Paola Ruiz Puentes, Laura Rueda-Gensini, Natalia Valderrama, Isabela Hernández, Cristina González, Laura Daza, Carolina Muñoz-Camargo, Juan C. Cruz and Pablo Arbeláez

Sci Rep, 2022, 12
DOI: 10.1038/s41598-022-12180-x

Elucidating the role of artificial intelligence in drug development from the perspective of drug-target interactions

Boyang Wang, Tingyu Zhang, Qingyuan Liu, Chayanis Sutcharitchan, Ziyi Zhou, Dingfan Zhang and Shao Li

Journal of Pharmaceutical Analysis, 2025, 15, 101144
DOI: 10.1016/j.jpha.2024.101144

MatchMaker: A Deep Learning Framework for Drug Synergy Prediction

Halil Ibrahim Kuru, Oznur Tastan and A. Ercument Cicek

IEEE/ACM Trans. Comput. Biol. and Bioinf., 2022, 19, 2334
DOI: 10.1109/TCBB.2021.3086702

A brief review of protein–ligand interaction prediction

Lingling Zhao, Yan Zhu, Junjie Wang, Naifeng Wen, Chunyu Wang and Liang Cheng

Computational and Structural Biotechnology Journal, 2022, 20, 2831
DOI: 10.1016/j.csbj.2022.06.004

Deep Learning in Virtual Screening: Recent Applications and Developments

Talia B. Kimber, Yonghui Chen and Andrea Volkamer

IJMS, 2021, 22, 4435
DOI: 10.3390/ijms22094435

DWPPI: A Deep Learning Approach for Predicting Protein–Protein Interactions in Plants Based on Multi-Source Information With a Large-Scale Biological Network

Jie Pan, Zhu-Hong You, Li-Ping Li, Wen-Zhun Huang, Jian-Xin Guo, Chang-Qing Yu, Li-Ping Wang and Zheng-Yang Zhao

Front. Bioeng. Biotechnol., 2022, 10
DOI: 10.3389/fbioe.2022.807522

Machine Learning-Enabled Genome Mining and Bioactivity Prediction of Natural Products

Yujie Yuan, Chengyou Shi and Huimin Zhao

ACS Synth. Biol., 2023, 12, 2650
DOI: 10.1021/acssynbio.3c00234

Visualizations for universal deep-feature representations: survey and taxonomy

Tomáš Skopal, Ladislav Peška, David Hoksza, Ivana Sixtová and David Bernhauer

Knowl Inf Syst, 2024, 66, 811
DOI: 10.1007/s10115-023-01933-3

Artificial intelligence revolution in drug discovery: A paradigm shift in pharmaceutical innovation

Somayah J. Jarallah, Fahad A. Almughem, Nada K. Alhumaid, Nojoud AL Fayez, Ibrahim Alradwan, Khulud A. Alsulami, Essam A. Tawfik and Abdullah A. Alshehri

International Journal of Pharmaceutics, 2025, 680, 125789
DOI: 10.1016/j.ijpharm.2025.125789

multi-type neighbors enhanced global topology and pairwise attribute learning for drug–protein interaction prediction

Ping Xuan, Xiaowen Zhang, Yu Zhang, Kaimiao Hu, Toshiya Nakaguchi and Tiangang Zhang

Briefings in Bioinformatics, 2022, 23
DOI: 10.1093/bib/bbac120

Advances in De Novo Drug Design: From Conventional to Machine Learning Methods

Varnavas D. Mouchlis, Antreas Afantitis, Angela Serra, Michele Fratello, Anastasios G. Papadiamantis, Vassilis Aidinis, Iseult Lynch, Dario Greco and Georgia Melagraki

IJMS, 2021, 22, 1676
DOI: 10.3390/ijms22041676

Computational healthcare: Present and future perspectives (Review)

Ayumu Asai, Masamitsu Konno, Masateru Taniguchi, Andrea Vecchione and Hideshi Ishii

Exp Ther Med, 2021, 22
DOI: 10.3892/etm.2021.10786

Machine Learning for Sequence and Structure-Based Protein–Ligand Interaction Prediction

Yunjiang Zhang, Shuyuan Li, Kong Meng and Shaorui Sun

J. Chem. Inf. Model., 2024, 64, 1456
DOI: 10.1021/acs.jcim.3c01841

A comprehensive survey of drug–target interaction analysis in allopathy and siddha medicine

Uma E., Mala T., Geetha A.V. and Priyanka D.

Artificial Intelligence in Medicine, 2024, 157, 102986
DOI: 10.1016/j.artmed.2024.102986

Validation guidelines for drug-target prediction methods

Ziaurrehman Tanoli, Aron Schulman and Tero Aittokallio

Expert Opinion on Drug Discovery, 2025, 20, 31
DOI: 10.1080/17460441.2024.2430955

SperoPredictor: An Integrated Machine Learning and Molecular Docking-Based Drug Repurposing Framework With Use Case of COVID-19

Faheem Ahmed, Jae Wook Lee, Anupama Samantasinghar, Young Su Kim, Kyung Hwan Kim, In Suk Kang, Fida Hussain Memon, Jong Hwan Lim and Kyung Hyun Choi

Front. Public Health, 2022, 10
DOI: 10.3389/fpubh.2022.902123

Trends and Potential of Machine Learning and Deep Learning in Drug Study at Single-Cell Level

