Chem High Throughput Screen 2024; 27:502-515. [PMID: 37409545 DOI: 10.2174/1386207326666230705150110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/30/2023] [Accepted: 05/30/2023] [Indexed: 07/07/2023]
Abstract
Chemical libraries and compound data sets are among the main inputs to start the drug discovery process at universities, research institutes, and the pharmaceutical industry. The approach used in the design of compound libraries, the chemical information they possess, and the representation of structures, play a fundamental role in the development of studies: chemoinformatics, food informatics, in silico pharmacokinetics, computational toxicology, bioinformatics, and molecular modeling to generate computational hits that will continue the optimization process of drug candidates. The prospects for growth in drug discovery and development processes in chemical, biotechnological, and pharmaceutical companies began a few years ago by integrating computational tools with artificial intelligence methodologies. It is anticipated that it will increase the number of drugs approved by regulatory agencies shortly.
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Affiliation(s)
- Dionisio A Olmedo
- Centro de Investigaciones Farmacognósticas de la Flora Panameña (CIFLORPAN), Facultad de Farmacia, Universidad de Panamá, Ciudad de Panamá, Apartado, 0824-00178, Panamá
- Sistema Nacional de Investigación (SNI), Secretaria Nacional de Ciencia, Tecnología e Innovación (SENACYT), Ciudad del Saber, Clayton, Panamá
| | - Armando A Durant-Archibold
- Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Apartado, 0843-01103, Panamá
- Departamento de Bioquímica, Facultad de Ciencias Naturales, Exactas y Tecnología, Universidad de Panamá, Ciudad de Panamá, Panamá
| | - José Luis López-Pérez
- CESIFAR, Departamento de Farmacología, Facultad de Medicina, Universidad de Panamá, Ciudad de Panamá, Panamá
- Departamento de Ciencias Farmacéuticas, Facultad de Farmacia, Universidad de Salamanca, Avda. Campo Charro s/n, 37071 Salamanca, España
| | - José Luis Medina-Franco
- DIFACQUIM Grupo de Investigación, Departamento de Farmacia, Escuela de Química, Universidad Nacional Autónoma de México, Ciudad de México, Apartado, 04510, México
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3
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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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4
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Truong J, George A, Holien JK. Analysis of physicochemical properties of protein-protein interaction modulators suggests stronger alignment with the "rule of five". RSC Med Chem 2021; 12:1731-1749. [PMID: 34778774 DOI: 10.1039/d1md00213a] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 07/27/2021] [Indexed: 11/21/2022] Open
Abstract
Despite the important roles played by protein-protein interactions (PPIs) in disease, they have been long considered as 'undruggable'. However, recent advances have suggested that PPIs are druggable but may not follow conventional rules of 'drug ability'. Here we explore which physicochemical parameters are essential for a PPI modulator to be a clinical drug by analysing the physicochemical properties of small-molecule PPI modulators in the market, in clinical trials, and published. Our analysis reveals that those compounds currently on the market have a larger range of values for most of the physicochemical parameters, whereas those in clinical trials fit much more stringently to standard drug-like parameters. This observation was particularly true for molecular weight, clog P and topological polar surface area, where aside from a few outliers, most of the compounds in clinical trials fit within standard drug-like parameters. This implies that the newer PPI modulators are more drug-like than those currently on the market, suggesting that designing new PPI-specific screening libraries should remain within standard drug-like parameters in order to obtain a clinical candidate. Taken together, our analysis has important implications for designing future drug discovery campaigns aimed at targeting PPIs.
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Affiliation(s)
- Jia Truong
- STEM College, RMIT University Vic Australia
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5
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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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6
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Clemons PA, Bittker JA, Wagner FF, Hands A, Dančík V, Schreiber SL, Choudhary A, Wagner BK. The Use of Informer Sets in Screening: Perspectives on an Efficient Strategy to Identify New Probes. SLAS DISCOVERY 2021; 26:855-861. [PMID: 34130532 DOI: 10.1177/24725552211019410] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Small-molecule discovery typically involves large-scale screening campaigns, spanning multiple compound collections. However, such activities can be cost- or time-prohibitive, especially when using complex assay systems, limiting the number of compounds tested. Further, low hit rates can make the process inefficient. Sparse coverage of chemical structure or biological activity space can lead to limited success in a primary screen and represents a missed opportunity by virtue of selecting the "wrong" compounds to test. Thus, the choice of screening collections becomes of paramount importance. In this perspective, we discuss the utility of generating "informer sets" for small-molecule discovery, and how this strategy can be leveraged to prioritize probe candidates. While many researchers may assume that informer sets are focused on particular targets (e.g., kinases) or processes (e.g., autophagy), efforts to assemble informer sets based on historical bioactivity or successful human exposure (e.g., repurposing collections) have shown promise as well. Another method for generating informer sets is based on chemical structure, particularly when the compounds have unknown activities and targets. We describe our efforts to screen an informer set representing a collection of 100,000 small molecules synthesized through diversity-oriented synthesis (DOS). This process enables researchers to identify activity early and more extensively screen only a few chemical scaffolds, rather than the entire collection. This elegant and economic outcome is a goal of the informer set approach. Here, we aim not only to shed light on this process, but also to promote the use of informer sets more widely in small-molecule discovery projects.
