{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T17:26:11Z","timestamp":1770830771278,"version":"3.50.1"},"reference-count":51,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2019,10,10]],"date-time":"2019-10-10T00:00:00Z","timestamp":1570665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Department of Biotechnology, Government of India","award":["BT\/PR16710\/BID\/7\/680\/2016"],"award-info":[{"award-number":["BT\/PR16710\/BID\/7\/680\/2016"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Protein aggregation is a major unsolved problem in biochemistry with implications for several human diseases, biotechnology and biomaterial sciences. A majority of sequence-structural properties known for their mechanistic roles in protein aggregation do not correlate well with the aggregation kinetics. This limits the practical utility of predictive algorithms.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We analyzed experimental data on 183 unique single point mutations that lead to change in aggregation rates for 23 polypeptides and proteins. Our initial mathematical model obtained a correlation coefficient of 0.43 between predicted and experimental change in aggregation rate upon mutation (P-value &amp;lt;0.0001). However, when the dataset was classified based on protein length and conformation at the mutation sites, the average correlation coefficient almost doubled to 0.82 (range: 0.74\u20130.87; P-value &amp;lt;0.0001). We observed that distinct sequence and structure-based properties determine protein aggregation kinetics in each class. In conclusion, the protein aggregation kinetics are impacted by local factors and not by global ones, such as overall three-dimensional protein fold, or mechanistic factors such as the presence of aggregation-prone regions.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The web server is available at http:\/\/www.iitm.ac.in\/bioinfo\/aggrerate-pred\/.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz764","type":"journal-article","created":{"date-parts":[[2019,10,8]],"date-time":"2019-10-08T08:19:25Z","timestamp":1570522765000},"page":"1439-1444","source":"Crossref","is-referenced-by-count":22,"title":["AggreRATE-Pred: a mathematical model for the prediction of change in aggregation rate upon point mutation"],"prefix":"10.1093","volume":"36","author":[{"given":"Puneet","family":"Rawat","sequence":"first","affiliation":[{"name":"Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras , Chennai, Tamil Nadu 600036, India"}]},{"given":"R","family":"Prabakaran","sequence":"additional","affiliation":[{"name":"Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras , Chennai, Tamil Nadu 600036, India"}]},{"given":"Sandeep","family":"Kumar","sequence":"additional","affiliation":[{"name":"Biotherapeutics Discovery, Boehringer-Ingelheim Pharmaceutical Inc. Ridgefield , CT, USA"}]},{"given":"M Michael","family":"Gromiha","sequence":"additional","affiliation":[{"name":"Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras , Chennai, Tamil Nadu 600036, India"},{"name":"Advanced Computational Drug Discovery Unit (ACDD), Tokyo Tech World Research Hub Initiative (WRHI), Institute of Innovative Research, Tokyo Institute of Technology , 4259 Nagatsuta-cho, Midori-ku, Yokohama, Japan"}]}],"member":"286","published-online":{"date-parts":[[2019,10,10]]},"reference":[{"key":"2023060910264964000_btz764-B1","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.mrfmmm.2015.07.005","article-title":"Discrimination of driver and passenger mutations in epidermal growth factor receptor in cancer","volume":"780","author":"Anoosha","year":"2015","journal-title":"Mutat Res"},{"key":"2023060910264964000_btz764-B2","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.ejpb.2017.01.019","article-title":"The effect of charge mutations on the stability and aggregation of a human single chain Fv fragment","volume":"115","author":"Austerberry","year":"2017","journal-title":"Eur. 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