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

Cited by (1,002)

Items 501–600 of 1,002

1. In Silico Study, Synthesis, and Cytotoxic Activities of Porphyrin Derivatives
   Fransiska Kurniawan, Youhei Miura, Rahmana Emran Kartasasmita, Naoki Yoshioka, Abdul Mutalib, Daryono Hadi Tjahjono · 2018 · Pharmaceuticals
2. Machine Learning Classification Models to Improve the Docking‐based Screening: A Case of PI3K‐Tankyrase Inhibitors
   Vladimir P. Berishvili, Andrew E. Voronkov, Eugene V. Radchenko, Vladimir A. Palyulin · 2018 · Molecular Informatics
3. Using a Consensus Docking Approach to Predict Adverse Drug Reactions in Combination Drug Therapies for Gulf War Illness
   Rajeev Jaundoo, Jonathan A. Bohmann, Gloria E. Gutierrez, Nancy G. Klimas, Gordon Broderick, Travis J. A. Craddock · 2018 · International Journal of Molecular Sciences
4. Improving inverse docking target identification with Z‐score selection
   Stephanie S. Kim, Melanie L. Aprahamian, Steffen Lindert · 2019 · Chemical Biology & Drug Design
5. Getting Docking into Shape Using Negative Image-Based Rescoring
   Sami T. Kurkinen, Sakari Lätti, Olli T. Pentikäinen, Pekka A. Postila · 2019 · Journal of Chemical Information and Modeling
6. Opioids as Substrates and Inhibitors of the Genetically Highly Variable Organic Cation Transporter OCT1
   Marleen J. Meyer, Viktoria Elisabeth Neumann, Hannah Rosa Friesacher, Barbara Zdrazil, Jürgen Brockmöller, Mladen Vassilev Tzvetkov · 2019 · Journal of Medicinal Chemistry
7. Pharmacophore model-based virtual screening, docking, biological evaluation and molecular dynamics simulations for inhibitors discovery against α-tryptophan synthase from Mycobacterium tuberculosis
   Sadia Naz, Umar Farooq, Sara Khan, Rizwana Sarwar, Yahia N. Mabkhot, Maria Saeed, Abdulrahman Alsayari, Abdullatif Bin Muhsinah, Zaheer Ul‐Haq · 2020 · Journal of Biomolecular Structure and Dynamics
8. Identification of natural products as selective PTP1B inhibitors via virtual screening
   Ying Yang, Jin‐Ying Tian, Fei Ye, Zhiyan Xiao · 2020 · Bioorganic Chemistry
9. EasyVS: a user-friendly web-based tool for molecule library selection and structure-based virtual screening
   Douglas E. V. Pires, Wandré Nunes de Pinho Veloso, Yoochan Myung, Carlos H. M. Rodrigues, Michael A. Silk, Pâmela Marinho Rezende, Francislon Silva, Joicymara Santos Xavier, João Paulo Linhares Velloso, Carlos Henrique da Silveira et al. · 2020 · Bioinformatics
10. KORP-PL: a coarse-grained knowledge-based scoring function for protein–ligand interactions
    Maria Kadukova, Karina Machado, Pablo Chacón, Sergei Grudinin · 2020 · Bioinformatics
11. Methylene blue analogues: In vitro antimicrobial minimum inhibitory concentrations and in silico pharmacophore modelling
    Louis Thesnaar, Johannes Jacobus Bezuidenhout, Anél Petzer, Jacobus Petrus Petzer, Theunis Theodorus Cloete · 2020 · European Journal of Pharmaceutical Sciences
12. Enzymes inhibition profiles and antibacterial activities of benzylidenemalononitrile derivatives
    Pınar Güller, Ziya Dağalan, Uğur Güller, Ulaş Çalışır, Bilal Nişancı · 2021 · Journal of Molecular Structure
13. Identification of Potent and Selective JAK1 Lead Compounds Through Ligand-Based Drug Design Approaches
    Sathya Babu, Santhosh Kumar Nagarajan, Sruthy Sathish, Vir Singh Negi, Honglae Sohn, Thirumurthy Madhavan · 2022 · Frontiers in Pharmacology
14. Protein-Based Virtual Screening Tools Applied for RNA–Ligand Docking Identify New Binders of the preQ 1 -Riboswitch
