Protocol Exchange

Author Information

Subject Terms

Keywords

Abstract

Introduction & Materials

Procedures

Outcomes

Conflicting Financial Interests

Associated Publications

Supplementary Files

Figures

Matthew Berriman

Avril Coghlan

Prudence Mutowo

Noel O'Boyle

Jane Lomax

Andrew R. Leach

Figure 1

Creating a screening set of potential anthelmintic compounds using ChEMBL

Many existing anthelmintic compounds are compromised by low efficacy, serious side-effects and/or rising resistance in parasite populations. Thus, to reveal potential new anthelmintic drug targets and drugs, we describe a protocol to identify the most promising nematode/flatworm targets, and compounds likely to interact with them from the ChEMBL database \(Gaulton _et al._ 2017), includes both targets of known drugs and of other biologically active compounds. Thus, this provides a potential screening set of drug-like compounds that can be tested for anthelmintic activity.





Our protocol \(Figure 1) starts by using predicted proteins from nematode and platyhelminth genomes to search using BLASTP \(E ≤ 1e-10) \(Altschul _et al._ 1997) against single-protein targets from ChEMBL. To remove redundant hits, the nematode and platyhelminth proteins with significant BLAST hits are collapsed by gene family using an in-house database of gene families \(e.g. built the Ensembl Compara pipeline; Vilella _et al._ 2009). Then, a ‘target score’ is calculated for each worm gene, taking into account similarity to known drug targets; lack of human homologues; and whether _C. elegans_ and _D. melanogaster_ homologues have lethal phenotypes, amongst other factors.





<a href="https://www.nature.com/protocolexchange/system/uploads/6593/original/Figure1.gif?1523716990"><img src="https://www.nature.com/protocolexchange/system/uploads/6593/original/Figure1.gif?1523716990"></a>





**Figure 1. Flowchart of the methods used for identifying potential new anthelmintic targets and drugs using ChEMBL.** The following images were used from Openclipart: ‘prescription-bottle-and-pills’ \(by algotruneman), ‘famous-and-infamous-molecules-13’ \(by Firkin) and ‘worm-gusano’ \(by ainara14).





Next, ChEMBL is used to identify hundreds of thousands of compounds with activities against ChEMBL targets to which worm proteins had BLAST matches. To calculate ‘compound scores’ for those compounds, we prioritise compounds in high clinical development phases, oral/topical administration, crystal structures, properties consistent with oral drugs, and lacking toxicity. At this stage, we focus on the compounds for the top 15% of highest-scoring worm targets, as these are the most promising novel targets. The set of compounds is filtered by selecting compounds that co-appear in a PDBe \(Velankar _et al._) structure with the ChEMBL target; or have high median pChEMBL score, reflecting high potency/affinity for the ChEMBL target. 





Lastly, the candidates are placed into chemical classes, based on molecular fingerprints. Then they are further filtered by \(i) checking availability for purchase in ZINC 15 \(Sterling _et al._ 2015); and \(ii) for each worm target, taking the highest-scoring compound from each chemical class.





This gives a relatively small diverse screening set of a few thousand compounds.





Many previous analyses of nematode and platyhelminth genomes have identified potential novel drug targets among their predicted proteins, and prioritised these based on factors such as lethal knockout phenotypes. However, relatively few previous studies have identified compounds predicted to target those nematode/platyhelminth proteins, and those that have done so \(e.g. Berriman _et al._ 2009) have generally been limited to small numbers of compounds. By analysing the huge wealth of data in the ChEMBL database, this protocol produces much larger sets of compounds to screen for anthelmintic activity.

<a href="https://www.ebi.ac.uk/chembl">ChEMBL database website</a>





<a href="http://www.ebi.ac.uk/pdbe/">PDBe database website</a>





<a href="http://zinc15.docking.org">ZINC15 database website</a>





<a href="https://www.ensembl.org/info/docs/webcode/mirror/index.html">Ensembl Compara pipeline</a>





<a href="http://www.ebi.ac.uk/ena">European Nucleotide Archive website</a>





 <a href="https://www.ebi.ac.uk/arrayexpress">ArrayExpress website</a>





<a href="https://pubchem.ncbi.nlm.nih.gov">PubChem database website</a>





<a href="http://www.genome.jp/kegg/drug">KEGG Drugs database website</a>





<a href="https://www.drugbank.ca">DrugBank database website</a> 





<a href="https://www.ebi.ac.uk/chebi">ChEBI database website</a>





<a href="https://www.wormbase.org">WormBase database website</a>





<a href="http://flybase.org">FlyBase database website</a>

The output from the procedure is a diverse screening set of several thousand compounds from ChEMBL \(including both approved drugs and medicinal chemistry compounds), and their putative targets in nematodes/platyhelminths.

