{"id":"https://openalex.org/W2822905239","doi":"https://doi.org/10.1109/ccgrid.2018.00005","title":"Enabling Trade-offs Between Accuracy and Computational Cost: Adaptive Algorithms to Reduce Time to Clinical Insight","display_name":"Enabling Trade-offs Between Accuracy and Computational Cost: Adaptive Algorithms to Reduce Time to Clinical Insight","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2822905239","doi":"https://doi.org/10.1109/ccgrid.2018.00005","mag":"2822905239"},"language":"en","primary_location":{"id":"doi:10.1109/ccgrid.2018.00005","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccgrid.2018.00005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://discovery.ucl.ac.uk/10059538/1/scale2018-ccgrid.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063744091","display_name":"Jumana Dakka","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jumana Dakka","raw_affiliation_strings":["Rutgers, the State University of New Jersey, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers, the State University of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090047974","display_name":"Kristof Farkas-Pall","orcid":null},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kristof Farkas-Pall","raw_affiliation_strings":["University College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088959784","display_name":"Vivek Balasubramanian","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vivek Balasubramanian","raw_affiliation_strings":["Rutgers, the State University of New Jersey, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers, the State University of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009954932","display_name":"Matteo Turilli","orcid":"https://orcid.org/0000-0003-0527-1435"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matteo Turilli","raw_affiliation_strings":["Rutgers, the State University of New Jersey, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers, the State University of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080572714","display_name":"Shunzhou Wan","orcid":"https://orcid.org/0000-0001-7192-1999"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shunzhou Wan","raw_affiliation_strings":["University College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066932343","display_name":"David W. Wright","orcid":"https://orcid.org/0000-0002-5124-8044"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"David W. Wright","raw_affiliation_strings":["University College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046138213","display_name":"Stefan J. Zasada","orcid":"https://orcid.org/0000-0003-4643-4982"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Stefan Zasada","raw_affiliation_strings":["University College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066453821","display_name":"Peter V. Coveney","orcid":"https://orcid.org/0000-0002-8787-7256"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peter V. Coveney","raw_affiliation_strings":["University College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038763846","display_name":"Shantenu Jha","orcid":"https://orcid.org/0000-0002-5040-026X"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shantenu Jha","raw_affiliation_strings":["Rutgers, the State University of New Jersey, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers, the State University of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.697,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.93989637,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"572","last_page":"577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12534","display_name":"Protein Degradation and Inhibitors","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12534","display_name":"Protein Degradation and Inhibitors","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7968034148216248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.747397780418396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46492862701416016},{"id":"https://openalex.org/keywords/supercomputer","display_name":"Supercomputer","score":0.45328736305236816},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.42129161953926086},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.38048219680786133},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3424362540245056},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3279799818992615},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.22338387370109558},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.16708073019981384},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13706457614898682}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7968034148216248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.747397780418396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46492862701416016},{"id":"https://openalex.org/C83283714","wikidata":"https://www.wikidata.org/wiki/Q121117","display_name":"Supercomputer","level":2,"score":0.45328736305236816},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.42129161953926086},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.38048219680786133},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3424362540245056},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3279799818992615},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.22338387370109558},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.16708073019981384},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13706457614898682},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ccgrid.2018.00005","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccgrid.2018.00005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10059538","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10059538/","pdf_url":"https://discovery.ucl.ac.uk/10059538/1/scale2018-ccgrid.