    Elisabeth Kallert, Tim R. Fischer, Simon Schneider, Maike Grimm, Mark Helm, Christian Kersten · 2022 · Journal of Chemical Information and Modeling
15. Developing a Naïve Bayesian Classification Model with PI3Kγ structural features for virtual screening against PI3Kγ: Combining molecular docking and pharmacophore based on multiple PI3Kγ conformations
    Yingmin Jiang, Wendian Xiong, Lei Jia, Lei Xu, Yanfei Cai, Yun Chen, Jian Jin, Mingzhu Gao, Jingyu Zhu · 2022 · European Journal of Medicinal Chemistry
16. Beyond sequence: Structure-based machine learning
    Janani Durairaj, Dick de Ridder, Aalt D. J. van Dijk · 2022 · Computational and Structural Biotechnology Journal
17. Protein Flexibility in Docking-Based Virtual Screening: Discovery of Novel Lymphoid-Specific Tyrosine Phosphatase Inhibitors Using Multiple Crystal Structures
    Xuben Hou, Kangshuai Li, Xiao Yu, Jin‐Peng Sun, Hao Fang · 2015 · Journal of Chemical Information and Modeling
18. A Molecular Dynamics–Shared Pharmacophore Approach to Boost Early‐Enrichment Virtual Screening: A Case Study on Peroxisome Proliferator‐Activated Receptor α
    Ugo Perricone, Marcus Wieder, Thomas Seidel, Thierry Langer, Alessandro Padova, Anna Maria Almerico, Marco Tutone · 2017 · ChemMedChem
19. HybridSim-VS: a web server for large-scale ligand-based virtual screening using hybrid similarity recognition techniques
    Jinling Shang, Xi Dai, Yecheng Li, Marco Pistolozzi, Ling Wang · 2017 · Bioinformatics
20. Novel natural non-nucleoside inhibitors of HIV-1 reverse transcriptase identified by shape- and structure-based virtual screening techniques
    Giosuè Costa, Roberta Rocca, Angela Corona, Nicole Grandi, Federica Moraca, Isabella Romeo, Carmine Talarico, Maria Giovanna Gagliardi, Francesca Alessandra Ambrosio, Francesco Ortuso et al. · 2018 · European Journal of Medicinal Chemistry
21. Optimization of Membrane Electrode Assembly of PEM Fuel Cell by Response Surface Method
    Rohit K. S. S. Vuppala, Benitta A. Chaedir, Lishuai Jiang, Lianjun Chen, Muhammad Aziz, AGUS PULUNG SASMITO · 2019 · Molecules
22. COVID-19: CADD to the rescue
    Abdulmujeeb T. Onawole, Kazeem O. Sulaiman, Temitope U. Kolapo, Fatimo O. Akinde, Rukayat O. Adegoke · 2020 · Virus Research
23. LC-MS characterized methanolic extract of zanthoxylum armatum possess anti-breast cancer activity through Nrf2-Keap1 pathway: An in-silico, in-vitro and in-vivo evaluation
    Roja Sahu, Rajiv K. Kar, Priyashree Sunita, Pritha Bose, Puja Kumari, Salona Bharti, Sharad Kumar Srivastava, Shakti Prasad Pattanayak · 2020 · Journal of Ethnopharmacology
24. Latent Biases in Machine Learning Models for Predicting Binding Affinities Using Popular Data Sets
    Ganesh Chandan Kanakala, Rishal Aggarwal, Divya Nayar, U. Deva Priyakumar · 2023 · ACS Omega
25. Discovery of 2-Aminopyrimidines as Potent Agonists for the Bitter Taste Receptor TAS2R14
    Lukas A. W. Waterloo, Harald Hübner, Fabrizio Fierro, Tara Pfeiffer, Regine Brox, Stefan Löber, Dorothée Weikert, Masha Y. Niv, Peter Gmeiner · 2023 · Journal of Medicinal Chemistry
26. Similarity Mapplet: Interactive Visualization of the Directory of Useful Decoys and ChEMBL in High Dimensional Chemical Spaces
    Mahendra Awale, Jean‐Louis Reymond · 2015 · Journal of Chemical Information and Modeling
27. Consensus models for CDK5 inhibitors in silico and their application to inhibitor discovery
    Jiansong Fang, Ranyao Yang, Li Gao, Shengqian Yang, Xiaocong Pang, Chao Li, Yangyang He, Ailin Liu, Guanhua Du · 2014 · Molecular Diversity
28. Discovery of Mycobacterium tuberculosis InhA Inhibitors by Binding Sites Comparison and Ligands Prediction