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Affiliation(s)
- Paul A Clemons
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | - Joshua A Bittker
- Center for the Development of Therapeutics, Broad Institute, Cambridge, MA, USA.,Vertex Pharmaceuticals, Boston, MA, USA
| | - Florence F Wagner
- Center for the Development of Therapeutics, Broad Institute, Cambridge, MA, USA
| | - Allison Hands
- Center for the Development of Therapeutics, Broad Institute, Cambridge, MA, USA
| | - Vlado Dančík
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | - Stuart L Schreiber
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | - Amit Choudhary
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
| | - Bridget K Wagner
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA, USA
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7
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Pitard I, Monet D, Goossens PL, Blondel A, Malliavin TE. Analyzing In Silico the Relationship Between the Activation of the Edema Factor and Its Interaction With Calmodulin. Front Mol Biosci 2020; 7:586544. [PMID: 33344505 PMCID: PMC7746812 DOI: 10.3389/fmolb.2020.586544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 11/02/2020] [Indexed: 11/25/2022] Open
Abstract
Molecular dynamics (MD) simulations have been recorded on the complex between the edema factor (EF) of Bacilllus anthracis and calmodulin (CaM), starting from a structure with the orthosteric inhibitor adefovir bound in the EF catalytic site. The starting structure has been destabilized by alternately suppressing different co-factors, such as adefovir ligand or ions, revealing several long-distance correlations between the conformation of CaM, the geometry of the CaM/EF interface, the enzymatic site and the overall organization of the complex. An allosteric communication between CaM/EF interface and the EF catalytic site, highlighted by these correlations, was confirmed by several bioinformatics approaches from the literature. A network of hydrogen bonds and stacking interactions extending from the helix V of of CaM, and the residues of the switches A, B and C, and connecting to catalytic site residues, is a plausible candidate for the mediation of allosteric communication. The greatest variability in volume between the different MD conditions was also found for cavities present at the EF/CaM interface and in the EF catalytic site. The similarity between the predictions from literature and the volume variability might introduce the volume variability as new descriptor of allostery.
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Affiliation(s)
- Irène Pitard
- Unité de Bioinformatique Structurale, Institut Pasteur and CNRS UMR 3528, Paris, France.,Center de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur and CNRS USR 3756, Paris, France.,Ecole Doctorale Université Paris Sorbonne, Paris, France
| | - Damien Monet
- Unité de Bioinformatique Structurale, Institut Pasteur and CNRS UMR 3528, Paris, France.,Center de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur and CNRS USR 3756, Paris, France.,Ecole Doctorale Université Paris Sorbonne, Paris, France
| | | | - Arnaud Blondel
- Unité de Bioinformatique Structurale, Institut Pasteur and CNRS UMR 3528, Paris, France.,Center de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur and CNRS USR 3756, Paris, France
| | - Thérèse E Malliavin
- Unité de Bioinformatique Structurale, Institut Pasteur and CNRS UMR 3528, Paris, France.,Center de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur and CNRS USR 3756, Paris, France
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8
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Vázquez J, López M, Gibert E, Herrero E, Luque FJ. Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches. Molecules 2020; 25:E4723. [PMID: 33076254 PMCID: PMC7587536 DOI: 10.3390/molecules25204723] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 10/06/2020] [Accepted: 10/11/2020] [Indexed: 12/20/2022] Open
Abstract
Virtual screening (VS) is an outstanding cornerstone in the drug discovery pipeline. A variety of computational approaches, which are generally classified as ligand-based (LB) and structure-based (SB) techniques, exploit key structural and physicochemical properties of ligands and targets to enable the screening of virtual libraries in the search of active compounds. Though LB and SB methods have found widespread application in the discovery of novel drug-like candidates, their complementary natures have stimulated continued efforts toward the development of hybrid strategies that combine LB and SB techniques, integrating them in a holistic computational framework that exploits the available information of both ligand and target to enhance the success of drug discovery projects. In this review, we analyze the main strategies and concepts that have emerged in the last years for defining hybrid LB + SB computational schemes in VS studies. Particularly, attention is focused on the combination of molecular similarity and docking, illustrating them with selected applications taken from the literature.
