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Heider J, Kilian J, Garifulina A, Hering S, Langer T, Seidel T. Apo2ph4: A Versatile Workflow for the Generation of Receptor-based Pharmacophore Models for Virtual Screening. J Chem Inf Model 2023; 63:101-110. [PMID: 36526584 PMCID: PMC9832483 DOI: 10.1021/acs.jcim.2c00814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Indexed: 12/23/2022]
Abstract
Pharmacophore models are widely used as efficient virtual screening (VS) filters for the target-directed enrichment of large compound libraries. However, the generation of pharmacophore models that have the power to discriminate between active and inactive molecules traditionally requires structural information about ligand-target complexes or at the very least knowledge of one active ligand. The fact that the discovery of the first known active ligand of a newly investigated target represents a major hurdle at the beginning of every drug discovery project underscores the need for methods that are able to derive high-quality pharmacophore models even without the prior knowledge of any active ligand structures. In this work, we introduce a novel workflow, called apo2ph4, that enables the rapid derivation of pharmacophore models solely from the three-dimensional structure of the target receptor. The utility of this workflow is demonstrated retrospectively for the generation of a pharmacophore model for the M2 muscarinic acetylcholine receptor. Furthermore, in order to show the general applicability of apo2ph4, the workflow was employed for all 15 targets of the recently published LIT-PCBA dataset. Pharmacophore-based VS runs using the apo2ph4-derived models achieved a significant enrichment of actives for 13 targets. In the last presented example, a pharmacophore model derived from the etomidate site of the α1β2γ2 GABAA receptor was used in VS campaigns. Subsequent in vitro testing of selected hits revealed that 19 out of 20 (95%) tested compounds were able to significantly enhance GABA currents, which impressively demonstrates the applicability of apo2ph4 for real-world drug design projects.
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Affiliation(s)
- Jörg Heider
- Department
of Pharmaceutical Sciences, University of
Vienna, Josef-Holaubek-Platz
2, 1090Vienna, Austria
- Vienna
Doctoral School of Pharmaceutical, Nutritional and Sport Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090Vienna, Austria
| | - Jonas Kilian
- Vienna
Doctoral School of Pharmaceutical, Nutritional and Sport Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090Vienna, Austria
- Department
of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear
Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090Vienna, Austria
| | - Aleksandra Garifulina
- Division
of Pharmacology and Toxicology, Department of Pharmaceutical Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090Vienna, Austria
| | - Steffen Hering
- Division
of Pharmacology and Toxicology, Department of Pharmaceutical Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090Vienna, Austria
| | - Thierry Langer
- Department
of Pharmaceutical Sciences, University of
Vienna, Josef-Holaubek-Platz
2, 1090Vienna, Austria
| | - Thomas Seidel
- Department
of Pharmaceutical Sciences, University of
Vienna, Josef-Holaubek-Platz
2, 1090Vienna, Austria
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2
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Mapping of Protein Binding Sites using clustering algorithms development of a pharmacophore based drug discovery tool. J Mol Graph Model 2022; 115:108228. [DOI: 10.1016/j.jmgm.2022.108228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 04/28/2022] [Accepted: 05/19/2022] [Indexed: 11/22/2022]
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3
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Tyagi R, Singh A, Chaudhary KK, Yadav MK. Pharmacophore modeling and its applications. Bioinformatics 2022. [DOI: 10.1016/b978-0-323-89775-4.00009-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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4
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Mermer A. The Importance of Rhodanine Scaffold in Medicinal Chemistry: A Comprehensive Overview. Mini Rev Med Chem 2021; 21:738-789. [PMID: 33334286 DOI: 10.2174/1389557521666201217144954] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 09/21/2020] [Accepted: 10/07/2020] [Indexed: 11/22/2022]
Abstract
After the clinical use of epalrestat that contains a rhodanine ring, in type II diabetes mellitus and diabetic complications, rhodanin-based compounds have become an important class of heterocyclic in the field of medicinal chemistry. Various modifications to the rhodanine ring have led to a broad spectrum of biological activity of these compounds. Synthesis of rhodanine derivatives, depended on advenced throughput scanning hits, frequently causes potent and selective modulators of targeted enzymes or receptors, which apply their pharmacological activities through different mechanisms of action. Rhodanine-based compounds will likely stay a privileged scaffold in drug discovery because of different probability of chemical modifications of the rhodanine ring. We have, therefore reviewed their biological activities and structure activity relationship.
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Affiliation(s)
- Arif Mermer
- Department of Biotechnology, Hamidiye Health Science Institute, University of Health Sciences Turkey, 34668, İstanbul, Turkey
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5
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Jiang S, Feher M, Williams C, Cole B, Shaw DE. AutoPH4: An Automated Method for Generating Pharmacophore Models from Protein Binding Pockets. J Chem Inf Model 2020; 60:4326-4338. [PMID: 32639159 DOI: 10.1021/acs.jcim.0c00121] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Pharmacophore models are widely used in computational drug discovery (e.g., in the virtual screening of drug molecules) to capture essential information about interactions between ligands and a target protein. Generating pharmacophore models from protein structures is typically a manual process, but there has been growing interest in automated pharmacophore generation methods. Automation makes feasible the processing of large numbers of protein conformations, such as those generated by molecular dynamics (MD) simulations, and thus may help achieve the longstanding goal of incorporating protein flexibility into virtual screening workflows. Here, we present AutoPH4, a new automated method for generating pharmacophore models based on protein structures; we show that a virtual screening workflow incorporating AutoPH4 ranks compounds more accurately than any other pharmacophore-based virtual screening workflow for which results on a public benchmark have been reported. The strong performance of the virtual screening workflow indicates that the AutoPH4 component of the workflow generates high-quality pharmacophores, making AutoPH4 promising for use in future virtual screening workflows as well, such as ones that use conformations generated by MD simulations.
