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

Cited by (1,002)

Items 401–500 of 1,002

1. iDrug: a web-accessible and interactive drug discovery and design platform
   Xia Wang, Haipeng Chen, Feng Yang, Jiayu Gong, Shiliang Li, Jianfeng Pei, Xiaofeng Liu, Hualiang Jiang, Luhua Lai, Honglin Li · 2014 · Journal of Cheminformatics
2. Discovery of a novel NEDD8 Activating Enzyme Inhibitor with Piperidin-4-amine Scaffold by Structure-Based Virtual Screening
   Peng Zhi Lu, Xiaoxin Liu, Xinrui Yuan, Minfang He, Yubin Wang, Qi Zhang, Pingkai Ouyang · 2016 · ACS Chemical Biology
3. Docking-based virtual screening of TβR1 inhibitors: evaluation of pose prediction and scoring functions
   Shuai Wang, Junhao Jiang, Ruo-Yu Li, Ping Deng · 2020 · BMC Chemistry
4. In vitro and in silico studies on the structural and biochemical insight of anti-biofilm activity of andrograpanin from Andrographis paniculata against Pseudomonas aeruginosa
   Moumita Majumdar, Amit Dubey, Ritobrata Goswami, Tarun Kumar Misra, Dijendra Nath Roy · 2020 · World Journal of Microbiology and Biotechnology
5. Discovery of SARS-CoV-2 Nsp14 and Nsp16 Methyltransferase Inhibitors by High-Throughput Virtual Screening
   Raitis Bobrovs, I. Kanepe, Nauris Narvaiss, Liene Patetko, G. Kalnins, M. Sisovs, Anna L. Bula, Solveiga Grı̄nberga, Mārtiņs Borodušķis, Anna Ramata‐Stunda et al. · 2021 · Pharmaceuticals
6. Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors
   Tânia F. G. G. Cova, Carla Vitorino, Márcio Ferreira, Sandra C. C. Nunes, Paola Rondón-Villarreal, Alberto A. C. C. Pais · 2021 · Methods in molecular biology
7. Computer-Aided Drug Design towards New Psychotropic and Neurological Drugs
   Georgia Dorahy, Zheng Chen, Thomas Balle · 2023 · Molecules
8. Consensus holistic virtual screening for drug discovery: a novel machine learning model approach
   Said Moshawih, Zhen Hui Bu, Hui Poh Goh, Nurolaini Kifli, Lam Hong Lee, Khang Wen Goh, Long Chiau Ming · 2024 · Journal of Cheminformatics
9. Analogues of ethionamide, a drug used for multidrug-resistant tuberculosis, exhibit potent inhibition of tyrosinase
   Joonhyeok Choi, Sung‐Jean Park, Jun‐Goo Jee · 2015 · European Journal of Medicinal Chemistry
10. Structural Properties of Non-Traditional Drug Targets Present New Challenges for Virtual Screening
    Ragul Gowthaman, Eric J. Deeds, John Karanicolas · 2013 · Journal of Chemical Information and Modeling
11. PoLi : A Virtual Screening Pipeline Based on Template Pocket and Ligand Similarity
    Ambrish Roy, Bharath Srinivasan, Jeffrey Skolnick · 2015 · Journal of Chemical Information and Modeling
12. Inexpensive Method for Selecting Receptor Structures for Virtual Screening
    Zunnan Huang, Chung F. Wong · 2015 · Journal of Chemical Information and Modeling
13. Discovery of a Potential HER2 Inhibitor from Natural Products for the Treatment of HER2-Positive Breast Cancer
    Jianzong Li, Haiyang Wang, Junjie Li, Jinku Bao, Chuanfang Wu · 2016 · International Journal of Molecular Sciences
14. Distributed Representation of Chemical Fragments
    Suman Chakravarti · 2018 · ACS Omega
15. Identification of a Novel Protein Arginine Methyltransferase 5 Inhibitor in Non-small Cell Lung Cancer by Structure-Based Virtual Screening
    Qianqian Wang, Jiahui Xu, Ying Li, Jumin Huang, Zebo Jiang, Yuwei Wang, Liang Liu, Elaine Lai‐Han Leung, Xiaojun Yao · 2018 · Frontiers in Pharmacology
16. Prediction of Compound Profiling Matrices Using Machine Learning