Ren Qi and Quan Zou

Research, 2023, 6
DOI: 10.34133/research.0050

CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations

Tunca Doğan, Heval Atas, Vishal Joshi, Ahmet Atakan, Ahmet Sureyya Rifaioglu, Esra Nalbat, Andrew Nightingale, Rabie Saidi, Vladimir Volynkin, Hermann Zellner, Rengul Cetin-Atalay, Maria Martin and Volkan Atalay

Nucleic Acids Research, 2021, 49, e96
DOI: 10.1093/nar/gkab543

ColdstartCPI: Induced-fit theory-guided DTI predictive model with improved generalization performance

Qichang Zhao, Haochen Zhao, Linyuan Guo, Kai Zheng, Yajie Li, Qiao Ling, Jing Tang, Yaohang Li and Jianxin Wang

Nat Commun, 2025, 16
DOI: 10.1038/s41467-025-61745-7

Drug-Target Interaction Prediction via Graph Auto-Encoder and Multi-Subspace Deep Neural Networks

Qing Ye, Xiaolong Zhang and Xiaoli Lin

IEEE/ACM Trans. Comput. Biol. and Bioinf., 2023, 20, 2647
DOI: 10.1109/TCBB.2022.3206907

DTA Atlas: A massive-scale drug repurposing database

Madina Sultanova, Elizaveta Vinogradova, Alisher Amantay, Ferdinand Molnár and Siamac Fazli

Artificial Intelligence in the Life Sciences, 2024, 6, 100115
DOI: 10.1016/j.ailsci.2024.100115

Protein domain-based prediction of drug/compound–target interactions and experimental validation on LIM kinases

Tunca Doğan, Ece Akhan Güzelcan, Marcus Baumann, Altay Koyas, Heval Atas, Ian R. Baxendale, Maria Martin, Rengul Cetin-Atalay and Feixiong Cheng

PLoS Comput Biol, 2021, 17, e1009171
DOI: 10.1371/journal.pcbi.1009171

Learning functional properties of proteins with language models

Serbulent Unsal, Heval Atas, Muammer Albayrak, Kemal Turhan, Aybar C. Acar and Tunca Doğan

Nat Mach Intell, 2022, 4, 227
DOI: 10.1038/s42256-022-00457-9

ACGCN: Graph Convolutional Networks for Activity Cliff Prediction between Matched Molecular Pairs

Junhui Park, Gaeun Sung, SeungHyun Lee, SeungHo Kang and ChunKyun Park

J. Chem. Inf. Model., 2022, 62, 2341
DOI: 10.1021/acs.jcim.2c00327

Multi-target prediction for dummies using two-branch neural networks

Dimitrios Iliadis, Bernard De Baets and Willem Waegeman

Mach Learn, 2022, 111, 651
DOI: 10.1007/s10994-021-06104-5

Screening of antibacterial compounds with novel structure from the FDA approved drugs using machine learning methods

Wen-Xing Li, Xin Tong, Peng-Peng Yang, Yang Zheng, Ji-Hao Liang, Gong-Hua Li, Dahai Liu, Dao-Gang Guan and Shao-Xing Dai

Aging, 2022, 14, 1448
DOI: 10.18632/aging.203887

ICAN: Interpretable cross-attention network for identifying drug and target protein interactions

Hiroyuki Kurata, Sho Tsukiyama and Lun Hu

PLoS ONE, 2022, 17, e0276609
DOI: 10.1371/journal.pone.0276609

Development of Antiepileptic Drugs throughout History: From Serendipity to Artificial Intelligence

María Corrales-Hernández, Sebastián Villarroel-Hagemann, Isabella Mendoza-Rodelo, Leonardo Palacios-Sánchez, Mariana Gaviria-Carrillo, Natalia Buitrago-Ricaurte, Santiago Espinosa-Lugo, Carlos-Alberto Calderon-Ospina and Jesús Rodríguez-Quintana

Biomedicines, 2023, 11, 1632
DOI: 10.3390/biomedicines11061632

Artificial Intelligence in Pharmaceutical Drug Development-challenges and the Way Forward

Venkateshwaran Krishnaswami, Selvakumar Muruganantham, Jacob Raja, Saravanakumar Arthanari, Brito Raj Selvaraj and Jose Prakash Dharmian

CAI, 2025, 03
DOI: 10.2174/0129503752359512250325061847

A deep learning and docking simulation-based virtual screening strategy enables the rapid identification of HIF-1α pathway activators from a marine natural product database

Neelakandan A. R. and Rajanikant G. K.

Journal of Biomolecular Structure and Dynamics, 2024, 42, 629
DOI: 10.1080/07391102.2023.2194997

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

A beginner’s approach to deep learning applied to VS and MD techniques

Stijn D’Hondt, José Oramas and Hans De Winter

J Cheminform, 2025, 17
DOI: 10.1186/s13321-025-00985-7

Application of 3D atom pair map in an attention model for enhanced drug virtual screening

Gina Ryu and Wankyu Kim

J Cheminform, 2025, 17
DOI: 10.1186/s13321-025-01023-2

Multimodal multi-task deep neural network framework for kinase–target prediction

Yi Hua, Lin Luo, Haodi Qiu, Dingfang Huang, Yang Zhao, Haichun Liu, Tao Lu, Yadong Chen, Yanmin Zhang and Yulei Jiang