Allegretti, S. M. _et al._ The Use of Brazilian Medicinal Plants to Combat _Schistosoma mansoni_. In _Schistosomiasis_, InTech. \(2012).





Altschul, S.F. _et al._ Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. _Nucleic acids res._ **25**, 3389-3402 \(1997).





Anand, N. and S. Sharma, Eds. _Approaches to Design and Synthesis of Antiparasitic Drugs_, Elsevier Science \(1997).





Anders, S. _et al._ Detecting differential usage of exons from RNA-seq data. _Genome res._ **22**, 2008-2017 \(2012).





Anders, S. _et al._ HTSeq--a Python framework to work with high-throughput sequencing data. _Bioinformatics_ **31**, 166-169 \(2015).





Aynaud, T. Community detection for NetworkX’s documentation, <a href="http://perso.crans.org/aynaud/communities/index.html">perso.crans.org/aynaud/communities/index.html</a> \(2009).





Berriman _et al._ The genome of the blood fluke _Schistosoma mansoni_. _Nature_. **460**, 352-358 \(2009).





Bickerton, G.R. _et al._ Quantifying the chemical beauty of drugs. _Nat Chem._ **4**, 90-98 \(2012).





Blondel, V. D. _et al._ Fast unfolding of communities in large networks. _J. Stat. Mechanics-Theory and Experiment_ **2008 \(10)**, P10008 \(2008).





Capra, J.A. & Singh, M. Predicting functionally important residues from sequence conservation. _Bioinformatics_ **23**, 1875-1882 \(2007).





Dalke, A. chemfp - fast and portable fingerprint formats and tools. _Journal of Cheminformatics_ **3\(Suppl 1)** \(2011).





Elks, J., Ed. _The Dictionary of Drugs: Chemical Data_, Springer US \(1990).





Gaulton, A. _et al_. The ChEMBL database in 2017. _Nucleic acids res._ **45**, D945-D954 \(2017).


 


Grieve, M. _A Modern Herbal: The Complete Edition_, Stone Basin Books \(2015).





Hastings, J. _et al._ ChEBI in 2016: Improved services and an expanding collection of metabolites. _Nucleic acids res._ **44**, D1214-D1219 \(2016).





Holden-Dye, L. & Walker, R.J. Anthelmintic drugs and nematicides: studies in _Caenorhabditis elegans._ _WormBook_, 1-29 \(2014).





Howe, K.L. _et al._ WormBase 2016: expanding to enable helminth genomic research. _Nucleic acids res._ **44**, D774-D780 \(2016).





Howe, K.L. _et al._ WormBase ParaSite - a comprehensive resource for helminth genomics. _Molecular and biochemical parasitology_ **215**, 2-10 \(2017).





Kanehisa, M. Molecular network analysis of diseases and drugs in KEGG. _Methods Mol. Biol._ **939**, 263-275 \(2013).





Kim, S. _et al._ PubChem Substance and Compound databases. _Nucleic acids res._ **44**, D1202-1213 \(2016).





Law, V. _et al._ DrugBank 4.0: shedding new light on drug metabolism. _Nucleic acids res._ **42**, D1091-1097 \(2014).





Lewis, R. A. _Lewis’ Dictionary of Toxicology_, CRC Press \(1998).





Lowe, D.M. _et al._ Chemical Name to Structure: OPSIN, an Open Source Solution. _Journal of Chemical Information and Modeling_ **51**, 739-753 \(2011).





Marr, J. J. _et al._, Eds.  _Molecular Medical Parasitology_, Academic Press \(2003).