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Affiliation(s)
- Siduo Jiang
- D. E. Shaw Research, New York, New York 10036, United States
| | - Miklos Feher
- D. E. Shaw Research, New York, New York 10036, United States
| | - Chris Williams
- Chemical Computing Group, Montreal, Quebec H3A 2R7, Canada
| | - Brian Cole
- D. E. Shaw Research, New York, New York 10036, United States
| | - David E Shaw
- D. E. Shaw Research, New York, New York 10036, United States.,Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032, United States
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6
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Mori M, Manetti F, Botta B, Tafi A. In Memory of Maurizio Botta: His Contribution to the Development of Computer-Aided Drug Design. J Chem Inf Model 2019; 59:4961-4967. [PMID: 31804073 DOI: 10.1021/acs.jcim.9b01043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Mattia Mori
- Department of Biotechnology, Chemistry and Pharmacy, Department of Excellence 2018-2022 , University of Siena , via Aldo Moro 2 , 53100 Siena , Italy
| | - Fabrizio Manetti
- Department of Biotechnology, Chemistry and Pharmacy, Department of Excellence 2018-2022 , University of Siena , via Aldo Moro 2 , 53100 Siena , Italy
| | - Bruno Botta
- Department of Chemistry and Technology of Drugs, Department of Excellence 2018-2022 , Sapienza University of Rome , Piazzale Aldo Moro 5 , 00185 Rome , Italy
| | - Andrea Tafi
- Department of Biotechnology, Chemistry and Pharmacy, Department of Excellence 2018-2022 , University of Siena , via Aldo Moro 2 , 53100 Siena , Italy
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7
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Lee JY, Krieger JM, Li H, Bahar I. Pharmmaker: Pharmacophore modeling and hit identification based on druggability simulations. Protein Sci 2019; 29:76-86. [PMID: 31576621 PMCID: PMC6933858 DOI: 10.1002/pro.3732] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 09/16/2019] [Accepted: 09/17/2019] [Indexed: 12/14/2022]
Abstract
Recent years have seen progress in druggability simulations, that is, molecular dynamics simulations of target proteins in solutions containing drug‐like probe molecules to characterize their drug‐binding abilities, if any. An important consecutive step is to analyze the trajectories to construct pharmacophore models (PMs) to use for virtual screening of libraries of small molecules. While considerable success has been observed in this type of computer‐aided drug discovery, a systematic tool encompassing multiple steps from druggability simulations to pharmacophore modeling, to identifying hits by virtual screening of libraries of compounds, has been lacking. We address this need here by developing a new tool, Pharmmaker, building on the DruGUI module of our ProDy application programming interface. Pharmmaker is composed of a suite of steps: (Step 1) identification of high affinity residues for each probe molecule type; (Step 2) selecting high affinity residues and hot spots in the vicinity of sites identified by DruGUI; (Step 3) ranking of the interactions between high affinity residues and specific probes; (Step 4) obtaining probe binding poses and corresponding protein conformations by collecting top‐ranked snapshots; and (Step 5) using those snapshots for constructing PMs. The PMs are then used as filters for identifying hits in structure‐based virtual screening. Pharmmaker, accessible online at http://prody.csb.pitt.edu/pharmmaker/, can be used in conjunction with other tools available in ProDy.
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Affiliation(s)
- Ji Young Lee
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - James M Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Hongchun Li
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
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8
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Bruno A, Costantino G, Sartori L, Radi M. The In Silico Drug Discovery Toolbox: Applications in Lead Discovery and Optimization. Curr Med Chem 2019; 26:3838-3873. [PMID: 29110597 DOI: 10.2174/0929867324666171107101035] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Revised: 09/27/2017] [Accepted: 09/28/2017] [Indexed: 01/04/2023]
Abstract
BACKGROUND Discovery and development of a new drug is a long lasting and expensive journey that takes around 20 years from starting idea to approval and marketing of new medication. Despite R&D expenditures have been constantly increasing in the last few years, the number of new drugs introduced into market has been steadily declining. This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. To cope with this issue, a number of in silico techniques are currently being used for an early stage evaluation/prediction of potential safety issues, allowing to increase the drug-discovery success rate and reduce costs associated with the development of a new drug. METHODS In the present review, we will analyse the early steps of the drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silico tools used to assess attrition risks and build a mitigation plan. RESULTS A comprehensive list of widely used in silico tools, databases, and public initiatives that can be effectively implemented and used in the drug discovery pipeline has been provided. A few examples of how these tools can be problem-solving and how they may increase the success rate of a drug discovery and development program have been also provided. Finally, selected examples where the application of in silico tools had effectively contributed to the development of marketed drugs or clinical candidates will be given. CONCLUSION The in silico toolbox finds great application in every step of early drug discovery: (i) target identification and validation; (ii) hit identification; (iii) hit-to-lead; and (iv) lead optimization. Each of these steps has been described in details, providing a useful overview on the role played by in silico tools in the decision-making process to speed-up the discovery of new drugs.
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Affiliation(s)
- Agostino Bruno
- Experimental Therapeutics Unit, IFOM - The FIRC Institute for Molecular Oncology Foundation, Via Adamello 16 - 20139 Milano, Italy
| | - Gabriele Costantino
- Dipartimento di Scienze degli Alimenti e del Farmaco, Universita degli Studi di Parma, Viale delle Scienze, 27/A, 43124 Parma, Italy
| | - Luca Sartori
- Experimental Therapeutics Unit, IFOM - The FIRC Institute for Molecular Oncology Foundation, Via Adamello 16 - 20139 Milano, Italy
| | - Marco Radi
- Dipartimento di Scienze degli Alimenti e del Farmaco, Universita degli Studi di Parma, Viale delle Scienze, 27/A, 43124 Parma, Italy
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9
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Receptor-based pharmacophore modeling, virtual screening, and molecular docking studies for the discovery of novel GSK-3β inhibitors. J Mol Model 2019; 25:171. [PMID: 31129879 DOI: 10.1007/s00894-019-4032-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Accepted: 04/07/2019] [Indexed: 10/26/2022]
Abstract
Considering the emerging importance of glycogen synthase kinase 3 beta (GSK-3β) inhibitors in treatment of Alzheimer's disease, multi-protein structure receptor-based pharmacophore modeling was adopted to generate a 3D pharmacophore model for (GSK-3β) inhibitors. The generated 3D pharmacophore was then validated using a test set of 1235 compounds. The ZINCPharmer web tool was used to virtually screen the public ZINC database using the generated 3D pharmacophore. A set of 12,251 hits was produced and then filtered according to their lead-like properties, predicted central nervous system (CNS) activity, and Pan-assay interference compounds (PAINS) fragments to 630 compounds. Scaffold Hunter was then used to cluster the filtered compounds according to their chemical structure framework. From the different clusters, 123 compounds were selected to cover the whole chemical space of the obtained hits. The SwissADME online tool was then used to filter out the compounds with undesirable pharmacokinetic properties giving a set of 91 compounds with promising predicted pharmacodynamic and pharmacokinetic properties. To confirm their binding capability to the GSK-3β binding site, molecular docking simulations were performed for the final 91 compounds in the GSK-3β binding site. Twenty-five compounds showed acceptable binding poses that bind to the key amino acids in the binding site Asp133 and Val135 with good binding scores. The quinolin-2-one derivative ZINC67773573 was found to be a promising lead for designing new GSK-3β inhibitors for Alzheimer's disease treatment. Graphical abstract A 3D pharmacophore model for the discovery of novel (GSK-3β) inhibitors.