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Affiliation(s)
- Javier Vázquez
- Pharmacelera, Plaça Pau Vila, 1, Sector C 2a, Edificio Palau de Mar, 08039 Barcelona, Spain;
- Department of Nutrition, Food Science and Gastronomy, Faculty of Pharmacy and Food Sciences, Institute of Biomedicine (IBUB), and Institute of Theoretical and Computational Chemistry (IQTC-UB), University of Barcelona, Av. Prat de la Riba 171, E-08921 Santa Coloma de Gramanet, Spain
| | - Manel López
- AB Science, Parc Scientifique de Luminy, Zone Luminy Enterprise, Case 922, 163 Av. de Luminy, 13288 Marseille, France;
| | - Enric Gibert
- Pharmacelera, Plaça Pau Vila, 1, Sector C 2a, Edificio Palau de Mar, 08039 Barcelona, Spain;
| | - Enric Herrero
- Pharmacelera, Plaça Pau Vila, 1, Sector C 2a, Edificio Palau de Mar, 08039 Barcelona, Spain;
| | - F. Javier Luque
- Department of Nutrition, Food Science and Gastronomy, Faculty of Pharmacy and Food Sciences, Institute of Biomedicine (IBUB), and Institute of Theoretical and Computational Chemistry (IQTC-UB), University of Barcelona, Av. Prat de la Riba 171, E-08921 Santa Coloma de Gramanet, Spain
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9
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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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10
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Swaminathan S, Kumar V, Kaul R. Need for alternatives to animals in experimentation: An Indian perspective. Indian J Med Res 2020; 149:584-592. [PMID: 31417025 PMCID: PMC6702685 DOI: 10.4103/ijmr.ijmr_2047_17] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Soumya Swaminathan
- Former Director-General, Indian Council of Medical Research (ICMR), Ansari Nagar, New Delhi 110 029, India
| | - Vijay Kumar
- Division of Basic Medical Sciences, ICMR, Ansari Nagar, New Delhi 110 029, India
| | - Rajni Kaul
- Division of Basic Medical Sciences, ICMR, Ansari Nagar, New Delhi 110 029, India
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11
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A Free Web-Based Protocol to Assist Structure-Based Virtual Screening Experiments. Int J Mol Sci 2019; 20:ijms20184648. [PMID: 31546814 PMCID: PMC6769597 DOI: 10.3390/ijms20184648] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 09/03/2019] [Accepted: 09/17/2019] [Indexed: 11/22/2022] Open
Abstract
Chemical biology and drug discovery are complex and costly processes. In silico screening approaches play a key role in the identification and optimization of original bioactive molecules and increase the performance of modern chemical biology and drug discovery endeavors. Here, we describe a free web-based protocol dedicated to small-molecule virtual screening that includes three major steps: ADME-Tox filtering (via the web service FAF-Drugs4), docking-based virtual screening (via the web service MTiOpenScreen), and molecular mechanics optimization (via the web service AMMOS2 [Automatic Molecular Mechanics Optimization for in silico Screening]). The online tools FAF-Drugs4, MTiOpenScreen, and AMMOS2 are implemented in the freely accessible RPBS (Ressource Parisienne en Bioinformatique Structurale) platform. The proposed protocol allows users to screen thousands of small molecules and to download the top 1500 docked molecules that can be further processed online. Users can then decide to purchase a small list of compounds for in vitro validation. To demonstrate the potential of this online-based protocol, we performed virtual screening experiments of 4574 approved drugs against three cancer targets. The results were analyzed in the light of published drugs that have already been repositioned on these targets. We show that our protocol is able to identify active drugs within the top-ranked compounds. The web-based protocol is user-friendly and can successfully guide the identification of new promising molecules for chemical biology and drug discovery purposes.
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12
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Protein structure and computational drug discovery. Biochem Soc Trans 2018; 46:1367-1379. [DOI: 10.1042/bst20180202] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 08/08/2018] [Accepted: 08/13/2018] [Indexed: 12/12/2022]
Abstract
The first protein structures revealed a complex web of weak interactions stabilising the three-dimensional shape of the molecule. Small molecule ligands were then found to exploit these same weak binding events to modulate protein function or act as substrates in enzymatic reactions. As the understanding of ligand–protein binding grew, it became possible to firstly predict how and where a particular small molecule might interact with a protein, and then to identify putative ligands for a specific protein site. Computer-aided drug discovery, based on the structure of target proteins, is now a well-established technique that has produced several marketed drugs. We present here an overview of the various methodologies being used for structure-based computer-aided drug discovery and comment on possible future developments in the field.
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13
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Perricone U, Gulotta MR, Lombino J, Parrino B, Cascioferro S, Diana P, Cirrincione G, Padova A. An overview of recent molecular dynamics applications as medicinal chemistry tools for the undruggable site challenge. MEDCHEMCOMM 2018; 9:920-936. [PMID: 30108981 PMCID: PMC6072422 DOI: 10.1039/c8md00166a] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Accepted: 04/19/2018] [Indexed: 12/14/2022]
Abstract
Molecular dynamics (MD) has become increasingly popular due to the development of hardware and software solutions and the improvement in algorithms, which allowed researchers to scale up calculations in order to speed them up. MD simulations are usually used to address protein folding issues or protein-ligand complex stability through energy profile analysis over time. In recent years, the development of new tools able to deeply explore a potential energy surface (PES) has allowed researchers to focus on the dynamic nature of the binding recognition process and binding-induced protein conformational changes. Moreover, modern approaches have been demonstrated to be effective and reliable in calculating some kinetic and thermodynamic parameters behind the host-guest recognition process. Starting from all of these considerations, several efforts have been made in order to integrate MD within the virtual screening process in drug discovery. Knowledge retrieved from MD can, in fact, be exploited as a starting point to build pharmacophores or docking constraints in the early stage of the screening campaign as well as to define key features, in order to unravel hidden binding modes and help the optimisation of the molecular structure of a lead compound. Based on these outcomes, researchers are nowadays using MD as an invaluable tool to discover and target previously considered undruggable binding sites, including protein-protein interactions and allosteric sites on a protein surface. As a matter of fact, the use of MD has been recognised as vital to the discovery of selective protein-protein interaction modulators. The use of a dynamic overview on how the host-guest recognition occurs and of the relative conformational modifications induced allows researchers to optimise small molecules and small peptides capable of tightly interacting within the cleft between two proteins. In this review, we aim to present the most recent applications of MD as an integrated tool to be used in the rational design of small molecules or small peptides able to modulate undruggable targets, such as allosteric sites and protein-protein interactions.