    Raquel Rodríguez-Pérez, Tomoyuki Miyao, Swarit Jasial, Martin Vogt, Jürgen Bajorath · 2018 · ACS Omega
17. Structure-based screening for discovery of sweet compounds
    Yaron Ben Shoshan-Galeczki, Masha Y. Niv · 2020 · Food Chemistry
18. Decoding the protein–ligand interactions using parallel graph neural networks
    Carter R. Knutson, Mridula Bontha, Jenna A. Bilbrey, Neeraj Kumar · 2022 · Scientific Reports
19. Drug discovery and development in the era of artificial intelligence: From machine learning to large language models
    Shenghui Guan, Guanyu Wang · 2024 · Artificial Intelligence Chemistry
20. Ultrafast protein structure-based virtual screening with Panther
    Sanna P. Niinivehmas, Kari Salokas, Sakari Lätti, Hannu Raunio, Olli T. Pentikäinen · 2015 · Journal of Computer-Aided Molecular Design
21. Structure-Guided Screening for Functionally Selective D2 Dopamine Receptor Ligands from a Virtual Chemical Library
    Barbara Männel, Mariama Jaiteh, Alexey A. Zeifman, Alena Randáková, Dorothée Weikert, Harald Hübner, Peter Gmeiner, Jens Carlsson · 2017 · ACS Chemical Biology
22. Multiple Virtual Screening Strategies for the Discovery of Novel Compounds Active Against Dengue Virus: A Hit Identification Study
    Kowit Hengphasatporn, Arthur Garon, Peter Wolschann, Thierry Langer, Yasuteru Shigeta, Thao Nguyen Thanh Huynh, Warinthorn Chavasiri, Thanaphon Saelee, Siwaporn Boonyasuppayakorn, Thanyada Rungrotmongkol · 2019 · Scientia Pharmaceutica
23. Machine learning and ligand binding predictions: A review of data, methods, and obstacles
    Sally R. Ellingson, Brian Davis, Jonathan Allen · 2020 · Biochimica et Biophysica Acta (BBA) - General Subjects
24. Identification of New Potential Inhibitors of Quorum Sensing through a Specialized Multi-Level Computational Approach
    Fábio G. Martins, André Melo, Sérgio Filipe Sousa · 2021 · Molecules
25. CAVIAR: a method for automatic cavity detection, description and decomposition into subcavities
    Jean‐Rémy Marchand, Bernard Pirard, Peter Ertl, Finton Sirockin · 2021 · Journal of Computer-Aided Molecular Design
26. Virtual screening of dipeptidyl peptidase-4 inhibitors using quantitative structure–activity relationship-based artificial intelligence and molecular docking of hit compounds
    Oky Hermansyah, Alhadi Bustamam, Arry Yanuar · 2021 · Computational Biology and Chemistry
27. Estimating the Similarity between Protein Pockets
    Merveille Eguida, Didier Rognan · 2022 · International Journal of Molecular Sciences
28. Systematic Investigation of Docking Failures in Large-Scale Structure-Based Virtual Screening
    Xu Min, Cheng Shen, Jincai Yang, Qing Wang, Niu Huang · 2022 · ACS Omega
29. Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science
    Ifra Saifi, Basharat Ahmad Bhat, Syed Suhail Hamdani, Umar Yousuf Bhat, Carlos Alberto Lobato-Tapia, Mushtaq Ahmad Mir, Tanvir Ul Hasan Dar, Showkat Ahmad Ganie · 2023 · Journal of Biomolecular Structure and Dynamics
30. eFindSite: Enhanced Fingerprint‐Based Virtual Screening Against Predicted Ligand Binding Sites in Protein Models
    Wei Pan Feinstein, Michał Bryliński · 2014 · Molecular Informatics
31. Modelling ligand selectivity of serine proteases using integrative proteochemometric approaches improves model performance and allows the multi-target dependent interpretation of features
    Qurrat Ul Ain, Oscar Méndez‐Lucio, Isidro Cortés‐Ciriano, Thérèse E. Malliavin, Gerard J. P. van Westen, Andreas Bender · 2014 · Integrative Biology