Mol Divers, 2023, 27, 2491
DOI: 10.1007/s11030-022-10565-8

SP-DTI: subpocket-informed transformer for drug–target interaction prediction

Sizhe Liu, Yuchen Liu, Haofeng Xu, Jun Xia, Stan Z Li and Jonathan Wren

Bioinformatics, 2025, 41
DOI: 10.1093/bioinformatics/btaf011

FP-GNN: a versatile deep learning architecture for enhanced molecular property prediction

Hanxuan Cai, Huimin Zhang, Duancheng Zhao, Jingxing Wu and Ling Wang

Briefings in Bioinformatics, 2022, 23
DOI: 10.1093/bib/bbac408

The Histone Deacetylase Family: Structural Features and Application of Combined Computational Methods

Antonio Curcio, Roberta Rocca, Stefano Alcaro and Anna Artese

Pharmaceuticals, 2024, 17, 620
DOI: 10.3390/ph17050620

Overfit deep neural network for predicting drug-target interactions

Xiao Xiaolin, Liu Xiaozhi, He Guoping, Liu Hongwei, Guo Jinkuo, Bian Xiyun, Tian Zhen, Ma Xiaofang, Li Yanxia, Xue Na, Zhang Chunyan, Gao Rui, Wang Kuan, Zhang Cheng, Wang Cuancuan, Liu Mingyong and Du Xinping

iScience, 2023, 26, 107646
DOI: 10.1016/j.isci.2023.107646

Artificial intelligence in drug discovery: applications and techniques

Jianyuan Deng, Zhibo Yang, Iwao Ojima, Dimitris Samaras and Fusheng Wang

Briefings in Bioinformatics, 2022, 23
DOI: 10.1093/bib/bbab430

Proteochemometrics – recent developments in bioactivity and selectivity modeling

Brandon J. Bongers, Adriaan. P. IJzerman and Gerard J.P. Van Westen

Drug Discovery Today: Technologies, 2019, 32-33, 89
DOI: 10.1016/j.ddtec.2020.08.003

An end-to-end method for predicting compound-protein interactions based on simplified homogeneous graph convolutional network and pre-trained language model

Yufang Zhang, Jiayi Li, Shenggeng Lin, Jianwei Zhao, Yi Xiong and Dong-Qing Wei

J Cheminform, 2024, 16
DOI: 10.1186/s13321-024-00862-9

DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning

Maha A. Thafar, Rawan S. Olayan, Somayah Albaradei, Vladimir B. Bajic, Takashi Gojobori, Magbubah Essack and Xin Gao

J Cheminform, 2021, 13
DOI: 10.1186/s13321-021-00552-w

Artificial Intelligence, Machine Learning, and Big Data for Ebola Virus Drug Discovery

Samuel K. Kwofie, Joseph Adams, Emmanuel Broni, Kweku S. Enninful, Clement Agoni, Mahmoud E. S. Soliman and Michael D. Wilson

Pharmaceuticals, 2023, 16, 332
DOI: 10.3390/ph16030332

A deep learning protocol for analyzing and predicting ionic conductivity of anion exchange membranes

Fu-Heng Zhai, Qing-Qing Zhan, Yun-Fei Yang, Ni-Ya Ye, Rui-Ying Wan, Jin Wang, Shuai Chen and Rong-Huan He

Journal of Membrane Science, 2022, 642, 119983
DOI: 10.1016/j.memsci.2021.119983

A Multi-Feature and Dual-Attribute Interaction Aggregation Model for Predicting Drug-Target Interactions

Yuandong Liu, Haoqin Yang, Longbo Zhang, Hongzhen Cai, Maozu Guo and Linlin Xing

IEEE Access, 2024, 12, 113463
DOI: 10.1109/ACCESS.2024.3442931

AttentionDTA: Drug–Target Binding Affinity Prediction by Sequence-Based Deep Learning With Attention Mechanism

Qichang Zhao, Guihua Duan, Mengyun Yang, Zhongjian Cheng, Yaohang Li and Jianxin Wang

IEEE/ACM Trans. Comput. Biol. and Bioinf., 2023, 20, 852
DOI: 10.1109/TCBB.2022.3170365

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

Mpox: disease manifestations and therapeutic development

Yining Wang, Xin Wang, Tunca Doğan, Nadia A. Sam-Agudu, Jaffar A. Al-Tawfiq, Qiuwei Pan and Herman W. Favoreel

J Virol, 2025
DOI: 10.1128/jvi.00152-25

Predicting pairwise interaction affinities with ℓ 0 -penalized least squares–a nonsmooth bi-objective optimization based approach*

Pauliina Paasivirta, Riikka Numminen, Antti Airola, Napsu Karmitsa and Tapio Pahikkala

Optimization Methods and Software, 2024, 1
DOI: 10.1080/10556788.2023.2280784

A comprehensive review of neural network-based approaches for drug–target interaction prediction

Fatemeh Panahandeh and Najme Mansouri

Mol Divers, 2025
DOI: 10.1007/s11030-025-11303-6

DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach

Yash Khemchandani, Stephen O’Hagan, Soumitra Samanta, Neil Swainston, Timothy J. Roberts, Danushka Bollegala and Douglas B. Kell

J Cheminform, 2020, 12
DOI: 10.1186/s13321-020-00454-3

Application of artificial intelligence in drug design: A review

Simrandeep Singh, Navjot Kaur and Anita Gehlot

Computers in Biology and Medicine, 2024, 179, 108810
DOI: 10.1016/j.compbiomed.2024.108810

