Precision fragment addition: domain-specific DeepFrag2 models for smarter lead optimization

César R. García-Jacas, Harrison Green, Shayne D. Wierbowski and Jacob D. Durrant

Digital Discovery, 2026, 5, 1340
DOI: 10.1039/D5DD00425J

Characterizing the ligand-binding affinity toward SARS-CoV-2 Mproviaphysics- and knowledge-based approaches

Son Tung Ngo, Trung Hai Nguyen, Nguyen Thanh Tung, Van V. Vu, Minh Quan Pham and Binh Khanh Mai

Phys. Chem. Chem. Phys., 2022, 24, 29266
DOI: 10.1039/D2CP04476E

Searching and designing potential inhibitors for SARS-CoV-2 Mpro from natural sources using atomistic and deep-learning calculations

Nguyen Minh Tam, Duc-Hung Pham, Dinh Minh Hiep, Phuong-Thao Tran, Duong Tuan Quang and Son Tung Ngo

RSC Adv., 2021, 11, 38495
DOI: 10.1039/D1RA06534C

Deep generative design with 3D pharmacophoric constraints

Fergus Imrie, Thomas E. Hadfield, Anthony R. Bradley and Charlotte M. Deane

Chem. Sci., 2021, 12, 14577
DOI: 10.1039/D1SC02436A

Active learning driven prioritisation of compounds from on-demand libraries targeting the SARS-CoV-2 main protease

Ben Cree, Mateusz K. Bieniek, Siddique Amin, Akane Kawamura and Daniel J. Cole

Digital Discovery, 2025, 4, 438
DOI: 10.1039/D4DD00343H

Implementation of an AI-assisted fragment-generator in an open-source platform

Alan E. Bilsland, Angelo Pugliese and Justin Bower

RSC Med. Chem., 2022, 13, 1205
DOI: 10.1039/D2MD00152G

PILOT: equivariant diffusion for pocket-conditioned de novo ligand generation with multi-objective guidance via importance sampling

Julian Cremer, Tuan Le, Frank Noé, Djork-Arné Clevert and Kristof T. Schütt

Chem. Sci., 2024, 15, 14954
DOI: 10.1039/D4SC03523B

Leveraging artificial intelligence and machine learning in kinase inhibitor development: advances, challenges, and future prospects

Mohamed S. Elgawish, Aya M. Almatary, Sawsan A. Zaitone and Mohamed S. H. Salem

RSC Med. Chem., 2025, 16, 4698
DOI: 10.1039/D5MD00494B

Progress of AI-Driven Drug–Target Interaction Prediction and Lead Optimization

Qiqi Wang, Boyan Sun, Yunpeng Yi, Tony Velkov, Jianzhong Shen, Chongshan Dai and Haiyang Jiang

IJMS, 2025, 26, 10037
DOI: 10.3390/ijms262010037

Targeting GPCRs and Their Signaling as a Therapeutic Option in Melanoma

Jérémy H. Raymond, Zackie Aktary, Lionel Larue and Véronique Delmas

Cancers, 2022, 14, 706
DOI: 10.3390/cancers14030706

Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations

Quynh Mai Thai, Trung Hai Nguyen, George Binh Lenon, Huong Thi Thu Phung, Jim-Tong Horng, Phuong-Thao Tran and Son Tung Ngo

Journal of Molecular Graphics and Modelling, 2025, 134, 108906
DOI: 10.1016/j.jmgm.2024.108906

A novel compound to overcome influenza drug resistance in endonuclease inhibitors

Yixin Ren, Li Wan and Shuang Cao

Mol Divers, 2024, 28, 1323
DOI: 10.1007/s11030-023-10659-x

Machine learning in antiviral drug design

Anja Kolarič, Marko Jukič and Urban Bren

Bioorganic & Medicinal Chemistry, 2026, 132, 118426
DOI: 10.1016/j.bmc.2025.118426

Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discovery

Nazreen Pallikkavaliyaveetil and Sriram Chandrasekaran

Advanced Drug Delivery Reviews, 2026, 229, 115762
DOI: 10.1016/j.addr.2025.115762

