1
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Boucherit H, Chikhi A, Bensegueni A, Merzoug A, Bolla JM. The Research of New Inhibitors of Bacterial Methionine Aminopeptidase by Structure Based Virtual Screening Approach of ZINC DATABASE and In Vitro Validation. Curr Comput Aided Drug Des 2021; 16:389-401. [PMID: 31244429 DOI: 10.2174/1573409915666190617165643] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 04/26/2019] [Accepted: 05/06/2019] [Indexed: 01/13/2023]
Abstract
BACKGROUND The great emergence of multi-resistant bacterial strains and the low renewal of antibiotics molecules are leading human and veterinary medicine to certain therapeutic impasses. Therefore, there is an urgent need to find new therapeutic alternatives including new molecules in the current treatments of infectious diseases. Methionine aminopeptidase (MetAP) is a promising target for developing new antibiotics because it is essential for bacterial survival. OBJECTIVE To screen for potential MetAP inhibitors by in silico virtual screening of the ZINC database and evaluate the best potential lead molecules by in vitro studies. METHODS We have considered 200,000 compounds from the ZINC database for virtual screening with FlexX software to identify potential inhibitors against bacterial MetAP. Nine chemical compounds of the top hits predicted were purchased and evaluated in vitro. The antimicrobial activity of each inhibitor of MetAP was tested by the disc-diffusion assay against one Gram-positive (Staphylococcus aureus) and two Gram-negative (Escherichia coli & Pseudomonas aeruginosa) bacteria. Among the studied compounds, compounds ZINC04785369 and ZINC03307916 showed promising antibacterial activity. To further characterize their efficacy, the minimum inhibitory concentration was determined for each compound by the microdilution method which showed significant results. RESULTS These results suggest compounds ZINC04785369 and ZINC03307916 as promising molecules for developing MetAP inhibitors. CONCLUSION Furthermore, they could therefore serve as lead molecules for further chemical modifications to obtain clinically useful antibacterial agents.
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Affiliation(s)
- Hanane Boucherit
- Laboratory of Applied Biochemistry, Department of Biochemistry and Cellular and Molecular Biology, Faculty of Natural and Life Sciences, Mentouri Brothers University, Constantine 1, Algeria
| | - Abdelouahab Chikhi
- Laboratory of Applied Biochemistry, Department of Biochemistry and Cellular and Molecular Biology, Faculty of Natural and Life Sciences, Mentouri Brothers University, Constantine 1, Algeria
| | - Abderrahmane Bensegueni
- Laboratory of Applied Biochemistry, Department of Biochemistry and Cellular and Molecular Biology, Faculty of Natural and Life Sciences, Mentouri Brothers University, Constantine 1, Algeria
| | - Amina Merzoug
- Laboratory of Applied Biochemistry, Department of Biochemistry and Cellular and Molecular Biology, Faculty of Natural and Life Sciences, Mentouri Brothers University, Constantine 1, Algeria
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2
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Data-science based analysis of perceptual spaces of odors in olfactory loss. Sci Rep 2021; 11:10595. [PMID: 34012047 PMCID: PMC8134481 DOI: 10.1038/s41598-021-89969-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 04/26/2021] [Indexed: 11/26/2022] Open
Abstract
Diminished sense of smell impairs the quality of life but olfactorily disabled people are hardly considered in measures of disability inclusion. We aimed to stratify perceptual characteristics and odors according to the extent to which they are perceived differently with reduced sense of smell, as a possible basis for creating olfactory experiences that are enjoyed in a similar way by subjects with normal or impaired olfactory function. In 146 subjects with normal or reduced olfactory function, perceptual characteristics (edibility, intensity, irritation, temperature, familiarity, hedonics, painfulness) were tested for four sets of 10 different odors each. Data were analyzed with (i) a projection based on principal component analysis and (ii) the training of a machine-learning algorithm in a 1000-fold cross-validated setting to distinguish between olfactory diagnosis based on odor property ratings. Both analytical approaches identified perceived intensity and familiarity with the odor as discriminating characteristics between olfactory diagnoses, while evoked pain sensation and perceived temperature were not discriminating, followed by edibility. Two disjoint sets of odors were identified, i.e., d = 4 “discriminating odors” with respect to olfactory diagnosis, including cis-3-hexenol, methyl salicylate, 1-butanol and cineole, and d = 7 “non-discriminating odors”, including benzyl acetate, heptanal, 4-ethyl-octanoic acid, methional, isobutyric acid, 4-decanolide and p-cresol. Different weightings of the perceptual properties of odors with normal or reduced sense of smell indicate possibilities to create sensory experiences such as food, meals or scents that by emphasizing trigeminal perceptions can be enjoyed by both normosmic and hyposmic individuals.