Drug Repurposing: Insights into Current Advances and Future Applications

Trisha Bhatia and Shweta Sharma

CMC, 2025, 32, 468
DOI: 10.2174/0109298673266470231023110841

CSConv2d: A 2-D Structural Convolution Neural Network with a Channel and Spatial Attention Mechanism for Protein-Ligand Binding Affinity Prediction

Xun Wang, Dayan Liu, Jinfu Zhu, Alfonso Rodriguez-Paton and Tao Song

Biomolecules, 2021, 11, 643
DOI: 10.3390/biom11050643

New Insights Into Drug Repurposing for COVID-19 Using Deep Learning

Chun Yen Lee and Yi-Ping Phoebe Chen

IEEE Trans. Neural Netw. Learning Syst., 2021, 32, 4770
DOI: 10.1109/TNNLS.2021.3111745

Artificial intelligence, computational tools and robotics for drug discovery, development, and delivery

Ayodele James Oyejide, Yemi Adekola Adekunle, Oluwatosin David Abodunrin and Ebenezer Oluwatosin Atoyebi

Intelligent Pharmacy, 2025, 3, 207
DOI: 10.1016/j.ipha.2025.01.001

Geometric Interaction Graph Neural Network for Predicting Protein–Ligand Binding Affinities from 3D Structures (GIGN)

Ziduo Yang, Weihe Zhong, Qiujie Lv, Tiejun Dong and Calvin Yu-Chian Chen

J. Phys. Chem. Lett., 2023, 14, 2020
DOI: 10.1021/acs.jpclett.2c03906

Phenotypic approaches for CNS drugs

Raahul Sharma, Caitlin R.M. Oyagawa, Hamid Abbasi, Michael Dragunow and Daniel Conole

Trends in Pharmacological Sciences, 2024, 45, 997
DOI: 10.1016/j.tips.2024.09.003

A review on compound-protein interaction prediction methods: Data, format, representation and model

Sangsoo Lim, Yijingxiu Lu, Chang Yun Cho, Inyoung Sung, Jungwoo Kim, Youngkuk Kim, Sungjoon Park and Sun Kim

Computational and Structural Biotechnology Journal, 2021, 19, 1541
DOI: 10.1016/j.csbj.2021.03.004

Drug Response Prediction of Liver Cancer Cell Line Using Deep Learning

Mehdi Hassan, Safdar Ali, Muhammad Sanaullah, Khuram Shahzad, Sadaf Mushtaq, Rashda Abbasi, Zulqurnain Ali and Hani Alquhayz

Computers, Materials & Continua, 2022, 70, 2743
DOI: 10.32604/cmc.2022.020055

Role of Artificial Intelligence in Drug Discovery to Revolutionize the Pharmaceutical Industry: Resources, Methods and Applications

Pranjal Kumar Singh, Kapil Sachan, Vishal Khandelwal, Sumita Singh and Smita Singh

BIOT, 2025, 19, 35
DOI: 10.2174/0118722083297406240313090140

Integrating Artificial Intelligence for Drug Discovery in the Context of Revolutionizing Drug Delivery

Anita Ioana Visan and Irina Negut

Life, 2024, 14, 233
DOI: 10.3390/life14020233

Heterogeneous sampled subgraph neural networks with knowledge distillation to enhance double-blind compound-protein interaction prediction

Ying Xia, Xiaoyong Pan and Hong-Bin Shen

Structure, 2024, 32, 611
DOI: 10.1016/j.str.2024.02.004

Integrative strategies in drug discovery: Harnessing genomics, deep learning, and computer-aided drug design

Nizakat Ali, Urooj Qureshi, Asaad Khalid and Zaheer Ul-Haq

Computational Biology and Chemistry, 2025, 119, 108530
DOI: 10.1016/j.compbiolchem.2025.108530

Ligand- and structure-based identification of novel CDK9 inhibitors for the potential treatment of leukemia

Huimin Zhang, Jindi Huang, Rui Chen, Hanxuan Cai, Yihao Chen, Shuyun He, Jianrong Xu, Jiquan Zhang and Ling Wang

Bioorganic & Medicinal Chemistry, 2022, 72, 116994
DOI: 10.1016/j.bmc.2022.116994

AI in drug discovery and its clinical relevance

Rizwan Qureshi, Muhammad Irfan, Taimoor Muzaffar Gondal, Sheheryar Khan, Jia Wu, Muhammad Usman Hadi, John Heymach, Xiuning Le, Hong Yan and Tanvir Alam

Heliyon, 2023, 9, e17575
DOI: 10.1016/j.heliyon.2023.e17575

The Development and Opportunities of Predictive Biotechnology

Bettina M. Nestl, Bernd A. Nebel, Verena Resch, Martin Schürmann and Dirk Tischler

ChemBioChem, 2024, 25
DOI: 10.1002/cbic.202300863

A Bayesian Convolutional Neural Network Model with Uncertainty for Multi-label Text Classification on Mechanisms of Action (MoA) Prediction

Xuming Tong, Zhisheng Zhao, Junhua Liang, Lihua Ding, Caijun Jia and Yanhong Yuan

ACM Trans. Asian Low-Resour. Lang. Inf. Process., 2023
DOI: 10.1145/3604428

Data Centric Molecular Analysis and Evaluation of Hepatocellular Carcinoma Therapeutics Using Machine Intelligence-Based Tools