32. GPCR-Bench: A Benchmarking Set and Practitioners’ Guide for G Protein-Coupled Receptor Docking
    Dahlia R. Weiss, Andrea Bortolato, Benjamin Gerald Tehan, Jonathan S. Mason · 2016 · Journal of Chemical Information and Modeling
33. Molecular Docking for Predictive Toxicology
    Daniela Trisciuzzi, Domenico Alberga, Francesco Leonetti, Ettore Novellino, Orazio Nicolotti, Giuseppe Felice Mangiatordi · 2018 · Methods in molecular biology
34. Virtual Screening Meets Deep Learning
    Javier Pérez-Sianes, Horacio Pérez‐Sánchez, Fernando Díaz · 2018 · Current Computer - Aided Drug Design
35. All in One: Cavity Detection, Druggability Estimate, Cavity-Based Pharmacophore Perception, and Virtual Screening
    Viet‐Khoa Tran‐Nguyen, Franck Da Silva, Guillaume Bret, Didier Rognan · 2018 · Journal of Chemical Information and Modeling
36. Anticancer compound XL765 as PI3K/mTOR dual inhibitor: A structural insight into the inhibitory mechanism using computational approaches
    Mohd Rehan · 2019 · PLoS ONE
37. Electrostatic-field and surface-shape similarity for virtual screening and pose prediction
    Ann E. Cleves, Stephen R. Johnson, Ajay N. Jain · 2019 · Journal of Computer-Aided Molecular Design
38. Ligand- and Structure-Based Virtual Screening in Drug Discovery
    Shome Sankar Bhunia, Mridula Saxena, Anil Kumar Saxena · 2021 · Topics in medicinal chemistry
39. Inhibiting a promiscuous GPCR: iterative discovery of bitter taste receptor ligands
    Fierro, Fabrizio, Peri, Lior, Hübner, Harald, Tabor-Schkade, Alina, Waterloo, Lukas, Löber, Stefan, Pfeiffer, Tara, Weikert, Dorothee, Dingjan, Tamir, Margulis, Eitan et al. · 2023 · Cellular and Molecular Life Sciences
40. Large-Scale Ligand Perturbations of the Protein Conformational Landscape Reveal State-Specific Interaction Hotspots
    Timothy R. Stachowski, Marcus M. Fischer · 2022 · Journal of Medicinal Chemistry
41. DeepBindGCN: Integrating Molecular Vector Representation with Graph Convolutional Neural Networks for Protein–Ligand Interaction Prediction
    Haiping Zhang, Konda Mani Saravanan, John Z. H. Zhang · 2023 · Molecules
42. Cobdock: an accurate and practical machine learning-based consensus blind docking method
    Sadettin Y. Ugurlu, David McDonald, Huangshu John Lei, Alan M. Jones, Shu Li, Henry Y. Tong, Mark S. Butler, Shan He · 2024 · Journal of Cheminformatics
43. Multiple Structures for Virtual Ligand Screening: Defining Binding Site Properties-Based Criteria to Optimize the Selection of the Query
    Nesrine Ben Nasr, Hélène Guillemain, Nathalie Lagarde, Jean‐François Zagury, Matthieu Montès · 2013 · Journal of Chemical Information and Modeling
44. In Silico Prediction of Human Sulfotransferase 1E1 Activity Guided by Pharmacophores from Molecular Dynamics Simulations
    Christin Rakers, Fabian Schumacher, Walter Meinl, Hansruedi R. Glatt, Burkhard Kleuser, Gerhard Wolber · 2015 · Journal of Biological Chemistry
45. RADER: a RApid DEcoy Retriever to facilitate decoy based assessment of virtual screening
    Ling Wang, Xiaoqian Pang, Yecheng Li, Ziying Zhang, Wen Tan · 2016 · Bioinformatics
46. The scoring bias in reverse docking and the score normalization strategy to improve success rate of target fishing
    Qiyao Luo, Liang Zhao, Jianxing Hu, Hongwei Jin, Zhenming Liu, Liangren Zhang · 2017 · PLoS ONE
47. PyPLIF HIPPOS: A Molecular Interaction Fingerprinting Tool for Docking Results of AutoDock Vina and PLANTS
