Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking.

Cited by (1,002)

Items 201–300 of 1,002

1. Artificial intelligence for science in quantum, atomistic, and continuum systems
   Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Xu Zhao, Keqiang Yan et al. · 2025 · Foundations and Trends® in Machine Learning
2. Practical Considerations in Virtual Screening and Molecular Docking
   Michael J. Berry, Burtram Clinton Fielding, Junaid Gamieldien · 2015 · Elsevier eBooks
3. Small-molecule inhibitors identify the RAD52-ssDNA interaction as critical for recovery from replication stress and for survival of BRCA2 deficient cells
   Sarah R Hengel, Eva Malacaria, Laura Folly da Silva Constantino, Fletcher E. Bain, Andrea Diaz, Brandon G Koch, Liping P. Yu, Meng Wu, Pietro Pichierri, Maria Spies et al. · 2016 · eLife
4. Structure-Based Virtual Screening Protocol for in Silico Identification of Potential Thyroid Disrupting Chemicals Targeting Transthyretin
   Jin Zhang, Afshan Begum, Kristoffer Brännström, Christin Grundström, Irina Iakovleva, Anders Olofsson, A.E. Sauer-Eriksson, Patrik L. Andersson · 2016 · Environmental Science & Technology
5. Common Hits Approach: Combining Pharmacophore Modeling and Molecular Dynamics Simulations
   Marcus Wieder, Arthur Garon, Ugo Perricone, Stefan Boresch, Thomas Seidel, Anna Maria Almerico, Thierry Langer · 2017 · Journal of Chemical Information and Modeling
6. De Novo Peptide and Protein Design Using Generative Adversarial Networks: An Update
   Eugene Lin, Chieh‐Hsin Lin, Hsien‐Yuan Lane · 2022 · Journal of Chemical Information and Modeling
7. Compound–protein interaction prediction by deep learning: Databases, descriptors and models
   Bing-Xue Du, Yuan Qin, Yanfeng Jiang, Yi Xu, Siu‐Ming Yiu, Hui Yu, Jian‐Yu Shi · 2022 · Drug Discovery Today
8. Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein–Ligand Scoring Functions
   Chao Yang, Yingkai Zhang · 2022 · Journal of Chemical Information and Modeling
9. Recent advances in AI-driven protein-ligand interaction predictions
   Jaemin Sim, Dongwoo Kim, Bomin Kim, Jieun Choi, Juyong Lee · 2025 · Current Opinion in Structural Biology
10. Molecular Docking Screening Using Agonist-Bound GPCR Structures: Probing the A2A Adenosine Receptor
    David J. Rodriguez, Zhang-Guo Gao, Steven M. Moss, Kenneth A. Jacobson, Jens Carlsson · 2015 · Journal of Chemical Information and Modeling
11. Ligand-Based Pharmacophore Modeling, Molecular Docking, and Molecular Dynamic Studies of Dual Tyrosine Kinase Inhibitor of EGFR and VEGFR2
    Frangky Sangande, Elin Julianti, Daryono Hadi Tjahjono · 2020 · International Journal of Molecular Sciences
12. Advances and Challenges in De Novo Drug Design Using Three-Dimensional Deep Generative Models
    Weixin Xie, Fanhao Wang, Yibo Li, Luhua Lai, Jianfeng Pei · 2022 · Journal of Chemical Information and Modeling
13. Computer-Aided Ligand Discovery for Estrogen Receptor Alpha
    Divya Bafna, Fuqiang Ban, Paul S. Rennie, Kriti Singh, Artem R Cherkasov · 2020 · International Journal of Molecular Sciences
14. Structure‐Based Drug Discovery with Deep Learning**
    Rıza Özçelik, Derek van Tilborg, José Jiménez-Luna, Francesca Grisoni · 2023 · ChemBioChem
15. SMIfp (SMILES fingerprint) Chemical Space for Virtual Screening and Visualization of Large Databases of Organic Molecules
