Detecting similar binding pockets to enable systems polypharmacology
In the era of systems biology, multi-target pharmacological strategies hold promise for tackling disease-related networks. In this regard, drug promiscuity may be leveraged to interfere with multiple receptors: the so-called polypharmacology of drugs can be anticipated by analyzing the similarity of...
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| Veröffentlicht in: | PLoS computational biology 2017-06, Vol.13 (6), p.e1005522-e1005522 |
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| creator | Duran-Frigola, Miquel Siragusa, Lydia Ruppin, Eytan Barril, Xavier Cruciani, Gabriele Aloy, Patrick |
| description | In the era of systems biology, multi-target pharmacological strategies hold promise for tackling disease-related networks. In this regard, drug promiscuity may be leveraged to interfere with multiple receptors: the so-called polypharmacology of drugs can be anticipated by analyzing the similarity of binding sites across the proteome. Here, we perform a pairwise comparison of 90,000 putative binding pockets detected in 3,700 proteins, and find that 23,000 pairs of proteins have at least one similar cavity that could, in principle, accommodate similar ligands. By inspecting these pairs, we demonstrate how the detection of similar binding sites expands the space of opportunities for the rational design of drug polypharmacology. Finally, we illustrate how to leverage these opportunities in protein-protein interaction networks related to several therapeutic classes and tumor types, and in a genome-scale metabolic model of leukemia. |
| doi_str_mv | 10.1371/journal.pcbi.1005522 |
| format | Article |
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In this regard, drug promiscuity may be leveraged to interfere with multiple receptors: the so-called polypharmacology of drugs can be anticipated by analyzing the similarity of binding sites across the proteome. Here, we perform a pairwise comparison of 90,000 putative binding pockets detected in 3,700 proteins, and find that 23,000 pairs of proteins have at least one similar cavity that could, in principle, accommodate similar ligands. By inspecting these pairs, we demonstrate how the detection of similar binding sites expands the space of opportunities for the rational design of drug polypharmacology. Finally, we illustrate how to leverage these opportunities in protein-protein interaction networks related to several therapeutic classes and tumor types, and in a genome-scale metabolic model of leukemia.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1005522</identifier><identifier>PMID: 28662117</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Antineoplastic Agents - chemistry ; Binding Sites ; Bioinformatics ; Biologia computacional ; Biology ; Biology and Life Sciences ; Cancer ; Computational biology ; Computer and Information Sciences ; Disease ; Disseny de medicaments ; Drug design ; Drug development ; Drug Discovery ; Drug interactions ; Drugs ; Farmacologia ; Genomes ; Humans ; Leukemia ; Ligands ; Medicine and Health Sciences ; Metabolism ; Molecular Docking Simulation ; Neoplasm Proteins - chemistry ; Observations ; Ontology ; Pharmaceutical industry ; Pharmacology ; Physical Sciences ; Polypharmacology ; Polypharmacy ; Protein Binding ; Protein Conformation ; Protein interaction ; Protein Interaction Domains and Motifs ; Protein Interaction Mapping ; Proteins ; Proteomes ; R&D ; Receptors ; Research & development ; Sequence Analysis, Protein ; Systems Biology</subject><ispartof>PLoS computational biology, 2017-06, Vol.13 (6), p.e1005522-e1005522</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Duran-Frigola M, Siragusa L, Ruppin E, Barril X, Cruciani G, Aloy P (2017) Detecting similar binding pockets to enable systems polypharmacology. PLoS Comput Biol 13(6): e1005522. https://doi.org/10.1371/journal.pcbi.1005522</rights><rights>cc-by (c) Duran Frigola, Miquel et al., 2017 info:eu-repo/semantics/openAccess <a href="http://creativecommons.org/licenses/by/3.0/es">http://creativecommons.org/licenses/by/3.0/es</a></rights><rights>2017 Duran-Frigola et al 2017 Duran-Frigola et al</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Duran-Frigola M, Siragusa L, Ruppin E, Barril X, Cruciani G, Aloy P (2017) Detecting similar binding pockets to enable systems polypharmacology. 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In this regard, drug promiscuity may be leveraged to interfere with multiple receptors: the so-called polypharmacology of drugs can be anticipated by analyzing the similarity of binding sites across the proteome. Here, we perform a pairwise comparison of 90,000 putative binding pockets detected in 3,700 proteins, and find that 23,000 pairs of proteins have at least one similar cavity that could, in principle, accommodate similar ligands. By inspecting these pairs, we demonstrate how the detection of similar binding sites expands the space of opportunities for the rational design of drug polypharmacology. 