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Affiliation(s)
- Ugo Perricone
- Computational and Medicinal Chemistry Group , Fondazione Ri.MED , Via Bandiera 11 , 90133 Palermo , Italy .
| | - Maria Rita Gulotta
- Computational and Medicinal Chemistry Group , Fondazione Ri.MED , Via Bandiera 11 , 90133 Palermo , Italy .
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Jessica Lombino
- Computational and Medicinal Chemistry Group , Fondazione Ri.MED , Via Bandiera 11 , 90133 Palermo , Italy .
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Barbara Parrino
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Stella Cascioferro
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Patrizia Diana
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Girolamo Cirrincione
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Alessandro Padova
- Computational and Medicinal Chemistry Group , Fondazione Ri.MED , Via Bandiera 11 , 90133 Palermo , Italy .
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Bojadzic D, Buchwald P. Toward Small-Molecule Inhibition of Protein-Protein Interactions: General Aspects and Recent Progress in Targeting Costimulatory and Coinhibitory (Immune Checkpoint) Interactions. Curr Top Med Chem 2018; 18:674-699. [PMID: 29848279 PMCID: PMC6067980 DOI: 10.2174/1568026618666180531092503] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 02/27/2018] [Accepted: 05/11/2018] [Indexed: 02/06/2023]
Abstract
Protein-Protein Interactions (PPIs) that are part of the costimulatory and coinhibitory (immune checkpoint) signaling are critical for adequate T cell response and are important therapeutic targets for immunomodulation. Biologics targeting them have already achieved considerable clinical success in the treatment of autoimmune diseases or transplant recipients (e.g., abatacept, belatacept, and belimumab) as well as cancer (e.g., ipilimumab, nivolumab, pembrolizumab, atezolizumab, durvalumab, and avelumab). In view of such progress, there have been only relatively limited efforts toward developing small-molecule PPI inhibitors (SMPPIIs) targeting these cosignaling interactions, possibly because they, as all other PPIs, are difficult to target by small molecules and were not considered druggable. Nevertheless, substantial progress has been achieved during the last decade. SMPPIIs proving the feasibility of such approaches have been identified through various strategies for a number of cosignaling interactions including CD40-CD40L, OX40-OX40L, BAFFR-BAFF, CD80-CD28, and PD-1-PD-L1s. Here, after an overview of the general aspects and challenges of SMPPII-focused drug discovery, we review them briefly together with relevant structural, immune-signaling, physicochemical, and medicinal chemistry aspects. While so far only a few of these SMPPIIs have shown activity in animal models (DRI-C21045 for CD40-D40L, KR33426 for BAFFR-BAFF) or reached clinical development (RhuDex for CD80-CD28, CA-170 for PD-1-PD-L1), there is proof-of-principle evidence for the feasibility of such approaches in immunomodulation. They can result in products that are easier to develop/ manufacture and are less likely to be immunogenic or encounter postmarket safety events than corresponding biologics, and, contrary to them, can even become orally bioavailable.
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Affiliation(s)
- Damir Bojadzic
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Peter Buchwald
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, Florida, USA
- Department of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, Florida, USA
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15
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Brossard D, Retailleau P, Dumontet V, Breton P, Desrat S, Roussi F. Fast & easy preparation of 3D scaffolds from methyl benzoate by a diversity oriented synthesis strategy based on Diels-Alder and ene-reactions. Org Biomol Chem 2017. [PMID: 28639654 DOI: 10.1039/c7ob01236e] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Thermic dimerization of methyl 1,3-cyclohexadiene 2-carboxylate gave original 3D-shape compounds by Diels-Alder cycloaddition and original [6 + 4]-ene reaction. Further selective modifications on an endo [4 + 2] cycloadduct via a diversity oriented synthesis (DOS) strategy quickly led to the preparation of a small library of original 3D scaffolds, providing access to a larger and unexplored chemical space for drug discovery processes.
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Affiliation(s)
- Dominique Brossard
- Institut de Chimie des Substances Naturelles, CNRS UPR 2301, Université Paris-Saclay, 1 avenue de la terrasse, 91198 Gif-sur-Yvette, France.
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16
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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: 89] [Impact Index Per Article: 12.7] [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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17
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Milhas S, Raux B, Betzi S, Derviaux C, Roche P, Restouin A, Basse MJ, Rebuffet E, Lugari A, Badol M, Kashyap R, Lissitzky JC, Eydoux C, Hamon V, Gourdel ME, Combes S, Zimmermann P, Aurrand-Lions M, Roux T, Rogers C, Müller S, Knapp S, Trinquet E, Collette Y, Guillemot JC, Morelli X. Protein-Protein Interaction Inhibition (2P2I)-Oriented Chemical Library Accelerates Hit Discovery. ACS Chem Biol 2016; 11:2140-8. [PMID: 27219844 DOI: 10.1021/acschembio.6b00286] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Protein-protein interactions (PPIs) represent an enormous source of opportunity for therapeutic intervention. We and others have recently pinpointed key rules that will help in identifying the next generation of innovative drugs to tackle this challenging class of targets within the next decade. We used these rules to design an oriented chemical library corresponding to a set of diverse "PPI-like" modulators with cores identified as privileged structures in therapeutics. In this work, we purchased the resulting 1664 structurally diverse compounds and evaluated them on a series of representative protein-protein interfaces with distinct "druggability" potential using homogeneous time-resolved fluorescence (HTRF) technology. For certain PPI classes, analysis of the hit rates revealed up to 100 enrichment factors compared with nonoriented chemical libraries. This observation correlates with the predicted "druggability" of the targets. A specific focus on selectivity profiles, the three-dimensional (3D) molecular modes of action resolved by X-ray crystallography, and the biological activities of identified hits targeting the well-defined "druggable" bromodomains of the bromo and extraterminal (BET) family are presented as a proof-of-concept. Overall, our present study illustrates the potency of machine learning-based oriented chemical libraries to accelerate the identification of hits targeting PPIs. A generalization of this method to a larger set of compounds will accelerate the discovery of original and potent probes for this challenging class of targets.