    Julian Schwartz, Mahendra Awale, Jean‐Louis Reymond · 2013 · Journal of Chemical Information and Modeling
16. A Pipeline To Enhance Ligand Virtual Screening: Integrating Molecular Dynamics and Fingerprints for Ligand and Proteins
    Francesca Spyrakis, Paolo Benedetti, Sergio Decherchi, Walter Rocchia, Andrea Cavalli, Stefano Alcaro, Francesco Ortuso, Massimo Baroni, Gabriele Cruciani · 2015 · Journal of Chemical Information and Modeling
17. vSDC: a method to improve early recognition in virtual screening when limited experimental resources are available
    Ludovic Chaput, Juan Martinez‐Sanz, Éric Quiniou, Pascal Rigolet, Nicolas Saettel, Liliane Mouawad · 2016 · Journal of Cheminformatics
18. Automated discovery of noncovalent inhibitors of SARS-CoV-2 main protease by consensus Deep Docking of 40 billion small molecules
    Francesco Gentile, Michael Fernández, Fuqiang Ban, Anh‐Tien Ton, Hazem Mslati, Carl F. Perez, Eric Leblanc, Jean Charle Yaacoub, James Gleave, Abraham C. Stern et al. · 2021 · Chemical Science
19. An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings
    Irene Maffucci, Xiao Hu, Valentina Fumagalli, Alessandro Contini · 2018 · Frontiers in Chemistry
20. Cross‐docking benchmark for automated pose and ranking prediction of ligand binding
    Shayne D. Wierbowski, Bentley M. Wingert, Jim Zheng, Carlos Jaime Camacho · 2019 · Protein Science
21. Identification of novel discoidin domain receptor 1 (DDR1) inhibitors using E-pharmacophore modeling, structure-based virtual screening, molecular dynamics simulation and MM-GBSA approaches
    Hossam Nada, Kyeong Lee, Lizaveta Gotina, Ae Nim Pae, Ahmed Elkamhawy · 2022 · Computers in Biology and Medicine
22. Application of artificial intelligence in drug design: A review
    Simrandeep Singh, Navjot Kaur, Anita Gehlot · 2024 · Computers in Biology and Medicine
23. Development of CDK-targeted scoring functions for prediction of binding affinity
    Nayara Maria Bernhardt Levin, Val Oliveira Pintro, Gabriela Bitencourt‐Ferreira, Bruna Boldrini de Mattos, Ariadne de Castro Silvério, Walter Filgueira de Azevedo · 2018 · Biophysical Chemistry
24. A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs
    Ambrose Plante, Derek M. Shore, Giulia Morra, George Khelashvili, Harel Weinstein · 2019 · Molecules
25. High-Throughput Docking Using Quantum Mechanical Scoring
    Claudio N. Cavasotto, M. Gabriela Aucar · 2020 · Frontiers in Chemistry
26. Assigning confidence to molecular property prediction
    AkshatKumar Nigam, Robert Pollice, Matthew F. D. Hurley, Riley J. Hickman, Matteo Aldeghi, Naruki Yoshikawa, Seyone Chithrananda, Vincent A. Voelz, Alán Aspuru‐Guzik · 2021 · Expert Opinion on Drug Discovery
27. Lean-Docking: Exploiting Ligands’ Predicted Docking Scores to Accelerate Molecular Docking
    Francois Berenger, Ashutosh Kumar, Kam Y. J. Zhang, Yoshihiro Yamanishi · 2021 · Journal of Chemical Information and Modeling
28. Structure-Based de Novo Molecular Generator Combined with Artificial Intelligence and Docking Simulations
    Biao Ma, Kei Terayama, Shigeyuki Matsumoto, Yuta Isaka, Yoko Sasakura, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno · 2021 · Journal of Chemical Information and Modeling
29. Target specificity of selective bioactive compounds in blocking α-dystroglycan receptor to suppress Lassa virus infection: an in silico approach