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3
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Hoffer L, Muller C, Roche P, Morelli X. Chemistry-driven Hit-to-lead Optimization Guided by Structure-based Approaches. Mol Inform 2018; 37:e1800059. [PMID: 30051601 DOI: 10.1002/minf.201800059] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Accepted: 06/24/2018] [Indexed: 12/17/2022]
Abstract
For several decades, hit identification for drug discovery has been facilitated by developments in both fragment-based and high-throughput screening technologies. However, a major bottleneck in drug discovery projects continues to be the optimization of primary hits from screening campaigns in order to derive lead compounds. Computational chemistry or molecular modeling can play an important role during this hit-to-lead (H2L) stage by both suggesting putative optimizations and decreasing the number of compounds to be experimentally synthesized and evaluated. However, it is also crucial to consider the feasibility of organically synthesizing these virtually designed compounds. Furthermore, the generated molecules should have reasonable physicochemical properties and be medicinally relevant. This review focuses on chemistry-driven and structure-based computational methods that can be used to tackle the difficult problem of H2L optimization, with emphasis being placed on the strategy developed in our laboratory.
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Affiliation(s)
- Laurent Hoffer
- CNRS, Inserm, Institut Paoli-Calmettes, Aix-Marseille Univ, CRCM, Marseille, France
| | | | - Philippe Roche
- CNRS, Inserm, Institut Paoli-Calmettes, Aix-Marseille Univ, CRCM, Marseille, France
| | - Xavier Morelli
- CNRS, Inserm, Institut Paoli-Calmettes, Aix-Marseille Univ, CRCM, Marseille, France.,Institut Paoli-Calmettes, IPC Drug Discovery, Marseille, France
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4
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Kratochvíl M, Vondrášek J, Galgonek J. Sachem: a chemical cartridge for high-performance substructure search. J Cheminform 2018; 10:27. [PMID: 29797000 PMCID: PMC5966370 DOI: 10.1186/s13321-018-0282-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 05/16/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Structure search is one of the valuable capabilities of small-molecule databases. Fingerprint-based screening methods are usually employed to enhance the search performance by reducing the number of calls to the verification procedure. In substructure search, fingerprints are designed to capture important structural aspects of the molecule to aid the decision about whether the molecule contains a given substructure. Currently available cartridges typically provide acceptable search performance for processing user queries, but do not scale satisfactorily with dataset size. RESULTS We present Sachem, a new open-source chemical cartridge that implements two substructure search methods: The first is a performance-oriented reimplementation of substructure indexing based on the OrChem fingerprint, and the second is a novel method that employs newly designed fingerprints stored in inverted indices. We assessed the performance of both methods on small, medium, and large datasets containing 1, 10, and 94 million compounds, respectively. Comparison of Sachem with other freely available cartridges revealed improvements in overall performance, scaling potential and screen-out efficiency. CONCLUSIONS The Sachem cartridge allows efficient substructure searches in databases of all sizes. The sublinear performance scaling of the second method and the ability to efficiently query large amounts of pre-extracted information may together open the door to new applications for substructure searches.
