Text mining in MOF research: from manual curation to large language model-based automation

Suyeon Bae, Mingyu Jeon and Hoi Ri Moon

Chem. Commun., 2025, 61, 11083
DOI: 10.1039/D5CC02511G

AI agents in chemical research: GVIM – an intelligent research assistant system

Kangyong Ma

Digital Discovery, 2025, 4, 355
DOI: 10.1039/D4DD00398E

AI and automation: democratizing automation and the evolution towards true AI-autonomous robotics

Lauren Takahashi, Mikael Kuwahara and Keisuke Takahashi

Chem. Sci., 2025, 16, 15769
DOI: 10.1039/D5SC03183D

Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry

Austin M. Mroz, Annabel R. Basford, Friedrich Hastedt, Isuru Shavindra Jayasekera, Irea Mosquera-Lois, Ruby Sedgwick, Pedro J. Ballester, Joshua D. Bocarsly, Ehecatl Antonio del Río Chanona, Matthew L. Evans, Jarvist M. Frost, Alex M. Ganose, Rebecca L. Greenaway, King Kuok (Mimi) Hii, Yingzhen Li, Ruth Misener, Aron Walsh, Dandan Zhang and Kim E. Jelfs

Chem. Soc. Rev., 2025, 54, 5433
DOI: 10.1039/D5CS00146C

General-Purpose Models for the Chemical Sciences: LLMs and Beyond

Nawaf Alampara, Anagha Aneesh, Martiño Ríos-García, Adrian Mirza, Mara Schilling-Wilhelmi, Ali Asghar Aghajani, Meiling Sun, Gordan Prastalo and Kevin Maik Jablonka

Chem. Rev., 2026, 126, 2484
DOI: 10.1021/acs.chemrev.5c00583

Application and Prospects of Large Language Models in Small-Molecule Drug Discovery

Jin Ma, Jia Liu, Dongyu Xu, Xiaoyu Song and Zhichang Zhang

Anal. Chem., 2025, 97, 27453
DOI: 10.1021/acs.analchem.5c04083

Large language models for building energy applications: Opportunities and challenges

Mingzhe Liu, Liang Zhang, Jianli Chen, Wei-An Chen, Zhiyao Yang, L. James Lo, Jin Wen and Zheng O’Neill

Build. Simul., 2025, 18, 225
DOI: 10.1007/s12273-025-1235-9

RPSubAlign: a novel sequence-based molecular representation method for retrosynthesis prediction with improved validity and robustness

Yuting Hu, Feng Hu, Hongwen Zhang, Hongling Xu, Jixiang Gao, Wenshuai Deng, Zijing Tian, Qiaoyu Hu, Honglin Li and Yanyan Diao

Briefings in Bioinformatics, 2025, 26
DOI: 10.1093/bib/bbaf257

Design, Synthesis and Biological Evaluation of Novel, Potent, Selective and Orally Available DGKα Inhibitors for the Treatment of Tumors

Hongfu Lu, Sujing Shi, Huaxing Yu, Deheng Sun, Haoyu Zhang, Hui Cui, Xin Cai, Xiao Ding, Shan Chen, Man Zhang, Jinxin Liu, Ryan Shi, Alex Aliper, Feng Ren and Alex Zhavoronkov

J. Med. Chem., 2025, 68, 25011
DOI: 10.1021/acs.jmedchem.5c01943

Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools

Varun Dewaker, Vivek Kumar Morya, Yoo Hee Kim, Sung Taek Park, Hyeong Su Kim and Young Ho Koh

Biomark Res, 2025, 13
DOI: 10.1186/s40364-025-00764-4

Multimodal pre-training models of molecular representation for drug discovery

Xiaoqi Wang, Chuanshi Wang, Boya Ji, Junwen Wang, Mingyue Zheng, Lingyun Song, Shaoliang Peng and Xuequn Shang

National Science Review, 2026, 13
DOI: 10.1093/nsr/nwaf495

Language Models for Predicting Organic Synthesis Procedures

Mantas Vaškevičius and Jurgita Kapočiūtė-Dzikienė

Applied Sciences, 2024, 14, 11526
DOI: 10.3390/app142411526

Measuring Chemical LLM robustness to molecular representations: a SMILES variation-based framework

Veronika Ganeeva, Kuzma Khrabrov, Artur Kadurin and Elena Tutubalina

J Cheminform, 2025, 17
DOI: 10.1186/s13321-025-01079-0

From LLM to Agent: A large-language-model-driven machine learning framework for catalyst design of MgH2 dehydrogenation

Tongao Yao, Yang Yang, Jianghao Cai, Rui Liu, Zhaoyan Dong, Xiaotian Tang, Xuqiang Shao, Zhengyang Gao, Guangyao An and Weijie Yang

Journal of Magnesium and Alloys, 2026, 14, 101858
DOI: 10.1016/j.jma.2025.08.021

Deep Learning vs Classical Methods in Potency and ADME Prediction: Insights from a Computational Blind Challenge