Rengul Cetin-Atalay, Deniz Cansen Kahraman, Esra Nalbat, Ahmet Sureyya Rifaioglu, Ahmet Atakan, Ataberk Donmez, Heval Atas, M. Volkan Atalay, Aybar C. Acar and Tunca Doğan

J Gastrointest Canc, 2021, 52, 1266
DOI: 10.1007/s12029-021-00768-x

A Review on Artificial Intelligence Approaches and Rational Approaches in Drug Discovery

Anjana Vidya Srivathsa, Nandini Markuli Sadashivappa, Apeksha Krishnamurthy Hegde, Srimathi Radha, Agasa Ramu Mahesh, Damodar Nayak Ammunje, Debanjan Sen, Panneerselvam Theivendren, Saravanan Govindaraj, Selvaraj Kunjiappan and Parasuraman Pavadai

CPD, 2023, 29, 1180
DOI: 10.2174/1381612829666230428110542

Data considerations for predictive modeling applied to the discovery of bioactive natural products

Hai Tao Xue, Michael Stanley-Baker, Adams Wai Kin Kong, Hoi Leung Li and Wilson Wen Bin Goh

Drug Discovery Today, 2022, 27, 2235
DOI: 10.1016/j.drudis.2022.05.009

HiGNN: A Hierarchical Informative Graph Neural Network for Molecular Property Prediction Equipped with Feature-Wise Attention

Weimin Zhu, Yi Zhang, Duancheng Zhao, Jianrong Xu and Ling Wang

J. Chem. Inf. Model., 2023, 63, 43
DOI: 10.1021/acs.jcim.2c01099

In-silico-library-based method enables rapid and comprehensive annotation of cardiolipins and cardiolipin oxidation products using high resolution tandem mass spectrometer

Yu He, Binghuan Yuan, Yao Lu, Xia Zhao, Cunsi Shen, Jianjian Ji, Lili Lin, Jianya Xu, Tong Xie and Jinjun Shan

Analytica Chimica Acta, 2021, 1180, 338879
DOI: 10.1016/j.aca.2021.338879

Systematic Analysis and Prediction of the Target Space of Bioactive Food Compounds: Filling the Chemobiological Gaps

Andrés Sánchez-Ruiz and Gonzalo Colmenarejo

J. Chem. Inf. Model., 2022, 62, 3734
DOI: 10.1021/acs.jcim.2c00888

Open-Source Machine Learning in Computational Chemistry

Alexander Hagg and Karl N. Kirschner

J. Chem. Inf. Model., 2023, 63, 4505
DOI: 10.1021/acs.jcim.3c00643

A program to automate the discovery of drugs for West Nile and Dengue virus—programmatic screening of over a billion compounds on PubChem, generation of drug leads and automatedin silicomodelling

Ben Geoffrey, Akhil Sanker, Rafal Madaj, Mario Sergio Valdés Tresanco, Manish Upadhyay and Judith Gracia

Journal of Biomolecular Structure and Dynamics, 2022, 40, 4293
DOI: 10.1080/07391102.2020.1856185

Molecular docking-based computational platform for high-throughput virtual screening

Baohua Zhang, Hui Li, Kunqian Yu and Zhong Jin

CCF Trans. HPC, 2022, 4, 63
DOI: 10.1007/s42514-021-00086-5

A bioactivity foundation model using pairwise meta-learning

Bin Feng, Zequn Liu, Nanlan Huang, Zhiping Xiao, Haomiao Zhang, Srbuhi Mirzoyan, Hanwen Xu, Jiaran Hao, Yinghui Xu, Ming Zhang and Sheng Wang

Nat Mach Intell, 2024, 6, 962
DOI: 10.1038/s42256-024-00876-w

Drug repurposing for viral cancers: A paradigm of machine learning, deep learning, and virtual screening‐based approaches

Faheem Ahmed, In Suk Kang, Kyung Hwan Kim, Arun Asif, Chethikkattuveli Salih Abdul Rahim, Anupama Samantasinghar, Fida Hussain Memon and Kyung Hyun Choi

Journal of Medical Virology, 2023, 95
DOI: 10.1002/jmv.28693

Beyond boundaries: exploring the transformative power of AI in pharmaceuticals

Gurparsad Singh Suri, Gurleen Kaur and Dheeraj Shinde

Discov Artif Intell, 2024, 4
DOI: 10.1007/s44163-024-00192-7

Drug-Target Affinity Unleashed: Integrating CNN and Graph Transformers for Superior Predictions

Neeraja Subhash, Linda Sara Mathew and Suryamol K S

Procedia Computer Science, 2025, 259, 1011
DOI: 10.1016/j.procs.2025.04.055

Binding Affinity Prediction for Pancreatic Ductal Adenocarcinoma Using Drug-Target Descriptors and Artificial Intelligence

Pragya, A. Amalin Prince and Jac Fredo Agastinose Ronickom

IEEE Access, 2025, 13, 113809
DOI: 10.1109/ACCESS.2025.3583338

Biomedical Data and Deep Learning Computational Models for Predicting Compound-Protein Relations

Qichang Zhao, Mengyun Yang, Zhongjian Cheng, Yaohang Li and Jianxin Wang

IEEE/ACM Trans. Comput. Biol. and Bioinf., 2022, 19, 2092
DOI: 10.1109/TCBB.2021.3069040

The method predicting interaction between protein targets and small-molecular ligands with the wide applicability domain

Dmitry A. Karasev, Boris N. Sobolev, Alexey A. Lagunin, Dmitry A. Filimonov and Vladimir V. Poroikov