    Tanja Štular, Samo Lešnik, Kaja Rožman, Julia Schink, Mitja M. Zdouc, An Ghysels, Feng Liu, Courtney C. Aldrich, V. Joachim Haupt, Sebastian Salentin et al. · 2016 · Journal of Medicinal Chemistry
29. Structure–Affinity Relationships and Structure–Kinetics Relationships of Pyrido[2,1- f ]purine-2,4-dione Derivatives as Human Adenosine A3 Receptor Antagonists
    Lizi Xia, Wessel A. C. Burger, Jacobus P. D. van Veldhoven, Boaz J. Kuiper, Tirsa T van Duijl, Eelke Bart Lenselink, Ellen Paasman, Laura H. Heitman, Adriaan P. IJzerman · 2017 · Journal of Medicinal Chemistry
30. Discovering new PI3Kα inhibitors with a strategy of combining ligand-based and structure-based virtual screening
    Miao Yu, Qiong Gu, Jun Xu · 2018 · Journal of Computer-Aided Molecular Design
31. Discovery of novel JAK1 inhibitors through combining machine learning, structure-based pharmacophore modeling and bio-evaluation
    Zixiao Wang, Lili Sun, Yu Xu, Peida Liang, Kaiyan Xu, Jing Long Huang · 2023 · Journal of Translational Medicine
32. Identification of 1,3,4-oxadiazoles as tubulin-targeted anticancer agents: a combined field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, molecular dynamics simulation, and density functional theory calculation approach
    Agnidipta Das, Manaswini Sarangi, Kailash Jangid, Vijay Kumar, Amit Kumar, Praval Pratap Singh, Kamalpreet Kaur, Vinod Kumar, Sudip Chakraborty, Vikas Jaitak · 2023 · Journal of Biomolecular Structure and Dynamics
33. HIt Discovery using docking ENriched by GEnerative Modeling (HIDDEN GEM): A novel computational workflow for accelerated virtual screening of ultra‐large chemical libraries
    Konstantin I. Popov, James Wellnitz, Travis Maxfield, Alexander Tropsha · 2023 · Molecular Informatics
34. Docking Score ML: Target-Specific Machine Learning Models Improving Docking-Based Virtual Screening in 155 Targets
    Haihan Liu, Baichun Hu, Peiying Chen, Xiao Wang, Hanxun Wang, Shizun Wang, Jian Wang, Bin Lin, Maosheng Cheng · 2024 · Journal of Chemical Information and Modeling
35. PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening
    Seonghwan Seo, Woo Youn Kim · 2024 · Chemical Science
36. High-Throughput, High-Quality: Benchmarking GNINA and AutoDock Vina for Precision Virtual Screening Workflow
    Rocco Buccheri, Antonio Rescifina · 2025 · Molecules
37. A topological similarity measure for proteins
    Gabriell Máté, Andreas Hofmann, Nicolas Wenzel, Dieter W. Heermann · 2013 · Biochimica et Biophysica Acta (BBA) - Biomembranes
38. MONA 2: A Light Cheminformatics Platform for Interactive Compound Library Processing
    Matthias Hilbig, Matthias Rarey · 2015 · Journal of Chemical Information and Modeling
39. Cosolvent-Based Protein Pharmacophore for Ligand Enrichment in Virtual Screening
    Juan Pablo Arcon, Lucas A. Defelipe, Elias Daniel Lopez, Osvaldo Burastero, Carlos Pablo Modenutti, Xavier Barril, Marcelo Adrian Marti, Adrian Gustavo Turjanski · 2019 · Journal of Chemical Information and Modeling
40. New anticonvulsant candidates prevent P-glycoprotein (P-gp) overexpression in a pharmacoresistant seizure model in mice
    Andrea Enrique, Mauricio Emiliano Di Ianni, Sofía Goicoechea, Alberto Lazarowski, María Guadalupe Valle-Dorado, Juan J. López Costa, Luísa Rocha, Elena Girardi, Alan Talevi · 2019 · Epilepsy & Behavior
41. Crystallographic structure versus homology model: a case study of molecular dynamics simulation of human and zebrafish histone deacetylase 10
    Abdullahi İbrahim Uba, Kemal Yelekçi · 2019 · Journal of Biomolecular Structure and Dynamics
