{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T12:17:43Z","timestamp":1787314663593,"version":"build-2736575974"},"reference-count":67,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T00:00:00Z","timestamp":1664496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NLnet Foundation","award":["RfP 2021-10-039"],"award-info":[{"award-number":["RfP 2021-10-039"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Molecules"],"abstract":"<jats:p>Drug repurposing in the context of neuroimmunological (NI) investigations is still in its primary stages. Drug repurposing is an important method that bypasses lengthy drug discovery procedures and focuses on discovering new usages for known medications. Neuroimmunological diseases, such as Alzheimer\u2019s, Parkinson\u2019s, multiple sclerosis, and depression, include various pathologies that result from the interaction between the central nervous system and the immune system. However, the repurposing of NI medications is hindered by the vast amount of information that needs mining. We previously presented Adera1.0, which was capable of text mining PubMed for answering query-based questions. However, Adera1.0 was not able to automatically identify chemical compounds within relevant sentences. To challenge the need for repurposing known medications for neuroimmunological diseases, we built a deep neural network named Adera2.0 to perform drug repurposing. The workflow uses three deep learning networks. The first network is an encoder and its main task is to embed text into matrices. The second network uses a mean squared error (MSE) loss function to predict answers in the form of embedded matrices. The third network, which constitutes the main novelty in our updated workflow, also uses a MSE loss function. Its main usage is to extract compound names from relevant sentences resulting from the previous network. To optimize the network function, we compared eight different designs. We found that a deep neural network consisting of an RNN neural network and a leaky ReLU could achieve 0.0001 loss and 67% sensitivity. Additionally, we validated Adera2.0\u2019s ability to predict NI drug usage against the DRUG Repurposing Hub database. These results establish the ability of Adera2.0 to repurpose drug candidates that can shorten the development of the drug cycle. The workflow could be download online.<\/jats:p>","DOI":"10.3390\/molecules27196453","type":"journal-article","created":{"date-parts":[[2022,10,9]],"date-time":"2022-10-09T04:00:02Z","timestamp":1665288002000},"page":"6453","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Adera2.0: A Drug Repurposing Workflow for Neuroimmunological Investigations Using Neural Networks"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1938-8143","authenticated-orcid":false,"given":"Marzena","family":"Lazarczyk","sequence":"first","affiliation":[{"name":"Department of Experimental Genomics, Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, ul. Postepu 36A, Jastrzebiec, 05-552 Magdalenka, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kamila","family":"Duda","sequence":"additional","affiliation":[{"name":"Centre for Preclinical Research and Technology, Department of Pharmacodynamics, Faculty of Pharmacy with the Laboratory Medicine Division, Medical University of Warsaw, Banacha 1B, 02-091 Warsaw, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4186-4900","authenticated-orcid":false,"given":"Michel Edwar","family":"Mickael","sequence":"additional","affiliation":[{"name":"Department of Experimental Genomics, Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, ul. Postepu 36A, Jastrzebiec, 05-552 Magdalenka, Poland"},{"name":"PM Research Center, V\u00e4pnaregatan 22, 58649 Link\u00f6ping, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Onurhan","family":"AK","sequence":"additional","affiliation":[{"name":"Department of Sociology, Queen\u2019s University at Kingston, 99 University Ave, Kingston, ON K7L 3N6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justyna","family":"Paszkiewicz","sequence":"additional","affiliation":[{"name":"Department of Health, John Paul II University of Applied Sciences in Biala Podlaska, Sidorska 95\/97, 21-500 Bia\u0142a Podlaska, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agnieszka","family":"Kowalczyk","sequence":"additional","affiliation":[{"name":"Centre for Preclinical Research and Technology, Department of Pharmacodynamics, Faculty of Pharmacy with the Laboratory Medicine Division, Medical University of Warsaw, Banacha 1B, 02-091 Warsaw, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaros\u0142aw Olav","family":"Horba\u0144czuk","sequence":"additional","affiliation":[{"name":"Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, ul. 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