    Adittya Arefin, Tanzila Ismail Ema, Tamnia Islam, Md. Saddam Hossen, Tariqul Islam, Salauddin Al Azad, Md. Nasir Uddin Badal, Md. Aminul Islam, Partha Biswas, Nafee Ul Alam et al. · 2021 · Journal of Biomedical Research
30. Towards computational solutions for precision medicine based big data healthcare system using deep learning models: A review
    Ramkumar Thirunavukarasu, C. George Priya Doss, Gnanasambandan Ramanathan, Mohanraj Gopikrishnan, Venketesh Palanisamy · 2022 · Computers in Biology and Medicine
31. OptiMol : Optimization of Binding Affinities in Chemical Space for Drug Discovery
    Jacques Boitreaud, Vincent Mallet, Carlos Oliver, Jérôme Waldispühl · 2020 · Journal of Chemical Information and Modeling
32. The latest automated docking technologies for novel drug discovery
    Julio Caballero · 2020 · Expert Opinion on Drug Discovery
33. Generation of 3D molecules in pockets via a language model
    Wei Feng, Lvwei Wang, Zaiyun Lin, Yanhao Zhu, Han Wang, Jianqiang Dong, Rong Bai, Huting Wang, Jielong Zhou, Wei Peng et al. · 2024 · Nature Machine Intelligence
34. AlphaFold accelerated discovery of psychotropic agonists targeting the trace amine–associated receptor 1
    Alejandro Díaz‐Holguín, Marcus Saarinen, Duc Duy Vo, Andrea Sturchio, Niclas Branzell, Israel Cabeza de Vaca, Huabin Hu, Núria Mitjavila-Domènech, Annika Lindqvist, Paweł Baranczewski et al. · 2024 · Science Advances
35. Ligand Discovery for the Alanine-Serine-Cysteine Transporter (ASCT2, SLC1A5) from Homology Modeling and Virtual Screening
    Claire Colas, Christof T. Grewer, Nicholas James Otte, Armanda M. Gameiro, Thomas Albers, Kurnvir Singh, Helen Shere, Massimiliano Bonomi, Jeff Holst, Avner Schlessinger · 2015 · PLoS Computational Biology
36. Adverse Drug Reaction Prediction Using Scores Produced by Large-Scale Drug-Protein Target Docking on High-Performance Computing Machines
    Montiago X. Labute, Xiaohua Zhang, Jason Lenderman, Brian J. Bennion, Sergio Wong, Felice C. Lightstone · 2014 · PLoS ONE
37. Efficient conformational sampling and weak scoring in docking programs? Strategy of the wisdom of crowds
    Ludovic Chaput, Liliane Mouawad · 2017 · Journal of Cheminformatics
38. Chemical space exploration guided by deep neural networks
    Dmitry S. Karlov, Sergey Sosnin, Igor V. Tetko, Maxim V. Fedorov · 2019 · RSC Advances
39. Machine Learning Models Based on Molecular Fingerprints and an Extreme Gradient Boosting Method Lead to the Discovery of JAK2 Inhibitors
    Minjian Yang, Bingzhong Tao, Chengjuan Chen, Wen‐Qiang Jia, Shaolei Sun, Tiantai Zhang, Xiaojian Wang · 2019 · Journal of Chemical Information and Modeling
40. Artificial intelligence in the early stages of drug discovery
    Claudio N. Cavasotto, Juan I. Di Filippo · 2020 · Archives of Biochemistry and Biophysics
41. Computational identification of 2,4-disubstituted amino-pyrimidines as L858R/T790M-EGFR double mutant inhibitors using pharmacophore mapping, molecular docking, binding free energy calculation, DFT study and molecular dynamic simulation
    Rahul H. Pawara, Iqrar Ahmad, Sanjay Javerilal Surana, Harun Patel · 2021 · In Silico Pharmacology
42. Molecular Modeling Strategies of Cancer Multidrug Resistance
    Gözde Yalçın · 2021 · Drug Resistance Updates