42. SQM/COSMO Scoring Function: Reliable Quantum‐Mechanical Tool for Sampling and Ranking in Structure‐Based Drug Design
    Adam Pecina, Saltuk M. Eyrilmez, Cemal Köprülüoğlu, Vijay Madhav Miriyala, Martin Lepšı́k, Jindřich Fanfrlík, Jan Řezáč, Pavel Hobza · 2020 · ChemPlusChem
43. Potential colchicine binding site inhibitors unraveled by virtual screening, molecular dynamics and MM/PBSA
    Leonardo Bruno Federico, Guilherme Martins Silva, Suzane Quintana Gomes, Isaque Antônio Galindo Francischini, Mariana Pegrucci Barcelos, Cleydson B. R. Santos, Luciano Tavares da Costa, Joaquín M. Campos Rosa, Carlos Henrique Tomich de Paula da Silva · 2021 · Computers in Biology and Medicine
44. Drug repurposing in silico screening platforms
    Jonathan G.L. Mullins · 2022 · Biochemical Society Transactions
45. Improved drug–target interaction prediction with intermolecular graph transformer
    Siyuan Liu, Yusong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie‐Yan Liu, Tong Wang · 2022 · Briefings in Bioinformatics
46. 3-(Adenosylthio)benzoic Acid Derivatives as SARS-CoV-2 Nsp14 Methyltransferase Inhibitors
    Olga Bobiļeva, Raitis Bobrovs, Evelina Elva Sirma, I. Kanepe, Anna L. Bula, Liene Patetko, Anna Ramata‐Stunda, Solveiga Grı̄nberga, Aigars Jirgensons, Kristaps Jaudzems · 2023 · Molecules
47. Discovery of Novel Inhibitors of BRD4 for Treating Prostate Cancer: A Comprehensive Case Study for Considering Water Networks in Virtual Screening and Drug Design
    Haiyang Zhong, Xinyue Wang, Shicheng Chen, Zhe Wang, Huating Wang, Lei Xu, Tingjun Hou, Xiaojun Yao, Dan Li, Peichen Pan · 2023 · Journal of Medicinal Chemistry
48. PL-PatchSurfer2: Improved Local Surface Matching-Based Virtual Screening Method That Is Tolerant to Target and Ligand Structure Variation
    Woong‐Hee Shin, Charles W. Christoffer, Jibo Wang, Daisuke Kihara · 2016 · Journal of Chemical Information and Modeling
49. Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products
    Qi Gao, Yijun Wang, Jiaying Hou, Qizheng Yao, Ji Zhang · 2017 · Journal of Computer-Aided Molecular Design
50. Prediction of the Favorable Hydration Sites in a Protein Binding Pocket and Its Application to Scoring Function Formulation
    Yan Li, Ying-Duo Gao, M. Katharine Holloway, Renxiao Wang · 2020 · Journal of Chemical Information and Modeling
51. MolModa: accessible and secure molecular docking in a web browser
    Yuri Kochnev, Mayar Ahmed, Alex M. Maldonado, Jacob D. Durrant · 2024 · Nucleic Acids Research
52. Protein language models are performant in structure-free virtual screening
    Hilbert Yuen In Lam, Jia Sheng Guan, Xing Er Ong, Robbe Pincket, Yuguang Mu · 2024 · Briefings in Bioinformatics
53. pROC-Chemotype Plots Enhance the Interpretability of Benchmarking Results in Structure-Based Virtual Screening
    Tamer M. Ibrahim, Matthias R. Bauer, Alexander Dörr, Erdem Veyisoglu, Frank M. Boeckler · 2015 · Journal of Chemical Information and Modeling
54. Discovery of Novel Inhibitors of Indoleamine 2,3-Dioxygenase 1 Through Structure-Based Virtual Screening
    Guoqing Zhang, Jing Xing, Yulan Wang, Lihao Wang, Yan Ye, Dong Lu, Jihui Zhao, Xiaomin Luo, Mingyue Zheng, Shiying Yan · 2018 · Frontiers in Pharmacology
55. Importance of a crystalline water network in docking-based virtual screening: a case study of BRD4
    Haiyang Zhong, Zhe Wang, Xuwen Wang, Hui Liu, Dan Li, Huanxiang Liu, Xiaojun Yao, Tingjun Hou · 2019 · Physical Chemistry Chemical Physics
56. Using machine learning to improve ensemble docking for drug discovery