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Affiliation(s)
- Miroslav Kratochvíl
- Institute of Organic Chemistry and Biochemistry of the CAS, Flemingovo náměstí 2, Prague 6, 166 10, Czech Republic.,Department of Software Engineering, Faculty of Mathematics and Physics, Charles University, Malostranské náměstí 25, Prague 1, 118 00, Czech Republic
| | - Jiří Vondrášek
- Institute of Organic Chemistry and Biochemistry of the CAS, Flemingovo náměstí 2, Prague 6, 166 10, Czech Republic
| | - Jakub Galgonek
- Institute of Organic Chemistry and Biochemistry of the CAS, Flemingovo náměstí 2, Prague 6, 166 10, Czech Republic.
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5
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Nalla V, Shaikh A, Bapat S, Vyas R, Karthikeyan M, Yogeeswari P, Sriram D, Muthukrishnan M. Identification of potent chromone embedded [1,2,3]-triazoles as novel anti-tubercular agents. ROYAL SOCIETY OPEN SCIENCE 2018; 5:171750. [PMID: 29765644 PMCID: PMC5936909 DOI: 10.1098/rsos.171750] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Accepted: 03/09/2018] [Indexed: 05/06/2023]
Abstract
A series of 20 novel chromone embedded [1,2,3]-triazoles derivatives were synthesized via an easy and convenient synthetic procedure starting from 2-hydroxy acetophenone. The in vitro anti-mycobacterial evaluation studies carried out in this work reveal that seven compounds exhibit significant inhibition against Mycobacterium tuberculosis H37Rv strain with MIC in the range of 1.56-12.5 µg ml-1. Noticeably, compound 6s was the most potent compound in vitro with a MIC value of 1.56 µg ml-1. Molecular docking and chemoinformatics studies revealed that compound 6s displayed drug-like properties against the enoyl-acyl carrier protein reductase of M. tuberculosis further establishing its potential as a potent inhibitor.
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Affiliation(s)
- Viswanadh Nalla
- CSIR-National Chemical Laboratory, Dr Homi Bhabha Road, Pune 411008, India
- Academy of Scientific and Innovative Research (AcSIR), New Delhi 110 025, India
| | - Aslam Shaikh
- CSIR-National Chemical Laboratory, Dr Homi Bhabha Road, Pune 411008, India
- Academy of Scientific and Innovative Research (AcSIR), New Delhi 110 025, India
| | - Sanket Bapat
- MIT School of Bioengineering Sciences and Research, MIT Art, Design and Technology University, Pune 412 201, India
| | - Renu Vyas
- MIT School of Bioengineering Sciences and Research, MIT Art, Design and Technology University, Pune 412 201, India
| | - M. Karthikeyan
- CSIR-National Chemical Laboratory, Dr Homi Bhabha Road, Pune 411008, India
- Academy of Scientific and Innovative Research (AcSIR), New Delhi 110 025, India
| | - P. Yogeeswari
- Tuberculosis Drug Discovery Laboratory, Pharmacy Group, Birla Institute of Technology and Science-Pilani, Hyderabad Campus, Hyderabad 500 0078, India
| | - D. Sriram
- Tuberculosis Drug Discovery Laboratory, Pharmacy Group, Birla Institute of Technology and Science-Pilani, Hyderabad Campus, Hyderabad 500 0078, India
| | - M. Muthukrishnan
- CSIR-National Chemical Laboratory, Dr Homi Bhabha Road, Pune 411008, India
- Academy of Scientific and Innovative Research (AcSIR), New Delhi 110 025, India
- Author for correspondence: M. Muthukrishnan e-mail:
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6
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Honegr J, Malinak D, Dolezal R, Soukup O, Benkova M, Hroch L, Benek O, Janockova J, Kuca K, Prymula R. Rational design of novel TLR4 ligands by in silico screening and their functional and structural characterization in vitro. Eur J Med Chem 2018; 146:38-46. [PMID: 29407964 DOI: 10.1016/j.ejmech.2017.12.074] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Revised: 12/20/2017] [Accepted: 12/21/2017] [Indexed: 12/31/2022]
Abstract
The purpose of this study was to identify new small molecules that possess activity on human toll-like receptor 4 associated with the myeloid differentiation protein 2 (hTLR4/MD2). Following current rational drug design principles, we firstly performed a ligand and structure based virtual screening of more than 130 000 compounds to discover until now unknown class of hTLR4/MD2 modulators that could be used as novel type of immunologic adjuvants. The core of the in silico study was molecular docking of flexible ligands in a partially flexible hTLR4/MD2 receptor model using a peta-flops-scale supercomputer. The most promising substances resulting from this study, related to anthracene-succimide hybrids, were synthesized and tested. The best prepared candidate exhibited 80% of Monophosphoryl Lipid A in vitro agonistic activity in cell lines expressing hTLR4/MD2.
