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Future Science OA Volume 7, 2021 - Issue 6

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Editorial

State-of-the-art of Artificial Intelligence in Medicinal Chemistry

Jürgen Bajorath1 Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-UniversitätFriedrich-Hirzebruch-Allee 6Bonn D, 53115, GermanyCorrespondence[email protected]

https://orcid.org/0000-0002-0557-5714

Article: FSO702 | Received 27 Feb 2021, Accepted 10 Mar 2021, Published online: 29 Mar 2021

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https://doi.org/10.2144/fsoa-2021-0030
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José J. Naveja, Fernanda I. Saldívar‐González, Diana L. Prado‐Romero, Angel J. Ruiz‐Moreno, Marco Velasco‐Velázquez, Ramón Alain Miranda‐Quintana & José L. Medina‐Franco. 2024. Computational Drug Discovery. Computational Drug Discovery 365 393 .

Xinyi Wu, Huitian Lin, Renren Bai & Hongliang Duan. (2024) Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design. European Journal of Medicinal Chemistry 268, pages 116262.
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Shadi Askari, Alireza Ghofrani & Hamed Taherdoost. (2023) Transforming Drug Design: Innovations in Computer-Aided Discovery for Biosimilar Agents. BioMedInformatics 3:4, pages 1178-1196.
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Jürgen Bajorath. (2023) Specific contributions of artificial intelligence to interdisciplinary life science research – exploring and communicating new opportunities. Artificial Intelligence in the Life Sciences 3, pages 100052.
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Andrea Mastropietro, Christian Feldmann & Jürgen Bajorath. (2023) Calculation of exact Shapley values for explaining support vector machine models using the radial basis function kernel. Scientific Reports 13:1.
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Natesh Singh, Philippe Vayer, Shivalika Tanwar, Jean-Luc Poyet, Katya Tsaioun & Bruno O. Villoutreix. (2023) Drug discovery and development: introduction to the general public and patient groups. Frontiers in Drug Discovery 3.
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Friederike Maite Siemers & Jürgen Bajorath. (2023) Differences in learning characteristics between support vector machine and random forest models for compound classification revealed by Shapley value analysis. Scientific Reports 13:1.
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Henning Otto Brinkhaus, Kohulan Rajan, Jonas Schaub, Achim Zielesny & Christoph Steinbeck. (2023) Open data and algorithms for open science in AI-driven molecular informatics. Current Opinion in Structural Biology 79, pages 102542.
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Tiago Janela, Kosuke Takeuchi & Jürgen Bajorath. (2023) Predicting Potent Compounds Using a Conditional Variational Autoencoder Based upon a New Structure–Potency Fingerprint. Biomolecules 13:2, pages 393.
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Atsushi Yoshimori & Jürgen Bajorath. (2022) Computational analysis, alignment and extension of analogue series from medicinal chemistry. Future Science OA 8:7.
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Yu Wei, Shanshan Li, Zhonglin Li, Ziwei Wan & Jianping Lin. (2022) Interpretable-ADMET: a web service for ADMET prediction and optimization based on deep neural representation. Bioinformatics 38:10, pages 2863-2871.
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Jürgen Bajorath. (2022) Artificial intelligence in interdisciplinary life science and drug discovery research. Future Science OA 8:4.
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Jaroslaw Polanski. (2022) Unsupervised Learning in Drug Design from Self-Organization to Deep Chemistry. International Journal of Molecular Sciences 23:5, pages 2797.
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Jürgen Bajorath. (2022) Deep Machine Learning for Computer-Aided Drug Design. Frontiers in Drug Discovery 2.
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Filip Miljković, Raquel Rodríguez-Pérez & Jürgen Bajorath. (2021) Impact of Artificial Intelligence on Compound Discovery, Design, and Synthesis. ACS Omega 6:49, pages 33293-33299.
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Raquel Rodríguez-Pérez & Jürgen Bajorath. (2021) Chemistry-centric explanation of machine learning models. Artificial Intelligence in the Life Sciences 1, pages 100009.
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Christian Feldmann, Maren Philipps & Jürgen Bajorath. (2021) Explainable machine learning predictions of dual-target compounds reveal characteristic structural features. Scientific Reports 11:1.
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José L. Medina-Franco. (2021) Grand Challenges of Computer-Aided Drug Design: The Road Ahead. Frontiers in Drug Discovery 1.
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Atsushi Yoshimori. (2021) Prediction of Molecular Properties Using Molecular Topographic Map. Molecules 26:15, pages 4475.
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