    Enade Perdana Istyastono, Muhammad Radifar, Nunung Yuniarti, Vivitri Dewi Prasasty, Sudi Mungkasi · 2020 · Journal of Chemical Information and Modeling
48. Discovery of Novel Hsp90 C-Terminal Inhibitors Using 3D-Pharmacophores Derived from Molecular Dynamics Simulations
    Tihomir Tomašič, Martina Durcik, Bradley M. Keegan, Darja Gramec Skledar, Živa Zajec, Brian S. J. Blagg, Sharon D. Bryant · 2020 · International Journal of Molecular Sciences
49. Computational Identification of Potential Anti-Inflammatory Natural Compounds Targeting the p38 Mitogen-Activated Protein Kinase (MAPK): Implications for COVID-19-Induced Cytokine Storm
    Seth O. Asiedu, Samuel K. Kwofie, Emmanuel Broni, Michael D. Wilson · 2021 · Biomolecules
50. Small-Molecule Allosteric Modulators of the Protein Kinase PDK1 from Structure-Based Docking
    T.J. Rettenmaier, Hao Fan, Joel D. Karpiak, Allison K. Doak, Andrej Šali, Brian K. Shoichet, James A. Wells · 2015 · Journal of Medicinal Chemistry
51. Predictive Structure-Based Toxicology Approaches To Assess the Androgenic Potential of Chemicals
    Daniela Trisciuzzi, Domenico Alberga, Kamel Mansouri, Richard Judson, Ettore Novellino, Giuseppe Felice Mangiatordi, Orazio Nicolotti · 2017 · Journal of Chemical Information and Modeling
52. FRAGSITE: A Fragment-Based Approach for Virtual Ligand Screening
    Zhou, Hongyi, Cao, Hongnan, Skolnick, Jeffrey · 2021 · Journal of Chemical Information and Modeling
53. Consensus docking and MM-PBSA computations identify putative furin protease inhibitors for developing potential therapeutics against COVID-19
    Bismark Dankwa, Emmanuel Broni, Kweku S. Enninful, Samuel K. Kwofie, Michael D. Wilson · 2022 · Structural Chemistry
54. Benchmarking compound activity prediction for real-world drug discovery applications
    2024
55. An in silico molecular docking and simulation study to identify potential anticancer phytochemicals targeting the RAS signaling pathway
    Mahir Azmal, Jibon Kumar Paul, Fatema Sultana Prima, Omar Faruk Talukder, Ajit Ghosh · 2024 · PLoS ONE
56. Pharmacophore modeling and in silico toxicity assessment of potential anticancer agents from African medicinal plants
    Fidele Ntie‐Kang, Conrad Veranso Simoben, Berin Karaman, Valery Fuh Ngwa, Philip Neville Judson, Wolfgang Sippl, Luc Mbaze Meva’à · 2016 · Drug Design Development and Therapy
57. Reliability of Docking-Based Virtual Screening for GPCR Ligands with Homology Modeled Structures: A Case Study of the Angiotensin II Type I Receptor
    Haiyi Chen, Weitao Fu, Zhe Wang, Xuwen Wang, Tailong Lei, Feng Zhu, Dan Li, Shan Chang, Lei Xu, Tingjun Hou · 2018 · ACS Chemical Neuroscience
58. Identification and antitumor activity of a novel inhibitor of the NIMA-related kinase NEK6
    Marta De Donato, Benedetta Righino, Flavia Filippetti, Alessandra Battaglia, Marco Petrillo, Davide Pirolli, Giovanni Scambia, Maria Cristina De Rosa, Daniela Gallo · 2018 · Scientific Reports
59. Evaluation of Cross-Validation Strategies in Sequence-Based Binding Prediction Using Deep Learning
    Angela Lopez-del Rio, Alfons Nonell‐Canals, David Vidal, Alexandre Perera-Lluna · 2019 · Journal of Chemical Information and Modeling
60. Development of Predictive Models for Identifying Potential S100A9 Inhibitors Based on Machine Learning Methods
    Jihyeun Lee, Surendra Kumar, Sangyoon Lee, Sung Jean Park, Mi‐Hyun Kim · 2019 · Frontiers in Chemistry
61. Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?