Computational Biology and Chemistry, 2022, 98, 107674
DOI: 10.1016/j.compbiolchem.2022.107674

Optimizing drug-target binding affinity prediction for kinase proteins: a novel all-MLP-transformer approach

Nassima Aleb

Netw Model Anal Health Inform Bioinforma, 2025, 14
DOI: 10.1007/s13721-025-00516-2

MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery

A S Rifaioglu, R Cetin Atalay, D Cansen Kahraman, T Doğan, M Martin, V Atalay and Wren Jonathan

Bioinformatics, 2021, 37, 693
DOI: 10.1093/bioinformatics/btaa858

Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction

Donghyuk Suh, Jai Woo Lee, Sun Choi and Yoonji Lee

IJMS, 2021, 22, 6032
DOI: 10.3390/ijms22116032

Fingerprint-enhanced hierarchical molecular graph neural networks for property prediction

Shuo Liu, Mengyun Chen, Xiaojun Yao and Huanxiang Liu

Journal of Pharmaceutical Analysis, 2025, 15, 101242
DOI: 10.1016/j.jpha.2025.101242

Graph regularized non-negative matrix factorization with $$L_{2,1}$$ norm regularization terms for drug–target interactions prediction

Junjun Zhang and Minzhu Xie

BMC Bioinformatics, 2023, 24
DOI: 10.1186/s12859-023-05496-6

Identification of a Histone Deacetylase 8 Inhibitor through Drug Screenings Based on Machine Learning

Atika Nurani, Yasunobu Yamashita, Yuuki Taki, Yuri Takada, Yukihiro Itoh and Takayoshi Suzuki

Chem. Pharm. Bull., 2024, 72, 173
DOI: 10.1248/cpb.c23-00577

Screening potential ligands of endothelin receptor A from Choerospondias axillaris and evaluation of their drug-like properties by affinity chromatographic methods

Xu Ji, Liji Ge, Ruixiao Ma, Xiaoying Zhang, Jie Li, Dan Song, Lingmin Pei, Fangyun Sun and Qin Zhao

Journal of Pharmaceutical and Biomedical Analysis, 2023, 226, 115240
DOI: 10.1016/j.jpba.2023.115240

Discovery of novel dual adenosine A1/A2A receptor antagonists using deep learning, pharmacophore modeling and molecular docking

Mukuo Wang, Shujing Hou, Yu Wei, Dongmei Li, Jianping Lin and Avner Schlessinger

PLoS Comput Biol, 2021, 17, e1008821
DOI: 10.1371/journal.pcbi.1008821

Recurrent Neural Network Based Drug Repurposing to Address SARS-CoV-2 (COVID-19), and the in vitro Antiviral Efficacy of Peroxisome Proliferator-Activated Receptors-Gamma Agonist

Nam Hee Kim and Jae June Dong

Korean J Fam Pract, 2021, 11, 312
DOI: 10.21215/kjfp.2021.11.4.312

Application of 3D Bioprinting in Liver Diseases

Wenhui Li, Zhaoyue Liu, Fengwei Tang, Hao Jiang, Zhengyuan Zhou, Xiuqing Hao and Jia Ming Zhang

Micromachines, 2023, 14, 1648
DOI: 10.3390/mi14081648

Polypharmacology prediction: the long road toward comprehensively anticipating small-molecule selectivity to de-risk drug discovery

Leticia Manen-Freixa and Albert A. Antolin

Expert Opinion on Drug Discovery, 2024, 19, 1043
DOI: 10.1080/17460441.2024.2376643

Sequence-based drug-target affinity prediction using weighted graph neural networks

Mingjian Jiang, Shuang Wang, Shugang Zhang, Wei Zhou, Yuanyuan Zhang and Zhen Li

BMC Genomics, 2022, 23
DOI: 10.1186/s12864-022-08648-9

NNDSVD-GRMF: A Graph Dual Regularization Matrix Factorization Method Using Non-Negative Initialization for Predicting Drug-Target Interactions

Junjun Zhang and Minzhu Xie

IEEE Access, 2022, 10, 91235
DOI: 10.1109/ACCESS.2022.3199667

Generative artificial intelligence in drug discovery: basic framework, recent advances, challenges, and opportunities

Amit Gangwal, Azim Ansari, Iqrar Ahmad, Abul Kalam Azad, Vinoth Kumarasamy, Vetriselvan Subramaniyan and Ling Shing Wong

Front. Pharmacol., 2024, 15
DOI: 10.3389/fphar.2024.1331062

A primer on applying AI synergistically with domain expertise to oncology

Jason Kim, Rebecca Kusko, Benjamin Zeskind, Jenny Zhang and Renan Escalante-Chong

Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, 2021, 1876, 188548
DOI: 10.1016/j.bbcan.2021.188548

Discovery of moiety preference by Shapley value in protein kinase family using random forest models

Yu-Wei Huang, Yen-Chao Hsu, Yi-Hsuan Chuang, Yun-Ti Chen, Xiang-Yu Lin, You-Wei Fan, Nikhil Pathak and Jinn-Moon Yang