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10
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Mousavi SM, Zarei M, Hashemi SA, Babapoor A, Amani AM. A conceptual review of rhodanine: current applications of antiviral drugs, anticancer and antimicrobial activities. ARTIFICIAL CELLS NANOMEDICINE AND BIOTECHNOLOGY 2019; 47:1132-1148. [DOI: 10.1080/21691401.2019.1573824] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Seyyed Mojtaba Mousavi
- Department of Medical Nanotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Maryam Zarei
- Department of Medical Nanotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Seyyed Alireza Hashemi
- Department of Medical Nanotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Aziz Babapoor
- Department of Chemical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
| | - Ali Mohammad Amani
- Department of Medical Nanotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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11
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Mortier J, Dhakal P, Volkamer A. Truly Target-Focused Pharmacophore Modeling: A Novel Tool for Mapping Intermolecular Surfaces. Molecules 2018; 23:molecules23081959. [PMID: 30082611 PMCID: PMC6222449 DOI: 10.3390/molecules23081959] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 07/27/2018] [Accepted: 07/27/2018] [Indexed: 12/19/2022] Open
Abstract
Pharmacophore models are an accurate and minimal tridimensional abstraction of intermolecular interactions between chemical structures, usually derived from a group of molecules or from a ligand-target complex. Only a limited amount of solutions exists to model comprehensive pharmacophores using the information of a particular target structure without knowledge of any binding ligand. In this work, an automated and customable tool for truly target-focused (T²F) pharmacophore modeling is introduced. Key molecular interaction fields of a macromolecular structure are calculated using the AutoGRID energy functions. The most relevant points are selected by a newly developed filtering cascade and clustered to pharmacophore features with a density-based algorithm. Using five different protein classes, the ability of this method to identify essential pharmacophore features was compared to structure-based pharmacophores derived from ligand-target interactions. This method represents an extremely valuable instrument for drug design in a situation of scarce ligand information available, but also in the case of underexplored therapeutic targets, as well as to investigate protein allosteric pockets and protein-protein interactions.
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Affiliation(s)
- Jérémie Mortier
- In-Silico Toxicology Group, Institute of Physiology, Charité-Universitätsmedizin Berlin, Virchowweg 6, 10117 Berlin, Germany.
| | - Pratik Dhakal
- In-Silico Toxicology Group, Institute of Physiology, Charité-Universitätsmedizin Berlin, Virchowweg 6, 10117 Berlin, Germany.
| | - Andrea Volkamer
- In-Silico Toxicology Group, Institute of Physiology, Charité-Universitätsmedizin Berlin, Virchowweg 6, 10117 Berlin, Germany.
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12
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Proschak E, Stark H, Merk D. Polypharmacology by Design: A Medicinal Chemist's Perspective on Multitargeting Compounds. J Med Chem 2018; 62:420-444. [PMID: 30035545 DOI: 10.1021/acs.jmedchem.8b00760] [Citation(s) in RCA: 276] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Multitargeting compounds comprising activity on more than a single biological target have gained remarkable relevance in drug discovery owing to the complexity of multifactorial diseases such as cancer, inflammation, or the metabolic syndrome. Polypharmacological drug profiles can produce additive or synergistic effects while reducing side effects and significantly contribute to the high therapeutic success of indispensable drugs such as aspirin. While their identification has long been the result of serendipity, medicinal chemistry now tends to design polypharmacology. Modern in vitro pharmacological methods and chemical probes allow a systematic search for rational target combinations and recent innovations in computational technologies, crystallography, or fragment-based design equip multitarget compound development with valuable tools. In this Perspective, we analyze the relevance of multiple ligands in drug discovery and the versatile toolbox to design polypharmacology. We conclude that despite some characteristic challenges remaining unresolved, designed polypharmacology holds enormous potential to secure future therapeutic innovation.
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Affiliation(s)
- Ewgenij Proschak
- Institute of Pharmaceutical Chemistry , Goethe University Frankfurt , Max-von-Laue-Strasse 9 , D-60438 Frankfurt , Germany
| | - Holger Stark
- Institute of Pharmaceutical and Medicinal Chemistry , Heinrich Heine University Düsseldorf , Universitaetsstrasse 1 , D-40225 , Duesseldorf , Germany
| | - Daniel Merk
- Institute of Pharmaceutical Chemistry , Goethe University Frankfurt , Max-von-Laue-Strasse 9 , D-60438 Frankfurt , Germany.,Department of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences , Swiss Federal Institute of Technology (ETH) Zürich , Vladimir-Prelog-Weg 4 , CH-8093 Zürich , Switzerland
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13
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Tintori C, Iovenitti G, Ceresola ER, Ferrarese R, Zamperini C, Brai A, Poli G, Dreassi E, Cagno V, Lembo D, Canducci F, Botta M. Rhodanine derivatives as potent anti-HIV and anti-HSV microbicides. PLoS One 2018; 13:e0198478. [PMID: 29870553 PMCID: PMC5988308 DOI: 10.1371/journal.pone.0198478] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 05/18/2018] [Indexed: 12/12/2022] Open
Abstract
Although highly active antiretroviral therapies (HAART) remarkably increased life expectancy of HIV positive people, the rate of novel HIV-1 infections worldwide still represent a major concern. In this context, pre-exposure prophylaxis (PrEP) approaches such as vaginal microbicide gels topically releasing antiretroviral drugs, showed to have a striking impact in limiting HIV-1 spread. Nevertheless, the co-presence of other genital infections, particularly those due to HSV-1 or 2, constitute a serious drawback that strongly limits the efficacy of PrEP approaches. For this reason, combinations of different compounds with mixed antiviral and antiretroviral activity are thoroughly investigated Here we report the synthesis and the biological evaluation of a novel series of rhodanine derivatives, which showed to inhibit both HIV-1 and HSV-1/2 replication at nanomolar concentration, and were found to be active also on acyclovir resistant HSV-2 strains. The compounds showed a considerable reduction of activity in presence of serum due to a high binding to serum albumin, as determined through in vitro ADME evaluations. However, the most promising compound of the series maintained a considerable activity in gel formulation, with an EC50 comparable to that obtained for the reference drug tenofovir. Moreover, the series of compounds showed pharmacokinetic properties suitable for topical formulation, thus suggesting that the novel rhodanine derivatives could represent effective agents to be used as dual anti HIV/HSV microbicides in PrEP approaches.