    Jon Kapla, Ismael Rodríguez‐Espigares, Flavio Ballante, Jana Selent, Jens Carlsson · 2021 · PLoS Computational Biology
62. A high quality, industrial data set for binding affinity prediction: performance comparison in different early drug discovery scenarios
    Andreas Tosstorff, Markus Georg Rudolph, Jason C. Cole, Michael Reutlinger, Christian Krämer, Hervé Schaffhauser, Agnès Nilly, Alexander Flohr, Bernd Kuhn · 2022 · Journal of Computer-Aided Molecular Design
63. AI-accelerated protein-ligand docking for SARS-CoV-2 is 100-fold faster with no significant change in detection
    Austin Clyde, Xuefeng Liu, Thomas Scott Brettin, Hyunseung Yoo, Alexander Partin, Yadu Babuji, Ben J. Blaiszik, Jamaludin Mohd-Yusof, André Merzky, Matteo Turilli et al. · 2023 · Scientific Reports
64. In Silico Discovery of a Substituted 6-Methoxy-quinaldine with Leishmanicidal Activity in Leishmania infantum
    Strahinja Stevanović, Andrej Perdih, Milan Senćanski, Sanja Glišić, Margarida Duarte, Ana M. Tomás, Filipa Sena, Filipe Maximiano Sousa, Manuela M. Pereira, Tom Šolmajer · 2018 · Molecules
65. Structure-kinetics relationships of Capadenoson derivatives as adenosine A 1 receptor agonists
    Julien Louvel, Dong Ming Guo, Marjolein Soethoudt, Tamara A. M. Mocking, Eelke Bart Lenselink, Thea Mulder‐Krieger, Laura H. Heitman, Adriaan P. IJzerman · 2015 · European Journal of Medicinal Chemistry
66. Energy penalties enhance flexible receptor docking in a model cavity
    Kamenik, Anna S., Singh, Isha, Lak, Parnian, Balius, Trent E., Liedl, Klaus R., Shoichet, Brian K. · 2021 · Proceedings of the National Academy of Sciences
67. Structural interaction fingerprints and machine learning for predicting and explaining binding of small molecule ligands to RNA
    Natalia A. Szulc, Zuzanna Mackiewicz, Janusz Marek Bujnicki, Filip Stefaniak · 2023 · Briefings in Bioinformatics
68. A Multimodal Protein Representation Framework for Quantifying Transferability Across Biochemical Downstream Tasks
    Fan Hu, Yishen Hu, Weihong Zhang, Huazhen Huang, Yi Feng Pan, Peng Yin · 2023 · Advanced Science
69. Advances in machine intelligence‐driven virtual screening approaches for big‐data
    Neeraj Kumar, Vishal Acharya · 2023 · Medicinal Research Reviews
70. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods
    Regina Politi, Ivan Rusyn, Alexander Tropsha · 2014 · Toxicology and Applied Pharmacology
71. Systemic QSAR and phenotypic virtual screening: chasing butterflies in drug discovery
    Maykel Cruz‐Monteagudo, Stephan C. Schürer, Eduardo Tejera, Yunierkis Pérez‐Castillo, José L. Medina‐Franco, Aminael Sánchez‐Rodríguez, Fernanda Borges · 2017 · Drug Discovery Today
72. WebMolCS: A Web-Based Interface for Visualizing Molecules in Three-Dimensional Chemical Spaces
    Mahendra Awale, Daniel Probst, Jean‐Louis Reymond · 2017 · Journal of Chemical Information and Modeling
73. Identification of a Novel Class of BRD4 Inhibitors by Computational Screening and Binding Simulations
    Bryce K. Allen, Saurabh Mehta, S.W. Ember, Jin-Yi Zhu, E. Schönbrunn, Nagi G. Ayad, Stephan C. Schürer · 2017 · ACS Omega
74. Chaos-embedded particle swarm optimization approach for protein-ligand docking and virtual screening
    Hio Kuan Tai, Siti Azma Jusoh, Shirley W. I. Siu · 2018 · Journal of Cheminformatics
75. Discovery of Novel IDH1 Inhibitor Through Comparative Structure-Based Virtual Screening