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Affiliation(s)
- Sabine Milhas
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
- CNRS, Aix-Marseille
Université, Screening Platform AD2P, AFMB UMR7257, 13288, Marseille, France
| | - Brigitt Raux
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Stéphane Betzi
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Carine Derviaux
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Philippe Roche
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Audrey Restouin
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Marie-Jeanne Basse
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Etienne Rebuffet
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Adrien Lugari
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Marion Badol
- Cisbio Bioassays, R&D, Parc Marcel Boiteux, BP 84175, 30200 Codolet, France
| | - Rudra Kashyap
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
- Department of Human Genetics, KU Leuven, B-3000 Leuven, Belgium
| | - Jean-Claude Lissitzky
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Cécilia Eydoux
- CNRS, Aix-Marseille
Université, Screening Platform AD2P, AFMB UMR7257, 13288, Marseille, France
| | - Véronique Hamon
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | | | - Sébastien Combes
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Pascale Zimmermann
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
- Department of Human Genetics, KU Leuven, B-3000 Leuven, Belgium
| | - Michel Aurrand-Lions
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Thomas Roux
- Cisbio Bioassays, R&D, Parc Marcel Boiteux, BP 84175, 30200 Codolet, France
| | - Catherine Rogers
- Target
Discovery Institute, University of Oxford, NDM Research Building, Roosevelt
Drive, Oxford OX3 7FZ, U.K
- Structural Genomics Consortium, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, U.K
| | - Susanne Müller
- Target
Discovery Institute, University of Oxford, NDM Research Building, Roosevelt
Drive, Oxford OX3 7FZ, U.K
- Structural Genomics Consortium, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, U.K
| | - Stefan Knapp
- Target
Discovery Institute, University of Oxford, NDM Research Building, Roosevelt
Drive, Oxford OX3 7FZ, U.K
- Structural Genomics Consortium, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, U.K
- Goethe-University, Institute
for Pharmaceutical Chemistry and Buchmann
Institute for Life Science, Campus Riedberg, Max-von Laue Str. 9, 60438 Frankfurt am Main, Germany
| | - Eric Trinquet
- Cisbio Bioassays, R&D, Parc Marcel Boiteux, BP 84175, 30200 Codolet, France
| | - Yves Collette
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
| | - Jean-Claude Guillemot
- CNRS, Aix-Marseille
Université, Screening Platform AD2P, AFMB UMR7257, 13288, Marseille, France
| | - Xavier Morelli
- CNRS, INSERM, Aix-Marseille Université, Institut Paoli-Calmettes, Centre de Recherche en Cancérologie de Marseille, CS30059, 13273 Marseille Cedex 9, France
- CNRS, Aix-Marseille
Université, Screening Platform AD2P, AFMB UMR7257, 13288, Marseille, France
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18
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Villoutreix B. Combining bioinformatics, chemoinformatics and experimental approaches to design chemical probes: Applications in the field of blood coagulation. ANNALES PHARMACEUTIQUES FRANÇAISES 2016; 74:253-66. [DOI: 10.1016/j.pharma.2016.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Revised: 03/21/2016] [Accepted: 03/21/2016] [Indexed: 11/08/2022]
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19
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20
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Basse MJ, Betzi S, Morelli X, Roche P. 2P2Idb v2: update of a structural database dedicated to orthosteric modulation of protein-protein interactions. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2016; 2016:baw007. [PMID: 26980515 PMCID: PMC4792518 DOI: 10.1093/database/baw007] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2015] [Accepted: 01/13/2016] [Indexed: 11/30/2022]
Abstract
2P2Idb is a hand-curated structural database dedicated to protein–protein interactions with known small molecule orthosteric modulators. It compiles the structural information related to orthosteric inhibitors and their target [i.e. related 3D structures available in the RCSB Protein Data Bank (PDB)] and provides links to other useful databases. 2P2Idb includes all interactions for which both the protein–protein and protein–inhibitor complexes have been structurally characterized. Since its first release in 2010, the database has grown constantly and the current version contains 27 protein–protein complexes and 274 protein–inhibitor complexes corresponding to 242 unique small molecule inhibitors which represent almost a 5-fold increase compared to the previous version. A number of new data have been added, including new protein–protein complexes, binding affinities, molecular descriptors, precalculated interface parameters and links to other webservers. A new query tool has been implemented to search for inhibitors within the database using standard molecular descriptors. A novel version of the 2P2I-inspector tool has been implemented to calculate a series of physical and chemical parameters of the protein interfaces. Several geometrical parameters including planarity, eccentricity and circularity have been added as well as customizable distance cutoffs. This tool has also been extended to protein–ligand interfaces. The 2P2I database thus represents a wealth of structural source of information for scientists interested in the properties of protein–protein interactions and the design of protein–protein interaction modulators. Database URL:http://2p2idb.cnrs-mrs.fr