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Affiliation(s)
- Cristina Tintori
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Giulia Iovenitti
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Elisa Rita Ceresola
- Laboratory of Microbiology and Virology, Ospedale San Raffaele, Milan, Italy
| | - Roberto Ferrarese
- Laboratory of Microbiology and Virology, Ospedale San Raffaele, Milan, Italy
| | - Claudio Zamperini
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
- Lead Discovery Siena S.r.l., Castelnuovo Berardenga, Siena, Italy
| | - Annalaura Brai
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
- Lead Discovery Siena S.r.l., Castelnuovo Berardenga, Siena, Italy
| | - Giulio Poli
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Elena Dreassi
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Valeria Cagno
- Laboratory of Molecular Virology and Antiviral Research. Department of Clinical and Biological Sciences, University of Torino, Orbassano, Torino, Italy
- Department of Molecular Microbiology, University of Geneva, Geneva, Switzerland
| | - David Lembo
- Laboratory of Molecular Virology and Antiviral Research. Department of Clinical and Biological Sciences, University of Torino, Orbassano, Torino, Italy
| | - Filippo Canducci
- Laboratory of Microbiology and Virology, Ospedale San Raffaele, Milan, Italy
| | - Maurizio Botta
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
- Lead Discovery Siena S.r.l., Castelnuovo Berardenga, Siena, Italy
- Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, Philadelphia, PA, United States of America
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14
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Affiliation(s)
- Norbert Handler
- RD&C Research, Development & Consulting GmbH; Neuwaldegger Strasse 35/2/3 Vienna 1170 Austria
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15
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Jha T, Adhikari N, Halder AK, Saha A. Ligand- and Structure-Based Drug Design of Non-Steroidal Aromatase Inhibitors (NSAIs) in Breast Cancer. Oncology 2017. [DOI: 10.4018/978-1-5225-0549-5.ch004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Aromatase is a multienzyme complex overexpressed in breast cancer and responsible for estrogen production. It is the potential target for designing anti-breast cancer drugs. Ligand and Structure-Based Drug Designing approaches (LBDD and SBDD) are involved in development of active and more specific Nonsteroidal Aromatase Inhibitors (NSAIs). Different LBDD and SBDD approaches are presented here to understand their utility in designing novel NSAIs. It is observed that molecules should possess a five or six membered heterocyclic nitrogen containing ring to coordinate with heme portion of aromatase for inhibition. Moreover, one or two hydrogen bond acceptor features, hydrophobicity, and steric factors may play crucial roles for anti-aromatase activity. Electrostatic, van der Waals, and p-p interactions are other important factors that determine binding affinity of inhibitors. HQSAR, LDA-QSAR, GQSAR, CoMFA, and CoMSIA approaches, pharmacophore mapping followed by virtual screening, docking, and dynamic simulation may be effective approaches for designing new potent anti-aromatase molecules.
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16
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Johnson DK, Karanicolas J. Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein-Protein Interactions. J Chem Inf Model 2016; 56:399-411. [PMID: 26726827 DOI: 10.1021/acs.jcim.5b00572] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased "pocket optimization" simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its "exemplar": a perfect, but nonphysical, pseudoligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 min on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against a "pocket-optimized" ensemble of protein conformations, which in turn facilitates identification of more diverse classes of active compounds for a given protein target.
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Affiliation(s)
- David K Johnson
- Center for Computational Biology, and ‡Department of Molecular Biosciences, University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - John Karanicolas
- Center for Computational Biology, and ‡Department of Molecular Biosciences, University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
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Ahmadi M, Nowroozi A, Shahlaei M. Constructing an atomic-resolution model of human P2X7 receptor followed by pharmacophore modeling to identify potential inhibitors. J Mol Graph Model 2015; 61:243-61. [PMID: 26298810 DOI: 10.1016/j.jmgm.2015.08.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2015] [Revised: 06/22/2015] [Accepted: 08/10/2015] [Indexed: 12/22/2022]
Abstract
The P2X purinoceptor 7 (P2X7R) is a trimeric ATP-activated ion channel gated by extracellular ATP. P2X7R has important role in numerous diseases including pain, neurodegeneration, and inflammatory diseases such as rheumatoid arthritis and osteoarthritis. In this prospective, the discovery of small-molecule inhibitors for P2X7R as a novel therapeutic target has received considerable attention in recent years. At first, 3D structure of P2X7R was built by using homology modeling (HM) and a 50ns molecular dynamics simulation (MDS). Ligand-based quantitative pharmacophore modeling methodology of P2X7R antagonists were developed based on training set of 49 compounds. The best four-feature pharmacophore model, includes two hydrophobic aromatic, one hydrophobic and one aromatic ring features, has the highest correlation coefficient (0.874), cost difference (368.677), low RMSD (2.876), as well as it shows a high goodness of fit and enrichment factor. Consequently, some hit compounds were introduced as final candidates by employing virtual screening and molecular docking procedure simultaneously. Among these compounds, six potential molecule were identified as potential virtual leads which, as such or upon further optimization, can be used to design novel P2X7R inhibitors.
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Affiliation(s)
- Mehdi Ahmadi
- Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Amin Nowroozi
- Pharmaceutical sciences Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Mohsen Shahlaei
- Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran.