    Tanay Chandak, John P. Mayginnes, Howard Mayes, Chung F. Wong · 2020 · Proteins Structure Function and Bioinformatics
57. Guiding Conventional Protein–Ligand Docking Software with Convolutional Neural Networks
    Huaipan Jiang, Mengran Fan, Jian Wang, Anup Sarma, Shruti Mohanty, Nikolay V. Dokholyan, Mehrdad Mahdavi, Mahmut Kandemir · 2020 · Journal of Chemical Information and Modeling
58. Multi-PLI: interpretable multi‐task deep learning model for unifying protein–ligand interaction datasets
    Fan Hu, Jiaxin Jiang, Dongqi Wang, Muchun Zhu, Peng Yin · 2021 · Journal of Cheminformatics
59. A comprehensive comparative assessment of 3D molecular similarity tools in ligand-based virtual screening
    Zhenla Jiang, Jianrong Xu, Aixia Yan, Ling Wang · 2021 · Briefings in Bioinformatics
60. Evaluation of Docking Machine Learning and Molecular Dynamics Methodologies for DNA-Ligand Systems
    Tiago Alves de Oliveira, Lucas Rolim Medaglia, Eduardo Habib Bechelane Maia, Letícia Cristina de Assis, Paulo Batista de Carvalho, Alisson Marques da Silva, Alex Gutterres Taranto · 2022 · Pharmaceuticals
61. Novel Small-Molecule Inhibitors of the SARS-CoV-2 Spike Protein Binding to Neuropilin 1
    Anja Kolarič, Marko Jukič, Urban Bren · 2022 · Pharmaceuticals
62. Structure-Based Design of a Chemical Probe Set for the 5-HT 5A Serotonin Receptor
    Anat Levit Kaplan, Ryan T. Strachan, João M. Bráz, Veronica Craik, Samuel T. Slocum, Thomas J. Mangano, Vanessa Amabo, Henry R. O’Donnell, Parnian Lak, Allan I. Basbaum et al. · 2022 · Journal of Medicinal Chemistry
63. fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions
    Natalia A. Szulc, Zuzanna Mackiewicz, Janusz Marek Bujnicki, Filip Stefaniak · 2022 · PLoS Computational Biology
64. Cheminformatics-Based Study Identifies Potential Ebola VP40 Inhibitors
    Emmanuel Broni, Carolyn N. Ashley, Joseph Adams, H. Manu, Ebenezer Aikins, Mary Okom, Whelton A. Miller, Michael D. Wilson, Samuel K. Kwofie · 2023 · International Journal of Molecular Sciences
65. Comprehensive in silico analyses of flavonoids elucidating the drug properties against kidney disease by targeting AIM2
    Mahmoud K Kandeel, Muhammad Nasir Iqbal, Iqra Fatima Munawar Ali, Saima Malik, Abbeha Malik, Sheikh Arslan Sehgal · 2023 · PLoS ONE
66. The Application of Artificial Intelligence Accelerates G Protein-Coupled Receptor Ligand Discovery
    Wei Chen, Chi Song, Liang Leng, Sanyin Zhang, Shilin Chen · 2023 · Engineering
67. MONA – Interactive manipulation of molecule collections
    Matthias Hilbig, Sascha Urbaczek, Inken Groth, Stefan Heuser, Matthias Rarey · 2013 · Journal of Cheminformatics
68. Incorporating replacement free energy of binding-site waters in molecular docking
    Hanzi Sun, Lifeng Zhao, Shiming Peng, Niu Huang · 2014 · Proteins Structure Function and Bioinformatics
69. Molecular dynamics to enhance structure-based virtual screening on cathepsin B
    Mitja Ogrizek, Samo Turk, Samo Lešnik, Izidor Sosič, Milan Hodošček, Bojana Mirković, Janko Kos, Dušanka Janežič, Stanislav Gobec, Janez Konc · 2015 · Journal of Computer-Aided Molecular Design
70. Ensemble-Based Virtual Screening Led to the Discovery of New Classes of Potent Tyrosinase Inhibitors
    Joonhyeok Choi, Kwang-Eun Choi, Sung Jean Park, Sun Yeou Kim, Jun‐Goo Jee · 2016 · Journal of Chemical Information and Modeling
71. Combined in silico approaches for the identification of novel inhibitors of human islet amyloid polypeptide (hIAPP) fibrillation