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Affiliation(s)
- Marie-Jeanne Basse
- Centre de Recherche en Cancérologie de Marseille (CRCM); CNRS, UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université; Marseille 13009, France
| | - Stéphane Betzi
- Centre de Recherche en Cancérologie de Marseille (CRCM); CNRS, UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université; Marseille 13009, France
| | - Xavier Morelli
- Centre de Recherche en Cancérologie de Marseille (CRCM); CNRS, UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université; Marseille 13009, France
| | - Philippe Roche
- Centre de Recherche en Cancérologie de Marseille (CRCM); CNRS, UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université; Marseille 13009, France
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21
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Raux B, Voitovich Y, Derviaux C, Lugari A, Rebuffet E, Milhas S, Priet S, Roux T, Trinquet E, Guillemot JC, Knapp S, Brunel JM, Fedorov AY, Collette Y, Roche P, Betzi S, Combes S, Morelli X. Exploring Selective Inhibition of the First Bromodomain of the Human Bromodomain and Extra-terminal Domain (BET) Proteins. J Med Chem 2016; 59:1634-41. [PMID: 26735842 DOI: 10.1021/acs.jmedchem.5b01708] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
A midthroughput screening follow-up program targeting the first bromodomain of the human BRD4 protein, BRD4(BD1), identified an acetylated-mimic xanthine derivative inhibitor. This compound binds with an affinity in the low micromolar range yet exerts suitable unexpected selectivity in vitro against the other members of the bromodomain and extra-terminal domain (BET) family. A structure-based program pinpointed a role of the ZA loop, paving the way for the development of potent and selective BET-BRDi probes.
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Affiliation(s)
- Brigitt Raux
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
| | - Yuliia Voitovich
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France.,Department of Organic Chemistry, Lobachevsky State University of Nizhni Novgorod , Gagarina av. 23, Nizhni Novgorod 603950, Russia
| | - Carine Derviaux
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
| | - Adrien Lugari
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
| | - Etienne Rebuffet
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
| | - Sabine Milhas
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France.,Screening Platform AD2P, CNRS, AFMB UMR 7257, Aix-Marseille Université , 13288 Marseille, France
| | - Stéphane Priet
- Screening Platform AD2P, CNRS, AFMB UMR 7257, Aix-Marseille Université , 13288 Marseille, France
| | - Thomas Roux
- Cisbio Bioassays, R&D , Parc Marcel Boiteux, BP 84175, 30200 Codolet, France
| | - Eric Trinquet
- Cisbio Bioassays, R&D , Parc Marcel Boiteux, BP 84175, 30200 Codolet, France
| | - Jean-Claude Guillemot
- Screening Platform AD2P, CNRS, AFMB UMR 7257, Aix-Marseille Université , 13288 Marseille, France
| | - Stefan Knapp
- Target Discovery Institute, University of Oxford , NDM Research Building, Roosevelt Drive, Oxford OX3 7FZ, U.K.,Structural Genomics Consortium, University of Oxford , Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, U.K.,Goethe-University , Institute for Pharmaceutical Chemistry and Buchmann Institute for Life Science, Campus Riedberg, Max-von Laue Str. 9, 60438 Frankfurt am Main, Germany
| | - Jean-Michel Brunel
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
| | - Alexey Yu Fedorov
- Department of Organic Chemistry, Lobachevsky State University of Nizhni Novgorod , Gagarina av. 23, Nizhni Novgorod 603950, Russia
| | - Yves Collette
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
| | - Philippe Roche
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
| | - Stéphane Betzi
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
| | - Sébastien Combes
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
| | - Xavier Morelli
- Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Cancérologie de Marseille (CRCM), UMR 7258; INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105 , 13273 Marseille, France
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22
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McCarthy M, Prakash P, Gorfe AA. Computational allosteric ligand binding site identification on Ras proteins. Acta Biochim Biophys Sin (Shanghai) 2016; 48:3-10. [PMID: 26487442 DOI: 10.1093/abbs/gmv100] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Accepted: 08/16/2015] [Indexed: 12/19/2022] Open
Abstract
A number of computational techniques have been proposed to expedite the process of allosteric ligand binding site identification in inherently flexible and hence challenging drug targets. Some of these techniques have been instrumental in the discovery of allosteric ligand binding sites on Ras proteins, a group of elusive anticancer drug targets. This review provides an overview of these techniques and their application to Ras proteins. A summary of molecular docking and binding site identification is provided first, followed by a more detailed discussion of two specific techniques for binding site identification in ensembles of Ras conformations generated by molecular simulations.