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chemistry</subject><subject>Observations</subject><subject>Ontology</subject><subject>Pharmaceutical industry</subject><subject>Pharmacology</subject><subject>Physical Sciences</subject><subject>Polypharmacology</subject><subject>Polypharmacy</subject><subject>Protein Binding</subject><subject>Protein Conformation</subject><subject>Protein interaction</subject><subject>Protein Interaction Domains and Motifs</subject><subject>Protein Interaction Mapping</subject><subject>Proteins</subject><subject>Proteomes</subject><subject>R&D</subject><subject>Receptors</subject><subject>Research & development</subject><subject>Sequence Analysis, Protein</subject><subject>Systems Biology</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>XX2</sourceid><sourceid>DOA</sourceid><recordid>eNqVktuO0zAQhiMEYg_wBggqcQMXLT47vkFa7XKotAKJw7XlOJOsSxIX20H07ddts9UW7Q2KrNjj7__tGU9RvMBoganE71Z-DIPpFmtbuQVGiHNCHhWnmHM6l5SXj-_NT4qzGFcI5akST4sTUgpBMJanxdUVJLDJDe0sut51JswqN9Tb9drbX5DiLPkZDKbqYBY3MUEf8063Wd-Y0BvrO99unhVPGtNFeD79z4ufHz_8uPw8v_76aXl5cT23EtE0l0aVWHELqMKMEqVqUhMLSoimKkuJGihtDcKKBnNWg0LMlEzkiAKGTEXpefFq77vufNRTAaLGKrsiLiTOxHJP1N6s9Dq43oSN9sbpXcCHVpuQnO1AK4pYY3gJtayYMFQ1iprG0CrfrGwEz17vp9PGqofawpCC6Y5Mj3cGd6Nb_0dzppBiKBvgvYGNo9UBLARr0k54WGwHQZJoiqQkLGveTIcG_3uEmHTvooWuMwP4cZcrp9lfiIy-_gd9uCIT1ZqctBsan-9qt6b6ginJSk4kydTiASp_NfTO-gEal-NHgrdHgswk-JtaM8aol9-__Qf75ZhlU82CjzFAc6g3Rnrb93dJ6m3f66nvs-zl_bc6iO4and4CgtT9yg</recordid><startdate>20170629</startdate><enddate>20170629</enddate><creator>Duran-Frigola, Miquel</creator><creator>Siragusa, Lydia</creator><creator>Ruppin, Eytan</creator><creator>Barril, Xavier</creator><creator>Cruciani, Gabriele</creator><creator>Aloy, Patrick</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISN</scope><scope>ISR</scope><scope>3V.</scope><scope>7QO</scope><scope>7QP</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>XX2</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-3557-0236</orcidid><orcidid>https://orcid.org/0000-0002-0281-1347</orcidid></search><sort><creationdate>20170629</creationdate><title>Detecting similar binding pockets to enable systems polypharmacology</title><author>Duran-Frigola, Miquel ; Siragusa, Lydia ; Ruppin, Eytan ; Barril, Xavier ; Cruciani, Gabriele ; Aloy, Patrick</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c703t-7a98195ce0b143299d2d2ce966fb8870fe8cde6c6f154de904a846de69e40ab33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Antineoplastic Agents - chemistry</topic><topic>Binding Sites</topic><topic>Bioinformatics</topic><topic>Biologia computacional</topic><topic>Biology</topic><topic>Biology and Life Sciences</topic><topic>Cancer</topic><topic>Computational biology</topic><topic>Computer and Information Sciences</topic><topic>Disease</topic><topic>Disseny de medicaments</topic><topic>Drug design</topic><topic>Drug development</topic><topic>Drug Discovery</topic><topic>Drug interactions</topic><topic>Drugs</topic><topic>Farmacologia</topic><topic>Genomes</topic><topic>Humans</topic><topic>Leukemia</topic><topic>Ligands</topic><topic>Medicine and Health Sciences</topic><topic>Metabolism</topic><topic>Molecular Docking Simulation</topic><topic>Neoplasm Proteins - chemistry</topic><topic>Observations</topic><topic>Ontology</topic><topic>Pharmaceutical industry</topic><topic>Pharmacology</topic><topic>Physical Sciences</topic><topic>Polypharmacology</topic><topic>Polypharmacy</topic><topic>Protein Binding</topic><topic>Protein Conformation</topic><topic>Protein interaction</topic><topic>Protein Interaction Domains and Motifs</topic><topic>Protein Interaction Mapping</topic><topic>Proteins</topic><topic>Proteomes</topic><topic>R&D</topic><topic>Receptors</topic><topic>Research & development</topic><topic>Sequence Analysis, Protein</topic><topic>Systems Biology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Duran-Frigola, Miquel</creatorcontrib><creatorcontrib>Siragusa, Lydia</creatorcontrib><creatorcontrib>Ruppin, Eytan</creatorcontrib><creatorcontrib>Barril, Xavier</creatorcontrib><creatorcontrib>Cruciani, Gabriele</creatorcontrib><creatorcontrib>Aloy, Patrick</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Recercat</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Duran-Frigola, Miquel</au><au>Siragusa, Lydia</au><au>Ruppin, Eytan</au><au>Barril, Xavier</au><au>Cruciani, Gabriele</au><au>Aloy, Patrick</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detecting similar binding pockets to enable systems polypharmacology</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2017-06-29</date><risdate>2017</risdate><volume>13</volume><issue>6</issue><spage>e1005522</spage><epage>e1005522</epage><pages>e1005522-e1005522</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>In the era of systems biology, multi-target pharmacological strategies hold promise for tackling disease-related networks. 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Finally, we illustrate how to leverage these opportunities in protein-protein interaction networks related to several therapeutic classes and tumor types, and in a genome-scale metabolic model of leukemia.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28662117</pmid><doi>10.1371/journal.pcbi.1005522</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-3557-0236</orcidid><orcidid>https://orcid.org/0000-0002-0281-1347</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Antineoplastic Agents - chemistry Binding Sites Bioinformatics Biologia computacional Biology Biology and Life Sciences Cancer Computational biology Computer and Information Sciences Disease Disseny de medicaments Drug design Drug development Drug Discovery Drug interactions Drugs Farmacologia Genomes Humans Leukemia Ligands Medicine and Health Sciences Metabolism Molecular Docking Simulation Neoplasm Proteins - chemistry Observations Ontology Pharmaceutical industry Pharmacology Physical Sciences Polypharmacology Polypharmacy Protein Binding Protein Conformation Protein interaction Protein Interaction Domains and Motifs Protein Interaction Mapping Proteins Proteomes R&D Receptors Research & development Sequence Analysis, Protein Systems Biology |
| title | Detecting similar binding pockets to enable systems polypharmacology |
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