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

Cited by (1,002)

Items 301–400 of 1,002

1. PlayMolecule BindScope: large scale CNN-based virtual screening on the web
   Miha Škalič, Gerard Martínez-Rosell, José Jiménez-Luna, Gianni De Fabritiis · 2018 · Bioinformatics
2. Identification of Zika Virus NS2B-NS3 Protease Inhibitors by Structure-Based Virtual Screening and Drug Repurposing Approaches
   Felipe Rocha da Silva Santos, Damiana A. F. Nunes, William Gustavo Lima, Danilo Davyt, Luciana Lara dos Santos, Alex Gutterres Taranto, Jaqueline Maria Siqueira Ferreira · 2019 · Journal of Chemical Information and Modeling
3. Discovery of Novel Inhibitors of a Critical Brain Enzyme Using a Homology Model and a Deep Convolutional Neural Network
   Adrian Stecuła, Muhammad S. Hussain, Ronald E. Viola · 2020 · Journal of Medicinal Chemistry
4. In silico investigation of potential inhibitors to main protease and spike protein of SARS-CoV-2 in propolis
   Azza Hanif Harisna, Rizky Nurdiansyah, Putri Hawa Syaifie, Dwi Nugroho, Kurniawan Eko Saputro, Firdayani Firdayani, Chandra Dwi Prakoso, Nurul Taufiqu Rochman, Nurwenda Novan Maulana, Alfian Noviyanto et al. · 2021 · Biochemistry and Biophysics Reports
5. Yes SIR! On the structure–inactivity relationships in drug discovery
   Edgar López‐López, Eli Fernández‐de Gortari, José L. Medina‐Franco · 2022 · Drug Discovery Today
6. Sfcnn: a novel scoring function based on 3D convolutional neural network for accurate and stable protein–ligand affinity prediction
   Yu Wang, Zhengxiao Wei, Lei Xi · 2022 · BMC Bioinformatics
7. Benchmarking different docking protocols for predicting the binding poses of ligands complexed with cyclooxygenase enzymes and screening chemical libraries
   Sara Shamsian, Babak Sokouti, Siavoush Dastmalchi · 2023 · Bioimpacts
8. Antibody design using deep learning: from sequence and structure design to affinity maturation
   Sara Joubbi, Alessio Micheli, Paolo Milazzo, Giuseppe Maccari, Giorgio Ciano, Dario Cardamone, Duccio Medini · 2024 · Briefings in Bioinformatics
9. A machine learning approach towards the prediction of protein–ligand binding affinity based on fundamental molecular properties
   Indra Kundu, Goutam Paul, Raja Banerjee · 2018 · RSC Advances
10. Development of machine learning models to predict inhibition of 3‐dehydroquinate dehydratase
    Maurício Boff de Ávila, Walter Filgueira de Azevedo · 2018 · Chemical Biology & Drug Design
11. Pharmacophore-Based Similarity Scoring for DOCK
    Lingling Jiang, Robert C. Rizzo · 2014 · The Journal of Physical Chemistry B
12. Improving the Virtual Screening Ability of Target-Specific Scoring Functions Using Deep Learning Methods
    Dingyan Wang, Chen Cui, Xiaoyu Ding, Zhaoping Xiong, Mingyue Zheng, Xiaomin Luo, Hualiang Jiang, Kaixian Chen · 2019 · Frontiers in Pharmacology
13. The impact of compound library size on the performance of scoring functions for structure-based virtual screening
    Louison Fresnais, Pedro J. Ballester · 2020 · Briefings in Bioinformatics
14. Structure-Based Virtual Screening of Perfluoroalkyl and Polyfluoroalkyl Substances (PFASs) as Endocrine Disruptors of Androgen Receptor Activity Using Molecular Docking and Machine Learning
    Ettayapuram Ramaprasad Azhagiya Singam, Phum Tachachartvanich, Denis Fourches, Anatoly A. Soshilov, Ching‐Yi Hsieh, Michele Andrea La Merrill, Martyn T. Smith, Kathleen A. Durkin · 2020 · Environmental Research