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Affiliation(s)
- Michael McCarthy
- Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Priyanka Prakash
- Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Alemayehu A Gorfe
- Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
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23
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Callegari D, Pala D, Scalvini L, Tognolini M, Incerti M, Rivara S, Mor M, Lodola A. Comparative Analysis of Virtual Screening Approaches in the Search for Novel EphA2 Receptor Antagonists. Molecules 2015; 20:17132-51. [PMID: 26393553 PMCID: PMC6331951 DOI: 10.3390/molecules200917132] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Revised: 09/08/2015] [Accepted: 09/11/2015] [Indexed: 11/29/2022] Open
Abstract
The EphA2 receptor and its ephrin-A1 ligand form a key cell communication system, which has been found overexpressed in many cancer types and involved in tumor growth. Recent medicinal chemistry efforts have identified bile acid derivatives as low micromolar binders of the EphA2 receptor. However, these compounds suffer from poor physicochemical properties, hampering their use in vivo. The identification of compounds able to disrupt the EphA2-ephrin-A1 complex lacking the bile acid scaffold may lead to new pharmacological tools suitable for in vivo studies. To identify the most promising virtual screening (VS) protocol aimed at finding novel EphA2 antagonists, we investigated the ability of both ligand-based and structure-based approaches to retrieve known EphA2 antagonists from libraries of decoys with similar molecular properties. While ligand-based VSs were conducted using UniPR129 and ephrin-A1 ligand as reference structures, structure-based VSs were performed with Glide, using the X-ray structure of the EphA2 receptor/ephrin-A1 complex. A comparison of enrichment factors showed that ligand-based approaches outperformed the structure-based ones, suggesting ligand-based methods using the G-H loop of ephrin-A1 ligand as template as the most promising protocols to search for novel EphA2 antagonists.
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Affiliation(s)
- Donatella Callegari
- Dipartimento di Farmacia, Università degli Studi di Parma, Parma 43124, Italy.
| | - Daniele Pala
- Dipartimento di Farmacia, Università degli Studi di Parma, Parma 43124, Italy.
| | - Laura Scalvini
- Dipartimento di Farmacia, Università degli Studi di Parma, Parma 43124, Italy.
| | | | - Matteo Incerti
- Dipartimento di Farmacia, Università degli Studi di Parma, Parma 43124, Italy.
| | - Silvia Rivara
- Dipartimento di Farmacia, Università degli Studi di Parma, Parma 43124, Italy.
| | - Marco Mor
- Dipartimento di Farmacia, Università degli Studi di Parma, Parma 43124, Italy.
| | - Alessio Lodola
- Dipartimento di Farmacia, Università degli Studi di Parma, Parma 43124, Italy.
- Department of Applied Sciences, Northumbria University at Newcastle, Newcastle-Upon-Tyne, NE1 8ST, UK.
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Pelay-Gimeno M, Glas A, Koch O, Grossmann TN. Structure-Based Design of Inhibitors of Protein-Protein Interactions: Mimicking Peptide Binding Epitopes. Angew Chem Int Ed Engl 2015; 54:8896-927. [PMID: 26119925 PMCID: PMC4557054 DOI: 10.1002/anie.201412070] [Citation(s) in RCA: 496] [Impact Index Per Article: 55.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2014] [Indexed: 12/15/2022]
Abstract
Protein-protein interactions (PPIs) are involved at all levels of cellular organization, thus making the development of PPI inhibitors extremely valuable. The identification of selective inhibitors is challenging because of the shallow and extended nature of PPI interfaces. Inhibitors can be obtained by mimicking peptide binding epitopes in their bioactive conformation. For this purpose, several strategies have been evolved to enable a projection of side chain functionalities in analogy to peptide secondary structures, thereby yielding molecules that are generally referred to as peptidomimetics. Herein, we introduce a new classification of peptidomimetics (classes A-D) that enables a clear assignment of available approaches. Based on this classification, the Review summarizes strategies that have been applied for the structure-based design of PPI inhibitors through stabilizing or mimicking turns, β-sheets, and helices.
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Affiliation(s)
- Marta Pelay-Gimeno
- Chemical Genomics Centre of the Max Planck SocietyOtto-Hahn-Strasse 15, 44227 Dortmund (Germany) E-mail:
| | - Adrian Glas
- Chemical Genomics Centre of the Max Planck SocietyOtto-Hahn-Strasse 15, 44227 Dortmund (Germany) E-mail:
| | - Oliver Koch
- TU Dortmund University, Department of Chemistry and Chemical BiologyOtto-Hahn-Strasse 6, 44227 Dortmund (Germany)
| | - Tom N Grossmann
- Chemical Genomics Centre of the Max Planck SocietyOtto-Hahn-Strasse 15, 44227 Dortmund (Germany) E-mail:
- TU Dortmund University, Department of Chemistry and Chemical BiologyOtto-Hahn-Strasse 6, 44227 Dortmund (Germany)
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Pelay-Gimeno M, Glas A, Koch O, Grossmann TN. Strukturbasierte Entwicklung von Protein-Protein-Interaktionsinhibitoren: Stabilisierung und Nachahmung von Peptidliganden. Angew Chem Int Ed Engl 2015. [DOI: 10.1002/ange.201412070] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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26
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Walkiewicz KW, Girault JA, Arold ST. How to awaken your nanomachines: Site-specific activation of focal adhesion kinases through ligand interactions. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2015; 119:60-71. [PMID: 26093249 DOI: 10.1016/j.pbiomolbio.2015.06.001] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2015] [Revised: 06/07/2015] [Accepted: 06/14/2015] [Indexed: 01/12/2023]
Abstract
The focal adhesion kinase (FAK) and the related protein-tyrosine kinase 2-beta (Pyk2) are highly versatile multidomain scaffolds central to cell adhesion, migration, and survival. Due to their key role in cancer metastasis, understanding and inhibiting their functions are important for the development of targeted therapy. Because FAK and Pyk2 are involved in many different cellular functions, designing drugs with partial and function-specific inhibitory effects would be desirable. Here, we summarise recent progress in understanding the structural mechanism of how the tug-of-war between intramolecular and intermolecular interactions allows these protein 'nanomachines' to become activated in a site-specific manner.