Mehlhorn, H., Ed. _Encyclopedia of Parasitology_, Springer \(2008).


 


Millburn, G.H. _et al._ FlyBase portals to human disease research using _Drosophila_ models. _Dis. Model Mech._ **9**, 245-252 \(2016).





Moffat, A. _et al._, Eds. _Clarke's Analysis of Drugs and Poisons_, Pharmaceutical Press \(2011).





Oliver-Bever, B. Medicinal plants in tropical West Africa. III. Anti-infection therapy with higher plants. _J. Ethnopharmacol._ **9**, 1-83 \(1983).





Oprea, T.I. & Overington, J.P. Computational and Practical Aspects of Drug Repositioning. _Assay Drug Dev. Technol._ **13**, 299-306 \(2015).





Sterling, T. & Irwin, J. J. ZINC 15--Ligand Discovery for Everyone. _J. Chem. Inf. Model._ **55**, 2324-2337 \(2015).





Trapnell, C. _et al._ Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. _Nat. Protoc._ **7**, 562-578 \(2012).





Tyagi, R. _et al._ Comparative analysis of metabolism in parasitic worms. _Protocol Exchange_ \(2018).





Velankar, S. _et al._ PDBe: improved accessibility of macromolecular structure data from PDB and EMDB. _Nucleic acids res._ **44**, D385-395 \(2016).





Vilella, A.J. _et al._ EnsemblCompara GeneTrees: Complete, duplication-aware phylogenetic trees in vertebrates. _Genome res._ **19**, 327-335 \(2009).

We would like to thank the WTSI Pathogen Informatics team, especially Jacqueline Keane and Andrew Page.

CC BY 4.0

Many existing anthelmintic compounds are compromised by low efficacy, serious side-effects and/or rising resistance in parasite populations. Thus, to reveal potential new drug targets and drugs, we describe a protocol to identify the most promising nematode/flatworm targets, and compounds likely to interact with them from the ChEMBL database \(which includes both targets of known drugs and of other biologically active compounds). This provides a potential screening set of drug-like compounds.

Method Article

Matthew Berriman, Avril Coghlan, Prudence Mutowo, Noel O'Boyle, Jane Lomax, Andrew R. Leach

Matthew Berriman

Berriman Lab Group, Sanger Institute

Corresponding Author

Avril Coghlan

Berriman Lab Group, Sanger Institute

Prudence Mutowo

European Bioinformatics Institute

Noel O'Boyle

NextMove Software

Jane Lomax

Berriman Lab Group, Sanger Institute

Andrew R. Leach

European Bioinformatics Institute

DOI:

10.1038/protex.2018.053

Download PDF

License:

This work is licensed under a CC BY 4.0 License. Read Full License

Abstract

Keywords

drug discovery, drugs, anthemintic, helminths, nematodes, flatworms, parasites, parasitic worms, platyhelminths, Nematoda, Platyhelminthes, compounds, anthelminthic, ChEMBL

Figures

Introduction

Reagents

Equipment

Procedure

Anticipated Results

References

Acknowledgements

Competing Interests

Comments

Version History

CURRENT STATUS: Posted

Version 1

No community comments so far

Metrics

Comments: 0

HTML Views: ...

Subject Areas

Computational biology and bioinformatics

Biotechnology

Method Article

Matthew Berriman, Avril Coghlan, Prudence Mutowo, Noel O'Boyle, Jane Lomax, Andrew R. Leach

Matthew Berriman

Berriman Lab Group, Sanger Institute

Corresponding Author

Avril Coghlan

Berriman Lab Group, Sanger Institute

Prudence Mutowo

European Bioinformatics Institute

Noel O'Boyle

NextMove Software

Jane Lomax

Berriman Lab Group, Sanger Institute

Andrew R. Leach

European Bioinformatics Institute

Badges

Peer Review Timeline

Version History

CURRENT STATUS: Posted

Version 1

No community comments so far

Metrics

Metrics

Comments: 0

HTML Views: ...

Subject Areas

Subject Areas

Computational biology and bioinformatics

Biotechnology

DOI & PDF

DOI:

10.1038/protex.2018.053

Download PDF

License

License:

This work is licensed under a CC BY 4.0 License. Read Full License

Declarations