Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning by Alice Capecchi, Jean-Louis Reymond

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Elucidation of the role of in silico methodologies in approaches to studying bioactive peptides derived from foods by Anna Iwaniak, Małgorzata Darewicz, Damir Mogut, Piotr Minkiewicz

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Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices by Maarten R. Dobbelaere, István Lengyel, Christian V. Stevens, Kevin M. Van Geem

Subjects: “…Cheminformatics…”
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Discovery of Kinase and Carbonic Anhydrase Dual Inhibitors by Machine Learning Classification and Experiments by Min-Jeong Kim, Sarita Pandit, Jun-Goo Jee

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An exploration strategy improves the diversity of de novo ligands using deep reinforcement learning: a case for the adenosine A2A receptor by Xuhan Liu, Kai Ye, Herman W. T. van Vlijmen, Adriaan P. IJzerman, Gerard J. P. van Westen

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Global analysis of the biosynthetic chemical space of marine prokaryotes by Bin Wei, Gang-Ao Hu, Zhen-Yi Zhou, Wen-Chao Yu, Ao-Qi Du, Cai-Ling Yang, Yan-Lei Yu, Jian-Wei Chen, Hua-Wei Zhang, Qihao Wu, Qi Xuan, Xue-Wei Xu, Hong Wang

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A Data-Challenge Case Study of Analyte Detection and Identification with Comprehensive Two-Dimensional Gas Chromatography with Mass Spectrometry (GC×GC-MS) by Stephen E. Reichenbach, Qingping Tao, Chiara Cordero, Carlo Bicchi

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PIKAChU: a Python-based informatics kit for analysing chemical units by Barbara R. Terlouw, Sophie P. J. M. Vromans, Marnix H. Medema

Subjects: “…Cheminformatics kit…”
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De novo drug design through artificial intelligence: an introduction by Davide Crucitti, Davide Crucitti, Carlos Pérez Míguez, José Ángel Díaz Arias, Diego Beltrán Fernandez Prada, Adrián Mosquera Orgueira, Adrián Mosquera Orgueira

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Corrigendum to “Exploiting cheminformatic and machine learning to navigate the available chemical space of potential small molecule inhibitors of SARS-CoV-2″ [Computational and Structural Biotechnology Journal 19 (2021) 424–438] by Abhinit Kumar, Saurabh Loharch, Sunil Kumar, Rajesh P. Ringe, Raman Parkesh

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TUCAN: A molecular identifier and descriptor applicable to the whole periodic table from hydrogen to oganesson by Jan C. Brammer, Gerd Blanke, Claudia Kellner, Alexander Hoffmann, Sonja Herres-Pawlis, Ulrich Schatzschneider

Subjects: “…Cheminformatics…”
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A Deep Learning-Based Quantitative Structure–Activity Relationship System Construct Prediction Model of Agonist and Antagonist with High Performance by Yasunari Matsuzaka, Yoshihiro Uesawa

Subjects: “…cheminformatics…”
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A review on machine learning approaches and trends in drug discovery by Paula Carracedo-Reboredo, Jose Liñares-Blanco, Nereida Rodríguez-Fernández, Francisco Cedrón, Francisco J. Novoa, Adrian Carballal, Victor Maojo, Alejandro Pazos, Carlos Fernandez-Lozano

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An industrial evaluation of proteochemometric modelling: Predicting drug-target affinities for kinases by Astrid Stroobants, Lewis H. Mervin, Ola Engkvist, Graeme R. Robb

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Talarolide A and Talaropeptides A–D: Potential Marine-Derived Therapeutic Peptides with Interesting Chemistry and Biological Activity Studied through Density Functional Theory (DFT... by Norma Flores-Holguín, Joan S. Salas-Leiva, Daniel Glossman-Mitnik

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QUIMIOINFORMÁTICA: UMA INTRODUÇÃO by Vinicius M. Alves, Rodolpho C. Braga, Eugene N. Muratov, Carolina Horta Andrade

Subjects: “…cheminformatics…”
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A Comprehensive Comparative Analysis of Deep Learning Based Feature Representations for Molecular Taste Prediction by Yu Song, Sihao Chang, Jing Tian, Weihua Pan, Lu Feng, Hongchao Ji

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Multi-channel PINN: investigating scalable and transferable neural networks for drug discovery by Munhwan Lee, Hyeyeon Kim, Hyunwhan Joe, Hong-Gee Kim

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RedPred, a machine learning model for the prediction of redox reaction energies of the aqueous organic electrolytes by Murat Cihan Sorkun, Elham Nour Ghassemi, Cihan Yatbaz, J.M. Vianney A. Koelman, Süleyman Er

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TCMIO: A Comprehensive Database of Traditional Chinese Medicine on Immuno-Oncology by Zhihong Liu, Chuipu Cai, Jiewen Du, Bingdong Liu, Lu Cui, Xiude Fan, Qihui Wu, Jiansong Fang, Jiansong Fang, Liwei Xie

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