43. Statistical and machine learning approaches to predicting protein–ligand interactions
    Lucy J. Colwell · 2018 · Current Opinion in Structural Biology
44. Ligand-Based Virtual Screening Using Graph Edit Distance as Molecular Similarity Measure
    Carlos Garcia-Hernandez, Alberto Fernández, Francesc Serratosa · 2019 · Journal of Chemical Information and Modeling
45. Structure based virtual screening: Fast and slow
    Alejandro Varela‐Rial, Maciej Majewski, Gianni De Fabritiis · 2021 · Wiley Interdisciplinary Reviews Computational Molecular Science
46. Predicting Drug–Target Interactions with Deep-Embedding Learning of Graphs and Sequences
    Wei Chen, Guanxing Chen, Lu Zhao, Calvin Yu‐Chian Chen · 2021 · The Journal of Physical Chemistry A
47. Virtual Screening with Gnina 1.0
    Jocelyn Sunseri, David Koes · 2021 · Molecules
48. Ligand-Optimized Homology Models of D1 and D2 Dopamine Receptors: Application for Virtual Screening
    Marcin Kołaczkowski, Adam Bucki, Marcin Feder, Maciej Pawłowski · 2013 · Journal of Chemical Information and Modeling
49. Improving Screening Efficiency through Iterative Screening Using Docking and Conformal Prediction
    Fredrik Svensson, Ulf Norinder, Andreas Bender · 2017 · Journal of Chemical Information and Modeling
50. Pharmacophore-based virtual screening and molecular docking to identify promising dual inhibitors of human acetylcholinesterase and butyrylcholinesterase
    Ana Mercia Silva Mascarenhas, Raquel Bianca Marchesine de Almeida, Moysés Fagundes de Araújo Neto, Géssica Oliveira Mendes, Jorddy Neves Cruz, Cleydson B. R. Santos, Mariana Borges Botura, Franco Henrique Andrade Leite · 2020 · Journal of Biomolecular Structure and Dynamics
51. Deep Learning with Neuroimaging and Genomics in Alzheimer’s Disease
    Eugene Lin, Chieh‐Hsin Lin, Hsien‐Yuan Lane · 2021 · International Journal of Molecular Sciences
52. Discovery of Competitive and Noncompetitive Ligands of the Organic Cation Transporter 1 (OCT1; SLC22A1)
    Eugene C. Chen, Natalia Khuri, Xiaomin Liang, Adrian Stecuła, Huan‐Chieh Chien, Sook Wah Yee, Yong Lin Huang, Andrej Šali, Kathleen M. Giacomini · 2017 · Journal of Medicinal Chemistry
53. In Silico Study to Identify New Antituberculosis Molecules from Natural Sources by Hierarchical Virtual Screening and Molecular Dynamics Simulations
    Vinícius de S. Pinto, Janay Stefany Carneiro Araújo, Raí C. Silva, Glauber Vilhena da Costa, Jorddy Neves Cruz, Moysés Fagundes de Araújo Neto, Joaquín M. Campos Rosa, Cleydson B. R. Santos, Franco Henrique Andrade Leite, Manoelito Coelho dos Santos · 2019 · Pharmaceuticals
54. New Trends in Virtual Screening
    W. Patrick Walters, Renxiao Wang · 2020 · Journal of Chemical Information and Modeling
55. Interpretable machine learning as a tool for scientific discovery in chemistry
    Richard Dybowski · 2020 · New Journal of Chemistry
56. Machine learning, artificial intelligence, and data science breaking into drug design and neglected diseases
    José Peña Guerrero, Paul Nguewa, Alfonso T. García‐Sosa · 2021 · Wiley Interdisciplinary Reviews Computational Molecular Science
57. Augmented base pairing networks encode RNA-small molecule binding preferences
    Carlos Oliver, Vincent Mallet, Roman Sarrazin‐Gendron, Vladimir Reinharz, William L. Hamilton, Nicolas Moitessier, Jérôme Waldispühl · 2020 · Nucleic Acids Research