15. Fragment tailoring strategy to design novel chemical entities as potential binders of novel corona virus main protease
    Chinmayee Choudhury · 2020 · Journal of Biomolecular Structure and Dynamics
16. Drug Repurposing Targeting Pseudomonas aeruginosa MvfR Using Docking, Virtual Screening, Molecular Dynamics, and Free-Energy Calculations
    Tatiana F. Vieira, Rita P. Magalhães, Manuel V. Simões, Sérgio Filipe Sousa · 2022 · Antibiotics
17. A strategy for screening novel umami dipeptides based on common feature pharmacophore and molecular docking
    Yongzhao Xiong, Xinchang Gao, Daodong Pan, Ting Zhang, Lulu Qi, Ning Wang, Yufen Zhao, Yali Dang · 2022 · Biomaterials
18. CHARMM‐GUI high‐throughput simulator for efficient evaluation of protein–ligand interactions with different force fields
    H. Guterres, Sang-Jun Park, Han Zhang, Thomas Perone, Jongtaek Kim, W. Im · 2022 · Protein Science
19. Benchmarking methods and data sets for ligand enrichment assessment in virtual screening
    Jie Xia, Ermias Lemma Tilahun, Terry-Elinor R. Reid, Liangren Zhang, Xiang Simon Wang · 2014 · Methods
20. Nonlinear Scoring Functions for Similarity-Based Ligand Docking and Binding Affinity Prediction
    Michał Bryliński · 2013 · Journal of Chemical Information and Modeling
21. Molecular Docking, 3D Structure-Based Pharmacophore Modeling, and ADME Prediction of Alpha Mangostin and Its Derivatives against Estrogen Receptor Alpha
    Muchtaridi Muchtaridi, Doni Dermawan, Muhammad Yusuf · 2018 · Journal of Young Pharmacists
22. DLIGAND2: an improved knowledge-based energy function for protein–ligand interactions using the distance-scaled, finite, ideal-gas reference state
    Pin Chen, Yaobin Ke, Yutong Lu, Yunfei Du, Jiahui Li, Yan Hui, Huiying Zhao, Yaoqi Zhou, Yuedong Yang · 2019 · Journal of Cheminformatics
23. Ligand-Binding-Site Refinement to Generate Reliable Holo Protein Structure Conformations from Apo Structures
    Hugo Guterres, Sang‐Jun Park, Wei Jiang, Wonpil Im · 2020 · Journal of Chemical Information and Modeling
24. Identification of 1H-purine-2,6-dione derivative as a potential SARS-CoV-2 main protease inhibitor: molecular docking, dynamic simulations, and energy calculations
    Hossam Nada, Ahmed Elkamhawy, Kyeong Lee · 2022 · PeerJ
25. Structure-Based Discovery of Inhibitors of the SARS-CoV-2 Nsp14 N7-Methyltransferase
    Isha Singh, Fengling Li, Elissa A. Fink, Irene Chau, Alice Shi Ming Li, Annia Rodríguez‐Hernández, Isabella Glenn, Francisco José Zapatero Belinchón, M. Luis Rodriguez, Kanchan Devkota et al. · 2023 · Journal of Medicinal Chemistry
26. Validation guidelines for drug-target prediction methods
    Ziaurrehman Tanoli, Aron Schulman, Tero A. Aittokallio · 2024 · Expert Opinion on Drug Discovery
27. Machine-Learning-Assisted Approach for Discovering Novel Inhibitors Targeting Bromodomain-Containing Protein 4
    Jing Xing, Wenchao Lu, Rongfeng Liu, Yulan Wang, Yiqian Xie, Hao Zhang, Zhe Shi, Hao Jiang, Julie Yu-Chih Liu, Kaixian Chen et al. · 2017 · Journal of Chemical Information and Modeling
28. Molecular Architect: A User-Friendly Workflow for Virtual Screening
    Eduardo Habib Bechelane Maia, Lucas Rolim Medaglia, Alisson Marques da Silva, Alex Gutterres Taranto · 2020 · ACS Omega
29. Improving structure-based virtual screening performance via learning from scoring function components
    Guo‐Li Xiong, Wen-Ling Ye, Chao Shen, Aiping Lü, Tingjun Hou, Dongsheng Cao · 2020 · Briefings in Bioinformatics