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Affiliation(s)
- Jan Honegr
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic; Department of Intensive Medicine and Forensic Science, Faculty of Medicine, University of Ostrava, Syllabova 19, 703 00 Ostrava, Czech Republic
| | - David Malinak
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic; Department of Chemistry, Faculty of Science, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic
| | - Rafael Dolezal
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic; Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic; Department of Chemistry, Faculty of Science, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic
| | - Ondrej Soukup
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic
| | - Marketa Benkova
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic
| | - Lukas Hroch
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic
| | - Ondrej Benek
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic; Department of Chemistry, Faculty of Science, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic
| | - Jana Janockova
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic
| | - Kamil Kuca
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic; Department of Chemistry, Faculty of Science, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic
| | - Roman Prymula
- Biomedical Research Centre, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic.
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7
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Ekins S, Clark AM, Dole K, Gregory K, Mcnutt AM, Spektor AC, Weatherall C, Litterman NK, Bunin BA. Data Mining and Computational Modeling of High-Throughput Screening Datasets. Methods Mol Biol 2018; 1755:197-221. [PMID: 29671272 DOI: 10.1007/978-1-4939-7724-6_14] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
We are now seeing the benefit of investments made over the last decade in high-throughput screening (HTS) that is resulting in large structure activity datasets entering public and open databases such as ChEMBL and PubChem. The growth of academic HTS screening centers and the increasing move to academia for early stage drug discovery suggests a great need for the informatics tools and methods to mine such data and learn from it. Collaborative Drug Discovery, Inc. (CDD) has developed a number of tools for storing, mining, securely and selectively sharing, as well as learning from such HTS data. We present a new web based data mining and visualization module directly within the CDD Vault platform for high-throughput drug discovery data that makes use of a novel technology stack following modern reactive design principles. We also describe CDD Models within the CDD Vault platform that enables researchers to share models, share predictions from models, and create models from distributed, heterogeneous data. Our system is built on top of the Collaborative Drug Discovery Vault Activity and Registration data repository ecosystem which allows users to manipulate and visualize thousands of molecules in real time. This can be performed in any browser on any platform. In this chapter we present examples of its use with public datasets in CDD Vault. Such approaches can complement other cheminformatics tools, whether open source or commercial, in providing approaches for data mining and modeling of HTS data.