58. Artificial intelligence for the discovery of novel antimicrobial agents for emerging infectious diseases
    Adam Bess, Frej Berglind, Supratik Mukhopadhyay, Michał Bryliński, Nicholas W. Griggs, Tiffany Cho, Chris Galliano, Kishor M. Wasan · 2021 · Drug Discovery Today
59. PIGNet2: a versatile deep learning-based protein–ligand interaction prediction model for binding affinity scoring and virtual screening
    Seokhyun Moon, Sang-Yeon Hwang, Jaechang Lim, Woo Youn Kim · 2023 · Digital Discovery
60. A review of deep learning methods for ligand based drug virtual screening
    Hongjie Wu, Junkai Liu, Runhua Zhang, Yaoyao Lu, Guozeng Cui, Zhiming Cui, Yijie Ding · 2024 · Fundamental Research
61. Natural Peptides in Drug Discovery Targeting Acetylcholinesterase
    Vivitri Dewi Prasasty, Muhammad Radifar, Enade Perdana Istyastono · 2018 · Molecules
62. Ligand Strain Energy in Large Library Docking
    Shuo Gu, Matthew S. Smith, Yang Ying, John J. Irwin, Brian K. Shoichet · 2021 · Journal of Chemical Information and Modeling
63. Improving Docking-Based Virtual Screening Ability by Integrating Multiple Energy Auxiliary Terms from Molecular Docking Scoring
    Wen-Ling Ye, Chao Shen, Guo‐Li Xiong, Junjie Ding, Aiping Lü, Tingjun Hou, Dongsheng Cao · 2020 · Journal of Chemical Information and Modeling
64. Comparative assessment of machine-learning scoring functions on PDBbind 2013
    Mohamed A. Khamis, Walid E. Gomaa · 2015 · Engineering Applications of Artificial Intelligence
65. Large-Scale Computational Screening Identifies First in Class Multitarget Inhibitor of EGFR Kinase and BRD4
    Bryce K. Allen, Saurabh Mehta, Stewart W. J. Ember, E. Schönbrunn, Nagi G. Ayad, Stephan C. Schürer · 2015 · Scientific Reports
66. Computational Tool for Fast in silico Evaluation of hERG K+ Channel Affinity
    Giulia Chemi, Sandra Gemma, Giuseppe Campiani, Simone Brogi, Stefania Butini, Margherita Brindisi · 2017 · Frontiers in Chemistry
67. Docking Screens for Dual Inhibitors of Disparate Drug Targets for Parkinson’s Disease
    Mariama Jaiteh, Alexey A. Zeifman, Marcus Saarinen, Per Svenningsson, Jose Manuel Brea, Marı́a Isabel Loza, Jens Carlsson · 2018 · Journal of Medicinal Chemistry
68. Comparative Assessment of Seven Docking Programs on a Nonredundant Metalloprotein Subset of the PDBbind Refined
    Süleyman Selim Çınaroğlu, Emel Timuçin · 2019 · Journal of Chemical Information and Modeling
69. Selecting Machine-Learning Scoring Functions for Structure-Based Virtual Screening
    Pedro J. Ballester · 2019 · Drug Discovery Today Technologies
70. Integrating structure-based approaches in generative molecular design
    Morgan C. Thomas, Andreas Bender, Chris de Graaf · 2023 · Current Opinion in Structural Biology
71. Data Set Augmentation Allows Deep Learning-Based Virtual Screening to Better Generalize to Unseen Target Classes and Highlight Important Binding Interactions
    Jack Scantlebury, Nathan Brown, F. von Delft, Charlotte Mary Deane · 2020 · Journal of Chemical Information and Modeling
72. NRLiSt BDB, the Manually Curated Nuclear Receptors Ligands and Structures Benchmarking Database
    Nathalie Lagarde, Nesrine Ben Nasr, Aurore Jérémie, Hélène Guillemain, Vincent Laville, Taoufik Labib, Jean‐François Zagury, Matthieu Montès · 2014 · Journal of Medicinal Chemistry