    Palak N. Patel, Krupali Parmar, Vivek Kumar Vyas, Dhaval Patel, Mili Das · 2017 · Journal of Molecular Graphics and Modelling
72. PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications
    Divya B. Korlepara, C. S. Vasavi, Shruti Jeurkar, Pradeep Kumar Pal, Subhajit Roy, Sarvesh Mehta, Shubham Sharma, Vishal Kumar, Charuvaka Muvva, Bhuvanesh Sridharan et al. · 2022 · Scientific Data
73. GraphGANFed: A Federated Generative Framework for Graph-Structured Molecules Towards Efficient Drug Discovery
    Daniel Manu, Jingjing Yao, Wuji Liu, Xiang Sun · 2024 · IEEE Transactions on Computational Biology and Bioinformatics
74. Prospective virtual screening combined with bio-molecular simulation enabled identification of new inhibitors for the KRAS drug target
    Amar Ajmal, Hind Ali Alkhatabi, Roaa M. Alreemi, Mubarak A. Alamri, Asaad Khalid, Ashraf N. Abdalla, Bader Saud Alotaibi, Abdul Wadood · 2024 · BMC Chemistry
75. Conformational Space Profiling Enhances Generic Molecular Representation for AI‐Powered Ligand‐Based Drug Discovery
    Lin Wang, Shihang Wang, Hao Yang, Shiwei Li, Xinyu Wang, Yongqi Zhou, Siyuan Tian, Lu Liu, Fang Bai · 2024 · Advanced Science
76. Leveraging artificial intelligence and machine learning in kinase inhibitor development: advances, challenges, and future prospects
    Mohamed Saleh Elgawish, Aya M. Almatary, Sawsan A. Zaitone, Mohamed S. H. Salem · 2025 · RSC Medicinal Chemistry
77. Improving Docking Performance Using Negative Image-Based Rescoring
    Sami T. Kurkinen, Sanna P. Niinivehmas, Mira Ahinko, Sakari Lätti, Olli T. Pentikäinen, Pekka A. Postila · 2018 · Frontiers in Pharmacology
78. Recent Trends and Applications of Molecular Modeling in GPCR–Ligand Recognition and Structure-Based Drug Design
    Xiaojing Yuan, Yechun Xu · 2018 · International Journal of Molecular Sciences
79. Natural phosphodiesterase 5 (PDE5) inhibitors: a computational approach
    Alberto Ongaro, Giuseppe Zagotto, Maurizio Memo, Alessandra Gianoncelli, Giovanni Ribaudo · 2019 · Natural Product Research
80. PyRod: Tracing Water Molecules in Molecular Dynamics Simulations
    David Schaller, Szymon Pach, Gerhard Wolber · 2019 · Journal of Chemical Information and Modeling
81. CompScore: Boosting Structure-Based Virtual Screening Performance by Incorporating Docking Scoring Function Components into Consensus Scoring
    Yunierkis Pérez‐Castillo, Stellamaris Sotomayor-Burneo, Karina Jimenes-Vargas, Mario González, Maykel Cruz‐Monteagudo, Vinicio Armijos‐Jaramillo, M. Natália D. S. Cordeiro, Fernanda Borges, Aminael Sánchez‐Rodríguez, Eduardo Tejera · 2019 · Journal of Chemical Information and Modeling
82. Assessing and improving the performance of consensus docking strategies using the DockBox package
    Jordane Preto, Francesco Gentile · 2019 · Journal of Computer-Aided Molecular Design
83. Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM, pharmacophore and docking model
    Jingwei Liang, Mingyang Wang, Shan Wang, Shilong Li, Wanqiu Li, Fan‐hao Meng · 2019 · Journal of Enzyme Inhibition and Medicinal Chemistry
84. Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations
    Павел Геннадьевич Полищук, Alina Kutlushina, Dayana Bashirova, Olena Mokshyna, Timur Madzhidov · 2019 · International Journal of Molecular Sciences
85. AutoPH4: An Automated Method for Generating Pharmacophore Models from Protein Binding Pockets
    Siduo Jiang, Miklós Fehér, Chris Williams, Brian Cole, David Elliot Shaw · 2020 · Journal of Chemical Information and Modeling
86. Targeting SARS‐CoV‐2 Spike Protein/ACE2 Protein‐Protein Interactions: a Computational Study