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Affiliation(s)
- Katarzyna W Walkiewicz
- King Abdullah University of Science and Technology (KAUST), Division of Biological and Environmental Sciences and Engineering, Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia
| | - Jean-Antoine Girault
- Inserm, UMR-S 839, F-75005 Paris, France; Université Pierre & Marie Curie (UPMC), Sorbonne Universités, F-75005 Paris, France; Institut du Fer à Moulin, F-75005 Paris, France
| | - Stefan T Arold
- King Abdullah University of Science and Technology (KAUST), Division of Biological and Environmental Sciences and Engineering, Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia.
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27
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Labbé CM, Rey J, Lagorce D, Vavruša M, Becot J, Sperandio O, Villoutreix BO, Tufféry P, Miteva MA. MTiOpenScreen: a web server for structure-based virtual screening. Nucleic Acids Res 2015; 43:W448-54. [PMID: 25855812 PMCID: PMC4489289 DOI: 10.1093/nar/gkv306] [Citation(s) in RCA: 112] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 03/28/2015] [Indexed: 11/26/2022] Open
Abstract
Open screening endeavors play and will play a key role to facilitate the identification of new bioactive compounds in order to foster innovation and to improve the effectiveness of chemical biology and drug discovery processes. In this line, we developed the new web server MTiOpenScreen dedicated to small molecule docking and virtual screening. It includes two services, MTiAutoDock and MTiOpenScreen, allowing performing docking into a user-defined binding site or blind docking using AutoDock 4.2 and automated virtual screening with AutoDock Vina. MTiOpenScreen provides valuable starting collections for screening, two in-house prepared drug-like chemical libraries containing 150 000 PubChem compounds: the Diverse-lib containing diverse molecules and the iPPI-lib enriched in molecules likely to inhibit protein–protein interactions. In addition, MTiOpenScreen offers users the possibility to screen up to 5000 small molecules selected outside our two libraries. The predicted binding poses and energies of up to 1000 top ranked ligands can be downloaded. In this way, MTiOpenScreen enables researchers to apply virtual screening using different chemical libraries on traditional or more challenging protein targets such as protein–protein interactions. The MTiOpenScreen web server is free and open to all users at http://bioserv.rpbs.univ-paris-diderot.fr/services/MTiOpenScreen/.
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Affiliation(s)
- Céline M Labbé
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France INSERM, U973, Paris, France
| | - Julien Rey
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France INSERM, U973, Paris, France RPBS, 75205 Paris, France
| | - David Lagorce
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France INSERM, U973, Paris, France
| | - Marek Vavruša
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France INSERM, U973, Paris, France RPBS, 75205 Paris, France
| | - Jérome Becot
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France INSERM, U973, Paris, France
| | - Olivier Sperandio
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France INSERM, U973, Paris, France
| | - Bruno O Villoutreix
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France INSERM, U973, Paris, France
| | - Pierre Tufféry
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France INSERM, U973, Paris, France RPBS, 75205 Paris, France
| | - Maria A Miteva
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France INSERM, U973, Paris, France
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28
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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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Chen TC, Lin KT, Chen CH, Lee SA, Lee PY, Liu YW, Kuo YL, Wang FS, Lai JM, Huang CYF. Using an in Situ Proximity Ligation Assay to Systematically Profile Endogenous Protein–Protein Interactions in a Pathway Network. J Proteome Res 2014; 13:5339-46. [DOI: 10.1021/pr5002737] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Tzu-Chi Chen
- Institute
of Clinical Medicine, National Yang-Ming University, Taipei 112, Taiwan
| | - Kuan-Ting Lin
- Institute
of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Taiwan
| | - Chun-Houh Chen
- Institute
of Statistics, Academia Sinica, Taipei 115, Taiwan
| | - Sheng-An Lee
- Department
of Information Management, Kainan University, Taoyuan 338, Taiwan
| | - Pei-Ying Lee
- Institute
of Biopharmaceutical Sciences, National Yang-Ming University, Taipei 112, Taiwan
| | - Yu-Wen Liu
- Institute
of Biopharmaceutical Sciences, National Yang-Ming University, Taipei 112, Taiwan
| | - Yu-Lun Kuo
- Department
of Computer Science and Information Engineering, National Taiwan University, Taipei 112, Taiwan
| | - Feng-Sheng Wang
- Department
of Chemical Engineering, National Chung Cheng University, Chiayi 621, Taiwan
| | - Jin-Mei Lai
- Department
of Life Science, Fu-Jen Catholic University, Taipei 242, Taiwan
| | - Chi-Ying F. Huang
- Institute
of Clinical Medicine, National Yang-Ming University, Taipei 112, Taiwan
- Institute
of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Taiwan
- Institute
of Biopharmaceutical Sciences, National Yang-Ming University, Taipei 112, Taiwan
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