73. Discovery of Potent Inhibitors for the Large Neutral Amino Acid Transporter 1 (LAT1) by Structure-Based Methods
    Natesh Singh, Mariafrancesca Scalise, Michele Galluccio, Marcus Wieder, Thomas Seidel, Thierry Langer, Cesare Indiveri, Gerhard Franz Ecker · 2018 · International Journal of Molecular Sciences
74. Deep contrastive learning enables genome-wide virtual screening
    Jia, Yinjun, Gao, Bowen, Tan, Jiaxin, Zheng, Jiqing, Hong, Xin, Zhu, Wenyu, Tan, Haichuan, Xiao, Yuan, Tan, Liping, Cai, Hongyi et al. · 2026 · Science
75. Rational design of ASCT2 inhibitors using an integrated experimental-computational approach
    Rachel‐Ann A. Garibsingh, Elias Ndaru, Alisa A. Garaeva, Yueyue Shi, Laura J. Zielewicz, Paul Zakrepine, Massimiliano Bonomi, Dirk Jan Slotboom, Cristina Paulino, Christof T. Grewer et al. · 2021 · Proceedings of the National Academy of Sciences
76. Active disease-related compound identification based on capsule network
    Bin Yang, Wenzheng Bao, Jinglong Wang · 2021 · Briefings in Bioinformatics
77. A fully differentiable ligand pose optimization framework guided by deep learning and a traditional scoring function
    Zechen Wang, Liangzhen Zheng, Sheng Wang, Mingzhi Lin, Zhihao Wang, Adams Wai‐Kin Kong, Yuguang Mu, Yanjie Wei, Weifeng Li · 2022 · Briefings in Bioinformatics
78. Conformer Generation for Structure-Based Drug Design: How Many and How Good?
    Andrew T. McNutt, Fatimah Bisiriyu, Sophia Song, Ananya Vyas, Geoffrey Hutchison, David Ryan Koes · 2023 · Journal of Chemical Information and Modeling
79. Deep Learning Pipeline for Accelerating Virtual Screening in Drug Discovery
    Fatima Noor, Muhammad Junaid, Atiah H. Almalki, Mohammed Almaghrabi, Shakira Ghazanfar, Muhammad Tahir ul Qamar · 2024 · Methods in molecular biology
80. Benchmarking AI-powered docking methods from the perspective of virtual screening
    Shukai Gu, Chao Shen, Xujun Zhang, Huiyong Sun, Heng Cai, Hao Luo, Huifeng Zhao, Bo Liu, Hongyan Du, Yihao Zhao et al. · 2025 · Nature Machine Intelligence
81. An Integrated Virtual Screening Approach for VEGFR-2 Inhibitors
    Yanmin Zhang, Shangyan Yang, Yu Jiao, Haichun Liu, Haoliang Yuan, Shuai Lü, Ting Ran, Sihui Yao, Zhipeng Ke, Jinxing Xu et al. · 2013 · Journal of Chemical Information and Modeling
82. An Unbiased Method To Build Benchmarking Sets for Ligand-Based Virtual Screening and its Application To GPCRs
    Jie Xia, Hongwei Jin, Zhenming Liu, Liangren Zhang, Xiang Simon Wang · 2014 · Journal of Chemical Information and Modeling
83. Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e-Pharmacophore Modeling and Docking
    Yu Wei, Jinlong Li, Jie Qing, Ming-Jie Huang, Ming Wu, Fenghua Gao, Dongmei Li, Zhangyong Hong, Lingbao Kong, Weiqiang Huang et al. · 2016 · PLoS ONE
84. Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation
    Morgan C. Thomas, Noel M. O’Boyle, Andreas Bender, Chris de Graaf · 2022 · Journal of Cheminformatics
85. Generic protein–ligand interaction scoring by integrating physical prior knowledge and data augmentation modelling
    Duanhua Cao, Geng Chen, Jiaxin Jiang, Jie Yu, Runze Zhang, Mingan Chen, Wei Zhang, Lifan Chen, Feisheng Zhong, Yingying Zhang et al. · 2024 · Nature Machine Intelligence
86. Pharmacophore Modeling for Cox-1 and -2 Inhibitors with Ligandscout in Comparison to Discovery Studio
