{"633879":{"#nid":"633879","#data":{"type":"news","title":"Expediting Drug Discovery: Sherrill Group Creates First Pure Machine Learning Model for Intermolecular Interactions","body":[{"value":"\u003Cp\u003EScientists know exactly where to look for potential weaknesses in viruses that cause disease: their protein shells.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe genetic material inside a virus is surrounded by a protein-based covering called a capsid. Searches for therapeutic treatments and vaccines are now focusing on proteins like capsids that drugs could attack, and a highly-read \u003Ca href=\u0022https:\/\/aip.scitation.org\/doi\/full\/10.1063\/1.5142636\u0022\u003Estudy\u003C\/a\u003E from a Georgia Tech \u003Ca href=\u0022http:\/\/vergil.chemistry.gatech.edu\/index.html\u0022\u003Eresearch group\u003C\/a\u003E is offering expertise to aid in efforts\u0026nbsp;like these.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/vergil.chemistry.gatech.edu\/index.html\u0022\u003EThe Sherrill Group\u003C\/a\u003E is studying artificial intelligence and machine learning in the hopes of making drug discovery faster and more efficient, says \u003Ca href=\u0022https:\/\/chemistry.gatech.edu\/faculty\/sherrill\/\u0022\u003EDavid Sherrill\u003C\/a\u003E, a computational chemist and professor in the \u003Ca href=\u0022https:\/\/chemistry.gatech.edu\/\u0022\u003ESchool of Chemistry and Biochemistry\u003C\/a\u003E and \u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/people\/c-david-sherrill\u0022\u003ESchool of Computational Science and Engineering\u003C\/a\u003E, who also serves as associate director of the \u003Ca href=\u0022http:\/\/ideas.gatech.edu\/\u0022\u003EGeorgia Tech Institute for Data Engineering and Science\u003C\/a\u003E. \u0026ldquo;AI promises to help us identify druggable target proteins, to predict what drugs might be effective, and even how to synthesize those drugs.\u0026rdquo;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe team has created the first pure machine learning model designed specifically for intermolecular interactions, such as those governing a drug binding to its target proteins.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe models described in a study published recently in \u003Ca href=\u0022https:\/\/aip.scitation.org\/journal\/jcp\u0022\u003EThe Journal of Chemical Physics\u003C\/a\u003E. Sherrill and \u003Ca href=\u0022https:\/\/www.linkedin.com\/in\/derekmetcalf\u0022\u003EDerek Metcalf\u003C\/a\u003E, a Ph.D. student in his group, have also given recent\u0026nbsp;lectures on their research.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETiny Molecules Meet Big Data\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESherrill says much work has already been done in\u0026nbsp;chemistry research using machine learning, where computers search for patterns and possible connections within data on their own without specific instructions. But so far that approach \u0026ldquo;has gone into predicting properties of single small molecules. Intermolecular interactions pose several subtle problems that we elucidate\u0026rdquo; in the study, he says.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe drug design process can benefit from artificial intelligence in several ways, including more accurate estimates of how drugs move within the body, and better predictions about their synthesizability.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the initial pilot study, the researchers developed a way to encode high-level quantum (subatomic) mechanical computations on molecule-to-molecule interactions into a machine learning model.\u0026nbsp;\u0026ldquo;Tests indicate that the model is promising, and it is much faster than the corresponding quantum computations, which involve fractions of a second for machine learning, compared to hours for quantum mechanics,\u0026rdquo; Sherrill says.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026ldquo;Although our initial study was focused primarily on hydrogen bonds, the group has already developed a more general model applicable to all the kinds of molecule-molecule interactions involved in drug-protein binding, and we are currently in the process of generating the large data set of quantum data required to train the model,\u0026rdquo; he says.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EUltimately, the team hopes to develop a model that will be nearly as accurate as quantum mechanics, while making predictions almost instantaneously.\u0026nbsp;Such a model could be very helpful in screening extremely large numbers of possible drug molecules for their ability to bind to a protein.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDuring his time at Georgia Tech, Sherrill\u0026rsquo;s work has focused on the intersection of computer software, chemistry, and physics. He is one of the co-principal investigators for the \u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/news\/629130\/hive-supercomputer-makes-its-debut\u0022\u003EGeorgia Tech Supercomputer Hive\u003C\/a\u003E.