30. Selecting an Optimal Number of Binding Site Waters To Improve Virtual Screening Enrichments Against the Adenosine A2A Receptor
    Eelke Bart Lenselink, Thijs Beuming, Woody Sherman, Herman van Vlijmen, Adriaan P. IJzerman · 2014 · Journal of Chemical Information and Modeling
31. Elucidating the molecular mechanisms of essential oils' insecticidal action using a novel cheminformatics protocol
    Eduardo José Azevedo Corrêa, Frederico Chaves Carvalho, Júlia Assunção de Castro Oliveira, Suzan Kelly Vilela Bertolucci, Marcus Tullius Scotti, Carlos Henrique da Silveira, Fabiana Costa Guedes, Júlio Onésio Ferreira Melo, Raquel C. de Melo-Minardi, Leonardo Henrique França de Lima · 2023 · Scientific Reports
32. Deep generative models for 3D molecular structure
    Benoît Baillif, Jason C. Cole, Patrick McCabe, Andreas Bender · 2023 · Current Opinion in Structural Biology
33. Pharmacoinformatics-based identification of potential bioactive compounds against Ebola virus protein VP24
    Samuel K. Kwofie, Emmanuel Broni, Joshua Teye, Erasmus Quansah, Ibrahim Issah, Michael D. Wilson, Whelton A. Miller, Elvis Kwason Tiburu, Joseph Humphrey Kofi Bonney · 2019 · Computers in Biology and Medicine
34. GanDTI: A multi-task neural network for drug-target interaction prediction
    Shuyu Wang, Peng Shan, Yuliang Zhao, Lei Zuo · 2021 · Computational Biology and Chemistry
35. Featurization strategies for protein–ligand interactions and their applications in scoring function development
    Guo‐Li Xiong, Chao Shen, Ziyi Yang, Dejun Jiang, Shao Liu, Aiping Lü, Xiang Chen, Tingjun Hou, Dongsheng Cao · 2021 · Wiley Interdisciplinary Reviews Computational Molecular Science
36. SCORCH: Improving structure-based virtual screening with machine learning classifiers, data augmentation, and uncertainty estimation
    Miles McGibbon, Sam Money-Kyrle, Vincent Blay, Douglas R. Houston · 2022 · Journal of Advanced Research
37. Interaction-Based Inductive Bias in Graph Neural Networks: Enhancing Protein-Ligand Binding Affinity Predictions From 3D Structures
    Ziduo Yang, Weihe Zhong, Qiujie Lv, Tiejun Dong, Guanxing Chen, Calvin Yu‐Chian Chen · 2024 · IEEE Transactions on Pattern Analysis and Machine Intelligence
38. In silico and in vitro identification of candidate SIRT1 activators from Indonesian medicinal plants compounds database
    Azminah Azminah, Linda Erlina, Maksum Radji, Abdul Mun’im, Rezi Riadhi Syahdi, Arry Yanuar · 2019 · Computational Biology and Chemistry
39. AncPhore: A versatile tool for anchor pharmacophore steered drug discovery with applications in discovery of new inhibitors targeting metallo-β-lactamases and indoleamine/tryptophan 2,3-dioxygenases
    Qing-Qing Dai, Yu‐Hang Yan, Xiang-Li Ning, Gen Li, Junlin Yu, Ji Wei Deng, Lingling Yang, Guo‐Bo Li · 2021 · Acta Pharmaceutica Sinica B
40. Discovery of novel polyamine analogs with anti-protozoal activity by computer guided drug repositioning
    Lucas N. Alberca, María Laura Sbaraglini, Darío Balcazar, Laura Fraccaroli, Carolina Carrillo, Andrea Medeiros, Diego Benítez, Marcelo Alberto Comini, Alan Talevi · 2016 · Journal of Computer-Aided Molecular Design
41. A hybrid framework for improving uncertainty quantification in deep learning-based QSAR regression modeling
    Dingyan Wang, Jie Yu, Lifan Chen, Xutong Li, Hualiang Jiang, Kaixian Chen, Mingyue Zheng, Xiaomin Luo · 2021 · Journal of Cheminformatics
42. Prediction of Potential Commercially Available Inhibitors against SARS-CoV-2 by Multi-Task Deep Learning Model