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18
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Kaalia R, Kumar A, Srinivasan A, Ghosh I. An Ab Initio Method for Designing Multi-Target Specific Pharmacophores using Complementary Interaction Field of Aspartic Proteases. Mol Inform 2015; 34:380-93. [PMID: 27490384 DOI: 10.1002/minf.201400157] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Accepted: 02/09/2014] [Indexed: 11/09/2022]
Abstract
For past few decades, key objectives of rational drug discovery have been the designing of specific and selective ligands for target proteins. Infectious diseases like malaria are continuously becoming resistant to traditional medicines, which inculcates need for new approaches to design inhibitors for antimalarial targets. A novel method for ab initio designing of multi target specific pharmacophores using the interaction field maps of active sites of multiple proteins has been developed to design 'specificity' pharmacophores for aspartic proteases. The molecular interaction field grid maps of active sites of aspartic proteases (plasmepsin II & IV from Plasmodium falciparum, plasmepsin from Plasmodium vivax, pepsin & cathepsin D from human) are calculated and common pharmacophoric features for favourable binding spots in active sites are extracted in the form of cliques of graphs using inductive logic programming (ILP). The two pharmacophore ensembles are constructed from largest common cliques by imposing size of receptor active site (L) and domain-specific receptor-ligand information (S). The overlap of chemical space between two ensembles and the results of virtual screening of inhibitor database with known activities show that this method can design efficient pharmacophores with no prior ligand information.
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Affiliation(s)
- Rama Kaalia
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110067, India phone/fax:9971287771
| | - Amit Kumar
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110067, India phone/fax:9971287771
| | - Ashwin Srinivasan
- Indraprastha Institute of Information Technology, New Delhi-110020, India.,Current address: Department of Computer Science, BITS-Pilani, Goa-403726, India
| | - Indira Ghosh
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110067, India phone/fax:9971287771.
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Johnson DK, Karanicolas J. Selectivity by small-molecule inhibitors of protein interactions can be driven by protein surface fluctuations. PLoS Comput Biol 2015; 11:e1004081. [PMID: 25706586 PMCID: PMC4338137 DOI: 10.1371/journal.pcbi.1004081] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Accepted: 12/10/2014] [Indexed: 12/13/2022] Open
Abstract
Small-molecules that inhibit interactions between specific pairs of proteins have long represented a promising avenue for therapeutic intervention in a variety of settings. Structural studies have shown that in many cases, the inhibitor-bound protein adopts a conformation that is distinct from its unbound and its protein-bound conformations. This plasticity of the protein surface presents a major challenge in predicting which members of a protein family will be inhibited by a given ligand. Here, we use biased simulations of Bcl-2-family proteins to generate ensembles of low-energy conformations that contain surface pockets suitable for small molecule binding. We find that the resulting conformational ensembles include surface pockets that mimic those observed in inhibitor-bound crystal structures. Next, we find that the ensembles generated using different members of this protein family are overlapping but distinct, and that the activity of a given compound against a particular family member (ligand selectivity) can be predicted from whether the corresponding ensemble samples a complementary surface pocket. Finally, we find that each ensemble includes certain surface pockets that are not shared by any other family member: while no inhibitors have yet been identified to take advantage of these pockets, we expect that chemical scaffolds complementing these “distinct” pockets will prove highly selective for their targets. The opportunity to achieve target selectivity within a protein family by exploiting differences in surface fluctuations represents a new paradigm that may facilitate design of family-selective small-molecule inhibitors of protein-protein interactions. Despite intense interest and considerable effort, there are few examples of small molecules that directly inhibit protein-protein interactions. Crystal structures of early successes have highlighted the plasticity of the protein surface, as some inhibitor-bound proteins are captured in conformations that are distinct from both their unbound and their protein-bound conformations. The lack of a single well-defined structure presents a challenge for predicting the members of a protein family to which a given compound will show activity (ligand selectivity). Here we generate ensembles of conformations from simulation, and show that we can predict ligand selectivity based on which family members sample conformations complementary to the ligand. This approach may present a new avenue for designing highly-selective inhibitors of protein-protein interactions.
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Affiliation(s)
- David K. Johnson
- Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America
| | - John Karanicolas
- Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America
- * E-mail:
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20
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Jha T, Adhikari N, Halder AK, Saha A. Ligand- and Structure-Based Drug Design of Non-Steroidal Aromatase Inhibitors (NSAIs) in Breast Cancer. QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS IN DRUG DESIGN, PREDICTIVE TOXICOLOGY, AND RISK ASSESSMENT 2015. [DOI: 10.4018/978-1-4666-8136-1.ch011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Aromatase is a multienzyme complex overexpressed in breast cancer and responsible for estrogen production. It is the potential target for designing anti-breast cancer drugs. Ligand and Structure-Based Drug Designing approaches (LBDD and SBDD) are involved in development of active and more specific Nonsteroidal Aromatase Inhibitors (NSAIs). Different LBDD and SBDD approaches are presented here to understand their utility in designing novel NSAIs. It is observed that molecules should possess a five or six membered heterocyclic nitrogen containing ring to coordinate with heme portion of aromatase for inhibition. Moreover, one or two hydrogen bond acceptor features, hydrophobicity, and steric factors may play crucial roles for anti-aromatase activity. Electrostatic, van der Waals, and p-p interactions are other important factors that determine binding affinity of inhibitors. HQSAR, LDA-QSAR, GQSAR, CoMFA, and CoMSIA approaches, pharmacophore mapping followed by virtual screening, docking, and dynamic simulation may be effective approaches for designing new potent anti-aromatase molecules.
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21
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An integrated approach to knowledge-driven structure-based virtual screening. J Comput Aided Mol Des 2014; 28:927-39. [PMID: 24993405 DOI: 10.1007/s10822-014-9769-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2014] [Accepted: 06/23/2014] [Indexed: 12/18/2022]
Abstract
In many practical applications of structure-based virtual screening (VS) ligands are already known. This circumstance requires that the obtained hits need to satisfy initial made expectations i.e., they have to fulfill a predefined binding pattern and/or lie within a predefined physico-chemical property range. Based on the RApid Index-based Screening Engine (RAISE) approach, we introduce CRAISE-a user-controllable structure-based VS method. It efficiently realizes pharmacophore-guided protein-ligand docking to assess the library content but thereby concentrates only on molecules that have a chance to fulfill the given binding pattern. In order to focus only on hits satisfying given molecular properties, library profiles can be utilized to simultaneously filter compounds. CRAISE was evaluated on a range of strict to rather relaxed hypotheses with respect to its capability to guide binding-mode predictions and VS runs. The results reveal insights into a guided VS process. If a pharmacophore model is chosen appropriately, a binding mode below 2 Å is successfully reproduced for 85% of well-prepared structures, enrichment is increased up to median AUC of 73%, and the selectivity of the screening process is significantly enhanced leading up to seven times accelerated runtimes. In general, CRAISE supports a versatile structure-based VS approach allowing to assess hypotheses about putative ligands on a large scale.