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Affiliation(s)
- Sean Ekins
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, NC, 27606, USA.
| | - Alex M Clark
- Collaborative Drug Discovery, Inc., Burlingame, CA, USA
- Molecular Materials Informatics, Inc., Montreal, QC, Canada
| | - Krishna Dole
- Collaborative Drug Discovery, Inc., Burlingame, CA, USA
| | | | | | | | | | | | - Barry A Bunin
- Collaborative Drug Discovery, Inc., Burlingame, CA, USA
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8
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Mello JDFRE, Gomes RA, Vital-Fujii DG, Ferreira GM, Trossini GHG. Fragment-based drug discovery as alternative strategy to the drug development for neglected diseases. Chem Biol Drug Des 2017; 90:1067-1078. [PMID: 28547936 DOI: 10.1111/cbdd.13030] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Revised: 04/12/2017] [Accepted: 05/08/2017] [Indexed: 12/24/2022]
Abstract
Neglected diseases (NDs) affect large populations and almost whole continents, representing 12% of the global health burden. In contrast, the treatment available today is limited and sometimes ineffective. Under this scenery, the Fragment-Based Drug Discovery emerged as one of the most promising alternatives to the traditional methods of drug development. This method allows achieving new lead compounds with smaller size of fragment libraries. Even with the wide Fragment-Based Drug Discovery success resulting in new effective therapeutic agents against different diseases, until this moment few studies have been applied this approach for NDs area. In this article, we discuss the basic Fragment-Based Drug Discovery process, brief successful ideas of general applications and show a landscape of its use in NDs, encouraging the implementation of this strategy as an interesting way to optimize the development of new drugs to NDs.
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Affiliation(s)
- Juliana da Fonseca Rezende E Mello
- Litec, Laboratório de Integração Entre Técnicas Computacionais e Experimentais no Planejamento de Fármacos, Departamento de Farmácia, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, São Paulo, Brazil
| | - Renan Augusto Gomes
- Litec, Laboratório de Integração Entre Técnicas Computacionais e Experimentais no Planejamento de Fármacos, Departamento de Farmácia, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, São Paulo, Brazil
| | - Drielli Gomes Vital-Fujii
- Litec, Laboratório de Integração Entre Técnicas Computacionais e Experimentais no Planejamento de Fármacos, Departamento de Farmácia, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, São Paulo, Brazil
| | - Glaucio Monteiro Ferreira
- Litec, Laboratório de Integração Entre Técnicas Computacionais e Experimentais no Planejamento de Fármacos, Departamento de Farmácia, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, São Paulo, Brazil.,Programa de Pós-graduação em Toxicologia e Análises Toxicológicas, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, São Paulo, Brazil
| | - Gustavo Henrique Goulart Trossini
- Litec, Laboratório de Integração Entre Técnicas Computacionais e Experimentais no Planejamento de Fármacos, Departamento de Farmácia, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, São Paulo, Brazil.,Programa de Pós-graduação em Toxicologia e Análises Toxicológicas, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, São Paulo, Brazil
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9
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Viira B, García-Sosa AT, Maran U. Chemical structure and correlation analysis of HIV-1 NNRT and NRT inhibitors and database-curated, published inhibition constants with chemical structure in diverse datasets. J Mol Graph Model 2017; 76:205-223. [PMID: 28738270 DOI: 10.1016/j.jmgm.2017.06.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 06/18/2017] [Accepted: 06/19/2017] [Indexed: 01/26/2023]
Abstract
Human immunodeficiency virus (HIV-1) reverse transcriptase is a major target for designing anti-HIV drugs. Developed inhibitors are divided into non-nucleoside analog reverse-transcriptase inhibitors (NNRTIs) and nucleoside analog reverse-transcriptase inhibitors (NRTIs) depending on their mechanism. Given that many inhibitors have been studied and for many of them binding affinity constants have been calculated, it is beneficial to analyze the chemical landscape of these families of inhibitors and correlate these inhibition constants with molecular structure descriptors. For this, the HIV-1 RT data was retrieved from the ChEMBL database, carefully curated, and original literature verified, grouped into NRTIs and NNRTIs, analyzed using a hierarchical scaffold classification method and modelled with best multi-linear regression approach. Analysis of the HIV-1 NNRTIs subset results in ten different common structural parent types of oxazepanone, piperazinone, pyrazine, oxazinanone, diazinanone, pyridine, pyrrole, diazepanone, thiazole, and triazine. The same analysis for HIV-1 NRTIs groups structures into four different parent types of uracil, pyrimide, pyrimidione, and imidazole. Each scaffold tree corresponding to the parent types has been carefully analyzed and examined, and changes in chemical structure favorable to potency and stability are highlighted. For both subsets, descriptive and predictive QSAR models are derived, discussed and externally validated, revealing general trends in relationships between molecular structure and binding affinity constants in structurally diverse datasets. Data and QSAR models are available at the QsarDB repository (http://dx.doi.org/10.15152/QDB.202).