BMC Bioinformatics, 2022, 23
DOI: 10.1186/s12859-022-04663-5

Image-based molecular representation learning for drug development: a survey

Yue Li, Bingyan Liu, Jinyan Deng, Yi Guo and Hongbo Du

Briefings in Bioinformatics, 2024, 25
DOI: 10.1093/bib/bbae294

Single-Cell Techniques and Deep Learning in Predicting Drug Response

Zhenyu Wu, Patrick J. Lawrence, Anjun Ma, Jian Zhu, Dong Xu and Qin Ma

Trends in Pharmacological Sciences, 2020, 41, 1050
DOI: 10.1016/j.tips.2020.10.004

Artificial intelligence in drug design: why a ‘one-size-fits-all’ approach remains out of reach

Rafael Lopes Almeida, Gabriella Matos Campera, Ina Pöhner and Vinicius Gonçalves Maltarollo

Expert Opinion on Drug Discovery, 2025, 1
DOI: 10.1080/17460441.2025.2543802

Synthesis and biological evaluation of novel isoxazole-piperazine hybrids as potential anti-cancer agents with inhibitory effect on liver cancer stem cells

Kübra İbiş, Esra Nalbat, Burcu Çalışkan, Deniz Cansen Kahraman, Rengul Cetin-Atalay and Erden Banoglu

European Journal of Medicinal Chemistry, 2021, 221, 113489
DOI: 10.1016/j.ejmech.2021.113489

Developing liver cancer drug response prediction system using late fusion of reduced deep features

Mehdi Hassan, Safdar Ali, Hani Alquhayz, Jin Young Kim and Muhammad Sanaullah

Journal of King Saud University - Computer and Information Sciences, 2022, 34, 8122
DOI: 10.1016/j.jksuci.2022.07.024

Design, synthesis, and evaluation of novel Indole‐Based small molecules as sirtuin inhibitors with anticancer activities

Busra Binarci, Ensar Korkut Kilic, Tunca Dogan, Rengul Cetin Atalay, Deniz Cansen Kahraman and Sultan Nacak Baytas

Drug Development Research, 2024, 85
DOI: 10.1002/ddr.70008

DeepH-DTA: Deep Learning for Predicting Drug-Target Interactions: A Case Study of COVID-19 Drug Repurposing

Mohamed Abdel-Basset, Hossam Hawash, Mohamed Elhoseny, Ripon K. Chakrabortty and Michael Ryan

IEEE Access, 2020, 8, 170433
DOI: 10.1109/ACCESS.2020.3024238

Virtual screening of potential anticancer drugs based on microbial products

Gaspar P. Pinto, Natalie M. Hendrikse, Jan Stourac, Jiri Damborsky and David Bednar

Seminars in Cancer Biology, 2022, 86, 1207
DOI: 10.1016/j.semcancer.2021.07.012

Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug–target interactions prediction

Junjun Zhang and Minzhu Xie

BMC Bioinformatics, 2022, 23
DOI: 10.1186/s12859-022-05119-6

Transfer learning for drug–target interaction prediction

Alperen Dalkıran, Ahmet Atakan, Ahmet S Rifaioğlu, Maria J Martin, Rengül Çetin Atalay, Aybar C Acar, Tunca Doğan and Volkan Atalay

Bioinformatics, 2023, 39, i103
DOI: 10.1093/bioinformatics/btad234

A review of deep learning methods for ligand based drug virtual screening

Hongjie Wu, Junkai Liu, Runhua Zhang, Yaoyao Lu, Guozeng Cui, Zhiming Cui and Yijie Ding

Fundamental Research, 2024, 4, 715
DOI: 10.1016/j.fmre.2024.02.011

Analysis of temporal metabolic rewiring for human respiratory syncytial virus infection by integrating metabolomics and proteomics

Yao Lu, Shan Xu, Huan Sun, Jinjun Shan, Cunsi Shen, Jianjian Ji, Lili Lin, Jianya Xu, Linxiu Peng, Chen Dai and Tong Xie

Metabolomics, 2023, 19
DOI: 10.1007/s11306-023-01991-2

LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design

Vendy Fialková, Jiaxi Zhao, Kostas Papadopoulos, Ola Engkvist, Esben Jannik Bjerrum, Thierry Kogej and Atanas Patronov

J. Chem. Inf. Model., 2022, 62, 2046
DOI: 10.1021/acs.jcim.1c00469

How to approach machine learning-based prediction of drug/compound–target interactions

Heval Atas Guvenilir and Tunca Doğan

J Cheminform, 2023, 15
DOI: 10.1186/s13321-023-00689-w

New strategies to enhance the efficiency and precision of drug discovery

Qi An, Liang Huang, Chuan Wang, Dongmei Wang and Yalan Tu

Front. Pharmacol., 2025, 16
DOI: 10.3389/fphar.2025.1550158

Artificial intelligence and machine learning for protein toxicity prediction using proteomics data

Shubham Vishnoi, Himani Matre, Prabha Garg and Shubham Kumar Pandey

Chem Biol Drug Des, 2020, 96, 902
DOI: 10.1111/cbdd.13701

Improving structure-based virtual screening performance via learning from scoring function components

Guo-Li Xiong, Wen-Ling Ye, Chao Shen, Ai-Ping Lu, Ting-Jun Hou and Dong-Sheng Cao

Briefings in Bioinformatics, 2021, 22
DOI: 10.1093/bib/bbaa094

EDC-DTI: An end-to-end deep collaborative learning model based on multiple information for drug-target interactions prediction

Yongna Yuan, Yuhao Zhang, Xiangbo Meng, Zhenyu Liu, Bohan Wang, Ruidong Miao, Ruisheng Zhang, Wei Su and Lei Liu