Yaëlle Fischer, Thibaud Southiratn, Dhoha Triki and Ruel Cedeno

J. Chem. Inf. Model., 2025, 65, 13115
DOI: 10.1021/acs.jcim.5c01982

Chemical Language Model Linker: Blending Text and Molecules with Modular Adapters

Yifan Deng, Spencer S. Ericksen and Anthony Gitter

J. Chem. Inf. Model., 2025, 65, 8944
DOI: 10.1021/acs.jcim.5c00853

Unified Deep Learning of Molecular and Protein Language Representations with T5ProtChem

Thomas Kelly, Song Xia, Jieyu Lu and Yingkai Zhang

J. Chem. Inf. Model., 2025, 65, 3990
DOI: 10.1021/acs.jcim.5c00051

On the use of chemical bonding descriptors in machine learning

Michele Tomasini, Lucia Caporaso, Martí Gimferrer and Albert Poater

Coordination Chemistry Reviews, 2026, 550, 217383
DOI: 10.1016/j.ccr.2025.217383

A survey on large language models in biology and chemistry

Islambek Ashyrmamatov, Su Ji Gwak, Su-Young Jin, Ikhyeong Jun, Umit V. Ucak, Jay-Yoon Lee and Juyong Lee

Exp Mol Med, 2026
DOI: 10.1038/s12276-025-01583-1

AI-driven toolset for IPF and aging research associates lung fibrosis with accelerated aging

Fedor Galkin, Shan Chen, Alex Aliper, Alex Zhavoronkov and Feng Ren

Aging, 2025
DOI: 10.18632/aging.206295

A Perspective on Foundation Models in Chemistry

Junyoung Choi, Gunwook Nam, Jaesik Choi and Yousung Jung

JACS Au, 2025, 5, 1499
DOI: 10.1021/jacsau.4c01160

A Novel Low-Resource Graph Convolutional Neural Network Approach for Entity Recognition

Zhen Zhao and Xinyu Li

IEEE Trans. Comput. Biol. Bioinform., 2025, 22, 3188
DOI: 10.1109/TCBBIO.2025.3614139

Machine learning predicts upper secondary education dropout as early as the end of primary school

Maria Psyridou, Fabi Prezja, Minna Torppa, Marja-Kristiina Lerkkanen, Anna-Maija Poikkeus and Kati Vasalampi

Sci Rep, 2024, 14
DOI: 10.1038/s41598-024-63629-0

An automatic end-to-end chemical synthesis development platform powered by large language models

Yixiang Ruan, Chenyin Lu, Ning Xu, Yuchen He, Yixin Chen, Jian Zhang, Jun Xuan, Jianzhang Pan, Qun Fang, Hanyu Gao, Xiaodong Shen, Ning Ye, Qiang Zhang and Yiming Mo

Nat Commun, 2024, 15
DOI: 10.1038/s41467-024-54457-x

Adversarial attacks and defenses for large language models (LLMs): methods, frameworks & challenges

Pranjal Kumar

Int J Multimed Info Retr, 2024, 13
DOI: 10.1007/s13735-024-00334-8

Advancements in Large Language Models (LLMs): Empowering Drug Discovery

Bosheng Song, Xiaowen Li, Xiuxiu Chao, Li Wang, Yiping Liu, Zhen Xia, Dongsheng Cao and Xiangzheng Fu

WIREs Comput Mol Sci, 2025, 15
DOI: 10.1002/wcms.70054

L’IA générative : une révolution technologique entre promesses et défis

Éric Moulines

Annales des Mines - Réalités industrielles, 2025, Mai 2025, 7
DOI: 10.3917/rindu1.252.0007

Development of LLM-assisted data curation tools for the Starrydata materials science database

Yukari Katsura, Tomoya Mato, Yu Takada, Eiji Koyama, Dewi Yana, Atsumi Tanaka and Masaya Kumagai

Science and Technology of Advanced Materials: Methods, 2025, 5
DOI: 10.1080/27660400.2025.2590811

Exploring open source as a strategy to enhance R&D productivity

Alexander Schuhmacher

Expert Opinion on Drug Discovery, 2024, 19, 1399
DOI: 10.1080/17460441.2024.2417352

Deep Learning for Computational Heterogeneous Catalysis: Fundamentals and Applications

Gaurav Deshmukh, Pushkar Ghanekar and Jeffrey Greeley

J Indian Inst Sci, 2025
DOI: 10.1007/s41745-025-00484-6

Practical guide for food scientists to build AI: data, algorithms, and applications

Dachuan Zhang

Food Chemistry, 2026, 499, 147281
DOI: 10.1016/j.foodchem.2025.147281

Discovery of Novel, Potent, Selective, and Orally Available DGKα Inhibitors for the Treatment of Tumors

Hongfu Lu, Deheng Sun, Haoyu Zhang, Sujing Shi, Huaxing Yu, Hui Cui, Xin Cai, Xiao Ding, Shan Chen, Man Zhang, Alex Aliper, Feng Ren and Alex Zhavoronkov

J. Med. Chem., 2025, 68, 19645
DOI: 10.1021/acs.jmedchem.5c01944