A Machine Learning-Guided Approach to Navigate the Substrate Activity Scope of Galactose Oxidase: Application in the Conversion of Pharmaceutically Relevant Bulky Secondary Alcohols

Shreyas Supekar, Dillon W. P. Tay, Wan Lin Yeo, Kwok Wai Eric Tam, Ying Sin Koo, Jie Yang See, Jhoann M. T. Miyajima, Sebastian Maurer-Stroh, Ee Lui Ang, Yee Hwee Lim and Hao Fan

ACS Catal., 2024, 14, 17233
DOI: 10.1021/acscatal.4c04660

Hit Identification Driven by Combining Artificial Intelligence and Computational Chemistry Methods: A PI5P4K-β Case Study

Lin Wei, Min Xu, Zhiqiang Liu, Chongguo Jiang, Xiaohua Lin, Yaogang Hu, Xiaoming Wen, Rongfeng Zou, Chunwang Peng, Hongrui Lin, Guo Wang, Lijun Yang, Lei Fang, Mingjun Yang and Peiyu Zhang

J. Chem. Inf. Model., 2023, 63, 5341
DOI: 10.1021/acs.jcim.3c00543

Augmenting optimization-based molecular design with graph neural networks

Shiqiang Zhang, Juan S. Campos, Christian Feldmann, Frederik Sandfort, Miriam Mathea and Ruth Misener

Computers & Chemical Engineering, 2024, 186, 108684
DOI: 10.1016/j.compchemeng.2024.108684

Drug Discovery in the Age of Artificial Intelligence: Transformative Target-Based Approaches

Akshata Yashwant Patne, Sai Madhav Dhulipala, William Lawless, Satya Prakash, Shyam S. Mohapatra and Subhra Mohapatra

IJMS, 2024, 25, 12233
DOI: 10.3390/ijms252212233

Unlocking the potential of marine natural product fragments for rational anticancer drug design: a computational approach

Marineil C. Gomez, Kavitha Rajendran and Lemmuel L. Tayo

Sci Rep, 2026
DOI: 10.1038/s41598-026-44280-3

Streamlining Computational Fragment-Based Drug Discovery through Evolutionary Optimization Informed by Ligand-Based Virtual Prescreening

Rohan Chandraghatgi, Hai-Feng Ji, Gail L. Rosen and Bahrad A. Sokhansanj

J. Chem. Inf. Model., 2024, 64, 3826
DOI: 10.1021/acs.jcim.4c00234

Limeade: Let integer molecular encoding aid

Shiqiang Zhang, Christian W. Feldmann, Frederik Sandfort, Miriam Mathea, Juan S. Campos and Ruth Misener

Computers & Chemical Engineering, 2025, 199, 109115
DOI: 10.1016/j.compchemeng.2025.109115

Designing Potential Inhibitors of SARS-CoV-2 Mpro Using Deep Learning and Steered Molecular Dynamic Simulations

Nguyen Minh Tam, Linh Hoang Tran, Quan V. Vo, Minh Quan Pham and Huong Thi Thu Phung

J. Comput. Biophys. Chem., 2023, 22, 525
DOI: 10.1142/S2737416523500242

FragExplorer: GRID-Based Fragment Growing and Replacement

Simon Cross and Gabriele Cruciani

J. Chem. Inf. Model., 2022, 62, 1224
DOI: 10.1021/acs.jcim.1c00821

Computing the relative binding affinity of ligands based on a pairwise binding comparison network

Jie Yu, Zhaojun Li, Geng Chen, Xiangtai Kong, Jie Hu, Dingyan Wang, Duanhua Cao, Yanbei Li, Ruifeng Huo, Gang Wang, Xiaohong Liu, Hualiang Jiang, Xutong Li, Xiaomin Luo and Mingyue Zheng

Nat Comput Sci, 2023, 3, 860
DOI: 10.1038/s43588-023-00529-9

Generative models for molecular discovery: Recent advances and challenges

Camille Bilodeau, Wengong Jin, Tommi Jaakkola, Regina Barzilay and Klavs F. Jensen