Journal of Molecular Graphics and Modelling, 2023, 122, 108498
DOI: 10.1016/j.jmgm.2023.108498

ResisenseNet hybrid neural network model for predicting drug sensitivity and repurposing in breast Cancer

Anush Karampuri, Bharath Kumar Jakkula and Shyam Perugu

Sci Rep, 2024, 14
DOI: 10.1038/s41598-024-71076-0

The changing scenario of drug discovery using AI to deep learning: Recent advancement, success stories, collaborations, and challenges

Chiranjib Chakraborty, Manojit Bhattacharya, Sang-Soo Lee, Zhi-Hong Wen and Yi-Hao Lo

Molecular Therapy - Nucleic Acids, 2024, 35, 102295
DOI: 10.1016/j.omtn.2024.102295

MMFi-DPBML: Multi-molecular fingerprint feature fusion for predicting ingredient-target interactions in traditional Chinese medicine

Xiaodan Wang, Runnan Li, Yuehong Zou and Jihong Wang

Journal of Ethnopharmacology, 2025, 353, 120451
DOI: 10.1016/j.jep.2025.120451

Drug–target affinity prediction method based on multi-scale information interaction and graph optimization

Zhiqin Zhu, Zheng Yao, Xin Zheng, Guanqiu Qi, Yuanyuan Li, Neal Mazur, Xinbo Gao, Yifei Gong and Baisen Cong

Computers in Biology and Medicine, 2023, 167, 107621
DOI: 10.1016/j.compbiomed.2023.107621

Artificial intelligence streamlines scientific discovery of drug–target interactions

Yuxin Yang and Feixiong Cheng

British J Pharmacology, 2025
DOI: 10.1111/bph.17427

Drug Repurposing Approach to Identify Candidate Drug Molecules for Hepatocellular Carcinoma

Tugce Baser, Ahmet Sureyya Rifaioglu, Mehmet Volkan Atalay and Rengul Cetin Atalay

IJMS, 2024, 25, 9392
DOI: 10.3390/ijms25179392

AttentionMGT-DTA: A multi-modal drug-target affinity prediction using graph transformer and attention mechanism

Hongjie Wu, Junkai Liu, Tengsheng Jiang, Quan Zou, Shujie Qi, Zhiming Cui, Prayag Tiwari and Yijie Ding

Neural Networks, 2024, 169, 623
DOI: 10.1016/j.neunet.2023.11.018

PreBINDS: An Interactive Web Tool to Create Appropriate Datasets for Predicting Compound–Protein Interactions

Kazuyoshi Ikeda, Takuo Doi, Masami Ikeda and Kentaro Tomii

Front. Mol. Biosci., 2021, 8
DOI: 10.3389/fmolb.2021.758480

Hierarchical multimodal self-attention-based graph neural network for DTI prediction

Jilong Bian, Hao Lu, Guanghui Dong and Guohua Wang

Briefings in Bioinformatics, 2024, 25
DOI: 10.1093/bib/bbae293

Machine learning-based prediction of drug approvals using molecular, physicochemical, clinical trial, and patent-related features

Fulya Ciray and Tunca Doğan

Expert Opinion on Drug Discovery, 2022, 17, 1425
DOI: 10.1080/17460441.2023.2153830

Advances in Artificial Intelligence (AI)-assisted approaches in drug screening

Samvedna Singh, Himanshi Gupta, Priyanshu Sharma and Shakti Sahi

Artificial Intelligence Chemistry, 2024, 2, 100039
DOI: 10.1016/j.aichem.2023.100039

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Rohan Gupta, Devesh Srivastava, Mehar Sahu, Swati Tiwari, Rashmi K. Ambasta and Pravir Kumar

Mol Divers, 2021, 25, 1315
DOI: 10.1007/s11030-021-10217-3

A Review on Deep Learning-driven Drug Discovery: Strategies, Tools and Applications

Sundaravadivelu Sumathi, Kanagaraj Suganya, Kandasamy Swathi, Balraj Sudha, Arumugam Poornima, Chalos Angel Varghese and Raghu Aswathy

CPD, 2023, 29, 1013
DOI: 10.2174/1381612829666230412084137

D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening

Yulong Shi, Xinben Zhang, Yanqing Yang, Tingting Cai, Cheng Peng, Leyun Wu, Liping Zhou, Jiaxin Han, Minfei Ma, Weiliang Zhu and Zhijian Xu

Computers in Biology and Medicine, 2023, 164, 107283
DOI: 10.1016/j.compbiomed.2023.107283

In silico and in vitro study of Mycobacterium tuberculosis H37Rv uncharacterized protein (RipD): an insight on tuberculosis therapeutics

Aregitu Mekuriaw Arega, Ajit Kumar Dhal, Sasmita Nayak and Rajani Kanta Mahapatra

J Mol Model, 2022, 28
DOI: 10.1007/s00894-022-05148-1

State-of-the-art Application of Artificial Intelligence to Transporter-centered Functional and Pharmaceutical Research

Jiayi Yin, Nanxin You, Fengcheng Li, Mingkun Lu, Su Zeng and Feng Zhu

CDM, 2023, 24, 162
DOI: 10.2174/1389200224666230523155759

Analysis of Data Interaction Process Based on Data Mining and Neural Network Topology Visualization

Nina Dai and Gengxin Sun

Computational Intelligence and Neuroscience, 2022, 2022, 1
DOI: 10.1155/2022/1817628