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESherrill also leads the Georgia Tech team that wrote Psi4, a suite of open-source quantum chemistry programs that \u003Ca href=\u0022https:\/\/cos.gatech.edu\/hg\/item\/598564\u0022\u003EGoogle selected in 2017\u003C\/a\u003E as a plug-in for OpenFermion, its free and open-source chemistry package for quantum computers.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHe is a Fellow of the American Association for the Advancement of Science (AAAS), the American Chemical Society, and the American Physical Society, and he has been Associate Editor of the Journal of Chemical Physics since 2009.\u003C\/p\u003E\r\n\r\n\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":[{"value":"David Sherrill\u2019s research group points to artificial intelligence and machine learning to speed up the process of identifying drugs with big data"}],"field_summary":[{"value":"\u003Cp\u003EA Georgia Tech research group led by computational chemist David Sherrill, professor in the School of Chemistry and Biochemistry, is offering new tools, including artificial intelligence-based resources, for helping scientists involved in drug discovery\u0026nbsp;efforts.\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"David Sherrill\u2019s research group points to artificial intelligence and machine learning to speed up the process of identifying drugs with big data"}],"uid":"34434","created_gmt":"2020-03-30 14:26:08","changed_gmt":"2020-03-30 20:05:28","author":"Renay San Miguel","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2020-03-30T00:00:00-04:00","iso_date":"2020-03-30T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"633880":{"id":"633880","type":"image","title":"David Sherrill, professor in the School of Chemistry and Biochemistry and School of Computational Science and Engineering; associate director of the Georgia Tech Institute for Data Engineering and Science.","body":null,"created":"1585578532","gmt_created":"2020-03-30 14:28:52","changed":"1679941393","gmt_changed":"2023-03-27 18:23:13","alt":"David Sherrill, professor in the School of Chemistry and Biochemistry and School of Computational Science and Engineering; associate director of the Georgia Tech Institute for Data Engineering and Science.","file":{"fid":"241192","name":"David Sherrill.png","image_path":"\/sites\/default\/files\/images\/David%20Sherrill.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/images\/David%20Sherrill.png","mime":"image\/png","size":762019,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/David%20Sherrill.png?itok=_PG9myk0"}},"633881":{"id":"633881","type":"image","title":"Artist\u0027s rendition of a virus. The blue spheres represent the protein capsid covering (courtesy Microbiology Online).","body":null,"created":"1585578853","gmt_created":"2020-03-30 14:34:13","changed":"1585581289","gmt_changed":"2020-03-30 15:14:49","alt":"","file":{"fid":"241193","name":"Virus Capsid.png","image_path":"\/sites\/default\/files\/images\/Virus%20Capsid.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/images\/Virus%20Capsid.png","mime":"image\/png","size":604972,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/Virus%20Capsid.png?itok=5i7o8X_j"}}},"media_ids":["633880","633881"],"related_links":[{"url":"https:\/\/cos.gatech.edu\/hg\/item\/598564","title":"Google Plugs In Georgia Tech Chemistry Team\u2019s Software for its Quantum Computing Product"},{"url":"https:\/\/www.cc.gatech.edu\/news\/629130\/hive-supercomputer-makes-its-debut","title":"Hive Supercomputer Makes Its Debut"},{"url":"https:\/\/rh.gatech.edu\/features\/cyber-forged","title":"Cyber Forged"},{"url":"https:\/\/rh.gatech.edu\/news\/612298\/materials-research-benefit-new-37m-nsf-grant","title":"Materials research to benefit from new $3.7M NSF grant"},{"url":"https:\/\/rh.gatech.edu\/features\/data-driven","title":"Data Driven: How Traditional Research is Being Rebooted"},{"url":"https:\/\/www.cc.gatech.edu\/news\/633633\/machine-learning-tool-may-help-us-better-understand-rna-viruses","title":"Machine Learning Tool May Help Us Better Understand RNA Viruses"}],"groups":[{"id":"1278","name":"College of Sciences"},{"id":"85951","name":"School of Chemistry and Biochemistry"}],"categories":[{"id":"134","name":"Student and Faculty"},{"id":"8862","name":"Student Research"},{"id":"135","name":"Research"},{"id":"138","name":"Biotechnology, Health, Bioengineering, Genetics"},{"id":"141","name":"Chemistry and Chemical Engineering"},{"id":"153","name":"Computer Science\/Information Technology and Security"}],"keywords":[{"id":"4896","name":"College of Sciences"},{"id":"166928","name":"School of Chemistry and Biochemistry"},{"id":"13933","name":"David Sherrill"},{"id":"166983","name":"School of Computational Science and Engineering"},{"id":"6723","name":"computational chemistry"},{"id":"9167","name":"machine learning"},{"id":"2556","name":"artificial intelligence"}],"core_research_areas":[{"id":"39441","name":"Bioengineering and Bioscience"},{"id":"39431","name":"Data Engineering and Science"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003ERenay San Miguel\u003Cbr \/\u003E\r\nCommunications Officer\u003Cbr \/\u003E\r\nCollege of Sciences\u003Cbr \/\u003E\r\n404-894-5209\u003C\/p\u003E\r\n","format":"limited_html"}],"email":["renay.san@cos.gatech.edu"],"slides":[],"orientation":[],"userdata":""}}}