PreprintCited by 37Computational Drug Discovery MethodsMachine Learning in Materials Sciencevaccines and immunoinformatics approaches

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Chemoinformatics and Artificial Intelligence Colloquium: Progress and Challenges to Develop Bioactive Compounds

Open access
Bajorath, Jürgen, Chávez-Hernández, Ana L., Duran-Frigola, Miquel, Fernández-de Gortari, Eli, Gasteiger, Johann, López-López, Edgar, Maggiora, Gerald M., Medina-Franco, José L., Méndez-Lucio, Oscar, Mestres, Jordi, Miranda-Quintana, Ramón Alain, Oprea, Tudor I., Plisson, Fabien, Prieto-Martínez, Fernando D., Rodríguez-Pérez, Raquel, Rondón-Villarreal, Paola, Saldívar-Gonzalez, Fernanda I., Sánchez-Cruz, Norberto, Valli, Marilia·2022·Journal of Cheminformatics

Preprint — published as 10.1186/s13321-022-00661-0 · Paper page

Abstract

We report the main conclusions of the first Chemoinformatics and Artificial Intelligence Colloquium, Mexico City, June 15-17, 2022. Fifteen lectures were presented during a virtual public event with speakers from industry, academia, and non-for-profit organizations. Twelve hundred and ninety students and academics from more than 60 countries. During the meeting, applications, challenges, and opportunities in drug discovery, de novo drug design, ADME-Tox (absorption, distribution, metabolism, excretion and toxicity) property predictions, organic chemistry, peptides, and antibiotic resistance were discussed. The program along with the recordings of all sessions are freely available at https://www.difacquim.com/english/events/2022-colloquium/

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Crossref · 10.26434/chemrxiv-2022-nr0dm-v2

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Authors
Bajorath, J., Chávez-Hernández, A. L., Duran-Frigola, M., Fernández-de Gortari, E., Gasteiger, J., López-López, E., Maggiora, G. M., Medina-Franco, J. L., Méndez-Lucio, O., Mestres, J., Miranda-Quintana, R. A., Oprea, T. I., Plisson, F., Prieto-Martínez, F. D., Rodríguez-Pérez, R., Rondón-Villarreal, P., Saldívar-Gonzalez, F. I., Sánchez-Cruz, N., & Valli, M.
Affiliations
  • University of Bonn (DE)
  • National Autonomous University of Mexico
  • Ersilia Open Source Initiative
  • International Iberian Nanotechnology Laboratory
  • Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
  • University of Arizona (US)
  • Recursion Pharmaceuticals
  • Universitat Pompeu Fabra (ES)
  • University of Florida
  • University of Copenhagen (DK)
  • Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (MX)
  • Universidad Nacional Autónoma de México (MX)
  • Novartis Institutes for BioMedical Research (CH)
  • Universidad De Santander (CO)
  • São Paulo State University
Venue
Journal of Cheminformatics
Published
2022-08-09
Volume
14
Issue
1
Pages
82-82
ISSN
1758-2946 (ISSN-L)
OpenAlex
W4311104054
Cited by
37
References
1
Citations by year
2026: 2 · 2025: 12 · 2024: 12 · 2023: 10 · 2022: 1
FWCI
4.73
Type
journal article
Language
en
Open access
Locations
  • Journal of Cheminformatics (publishedVersion, cc-by)
  • ChemRxiv (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
  • Repositori digital de la UPF (Universitat Pompeu Fabra) (publishedVersion, cc-by)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, other-oa)
  • UA Campus Repository (The University of Arizona) (acceptedVersion, cc-by)
  • OPUS Repository (Kooperativer Bibliotheksverbund Berlin-Brandenburg) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • The Novartis Repository (Novartis) (submittedVersion)
  • Greater South Information System
Funders
Universidad Nacional Autónoma de México
Topics
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
  • Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
Keywords
cheminformatics, artificial intelligence, drug discovery, de novo drug design, ADMET prediction, organic chemistry, peptides, antibiotic resistance, bioactive compounds

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