    Fan Hu, Jiaxin Jiang, Peng Yin · 2022 · Biomolecules
43. Characterization of the non-covalent interaction between the PF-07321332 inhibitor and the SARS-CoV-2 main protease
    Marina Macchiagodena, Marco Pagliai, Piero Procacci · 2021 · Journal of Molecular Graphics and Modelling
44. Comprehensive assessment of nine docking programs on type II kinase inhibitors: prediction accuracy of sampling power, scoring power and screening power
    Chao Shen, Zhe Wang, Xiaojun Yao, Youyong Li, Tailong Lei, Ercheng Wang, Lei Xu, Feng Zhu, Dan Li, Tingjun Hou · 2018 · Briefings in Bioinformatics
45. Carvedilol serves as a novel CYP1B1 inhibitor, a systematic drug repurposing approach through structure-based virtual screening and experimental verification
    Ying Wang, Xiaomei He, Chunshi Li, Yan Ma, Wen-chi Xue, Baichun Hu, Jian Wang, Tingting Zhang, Fengjiao Zhang · 2020 · European Journal of Medicinal Chemistry
46. A comprehensive review of computational techniques for the prediction of drug side effects
    Kanica Sachdev, Manoj K. Gupta · 2020 · Drug Development Research
47. Discovery of anti-MERS-CoV small covalent inhibitors through pharmacophore modeling, covalent docking and molecular dynamics simulation
    Mubarak A. Alamri, Muhammad Tahir ul Qamar, Obaid Afzal, Alhumaidi B. Alabbas, Yassine Riadi, Safar M. Alqahtani · 2021 · Journal of Molecular Liquids
48. Targeting JMJD1C to selectively disrupt tumor Treg cell fitness enhances antitumor immunity
    Xue-Hui Long, Su-Lin Zhang, Yu-Liang Wang, Jing-Jing Chen, Yan-Lai Lu, Hui Hou, Bichun Lin, Xu-Tong Li, Chang Shen, Rui-Rui Yang et al. · 2024 · Nature Immunology
49. Drug-target interaction/affinity prediction: Deep learning models and advances review
    Ali Vefghi, Zahed Rahmati, Mohammad Akbari · 2025 · Computers in Biology and Medicine
50. An improved approach for predicting drug–target interaction: proteochemometrics to molecular docking
    Naeem Shaikh, Mahesh C. Sharma, Prabha Garg · 2016 · Molecular BioSystems
51. IVS2vec: A tool of Inverse Virtual Screening based on word2vec and deep learning techniques
    Haiping Zhang, Linbu Liao, Y.F. Cai, Yuhui Hu, Hao Wang · 2019 · Methods
52. Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening?
    Chao Shen, Gaoqi Weng, Xujun Zhang, Elaine Lai‐Han Leung, Xiaojun Yao, Jinping Pang, Xin Chai, Dan Li, Ercheng Wang, Dongsheng Cao et al. · 2021 · Briefings in Bioinformatics
53. Identification of a novel inhibitor of SARS-CoV-2 3CL-PRO through virtual screening and molecular dynamics simulation
    Asim Kumar Bepari, Hasan Mahmud Reza · 2021 · PeerJ
54. Leveraging nonstructural data to predict structures and affinities of protein–ligand complexes
    Joseph M. Paggi, Julia A. Belk, Scott A. Hollingsworth, Nicolas Villanueva, Alexander S. Powers, Mary Jo Clark, Augustine Chemparathy, Jonathan Tynan, Thomas K. Lau, Roger K. Sunahara et al. · 2021 · Proceedings of the National Academy of Sciences
55. Importance of Binding Site Hydration and Flexibility Revealed When Optimizing a Macrocyclic Inhibitor of the Keap1–Nrf2 Protein–Protein Interaction
    Fabio Begnini, Stefan Geschwindner, Patrik Johansson, Lisa Wissler, Richard J. Lewis, Emma Danelius, Andreas Luttens, Pierre G. Matricon, Jens Carlsson, Stijn Lenders et al. · 2022 · Journal of Medicinal Chemistry
56. On the Value of Using 3D Shape and Electrostatic Similarities in Deep Generative Methods
    Giovanni Bolcato, Esther Heid, Jonas Boström · 2022 · Journal of Chemical Information and Modeling