    Davide Pirolli, Benedetta Righino, Maria Cristina De Rosa · 2021 · Molecular Informatics
87. dockECR: Open consensus docking and ranking protocol for virtual screening of small molecules
    Rodrigo Ochoa, Karen Palacio‐Rodríguez, Camila Mara Clemente, Natalia S. Adler · 2021 · Journal of Molecular Graphics and Modelling
88. The Inhibitors of CDK4/6 from a Library of Marine Compound Database: A Pharmacophore, ADMET, Molecular Docking and Molecular Dynamics Study
    Lianxiang Luo, Wang Qu, Yinglin Liao · 2022 · Marine Drugs
89. Applications of machine learning in computer-aided drug discovery
    SM Bargeen Alam Turzo, Eric R. Hantz, Steffen Lindert · 2022 · QRB Discovery
90. DENVIS: Scalable and High-Throughput Virtual Screening Using Graph Neural Networks with Atomic and Surface Protein Pocket Features
    Agamemnon Krasoulis, Nick Antonopoulos, Vassilis Pitsikalis, Stavros Theodorakis · 2022 · Journal of Chemical Information and Modeling
91. DNMG: Deep molecular generative model by fusion of 3D information for de novo drug design
    Tao Song, Yongqi Ren, Shuang Wang, Peifu Han, Lulu Wang, Xue Li, Alfonso Rodríguez‐Patón · 2023 · Methods
92. Comparative Modeling and Benchmarking Data Sets for Human Histone Deacetylases and Sirtuin Families
    Jie Xia, Ermias Lemma Tilahun, Eyob Hailu Kebede, Terry-Elinor R. Reid, Liangren Zhang, Xiang Simon Wang · 2015 · Journal of Chemical Information and Modeling
93. A rotation-translation invariant molecular descriptor of partial charges and its use in ligand-based virtual screening
    Francois Berenger, Arnout R. D. Voet, Xiao Yin Lee, Kam Y. J. Zhang · 2014 · Journal of Cheminformatics
94. Identification of potential Gly/NMDA receptor antagonists by cheminformatics approach: a combination of pharmacophore modelling, virtual screening and molecular docking studies
    Vinod G. Ugale, Sanjay B. Bari · 2016 · SAR and QSAR in environmental research
95. Protein–Ligand Informatics Force Field (PLIff): Toward a Fully Knowledge Driven “Force Field” for Biomolecular Interactions
    Marcel L. Verdonk, R. Frederick Ludlow, Ilenia Giangreco, Prakash Chandra Rathi · 2016 · Journal of Medicinal Chemistry
96. Extensive Reliability Evaluation of Docking-Based Target-Fishing Strategies
    Margherita Lapillo, Tiziano Tuccinardi, Adriano Martinelli, Marco Macchia, Antonio Giordano, Giulio Poli · 2019 · International Journal of Molecular Sciences
97. ProBiS-Dock Database: A Web Server and Interactive Web Repository of Small Ligand–Protein Binding Sites for Drug Design
    Janez Konc, Samo Lešnik, Blaž Škrlj, Dušanka Janežič · 2021 · Journal of Chemical Information and Modeling
98. Discovery of novel CDK2 inhibitors for cancer treatment: integrating ligand-based pharmacophore modelling, molecular docking, DFT, ADMET, and molecular dynamics simulation studies
    Bharath Kumar Chagaleti, Venkatesan Saravanan, M. K. Kathiravan · 2024 · Beni-Suef University Journal of Basic and Applied Sciences
99. Integrating machine learning driven virtual screening and molecular dynamics simulations to identify potential inhibitors targeting PARP1 against prostate cancer
    Fahad M. Aldakheel, Shatha Ahmed Alduraywish, Khaled H. Dabwan · 2025 · Scientific Reports
100. Protein ligand interaction analysis against new CaMKK2 inhibitors by use of X-ray crystallography and the fragment molecular orbital (FMO) method
     Daisuke Takaya, Hideaki Niwa, Junko Mikuni, Kana Nakamura, Noriko Handa, Akiko Tanaka, Shigeyuki Yokoyama, Teruki Honma · 2020 · Journal of Molecular Graphics and Modelling