    Veronika Temml, Teresa Kaserer, Zsófia Kutil, Přemysl Landa, Tomáš Vaněk, Daniela Schuster · 2014 · Future Medicinal Chemistry
87. AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking
    Shota Uehara, Shigenori Tanaka · 2016 · Molecules
88. Identification of G-quadruplex DNA/RNA binders: Structure-based virtual screening and biophysical characterization
    Roberta Rocca, Federica Moraca, Giosuè Costa, Matteo Nadai, Matteo Scalabrin, Carmine Talarico, Simona Distinto, Elias Maccioni, Francesco Ortuso, Anna Artese et al. · 2016 · Biochimica et Biophysica Acta (BBA) - General Subjects
89. Overview of Methods and Strategies for Conducting Virtual Small Molecule Screening
    Xavier Fradera, Kerim Babaoglu · 2017 · Current Protocols in Chemical Biology
90. SSnet: A Deep Learning Approach for Protein-Ligand Interaction Prediction
    Niraj Verma, Xingming Qu, Francesco Trozzi, Mohamed Elsaied, Nischal Karki, Peng Tao, Brian D. Zoltowski, Eric C. Larson, Elfi Kraka · 2021 · International Journal of Molecular Sciences
91. Decoding the limits of deep learning in molecular docking for drug discovery
    Yue Li, Jiacai Yi, Hui Li, Kun Li, Fenghua Kang, Youchao Deng, Chengkun Wu, Xiangzheng Fu, Dejun Jiang, Dongsheng Cao · 2025 · Chemical Science
92. In Silico Screening of Isocitrate Lyase for Novel Anti-Buruli Ulcer Natural Products Originating from Africa
    Samuel K. Kwofie, Bismark Dankwa, Emmanuel Odame, Francis Edem Agamah, Lady P. A. Doe, Joshua Teye, Odame Agyapong, Whelton A. Miller, Lydia Mosi, Michael D. Wilson · 2018 · Molecules
93. CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials
    Jonathan A. Fine, Janez Konc, Ram Samudrala, Gaurav Chopra · 2020 · Journal of Chemical Information and Modeling
94. Structure- and Ligand-Based Virtual Screening on DUD-E+: Performance Dependence on Approximations to the Binding Pocket
    Ann E. Cleves, Ajay N. Jain · 2020 · Journal of Chemical Information and Modeling
95. DeepDock: Enhancing Ligand-protein Interaction Prediction by a Combination of Ligand and Structure Information
    Zhirui Liao, Ronghui You, Xiaodi Huang, Xiaojun Yao, Tao Huang, Shanfeng Zhu · 2019 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
96. Structure‐Activity Relationships of Benzamides and Isoindolines Designed as SARS‐CoV Protease Inhibitors Effective against SARS‐CoV‐2
    Armin Welker, Christian Kersten, Christin Müller, Ramakanth Madhugiri, Collin Zimmer, Patrick Müller, Robert A. Zimmermann, Stefan Hammerschmidt, Hannah Maus, John Ziebuhr et al. · 2020 · ChemMedChem
97. Pharmacophore model, docking, QSAR, and molecular dynamics simulation studies of substituted cyclic imides and herbal medicines as COX-2 inhibitors
    Nathalie Moussa, Ahmad Hassan, Sajjad Gharaghani · 2021 · Heliyon
98. Few-Shot Learning for Low-Data Drug Discovery
    Daniel Vella, Jean-Paul Ebejer · 2022 · Journal of Chemical Information and Modeling
99. Utility of the Morgan Fingerprint in Structure-Based Virtual Ligand Screening
    Hongyi Zhou, Jeffrey Skolnick · 2024 · The Journal of Physical Chemistry B
100. Discovery of VEGFR2 inhibitors by integrating naïve Bayesian classification, molecular docking and drug screening approaches
     De Kang, Xiaocong Pang, Wenwen Lian, Lvjie Xu, Jinhua Wang, Hao Jia, Baoyue Zhang, Ailin Liu, Guanhua Du · 2018 · RSC Advances