57. DiffBindFR: an SE(3) equivariant network for flexible protein–ligand docking
    Jintao Zhu, Zhonghui Gu, Jianfeng Pei, Luhua Lai · 2024 · Chemical Science
58. Modeling protein–ligand interactions for drug discovery in the era of deep learning
    Y.X. Wang, Yibo Li, Jiaxiao Chen, Luhua Lai · 2025 · Chemical Society Reviews
59. Enhancing the Sensitivity of Pharmacophore-Based Virtual Screening by Incorporating Customized ZBG Features: A Case Study Using Histone Deacetylase 8
    Xuben Hou, Jintong Du, Renshuai Liu, Yi Zhou, Minyong Li, Wenfang Xu, Hao Fang · 2015 · Journal of Chemical Information and Modeling
60. Virtual Screening for UDP-Galactopyranose Mutase Ligands Identifies a New Class of Antimycobacterial Agents
    Virginia A. Kincaid, Nir London, Kittikhun Wangkanont, Darryl A. Wesener, Sarah A. Marcus, Annie Heroux, Lyudmila Nedyalkova, Adel M. Talaat, Katrina T. Forest, Brian K. Shoichet et al. · 2015 · ACS Chemical Biology
61. Endocrine Disruption at the Androgen Receptor: Employing Molecular Dynamics and Docking for Improved Virtual Screening and Toxicity Prediction
    Joël Wahl, Martin Smieško · 2018 · International Journal of Molecular Sciences
62. RASPD+: Fast Protein-Ligand Binding Free Energy Prediction Using Simplified Physicochemical Features
    Stefan Holderbach, Lukas Adam, Bhyravabhotla Jayaram, Rebecca C. Wade, Goutam Mukherjee · 2020 · Frontiers in Molecular Biosciences
63. OctSurf: Efficient hierarchical voxel-based molecular surface representation for protein-ligand affinity prediction
    Qinqing Liu, Peng‐Shuai Wang, Chunjiang Zhu, Blake Blumenfeld Gaines, Tan Zhu, Jinbo Bi, Minghu Song · 2021 · Journal of Molecular Graphics and Modelling
64. Temperature artifacts in protein structures bias ligand-binding predictions
    S. Bradford, L. El Khoury, Yun-Hui Ge, Meghan Osato, David L. Mobley, Marcus Fischer · 2021 · Chemical Science
65. MetaDOCK: A Combinatorial Molecular Docking Approach
    Izaz Monir Kamal, Saikat Chakrabarti · 2023 · ACS Omega
66. Structure-Based Discovery of Novel and Selective 5-Hydroxytryptamine 2B Receptor Antagonists for the Treatment of Irritable Bowel Syndrome
    Yu Zhou, Jing Ma, Xingyu Lin, Xi‐Ping Huang, Kaichun Wu, Niu Huang · 2015 · Journal of Medicinal Chemistry
67. In silico Guided Drug Repurposing: Discovery of New Competitive and Non-competitive Inhibitors of Falcipain-2
    Lucas N. Alberca, Sara Chuguransky, Cora Lilia Alvarez, Alan Talevi, Emir Salas‐Sarduy · 2019 · Frontiers in Chemistry
68. An Integrated Pharmacophore/Docking/3D-QSAR Approach to Screening a Large Library of Products in Search of Future Botulinum Neurotoxin A Inhibitors
    Davide Gentile, Giuseppe Floresta, Vincenzo Patamia, Rita Chiaramonte, Giulia Letizia Mauro, Antonio Rescifina, Michele Maria Vecchio · 2020 · International Journal of Molecular Sciences
69. Computational basis of SARS-CoV 2 main protease inhibition: an insight from molecular dynamics simulation based findings
    Pramod Avti, Arushi Chauhan, Nishant Shekhar, Manisha Prajapat, Phulen Sarma, Hardeep Kaur, Anusuya Bhattacharyya, Subodh Kumar, Ajay Prakash, Saurabh Sharma et al. · 2021 · Journal of Biomolecular Structure and Dynamics
70. Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
    Morgan C. Thomas, Andrew Boardman, Miguel García-Ortegón, Hongbin Yang, Chris de Graaf, Andreas Bender · 2021 · Methods in molecular biology