    Yuwei Wang, Shuai Tang, Huanling Lai, Ruyi Jin, Long Xu, Na Li, Yuping Tang, Hui Guo, Xiaojun Yao, Elaine Lai‐Han Leung · 2020 · Frontiers in Pharmacology
76. Trends in Deep Learning for Property-driven Drug Design
    Jannis Born, Matteo Manica · 2021 · Current Medicinal Chemistry
77. Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy
    Yu-jie Wu, C. Brooks · 2021 · Journal of Chemical Information and Modeling
78. Shape‐based virtual screening with volumetric aligned molecular shapes
    David Ryan Koes, Carlos Jaime Camacho · 2014 · Journal of Computational Chemistry
79. A Binding Mode Hypothesis of Tiagabine Confirms Liothyronine Effect on γ-Aminobutyric Acid Transporter 1 (GAT1)
    Andreas Jurik, Barbara Zdrazil, Marion Holy, Thomas Stockner, Harald H. Sitte, Gerhard Franz Ecker · 2015 · Journal of Medicinal Chemistry
80. Cascade Ligand- and Structure-Based Virtual Screening to Identify New Trypanocidal Compounds Inhibiting Putrescine Uptake
    Lucas N. Alberca, María Laura Sbaraglini, Juan Francisco Morales, Roque Carlos Dietrich, María D. Ruiz, Agustina M. Pino-Martinez, Cristian Miranda, Laura Fraccaroli, Catalina D. Alba Soto, Carolina Carrillo et al. · 2018 · Frontiers in Cellular and Infection Microbiology
81. Discovery of small molecular inhibitors for interleukin-33/ST2 protein–protein interaction: a virtual screening, molecular dynamics simulations and binding free energy calculations
    Tan Thanh Mai, Phuc Gia Nguyen, Minh-Tri Le, Thanh‐Dao Tran, Phuong Nguyen Hoai Huynh, Dieu-Thuong Thi Trinh, Quoc‐Thai Nguyen, Khac‐Minh Thai · 2022 · Molecular Diversity
82. A survey of the recent trends in deep learning for literature based discovery in the biomedical domain
    Eugenio Cesario, Carmela Comito, Ester Zumpano · 2023 · Neurocomputing
83. Natural Language Processing Methods for the Study of Protein–Ligand Interactions
    James Michels, Ramya Bandarupalli, Amin Ahangar Akbari, Thai Le, Hong Yu Xiao, Jing Li, Erik F. Y. Hom · 2025 · Journal of Chemical Information and Modeling
84. Fast Identification of Novel Lymphoid Tyrosine Phosphatase Inhibitors Using Target–Ligand Interaction-Based Virtual Screening
    Xuben Hou, Rong Li, Kangshuai Li, Xiao Yu, Jin‐Peng Sun, Hao Fang · 2014 · Journal of Medicinal Chemistry
85. Lessons Learned over Four Benchmark Exercises from the Community Structure–Activity Resource
    Heather A. Carlson · 2016 · Journal of Chemical Information and Modeling
86. An integrated approach towards the discovery of novel non-nucleoside Leishmania major pteridine reductase 1 inhibitors
    Franco Henrique Andrade Leite, Thamires Quadros Froes, Suellen Gonçalves da Silva, Evandro Italo Macêdo de Souza, Drielli Gomes Vital, Gustavo Henrique Goulart Trossini, Samuel Silva da Rocha Pita, Marcelo S. Castilho · 2017 · European Journal of Medicinal Chemistry
87. Chiral Derivatives of Xanthones: Investigation of the Effect of Enantioselectivity on Inhibition of Cyclooxygenases (COX-1 and COX-2) and Binding Interaction with Human Serum Albumin
    Carla Fernandes, Andreia Palmeira, Inês I. Ramos, Carlos Carneiro, Carlos Afonso, Maria Elizabeth Tiritan, Honorina M. Cidade, Paula C.A.G. Pinto, Maria Lúcia M. F. S. Saraiva, Salette Reis et al. · 2017 · Pharmaceuticals
88. Integrated In Silico Fragment-Based Drug Design: Case Study with Allosteric Modulators on Metabotropic Glutamate Receptor 5