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Affiliation(s)
- Birgit Viira
- Institute of Chemistry, University of Tartu, Tartu 50411, Estonia
| | | | - Uko Maran
- Institute of Chemistry, University of Tartu, Tartu 50411, Estonia.
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10
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Schäfer T, Kriege N, Humbeck L, Klein K, Koch O, Mutzel P. Scaffold Hunter: a comprehensive visual analytics framework for drug discovery. J Cheminform 2017; 9:28. [PMID: 29086162 PMCID: PMC5425364 DOI: 10.1186/s13321-017-0213-3] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2016] [Accepted: 04/10/2017] [Indexed: 01/31/2023] Open
Abstract
The era of big data is influencing the way how rational drug discovery and the development of bioactive molecules is performed and versatile tools are needed to assist in molecular design workflows. Scaffold Hunter is a flexible visual analytics framework for the analysis of chemical compound data and combines techniques from several fields such as data mining and information visualization. The framework allows analyzing high-dimensional chemical compound data in an interactive fashion, combining intuitive visualizations with automated analysis methods including versatile clustering methods. Originally designed to analyze the scaffold tree, Scaffold Hunter is continuously revised and extended. We describe recent extensions that significantly increase the applicability for a variety of tasks.
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Affiliation(s)
- Till Schäfer
- Department of Computer Science, TU Dortmund University, Otto-Hahn-Str. 14, Dortmund, 44227, Germany
| | - Nils Kriege
- Department of Computer Science, TU Dortmund University, Otto-Hahn-Str. 14, Dortmund, 44227, Germany
| | - Lina Humbeck
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Str. 6, Dortmund, 44227, Germany
| | - Karsten Klein
- Department of Computer and Information Science, University of Konstanz, Universitaetsstrasse 10, Konstanz, 78464, Germany
| | - Oliver Koch
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Str. 6, Dortmund, 44227, Germany.
| | - Petra Mutzel
- Department of Computer Science, TU Dortmund University, Otto-Hahn-Str. 14, Dortmund, 44227, Germany.
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11
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Humbeck L, Koch O. What Can We Learn from Bioactivity Data? Chemoinformatics Tools and Applications in Chemical Biology Research. ACS Chem Biol 2017; 12:23-35. [PMID: 27779378 DOI: 10.1021/acschembio.6b00706] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The ever increasing bioactivity data that are produced nowadays allow exhaustive data mining and knowledge discovery approaches that change chemical biology research. A wealth of chemoinformatics tools, web services, and applications therefore exists that supports a careful evaluation and analysis of experimental data to draw conclusions that can influence the further development of chemical probes and potential lead structures. This review focuses on open-source approaches that can be handled by scientists who are not familiar with computational methods having no expert knowledge in chemoinformatics and modeling. Our aim is to present an easily manageable toolbox for support of every day laboratory work. This includes, among other things, the available bioactivity and related molecule databases as well as tools to handle and analyze in-house data.
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Affiliation(s)
- Lina Humbeck
- Faculty
of Chemistry and
Chemical Biology, TU Dortmund University, Otto-Hahn-Straße 6, 44227 Dortmund, Germany
| | - Oliver Koch
- Faculty
of Chemistry and
Chemical Biology, TU Dortmund University, Otto-Hahn-Straße 6, 44227 Dortmund, Germany
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12
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Abstract
The success of molecular modeling and computational chemistry efforts are, by definition, dependent on quality software applications. Open source software development provides many advantages to users of modeling applications, not the least of which is that the software is free and completely extendable. In this review we categorize, enumerate, and describe available open source software packages for molecular modeling and computational chemistry. An updated online version of this catalog can be found at https://opensourcemolecularmodeling.github.io.