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22
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Hu B, Lill MA. PharmDock: a pharmacophore-based docking program. J Cheminform 2014; 6:14. [PMID: 24739488 PMCID: PMC4012150 DOI: 10.1186/1758-2946-6-14] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2014] [Accepted: 04/04/2014] [Indexed: 11/27/2022] Open
Abstract
Background Protein-based pharmacophore models are enriched with the information of potential interactions between ligands and the protein target. We have shown in a previous study that protein-based pharmacophore models can be applied for ligand pose prediction and pose ranking. In this publication, we present a new pharmacophore-based docking program PharmDock that combines pose sampling and ranking based on optimized protein-based pharmacophore models with local optimization using an empirical scoring function. Results Tests of PharmDock on ligand pose prediction, binding affinity estimation, compound ranking and virtual screening yielded comparable or better performance to existing and widely used docking programs. The docking program comes with an easy-to-use GUI within PyMOL. Two features have been incorporated in the program suite that allow for user-defined guidance of the docking process based on previous experimental data. Docking with those features demonstrated superior performance compared to unbiased docking. Conclusion A protein pharmacophore-based docking program, PharmDock, has been made available with a PyMOL plugin. PharmDock and the PyMOL plugin are freely available from http://people.pharmacy.purdue.edu/~mlill/software/pharmdock.
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Affiliation(s)
- Bingjie Hu
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, IN 47906, USA
| | - Markus A Lill
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, IN 47906, USA
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Drwal MN, Agama K, Pommier Y, Griffith R. Development of purely structure-based pharmacophores for the topoisomerase I-DNA-ligand binding pocket. J Comput Aided Mol Des 2013; 27:1037-49. [PMID: 24293134 PMCID: PMC7578780 DOI: 10.1007/s10822-013-9695-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2013] [Accepted: 11/26/2013] [Indexed: 12/30/2022]
Abstract
Purely structure-based pharmacophores (SBPs) are an alternative method to ligand-based approaches and have the advantage of describing the entire interaction capability of a binding pocket. Here, we present the development of SBPs for topoisomerase I, an anticancer target with an unusual ligand binding pocket consisting of protein and DNA atoms. Different approaches to cluster and select pharmacophore features are investigated, including hierarchical clustering and energy calculations. In addition, the performance of SBPs is evaluated retrospectively and compared to the performance of ligand- and complex-based pharmacophores. SBPs emerge as a valid method in virtual screening and a complementary approach to ligand-focussed methods. The study further reveals that the choice of pharmacophore feature clustering and selection methods has a large impact on the virtual screening hit lists. A prospective application of the SBPs in virtual screening reveals that they can be used successfully to identify novel topoisomerase inhibitors.
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Affiliation(s)
- Malgorzata N Drwal
- Department of Pharmacology, School of Medical Sciences, University of New South Wales, Sydney, NSW, 2052, Australia
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24
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Hu B, Lill MA. Exploring the potential of protein-based pharmacophore models in ligand pose prediction and ranking. J Chem Inf Model 2013; 53:1179-90. [PMID: 23621564 DOI: 10.1021/ci400143r] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Protein-based pharmacophore models derived from protein binding site atoms without the inclusion of any ligand information have become more popular in virtual screening studies. However, the accuracy of protein-based pharmacophore models for reproducing the critical protein-ligand interactions has never been explicitly assessed. In this study, we used known protein-ligand contacts from a large set of experimentally determined protein-ligand complexes to assess the quality of the protein-based pharmacophores in reproducing these critical contacts. We demonstrate how these contacts can be used to optimize the pharmacophore generation procedure to produce pharmacophore models that optimally cover the known protein-ligand interactions. Finally, we explored the potential of the optimized protein-based pharmacophore models for pose prediction and pose rankings. Our results demonstrate that there are significant variations in the success of protein-based pharmacophore models to reproduce native contacts and consequently native ligand poses dependent on the details of the pharmacophore generation process. We show that the generation of optimized protein-based pharmacophore models is a promising approach for ligand pose prediction and pose rankings.
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Affiliation(s)
- Bingjie Hu
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, West Lafayette, Indiana 47906, United States
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25
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Maga G, Veljkovic N, Crespan E, Spadari S, Prljic J, Perovic V, Glisic S, Veljkovic V. New in silico and conventional in vitro approaches to advance HIV drug discovery and design. Expert Opin Drug Discov 2012; 8:83-92. [PMID: 23167743 DOI: 10.1517/17460441.2013.741118] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
INTRODUCTION Recently, the new concept of the long-range intermolecular interactions in biological systems has been proposed. Combined use of molecular modeling techniques and the screening techniques based on the long-range interaction concept could significantly improve and accelerate discovery of new HIV drugs. However, any hit identified in silico needs to be characterized with respect to its biological target by enzymatic studies. Combined use of the in silico screening and the enzymatic studies allows an efficient selection of new anti-HIV drugs. AREAS COVERED The focus of this article is on the in silico screening of molecular libraries for candidate new HIV drugs, which is based on the molecular descriptors determining the long-range interaction between the drugs and their therapeutic target. This article also reviews the techniques for enzyme kinetic studies which are required for optimization of in silico selected candidate anti-HIV drugs. EXPERT OPINION The novel approach of combining in silico screening techniques with enzymatic studies enables the accurate measurement of the quantitative descriptors of ligand-enzyme interactions. This novel method is a powerful tool for new anti-HIV drug discovery which can also reduce the drug development costs.
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Affiliation(s)
- Giovanni Maga
- Institute of Molecular Genetics, IGM-CNR, DNA Enzymology & Molecular Virology, Pavia, Italy
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26
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Sanders MPA, McGuire R, Roumen L, de Esch IJP, de Vlieg J, Klomp JPG, de Graaf C. From the protein's perspective: the benefits and challenges of protein structure-based pharmacophore modeling. MEDCHEMCOMM 2012. [DOI: 10.1039/c1md00210d] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Protein structure-based pharmacophore (SBP) models derive the molecular features a ligand must contain to be biologically active by conversion of protein properties to reciprocal ligand space. SBPs improve molecular understanding of ligand–protein interactions and can be used as valuable tools for hit and lead optimization, compound library design, and target hopping.