71. Evaluating GPCR modeling and docking strategies in the era of deep learning-based protein structure prediction
    Sumin Lee, Seeun Kim, Gyu Rie Lee, Sohee Kwon, Hyeonuk Woo, Chaok Seok, Hahnbeom Park · 2022 · Computational and Structural Biotechnology Journal
72. PETrans: De Novo Drug Design with Protein-Specific Encoding Based on Transfer Learning
    Xun Wang, Changnan Gao, Peifu Han, Xue Li, Wenqi Chen, Alfonso Rodríguez‐Patón, Shuang Wang, Pan Zheng · 2023 · International Journal of Molecular Sciences
73. Machine learning small molecule properties in drug discovery
    Nikolai Schapin, Maciej Majewski, Alejandro Varela‐Rial, Carlos Arróniz, Gianni De Fabritiis · 2023 · Artificial Intelligence Chemistry
74. Docking for EP4R antagonists active against inflammatory pain
    Stefan Gahbauer, Chelsea DeLeon, Joao M. Braz, Veronica Craik, Hye Jin Kang, Xiaobo Wan, Xi‐Ping Huang, Christian B. Billesbølle, Yongfeng Liu, Tao Che et al. · 2023 · Nature Communications
75. Redocking the PDB
    Florian Flachsenberg, Christiane Ehrt, Torben Gutermuth, Matthias Rarey · 2023 · Journal of Chemical Information and Modeling
76. A new paradigm for applying deep learning to protein–ligand interaction prediction
    Wang, Zechen, Wang, Sheng, Li, Yangyang, Guo, Jingjing, Wei, Yanjie, Mu, Yuguang, Zheng, Liangzhen, Li, Weifeng · 2024 · Briefings in Bioinformatics
77. Modern machine‐learning for binding affinity estimation of protein–ligand complexes: Progress, opportunities, and challenges
    Tobias Harren, Torben Gutermuth, Christoph Grebner, Gerhard Heßler, Matthias Rarey · 2024 · Wiley Interdisciplinary Reviews Computational Molecular Science
78. The future of machine learning for small-molecule drug discovery will be driven by data
    Guy Durant, Fergus Boyles, Kristian Birchall, Charlotte Mary Deane · 2024 · Nature Computational Science
79. Docking Ligands into Flexible and Solvated Macromolecules. 7. Impact of Protein Flexibility and Water Molecules on Docking-Based Virtual Screening Accuracy
    Éric Therrien, Nathanaël Weill, Anna Tomberg, Christopher R. Corbeil, Devin Lee, Nicolas Moitessier · 2014 · Journal of Chemical Information and Modeling
80. Multi-Body Interactions in Molecular Docking Program Devised with Key Water Molecules in Protein Binding Sites
    Wei Xiao, Disha Wang, Zihao Shen, Shiliang Li, Honglin Li · 2018 · Molecules
81. Sequential ligand- and structure-based virtual screening approach for the identification of potential G protein-coupled estrogen receptor-1 (GPER-1) modulators
    Shafi Ullah Khan, Nafees Ahemad, Lay‐Hong Chuah, Rakesh Naidu, Thet Thet Htar · 2019 · RSC Advances
82. A Deep-Learning View of Chemical Space Designed to Facilitate Drug Discovery
    Paul Maragakis, Hunter M. Nisonoff, Brian Cole, David Elliot Shaw · 2020 · Journal of Chemical Information and Modeling
83. Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity
    Mariama Jaiteh, Ismael Rodríguez‐Espigares, Jana Selent, Jens Carlsson · 2020 · PLoS Computational Biology
84. In silico Design of Novel HIV-1 NNRTIs Based on Combined Modeling Studies of Dihydrofuro[3,4-d]pyrimidines
    Yanming Chen, Yafeng Tian, Ya Gao, Fengshou Wu, Xiaogang Luo, Xiu-Lian Ju, Genyan Liu · 2020 · Frontiers in Chemistry
85. Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking
    Tamer M. Ibrahim, Muhammad I. Ismail, Matthias R. Bauer, Adnan A. Bekhit, Frank M. Boeckler · 2020 · Frontiers in Chemistry
86. Docking Paradigm in Drug Design