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13
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Structure-based virtual screening of hypothetical inhibitors of the enzyme longiborneol synthase—a potential target to reduce Fusarium head blight disease. J Mol Model 2016; 22:163. [DOI: 10.1007/s00894-016-3021-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2015] [Accepted: 05/27/2016] [Indexed: 01/12/2023]
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14
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Genetic programming based quantitative structure–retention relationships for the prediction of Kovats retention indices. J Chromatogr A 2015; 1420:98-109. [DOI: 10.1016/j.chroma.2015.09.086] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2015] [Revised: 09/25/2015] [Accepted: 09/25/2015] [Indexed: 11/20/2022]
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15
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Hilbig M, Rarey M. MONA 2: A Light Cheminformatics Platform for Interactive Compound Library Processing. J Chem Inf Model 2015; 55:2071-8. [PMID: 26389652 DOI: 10.1021/acs.jcim.5b00292] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Because of the availability of large compound collections on the Web, elementary cheminformatics tasks such as chemical library browsing, analyzing, filtering, or unifying have become widespread in the life science community. Furthermore, the high performance of desktop hardware allows an interactive, problem-driven approach to these tasks, avoiding rigid processing scripts and workflows. Here, we present MONA 2, which is the second major release of our cheminformatics desktop application addressing this need. Using MONA requires neither complex database setups nor expert knowledge of cheminformatics. A new molecular set concept purely based on structural entities rather than individual compounds has allowed the development of an intuitive user interface. Based on a chemically precise, high-performance software library, typical tasks on chemical libraries with up to one million compounds can be performed mostly interactively. This paper describes the functionality of MONA, its fundamental concepts, and a collection of application scenarios ranging from file conversion, compound library curation, and management to the post-processing of large-scale experiments.
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Affiliation(s)
- Matthias Hilbig
- University of Hamburg, Center for Bioinformatics , Research Group for Computational Molecular Design, Bundesstraße 43, 20146 Hamburg, Germany
| | - Matthias Rarey
- University of Hamburg, Center for Bioinformatics , Research Group for Computational Molecular Design, Bundesstraße 43, 20146 Hamburg, Germany
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Osolodkin DI, Radchenko EV, Orlov AA, Voronkov AE, Palyulin VA, Zefirov NS. Progress in visual representations of chemical space. Expert Opin Drug Discov 2015; 10:959-73. [DOI: 10.1517/17460441.2015.1060216] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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17
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Warr WA. Many InChIs and quite some feat. J Comput Aided Mol Des 2015; 29:681-94. [PMID: 26081259 DOI: 10.1007/s10822-015-9854-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Accepted: 06/10/2015] [Indexed: 12/14/2022]
Affiliation(s)
- Wendy A Warr
- Wendy Warr & Associates, Holmes Chapel, Crewe, Cheshire, CW4 7HZ, UK,
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Mujahid M, Yogeeswari P, Sriram D, Basavanag UMV, Díaz-Cervantes E, Córdoba-Bahena L, Robles J, Gonnade RG, Karthikeyan M, Vyas R, Muthukrishnan M. Spirochromone-chalcone conjugates as antitubercular agents: synthesis, bio evaluation and molecular modeling studies. RSC Adv 2015. [DOI: 10.1039/c5ra21737g] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
We report new spiro chromone scaffold derived molecules possessing in vitro anti-tubercular activities. QSAR based molecular modeling studies correlated the bioactivities with the frontier molecular orbital energies.