WIREs Comput Mol Sci, 2022, 12
DOI: 10.1002/wcms.1608

MolMod: a molecular modification platform for molecular property optimization via fragment-based generation

Yao Zhou, Zhipei Sang, Chao Xu, Ze Cao, Kaixiang Xiao, Qian Jia, Yutao He, Haibin Luo and Shuheng Huang

Mol Divers, 2025
DOI: 10.1007/s11030-025-11342-z

PepLand: a large-scale pre-trained peptide representation model for a comprehensive landscape of both canonical and non-canonical amino acids

Ruochi Zhang, Haoran Wu, Chang Liu, Qian Yang, Yuting Xiu, Kewei Li, Ningning Chen, Yu Wang, Yan Wang, Xin Gao and Fengfeng Zhou

Briefings in Bioinformatics, 2025, 26
DOI: 10.1093/bib/bbaf367

BMaps: A Web Application for Fragment-Based Drug Design and Compound Binding Evaluation

Daniel R. Bryan, John L. Kulp, Manoj K. Mahapatra, Richard L. Bryan, Usha Viswanathan, Micah N. Carlisle, Surim Kim, William D. Schutte, Kevaughn V. Clarke, Tony T. Doan and John L. Kulp

J. Chem. Inf. Model., 2023, 63, 4229
DOI: 10.1021/acs.jcim.3c00209

Upgrading nirmatrelvir to inhibit SARS-CoV-2 Mpro via DeepFrag and free energy calculations

Nguyen Minh Tam, Trung Hai Nguyen, Minh Quan Pham, Nam Dao Hong, Nguyen Thanh Tung, Van V. Vu, Duong Tuan Quang and Son Tung Ngo

Journal of Molecular Graphics and Modelling, 2023, 124, 108535
DOI: 10.1016/j.jmgm.2023.108535

Utilizing artificial intelligence for precision exploration of N protein targeting phenanthridine sars-cov-2 inhibitors: A novel approach

Zheng-rui Xiang, Shi-rui Fan, Juan Ren, Ting Ruan, Yuan Chen, Yun-wu Zhang, Yi-ting Wang, Ze-zhou Yu, Chao-fan Wang, Xiao-long Sun, Xiao-Jiang Hao and Duo-Zhi Chen

European Journal of Medicinal Chemistry, 2024, 279, 116885
DOI: 10.1016/j.ejmech.2024.116885

Systemic evolutionary chemical space exploration for drug discovery

Chong Lu, Shien Liu, Weihua Shi, Jun Yu, Zhou Zhou, Xiaoxiao Zhang, Xiaoli Lu, Faji Cai, Ning Xia and Yikai Wang

J Cheminform, 2022, 14
DOI: 10.1186/s13321-022-00598-4

Fragment‐based drug discovery—the importance of high‐quality molecule libraries

Marta Bon, Alan Bilsland, Justin Bower and Kirsten McAulay

Molecular Oncology, 2022, 16, 3761
DOI: 10.1002/1878-0261.13277

FragGrow: A Web Server for Structure-Based Drug Design by Fragment Growing within Constraints

Yueqing Zhang, Zhihan Zhang, Dongliang Ke, Xiaolin Pan, Xingyu Wang, Xudong Xiao and Changge Ji

J. Chem. Inf. Model., 2024, 64, 3970
DOI: 10.1021/acs.jcim.4c00154

Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations

Alejandro Martínez León, Benjamin Ries, Jochen S. Hub and Aniket Magarkar

J Cheminform, 2025, 17
DOI: 10.1186/s13321-025-01022-3

MolSHAP: Interpreting Quantitative Structure–Activity Relationships Using Shapley Values of R-Groups

Tingzhong Tian, Shuya Li, Meng Fang, Dan Zhao and Jianyang Zeng

J. Chem. Inf. Model., 2024, 64, 2236
DOI: 10.1021/acs.jcim.3c00465

A deep learning model for structure-based bioactivity optimization and its application in the bioactivity optimization of a SARS-CoV-2 main protease inhibitor