    Vladimir Borisovich Sulimov, Danil C. Kutov, Anna S. Taschilova, Ivan S. Ilin, Eugene Evgen'evich Tyrtyshnikov, Alexey V. Sulimov · 2020 · Current Topics in Medicinal Chemistry
87. Identification of Novel Protein Kinase Receptor Type 2 Inhibitors Using Pharmacophore and Structure-Based Virtual Screening
    Josiane Viana Cruz, Moysés Fagundes de Araújo Neto, Luciane Barros Silva, Ryan da Silva Ramos, Josivan da Silva Costa, Davi do Socorro Barros Brasil, Cleison Carvalho Lobato, Glauber Vilhena da Costa, José Adolfo Homobono Machado Bittencourt, Carlos Henrique Tomich de Paula da Silva et al. · 2018 · Molecules
88. wSDTNBI: a novel network-based inference method for virtual screening
    Zengrui Wu, Hui Ma, Zehui Liu, Lulu Zheng, Zhuohang Yu, Shuying Cao, Wenqing Fang, Lili Wu, Weihua Li, Guixia Liu et al. · 2021 · Chemical Science
89. Absolute binding free energy calculations improve enrichment of actives in virtual compound screening
    Mudong Feng, Germano Heinzelmann, Michael K. Gilson · 2022 · Scientific Reports
90. Applying DEKOIS 2.0 in structure-based virtual screening to probe the impact of preparation procedures and score normalization
    Tamer M. Ibrahim, Matthias R. Bauer, Frank M. Boeckler · 2015 · Journal of Cheminformatics
91. Screen3D: A Novel Fully Flexible High-Throughput Shape-Similarity Search Method
    Adrián Kalászi, Dániel Szisz, Gábor Imre, Tímea Polgár · 2014 · Journal of Chemical Information and Modeling
92. A graph-based approach to construct target-focused libraries for virtual screening
    Misagh Naderi, Chris Alvin, Yun Ding, Supratik Mukhopadhyay, Michał Bryliński · 2016 · Journal of Cheminformatics
93. ROCS-derived features for virtual screening
    Steven M. Kearnes, Vijay S. Pande · 2016 · Journal of Computer-Aided Molecular Design
94. α-Mangostin and its derivatives against estrogen receptor alpha
    Richa Mardianingrum, Muhammad Yusuf, Maywan Hariono, Amirah Mohd Gazzali, Muchtaridi Muchtaridi · 2020 · Journal of Biomolecular Structure and Dynamics
95. LigTMap: ligand and structure-based target identification and activity prediction for small molecular compounds
    Faraz Shaikh, Hio Kuan Tai, Nirali Desai, Shirley W. I. Siu · 2021 · Journal of Cheminformatics
96. Structure-Based Predictions of Activity Cliffs
    Jarmila Husby, Giovanni Bottegoni, Irina Kufareva, Ruben A Abagyan, Andrea Cavalli · 2015 · Journal of Chemical Information and Modeling
97. FINDSITE^comb2.0: A New Approach for Virtual Ligand Screening of Proteins and Virtual Target Screening of Biomolecules
    Zhou, Hongyi, Cao, Hongnan, Skolnick, Jeffrey · 2018 · Journal of Chemical Information and Modeling
98. Targeting NMDA receptor in Alzheimer’s disease: identifying novel inhibitors using computational approaches
    Arif Jamal Siddiqui, Riadh Badraoui, Sadaf Jahan, Mohammed Merae Alshahrani, Maqsood Ahmed Siddiqui, Andleeb Khan, Mohd Adnan · 2023 · Frontiers in Pharmacology
99. Identification of Potent Acetylcholinesterase Inhibitors as New Candidates for Alzheimer Disease via Virtual Screening, Molecular Docking, Dynamic Simulation, and Molecular Mechanics–Poisson–Boltzmann Surface Area Calculations
    Hind Yassmine Chennai, Salah Belaıdı, Lotfi Bourougaa, Mebarka Ouassaf, Leena Sinha, Abdelouahid Samadi, Samir Chtita · 2024 · Molecules
100. Compound Activity Prediction Using Models of Binding Pockets or Ligand Properties in 3D
     Irina Kufareva, Yuchen Chen, Andrey V. Ilatovskiy, Ruben A Abagyan · 2012 · Current Topics in Medicinal Chemistry