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Affiliation(s)
- Marijn P. A. Sanders
- Computational Drug Discovery Group
- CMBI
- Radboud University Nijmegen
- Nijmegen
- The Netherlands
| | | | - Luc Roumen
- Division of Medicinal Chemistry
- LACDR
- VU University Amsterdam
- Amsterdam
- The Netherlands
| | - Iwan J. P. de Esch
- Division of Medicinal Chemistry
- LACDR
- VU University Amsterdam
- Amsterdam
- The Netherlands
| | - Jacob de Vlieg
- Computational Drug Discovery Group
- CMBI
- Radboud University Nijmegen
- Nijmegen
- The Netherlands
| | | | - Chris de Graaf
- Division of Medicinal Chemistry
- LACDR
- VU University Amsterdam
- Amsterdam
- The Netherlands
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27
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Löwer M, Geppert T, Schneider P, Hoy B, Wessler S, Schneider G. Inhibitors of Helicobacter pylori protease HtrA found by 'virtual ligand' screening combat bacterial invasion of epithelia. PLoS One 2011; 6:e17986. [PMID: 21483848 PMCID: PMC3069028 DOI: 10.1371/journal.pone.0017986] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2010] [Accepted: 02/17/2011] [Indexed: 02/03/2023] Open
Abstract
Background The human pathogen Helicobacter pylori (H. pylori) is a main cause for gastric inflammation and cancer. Increasing bacterial resistance against antibiotics demands for innovative strategies for therapeutic intervention. Methodology/Principal Findings We present a method for structure-based virtual screening that is based on the comprehensive prediction of ligand binding sites on a protein model and automated construction of a ligand-receptor interaction map. Pharmacophoric features of the map are clustered and transformed in a correlation vector (‘virtual ligand’) for rapid virtual screening of compound databases. This computer-based technique was validated for 18 different targets of pharmaceutical interest in a retrospective screening experiment. Prospective screening for inhibitory agents was performed for the protease HtrA from the human pathogen H. pylori using a homology model of the target protein. Among 22 tested compounds six block E-cadherin cleavage by HtrA in vitro and result in reduced scattering and wound healing of gastric epithelial cells, thereby preventing bacterial infiltration of the epithelium. Conclusions/Significance This study demonstrates that receptor-based virtual screening with a permissive (‘fuzzy’) pharmacophore model can help identify small bioactive agents for combating bacterial infection.
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Affiliation(s)
- Martin Löwer
- Institute of Organic Chemistry and Chemical Biology, Goethe-University, Frankfurt, Germany
| | - Tim Geppert
- Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Zürich, Switzerland
| | - Petra Schneider
- Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Zürich, Switzerland
| | - Benjamin Hoy
- Division of Microbiology, University of Salzburg, Salzburg, Austria
| | - Silja Wessler
- Division of Microbiology, University of Salzburg, Salzburg, Austria
| | - Gisbert Schneider
- Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Zürich, Switzerland
- * E-mail:
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Rinaldi M, Tintori C, Franchi L, Vignaroli G, Innitzer A, Massa S, Esté JA, Gonzalo E, Christ F, Debyser Z, Botta M. A versatile and practical synthesis toward the development of novel HIV-1 integrase inhibitors. ChemMedChem 2011; 6:343-52. [PMID: 21246739 DOI: 10.1002/cmdc.201000510] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2010] [Revised: 12/22/2010] [Indexed: 11/08/2022]
Abstract
As a continuation of our previous work, which resulted in the identification of a new hit compound as an HIV-1 integrase inhibitor, three novel series of salicylic acid derivatives were synthesized using three versatile and practical synthetic strategies and were assayed for their capacity to inhibit the catalytic activity of HIV-1 integrase. Biological evaluations revealed that some of the synthesized compounds possess good inhibitory potency in enzymatic assays and are able to inhibit viral replication in MT-4 cells at low micromolar concentrations. Finally, docking studies were conducted to analyze the binding mode of the synthesized compounds within the DNA binding site of integrase in order to refine their structure-activity relationships.
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Affiliation(s)
- Marta Rinaldi
- Dipartimento Farmaco Chimico Tecnologico, Università degli Studi di Siena, Via A. De Gasperi 2, 53100 Siena, Italy
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Manetti F. LIM kinases are attractive targets with many macromolecular partners and only a few small molecule regulators. Med Res Rev 2011; 32:968-98. [PMID: 22886629 DOI: 10.1002/med.20230] [Citation(s) in RCA: 86] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The LIM kinases 1 and 2 (LIMK1 and LIMK2) are dual specificity (serine/threonine and tyrosine) kinases. Although they show significant structural similarity, LIMK1 and LIMK2 show different expression, subcellular localization, and functions. They are involved in many cellular functions, such as migration, cycle, and neuronal differentiation and also have a role in pathological processes, such as cancer cell invasion and metastatis, as well as in neurodevelopmental disorders (namely, the William's syndrome). LIM kinases have a relevant number of known partners that are able to induce or limit the ability of LIMK1 and LIMK2 to phosphorylate and inactivate their major substrate, cofilin. On the contrary, only a limited number of small molecules that interact with the two proteins to modulate their kinase activity have been identified. In this review, the most important partners of LIM kinases and their modulating activity toward LIMKs are described. The small compounds identified as LIMK1 and LIMK2 modulators are also reported, as well as their role as possible therapeutic agents for LIMK-induced diseases.
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Affiliation(s)
- Fabrizio Manetti
- Dipartimento Farmaco Chimico Tecnologico, Università degli Studi di Siena, via Alcide de Gasperi 2, I-53100 Siena, Italy.
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Abstract
This chapter is a review of the most recent developments in the field of pharmacophore modeling, covering both methodology and application. Pharmacophore-based virtual screening is nowadays a mature technology, very well accepted in the medicinal chemistry laboratory. Nevertheless, like any empirical approach, it has specific limitations and efforts to improve the methodology are still ongoing. Fundamentally, the core idea of "stripping" functional groups of their actual chemical nature in order to classify them into very few pharmacophore types, according to their dominant physico-chemical features, is both the main advantage and the main drawback of pharmacophore modeling. The advantage is the one of simplicity - the complex nature of noncovalent ligand binding interactions is rendered intuitive and comprehensible by the human mind. Although computers are much better suited for comparisons of pharmacophore patterns, a chemist's intuition is primarily scaffold-oriented. Its underlying simplifications render pharmacophore modeling unable to provide perfect predictions of ligand binding propensities - not even if all its subsisting technical problems would be solved. Each step in pharmacophore modeling and exploitation has specific drawbacks: from insufficient or inaccurate conformational sampling to ambiguities in pharmacophore typing (mainly due to uncertainty regarding the tautomeric/protonation status of compounds), to computer time limitations in complex molecular overlay calculations, and to the choice of inappropriate anchoring points in active sites when ligand cocrystals structures are not available. Yet, imperfections notwithstanding, the approach is accurate enough in order to be practically useful and actually is the most used virtual screening technique in medicinal chemistry - notably for "scaffold hopping" approaches, allowing the discovery of new chemical classes carriers of a desired biological activity.