    Yuemin Bian, Zhiwei Feng, Peng Yang, Xiang‐Qun Xie · 2017 · The AAPS Journal
89. SCRAMBLE’N’GAMBLE: a tool for fast and facile generation of random data for statistical evaluation of QSAR models
    Piotr F. J. Lipiński, Przemysław Szurmak · 2017 · Chemical Papers
90. Design, synthesis, and biological evaluation of novel combretastatin A-4 thio derivatives as microtubule targeting agents
    Tomasz Stefański, Renata Mikstacka, Rafał Kurczab, Zbigniew Dutkiewicz, Małgorzata Kucińska, Marek Murias, Małgorzata Zielińska‐Przyjemska, Michał Cichocki, Anna Teubert, Mariusz Kaczmarek et al. · 2017 · European Journal of Medicinal Chemistry
91. A computer-assisted discovery of novel potential anti-obesity compounds as selective carbonic anhydrase VA inhibitors
    Giosuè Costa, Fabrizio Carta, Francesca Alessandra Ambrosio, Anna Artese, Francesco Ortuso, Federica Moraca, Roberta Rocca, Isabella Romeo, Antonio Lupia, Annalisa Maruca et al. · 2019 · European Journal of Medicinal Chemistry
92. Innovative Three-Step Microwave-Promoted Synthesis of N-Propargyltetrahydroquinoline and 1,2,3-Triazole Derivatives as a Potential Factor Xa (FXa) Inhibitors: Drug Design, Synthesis, and Biological Evaluation
    F. Santana-Romo, Carlos F. Lagos, Yorley Duarte, Francisco Castillo, Y. Moglie, M. Maestro, Nitin Charbe, Flavia C. Zacconi · 2020 · Molecules
93. Docking-based identification of small-molecule binding sites at protein-protein interfaces
    Mireia Rosell, Juan Fernández‐Recio · 2020 · Computational and Structural Biotechnology Journal
94. Multiple machine learning, molecular docking, and ADMET screening approach for identification of selective inhibitors of CYP1B1
    Baddipadige Raju, Himanshu Verma, Gera Narendra, Bharti Sapra, Om Silakari · 2021 · Journal of Biomolecular Structure and Dynamics
95. TocoDecoy: A New Approach to Design Unbiased Datasets for Training and Benchmarking Machine-Learning Scoring Functions
    Xujun Zhang, Chao Shen, Ben Liao, Dejun Jiang, Jike Wang, Zhenxing Wu, Hongyan Du, Tianyue Wang, Wenbo Huo, Lei Xu et al. · 2022 · Journal of Medicinal Chemistry
96. Molecular Modeling of the 3D Structure of 5-HT 1A R: Discovery of Novel 5-HT 1A R Agonists via Dynamic Pharmacophore-Based Virtual Screening
    Lili Xu, Shanglin Zhou, Kunqian Yu, Bo Gao, Hualiang Jiang, Xuechu Zhen, Wei Fu · 2013 · Journal of Chemical Information and Modeling
97. Identification of Novel Disruptor of Telomeric Silencing 1-like (DOT1L) Inhibitors through Structure-Based Virtual Screening and Biological Assays
    Shijie Chen, Linjuan Li, Yantao Chen, Junchi Hu, Jingqiu Liu, Julie Yu-Chih Liu, Rongfeng Liu, Yuanyuan Zhang, Fanwang Meng, Kongkai Zhu et al. · 2016 · Journal of Chemical Information and Modeling
98. MILCDock: Machine Learning Enhanced Consensus Docking for Virtual Screening in Drug Discovery
    Connor J. Morris, Jacob A. Stern, Brenden Stark, Max Christopherson, Dennis Della Corte · 2022 · Journal of Chemical Information and Modeling
99. AutoDock-SS: AutoDock for Multiconformational Ligand-Based Virtual Screening
    Boyang Ni, Haoying Wang, Huda Khalaf, Vincent Blay, Douglas R. Houston · 2024 · Journal of Chemical Information and Modeling
100. Discovery of neuroprotective compounds by machine learning approaches
     Fang, Jiansong, Pang, Xiaocong, Yan, Rong, Lian, Wenwen, Li, Chao, Wang, Qi, Liu, Ai-Lin, Du, Guan-Hua · 2016 · RSC Advances