Zhenyu Yang, Kai Wang, Guo Zhang, Yuanyuan Jiang, Rui Zeng, Jingxin Qiao, Yueyue Li, Xinyue Deng, Ziyi Xia, Rui Yao, Xiaoxi Zeng, Liyun Zhang, Yi Zhao, Jian Lei and Runsheng Chen

European Journal of Medicinal Chemistry, 2025, 291, 117602
DOI: 10.1016/j.ejmech.2025.117602

Geometric Deep Learning for Structure-Based Ligand Design

Alexander S. Powers, Helen H. Yu, Patricia Suriana, Rohan V. Koodli, Tianyu Lu, Joseph M. Paggi and Ron O. Dror

ACS Cent. Sci., 2023, 9, 2257
DOI: 10.1021/acscentsci.3c00572

Bridging chemical space and biological efficacy: advances and challenges in applying generative models in structural modification of natural products

Chuan-Su Liu, Bing-Chao Yan, Han-Dong Sun, Jin-Cai Lu and Pema-Tenzin Puno

Nat. Prod. Bioprospect., 2025, 15
DOI: 10.1007/s13659-025-00521-y

An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors

Tony Eight Lin, Dyan Yen, Wei‐Chun HuangFu, Yi‐Wen Wu, Jui‐Yi Hsu, Shih‐Chung Yen, Tzu‐Ying Sung, Jui‐Hua Hsieh, Shiow‐Lin Pan, Chia‐Ron Yang, Wei‐Jan Huang and Kai‐Cheng Hsu

Protein Science, 2024, 33
DOI: 10.1002/pro.5007

Incorporating Target-Specific Pharmacophoric Information into Deep Generative Models for Fragment Elaboration

Thomas E. Hadfield, Fergus Imrie, Andy Merritt, Kristian Birchall and Charlotte M. Deane

J. Chem. Inf. Model., 2022, 62, 2280
DOI: 10.1021/acs.jcim.1c01311

Generative AI in structure-based drug discovery

Zhuoya Zhong and Jacob D. Durrant

BMC Biol, 2026
DOI: 10.1186/s12915-026-02575-x

Structure-Based Drug Design with a Deep Hierarchical Generative Model

Jesse A. Weller and Remo Rohs

J. Chem. Inf. Model., 2024, 64, 6450
DOI: 10.1021/acs.jcim.4c01193

Structure-based design of anticancer drugs based on β-elemene: Research foundations and development potential

Haiyi Chen, Yuntao Yu, Chenghong Hu, Lehuang Zhou, Zhe Wang, Odin Zhang, Yi Wang and Tian Xie

Journal of Pharmaceutical Analysis, 2025, 15, 101325
DOI: 10.1016/j.jpha.2025.101325

Role of artificial intelligence in cancer drug discovery and development

Sruthi Sarvepalli and ShubhaDeepthi Vadarevu

Cancer Letters, 2025, 627, 217821
DOI: 10.1016/j.canlet.2025.217821

Concept-Driven Deep Learning for Enhanced Protein-Specific Molecular Generation

Taojie Kuang, Qianli Ma, Athanasios V. Vasilakos, Yu Wang, Qiang Cheng and Zhixiang Ren

ACM Trans. Knowl. Discov. Data, 2026, 20, 1
DOI: 10.1145/3779063

BEGAN: Boltzmann-Reweighted Data Augmentation for Enhanced GAN-Based Molecule Design in Insect Pheromone Receptors

Jialei Dai, Yutong Zhang, Chen Shi, Yang Liu, Peng Xiu and Yong Wang

J. Phys. Chem. B, 2024, 128, 11666
DOI: 10.1021/acs.jpcb.4c06729

Efficient Hit-to-Lead Searching of Kinase Inhibitor Chemical Space via Computational Fragment Merging

Grigorii V. Andrianov, Wern Juin Gabriel Ong, Ilya Serebriiskii and John Karanicolas