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Affiliation(s)
- Dragos Horvath
- Laboratoire d'InfoChime, UMR 7177, Université de Strasbourg - CNRSInstitut de Chimie, Strasbourg, France
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31
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Ziarek JJ, Peterson FC, Lytle BL, Volkman BF. Binding site identification and structure determination of protein-ligand complexes by NMR a semiautomated approach. Methods Enzymol 2011; 493:241-75. [PMID: 21371594 PMCID: PMC3635485 DOI: 10.1016/b978-0-12-381274-2.00010-8] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Over the last 15 years, the role of NMR spectroscopy in the lead identification and optimization stages of pharmaceutical drug discovery has steadily increased. NMR occupies a unique niche in the biophysical analysis of drug-like compounds because of its ability to identify binding sites, affinities, and ligand poses at the level of individual amino acids without necessarily solving the structure of the protein-ligand complex. However, it can also provide structures of flexible proteins and low-affinity (K(d)>10(-6)M) complexes, which often fail to crystallize. This chapter emphasizes a throughput-focused protocol that aims to identify practical aspects of binding site characterization, automated and semiautomated NMR assignment methods, and structure determination of protein-ligand complexes by NMR.
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Affiliation(s)
- Joshua J. Ziarek
- Department of Biochemistry, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, Wisconsin, 53226 USA
| | - Francis C. Peterson
- Department of Biochemistry, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, Wisconsin, 53226 USA
| | - Betsy L. Lytle
- Department of Biochemistry, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, Wisconsin, 53226 USA
| | - Brian F. Volkman
- Department of Biochemistry, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, Wisconsin, 53226 USA
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Agamennone M, Cesari L, Lalli D, Turlizzi E, Del Conte R, Turano P, Mangani S, Padova A. Fragmenting the S100B-p53 interaction: combined virtual/biophysical screening approaches to identify ligands. ChemMedChem 2010; 5:428-35. [PMID: 20077460 DOI: 10.1002/cmdc.200900393] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
S100B contributes to cell proliferation by binding the C terminus of p53 and inhibiting its tumor suppressor function. The use of multiple computational approaches to screen fragment libraries targeting the human S100B-p53 interaction site is reported. This in silico screening led to the identification of 280 novel prospective ligands. NMR spectroscopic experiments revealed specific binding at the p53 interaction site for a set of these compounds and confirmed their potential for further rational optimization. The X-ray crystal structure determined for one of the binders revealed key intermolecular interactions, thus paving the way for structure-based ligand optimization.
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Affiliation(s)
- Mariangela Agamennone
- Dipartimento di Scienze del Farmaco, Università "G. d'Annunzio", Via dei Vestini, 66013 Chieti, Italy
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Leach AR, Gillet VJ, Lewis RA, Taylor R. Three-dimensional pharmacophore methods in drug discovery. J Med Chem 2010; 53:539-58. [PMID: 19831387 DOI: 10.1021/jm900817u] [Citation(s) in RCA: 245] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Andrew R Leach
- Computational and Structural Chemistry, GlaxoSmithKline Research & Development, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, UK.
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Cross S, Cruciani G. Grid-derived structure-based 3D pharmacophores and their performance compared to docking. DRUG DISCOVERY TODAY. TECHNOLOGIES 2010; 7:e203-e270. [PMID: 24103797 DOI: 10.1016/j.ddtec.2010.09.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
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Valadares NF, Salum LB, Polikarpov I, Andricopulo AD, Garratt RC. Role of Halogen Bonds in Thyroid Hormone Receptor Selectivity: Pharmacophore-Based 3D-QSSR Studies. J Chem Inf Model 2009; 49:2606-16. [DOI: 10.1021/ci900316e] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Napoleão F. Valadares
- Centro de Biotecnologia Molecular Estrutural, Departamento de Física e Informática, Instituto de Física de São Carlos, Universidade de São Paulo, Av. Trabalhador São-Carlense 400, 13560-970 São Carlos-SP, Brazil
| | - Lívia B. Salum
- Centro de Biotecnologia Molecular Estrutural, Departamento de Física e Informática, Instituto de Física de São Carlos, Universidade de São Paulo, Av. Trabalhador São-Carlense 400, 13560-970 São Carlos-SP, Brazil
| | - Igor Polikarpov
- Centro de Biotecnologia Molecular Estrutural, Departamento de Física e Informática, Instituto de Física de São Carlos, Universidade de São Paulo, Av. Trabalhador São-Carlense 400, 13560-970 São Carlos-SP, Brazil
| | - Adriano D. Andricopulo
- Centro de Biotecnologia Molecular Estrutural, Departamento de Física e Informática, Instituto de Física de São Carlos, Universidade de São Paulo, Av. Trabalhador São-Carlense 400, 13560-970 São Carlos-SP, Brazil
| | - Richard C. Garratt
- Centro de Biotecnologia Molecular Estrutural, Departamento de Física e Informática, Instituto de Física de São Carlos, Universidade de São Paulo, Av. Trabalhador São-Carlense 400, 13560-970 São Carlos-SP, Brazil
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Rajamaki S, Innitzer A, Falciani C, Tintori C, Christ F, Witvrouw M, Debyser Z, Massa S, Botta M. Exploration of novel thiobarbituric acid-, rhodanine- and thiohydantoin-based HIV-1 integrase inhibitors. Bioorg Med Chem Lett 2009; 19:3615-8. [PMID: 19447621 DOI: 10.1016/j.bmcl.2009.04.132] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2009] [Revised: 04/24/2009] [Accepted: 04/25/2009] [Indexed: 11/26/2022]
Abstract
A novel compound inhibiting HIV-1 integrase has been identified by means of virtual screening techniques. A small family of structurally related molecules has been synthesized and biologically evaluated with some of the compounds possessing micromolar activity both in enzymatic and cellular assays.
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Affiliation(s)
- Suvi Rajamaki
- Dipartimento Farmaco Chimico Tecnologico, Università degli Studi di Siena, Via A. De Gasperi 2, I-53100 Siena, Italy
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