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Affiliation(s)
- M. Mujahid
- CSIR-National Chemical Laboratory
- Pune
- India
| | - P. Yogeeswari
- Medicinal Chemistry & Antimycobacterial Research Laboratory
- Pharmacy Group
- Birla Institute of Technology & Science – Pilani
- Hyderabad 500 078
- India
| | - D. Sriram
- Medicinal Chemistry & Antimycobacterial Research Laboratory
- Pharmacy Group
- Birla Institute of Technology & Science – Pilani
- Hyderabad 500 078
- India
| | - U. M. V. Basavanag
- Departamento de Química y Departamento de Farmacia
- Universidad de Guanajuato
- Guanajuato
- Mexico
| | - Erik Díaz-Cervantes
- Departamento de Química y Departamento de Farmacia
- Universidad de Guanajuato
- Guanajuato
- Mexico
| | - Luis Córdoba-Bahena
- Departamento de Química y Departamento de Farmacia
- Universidad de Guanajuato
- Guanajuato
- Mexico
| | - Juvencio Robles
- Departamento de Química y Departamento de Farmacia
- Universidad de Guanajuato
- Guanajuato
- Mexico
| | | | | | - Renu Vyas
- CSIR-National Chemical Laboratory
- Pune
- India
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Abstract
Background Sound statistical validation is important to evaluate and compare the overall performance of (Q)SAR models. However, classical validation does not support the user in better understanding the properties of the model or the underlying data. Even though, a number of visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allow the investigation of model validation results are still lacking. Results We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. The approach applies the 3D viewer CheS-Mapper, an open-source application for the exploration of small molecules in virtual 3D space. The present work describes the new functionalities in CheS-Mapper 2.0, that facilitate the analysis of (Q)SAR information and allows the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. The approach is generic: It is model-independent and can handle physico-chemical and structural input features as well as quantitative and qualitative endpoints. Conclusions Visual validation with CheS-Mapper enables analyzing (Q)SAR information in the data and indicates how this information is employed by the (Q)SAR model. It reveals, if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at http://ches-mapper.org. Graphical abstract Comparing actual and predicted activity values with CheS-Mapper.
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Focused chemical libraries--design and enrichment: an example of protein-protein interaction chemical space. Future Med Chem 2014; 6:1291-307. [PMID: 24773599 DOI: 10.4155/fmc.14.57] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
One of the many obstacles in the development of new drugs lies in the limited number of therapeutic targets and in the quality of screening collections of compounds. In this review, we present general strategies for building target-focused chemical libraries with a particular emphasis on protein-protein interactions (PPIs). We describe the chemical spaces spanned by nine commercially available PPI-focused libraries and compare them to our 2P2I3D academic library, dedicated to orthosteric PPI modulators. We show that although PPI-focused libraries have been designed using different strategies, they share common subspaces. PPI inhibitors are larger and more hydrophobic than standard drugs; however, an effort has been made to improve the drug-likeness of focused chemical libraries dedicated to this challenging class of targets.
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Recent Advances in the Open Access Cheminformatics Toolkits, Software Tools, Workflow Environments, and Databases. METHODS IN PHARMACOLOGY AND TOXICOLOGY 2014. [DOI: 10.1007/7653_2014_35] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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Klein K, Koch O, Kriege N, Mutzel P, Schäfer T. Visual Analysis of Biological Activity Data with Scaffold Hunter. Mol Inform 2013; 32:964-75. [DOI: 10.1002/minf.201300087] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2013] [Accepted: 07/25/2013] [Indexed: 02/03/2023]
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Neves BJ, Bueno RV, Braga RC, Andrade CH. Discovery of new potential hits of Plasmodium falciparum enoyl-ACP reductase through ligand- and structure-based drug design approaches. Bioorg Med Chem Lett 2013; 23:2436-41. [DOI: 10.1016/j.bmcl.2013.02.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2012] [Revised: 01/21/2013] [Accepted: 02/01/2013] [Indexed: 11/16/2022]
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