J. Chem. Inf. Model., 2021, 61, 5967
DOI: 10.1021/acs.jcim.1c00630

MolModa: accessible and secure molecular docking in a web browser

Yuri Kochnev, Mayar Ahmed, Alex M Maldonado and Jacob D Durrant

Nucleic Acids Research, 2024, 52, W498
DOI: 10.1093/nar/gkae406

Simulation- and AI-directed optimization of 4,6-substituted 1,3,5-triazin-2(1H)-ones as inhibitors of human DNA topoisomerase IIα

Barbara Herlah, Tjaša Goričan, Nika Strašek Benedik, Simona Golič Grdadolnik, Izidor Sosič and Andrej Perdih

Computational and Structural Biotechnology Journal, 2024, 23, 2995
DOI: 10.1016/j.csbj.2024.06.037

Deep Learning Based Methods for Molecular Similarity Searching: A Systematic Review

Maged Nasser, Umi Kalsom Yusof and Naomie Salim

Processes, 2023, 11, 1340
DOI: 10.3390/pr11051340

Design of RNA Polymerase Inhibitors as Therapeutics for Tuberculous Meningitis

Varalakshmi Vummidi and Sekhar Talluri

IDDT, 2025, 25
DOI: 10.2174/0118715265341228240827062721

Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds

Trung Hai Nguyen, Quynh Mai Thai, Minh Quan Pham, Pham Thi Hong Minh and Huong Thi Thu Phung

Mol Divers, 2024, 28, 553
DOI: 10.1007/s11030-023-10601-1

ACFIS 2.0: an improved web-server for fragment-based drug discovery via a dynamic screening strategy

Xing-Xing Shi, Zhi-Zheng Wang, Fan Wang, Ge-Fei Hao and Guang-Fu Yang

Nucleic Acids Research, 2023, 51, W25
DOI: 10.1093/nar/gkad348

Artificial intelligence-driven discovery of novel scaffolds for selective TLR7 antagonists and their application in enhancing mRNA translation efficiency

Soyeon Yoo, Kounghwa Youn, Nawoon Kim, Gyochang Keum, Hahnbeom Park and Eun-Kyoung Bang

European Journal of Pharmaceutical Sciences, 2025, 212, 107172
DOI: 10.1016/j.ejps.2025.107172

3D molecular generative framework for interaction-guided drug design

Wonho Zhung, Hyeongwoo Kim and Woo Youn Kim

Nat Commun, 2024, 15
DOI: 10.1038/s41467-024-47011-2

Open-Source Browser-Based Tools for Structure-Based Computer-Aided Drug Discovery

Ann Wang and Jacob D. Durrant

Molecules, 2022, 27, 4623
DOI: 10.3390/molecules27144623

An open-source molecular builder and free energy preparation workflow

Mateusz K. Bieniek, Ben Cree, Rachael Pirie, Joshua T. Horton, Natalie J. Tatum and Daniel J. Cole

Commun Chem, 2022, 5
DOI: 10.1038/s42004-022-00754-9

Deep lead optimization enveloped in protein pocket and its application in designing potent and selective ligands targeting LTK protein

Shicheng Chen, Odin Zhang, Chenran Jiang, Huifeng Zhao, Xujun Zhang, Mengting Chen, Yun Liu, Qun Su, Zhenxing Wu, Xinyue Wang, Wanglin Qu, Yuanyi Ye, Xin Chai, Ning Wang, Tianyue Wang, Yuan An, Guanlin Wu, Qianqian Yang, Jiean Chen, Wei Xie, Haitao Lin, Dan Li, Chang-Yu Hsieh, Yong Huang, Yu Kang, Tingjun Hou and Peichen Pan

Nat Mach Intell, 2025, 7, 448
DOI: 10.1038/s42256-025-00997-w

A multilevel generative framework with hierarchical self-contrasting for bias control and transparency in structure-based ligand design

Lucian Chan, Rajendra Kumar, Marcel Verdonk and Carl Poelking

Nat Mach Intell, 2022, 4, 1130
DOI: 10.1038/s42256-022-00564-7

FGDB: a comprehensive graph database of ligand fragments from the Protein Data Bank