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"In: (Proceedings) 2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). (pp. pp. 572-577). IEEE: Washington DC, USA. (2018)","raw_type":"Proceedings paper"}],"best_oa_location":{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10059538","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10059538/","pdf_url":"https://discovery.ucl.ac.uk/10059538/1/scale2018-ccgrid.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"In: (Proceedings) 2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). (pp. pp. 572-577). IEEE: Washington DC, USA. (2018)","raw_type":"Proceedings paper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2822905239.pdf"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1553864921","https://openalex.org/W1587176568","https://openalex.org/W1966509953","https://openalex.org/W1998645872","https://openalex.org/W2084769555","https://openalex.org/W2104567958","https://openalex.org/W2112005274","https://openalex.org/W2147993766","https://openalex.org/W2154670681","https://openalex.org/W2154908037","https://openalex.org/W2221713243","https://openalex.org/W2345406112","https://openalex.org/W2411462408","https://openalex.org/W2560233715","https://openalex.org/W2566391875","https://openalex.org/W2781848074","https://openalex.org/W2963368932","https://openalex.org/W2964077466","https://openalex.org/W6633425787","https://openalex.org/W6747049655"],"related_works":["https://openalex.org/W2384867379","https://openalex.org/W4400094300","https://openalex.org/W2329539859","https://openalex.org/W1982914007","https://openalex.org/W2159583675","https://openalex.org/W1824242903","https://openalex.org/W1493858311","https://openalex.org/W2155470929","https://openalex.org/W2394465510","https://openalex.org/W2111125783"],"abstract_inverted_index":{"The":[0],"efficacy":[1,194],"of":[2,19,31,117,132,144,178,188,206,217,229,232,239,246,258],"drug":[3,38,148,179,221],"treatments":[4],"depends":[5],"on":[6,112,151],"how":[7],"tightly":[8],"small":[9],"molecules":[10],"bind":[11],"to":[12,77,81,95,173,182,200,212],"their":[13],"target":[14,266],"proteins.":[15],"Quantifying":[16],"the":[17,42,140,183,204,214,227,230,236,244,256],"strength":[18],"these":[20,88],"interactions":[21],"(the":[22],"so":[23,93],"called":[24,209],"`binding":[25],"affinity')":[26],"is":[27,75,137,156],"a":[28,152,166,175,207,265],"grand":[29],"challenge":[30,52],"computational":[32,259],"chemistry,":[33],"surmounting":[34],"which":[35,189,251],"could":[36],"revolutionize":[37],"design":[39],"and":[40,54,83,127,129,171,219],"provide":[41],"platform":[43],"for":[44],"patient":[45],"specific":[46],"medicine.":[47],"Recently,":[48],"evidence":[49],"from":[50,147,165,198],"blind":[51],"predictions":[53],"retrospective":[55],"validation":[56],"studies":[57],"has":[58],"suggested":[59],"that":[60,103,155],"molecular":[61],"dynamics":[62],"(MD)":[63],"can":[64],"now":[65],"achieve":[66],"useful":[67],"predictive":[68,91],"accuracy":[69,74,92],"(":[70],"1":[71],"kcal/mol)":[72],"This":[73,119,135],"sufficient":[76],"greatly":[78],"accelerate":[79],"hit":[80],"lead":[82,84],"optimization.":[85],"To":[86],"translate":[87],"advances":[89,121],"in":[90,122,195,253],"as":[94,157,159],"impact":[96],"clinical":[97],"and/or":[98],"industrial":[99],"decision":[100],"making":[101],"requires":[102],"binding":[104,181,222],"free":[105],"energy":[106],"results":[107,164,263],"must":[108],"be":[109],"turned":[110],"around":[111],"reduced":[113],"timescales":[114],"without":[115],"loss":[116],"accuracy.":[118],"demands":[120],"algorithms,":[123],"scalable":[124],"software":[125],"systems,":[126],"intelligent":[128],"efficient":[130],"utilization":[131],"supercomputing":[133],"resources.":[134],"work":[136],"motivated":[138],"by":[139],"real":[141],"world":[142],"problem":[143],"providing":[145],"insight":[146],"candidate":[149],"data":[150],"time":[153],"scale":[154],"short":[158],"possible.":[160],"Specifically,":[161],"we":[162],"reproduce":[163],"collaborative":[167],"project":[168],"between":[169],"UCL":[170],"GlaxoSmithKline":[172],"study":[174],"congeneric":[176],"series":[177],"candidates":[180],"BRD4":[184],"protein":[185],"-":[186],"inhibitors":[187],"have":[190],"shown":[191],"promising":[192],"preclinical":[193],"pathologies":[196],"ranging":[197],"cancer":[199],"inflammation.":[201],"We":[202],"demonstrate":[203],"use":[205,257],"framework":[208],"HTBAC,":[210],"designed":[211],"support":[213],"aforementioned":[215],"requirements":[216],"accurate":[218],"rapid":[220],"affinity":[223],"calculations.":[224],"HTBAC":[225,242],"facilitates":[226],"execution":[228,238],"numbers":[231],"simulations":[233],"while":[234],"supporting":[235],"adaptive":[237],"algorithms.":[240],"Furthermore,":[241],"enables":[243],"selection":[245],"simulation":[247],"parameters":[248],"during":[249],"runtime":[250],"can,":[252],"principle,":[254],"optimize":[255],"resources":[260],"whilst":[261],"producing":[262],"within":[264],"uncertainty.":[267]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