Daniele Toti, Gabriele Macari, Enrico Barbierato and Fabio Polticelli

Database, 2022, 2022
DOI: 10.1093/database/baac044

Fragment-based drug discovery supports drugging ‘undruggable’ protein–protein interactions

Zhi-Zheng Wang, Xing-Xing Shi, Guang-Yi Huang, Ge-Fei Hao and Guang-Fu Yang

Trends in Biochemical Sciences, 2023, 48, 539
DOI: 10.1016/j.tibs.2023.01.008

ChemistGA: A Chemical Synthesizable Accessible Molecular Generation Algorithm for Real-World Drug Discovery

Jike Wang, Xiaorui Wang, Huiyong Sun, Mingyang Wang, Yundian Zeng, Dejun Jiang, Zhenxing Wu, Zeyi Liu, Ben Liao, Xiaojun Yao, Chang-Yu Hsieh, Dongsheng Cao, Xi Chen and Tingjun Hou

J. Med. Chem., 2022, 65, 12482
DOI: 10.1021/acs.jmedchem.2c01179

Recent advances and applications of deep learning methods in materials science

Kamal Choudhary, Brian DeCost, Chi Chen, Anubhav Jain, Francesca Tavazza, Ryan Cohn, Cheol Woo Park, Alok Choudhary, Ankit Agrawal, Simon J. L. Billinge, Elizabeth Holm, Shyue Ping Ong and Chris Wolverton

npj Comput Mater, 2022, 8
DOI: 10.1038/s41524-022-00734-6

Machine learning‐assisted search for novel coagulants: When machine learning can be efficient even if data availability is low

Andrij Rovenchak and Maksym Druchok

J Comput Chem, 2024, 45, 937
DOI: 10.1002/jcc.27292

Deep Lead Optimization: Leveraging Generative AI for Structural Modification

Odin Zhang, Haitao Lin, Hui Zhang, Huifeng Zhao, Yufei Huang, Chang-Yu Hsieh, Peichen Pan and Tingjun Hou

J. Am. Chem. Soc., 2024, 146, 31357
DOI: 10.1021/jacs.4c11686

A 3D pocket-aware lead optimization model with knowledge guidance and its application for discovery of new glutaminyl cyclase inhibitors

Anjie Qiao, Yuting Chen, Junjie Xie, Weifeng Huang, Hao Zhang, Qirui Deng, Jiahua Rao, Ji Deng, Fanbo Meng, Zhen Wang, Mingyuan Xu, Hongming Chen, Jiancong Xie, Shuangjia Zheng, Yuedong Yang, Guo-Bo Li and Jinping Lei

Briefings in Bioinformatics, 2025, 26
DOI: 10.1093/bib/bbaf345

Text-guided multi-property molecular optimization with a diffusion language model

Yida Xiong, Kun Li, Jiameng Chen, Hongzhi Zhang, Di Lin, Yan Che and Wenbin Hu

Information Fusion, 2026, 127, 103907
DOI: 10.1016/j.inffus.2025.103907

An effective fragment-based dual conditional diffusion framework for molecular generation

Haotian Chen, Yiting Shen, Jichun Li and Weizhong Zhao

Briefings in Bioinformatics, 2026, 27
DOI: 10.1093/bib/bbaf727

Computational Design of Multitargeted Ligands to Counter Drug Resistance of Mycobacterium Tuberculosis

Varalakshmi Vummidi and Sekhar Talluri

TOMCJ, 2025, 19
DOI: 10.2174/0118741045367943250203071653

Transfer learning with molecular graph convolutional networks for accurate modeling and representation of bioactivities of ligands targeting GPCRs without sufficient data

Jiansheng Wu, Chuangchuang Lan, Zheming Mei, Xiaohuyan Chen, Yanxiang Zhu, Haifeng Hu and Yemin Diao

Computational Biology and Chemistry, 2022, 98, 107664
DOI: 10.1016/j.compbiolchem.2022.107664