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

Cited by (1,002)

Items 801–900 of 1,002

1. Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning
   Shōgo Nakamura, Nobuaki Yasuo, Masakazu Sekijima · 2025 · Communications Chemistry
2. FeatureDock for protein-ligand docking guided by physicochemical feature-based local environment learning using transformer
   Mingyi Xue, Bojun Liu, Siqin Cao, Xuhui Huang · 2025 · npj Drug Discovery.
3. Pharmacophore modeling improves virtual screening for novel peroxisome proliferator-activated receptor-gamma ligands
   Stephanie N. Lewis, Zulma Garcia, Raquel Hontecillas, Josep Bassaganya-Riera, David R. Bevan · 2015 · Journal of Computer-Aided Molecular Design
4. Receptor pharmacophore ensemble (REPHARMBLE): a probabilistic pharmacophore modeling approach using multiple protein-ligand complexes
   Sivakumar Prasanth Kumar · 2018 · Journal of Molecular Modeling
5. Potential off-target effects of beta-blockers on gut hormone receptors: In silico study including GUT-DOCK—A web service for small-molecule docking
   Paweł Pasznik, Ewelina E. Rutkowska, Szymon Niewieczerzał, Judyta Cielecka‐Piontek, Dorota Latek · 2019 · PLoS ONE
6. Rescoring Virtual Screening Results with the MM-PBSA Methods: Beware of Internal Dielectric Constants
   Xiao Hu, Alessandro Contini · 2019 · Journal of Chemical Information and Modeling
7. Evaluation of Artificial Intelligence in Participating Structure-Based Virtual Screening for Identifying Novel Interleukin-1 Receptor Associated Kinase-1 Inhibitors
   Jinxin Che, Ruiwei Feng, Jian Gao, Hongyun Yu, Qinjie Weng, Qiaojun He, Xiaowu Dong, Jian Feng Wu, Bo Yang · 2020 · Frontiers in Oncology
8. Multiple machine learning models combined with virtual screening and molecular docking to identify selective human ALDH1A1 inhibitors
   Gera Narendra, Baddipadige Raju, Himanshu Verma, Bharti Sapra, Om Silakari · 2021 · Journal of Molecular Graphics and Modelling
9. Identification of Some Promising Heterocycles Useful in Treatment of Allergic Rhinitis: Virtual Screening, Pharmacophore Mapping, Molecular Docking, and Molecular Dynamics
   Xiaopeng Sun, Amany Belal, Mohamed A. Elanany, Reem I. Alsantali, Munira M. Alrooqi, Abdalla R. Mohamed, Sherifa M. Hasabelnaby · 2022 · Russian Journal of Bioorganic Chemistry
10. Natural inhibitors of SARS-CoV-2 main protease: structure based pharmacophore modeling, molecular docking and molecular dynamic simulation studies
    Mohammad Halimi, Elmira Parvindokht Bararpour · 2022 · Journal of Molecular Modeling
11. Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation
    Shahkaar Aziz, Muhammad Salman Waqas, Tapan Kumar Mohanta, Sobia Ahsan Halim, Aqib Iqbal, Amjad Ali, Asaad Khalid, Ashraf N. Abdalla, Ajmal Khan, Ahmed Al‐Harrasi · 2023 · Journal of Infection and Public Health
12. Molecular dynamics simulation of the human estrogen receptor alpha: contribution to the pharmacophore of the agonists
    Dessislava Jereva, F. Fratev, Ivanka Tsakovska, Petko Alov, Tania Pencheva, Ilza K. Pajeva · 2015 · Mathematics and Computers in Simulation
13. PENG: A Neural Gas-Based Approach for Pharmacophore Elucidation. Method Design, Validation, and Virtual Screening for Novel Ligands of LTA4H
    Daniel Martin Moser, Sandra K. Wittmann, Jan S. Kramer, René Blöcher, Janosch Achenbach, Denys Pogoryelov, Ewgenij Proschak · 2015 · Journal of Chemical Information and Modeling
14. Novel Scaffolds for Modulation of TRPV1 Identified with Pharmacophore Modeling and Virtual Screening
    Daria Goldmann, Peter Pakfeifer, Steffen Hering, Gerhard Franz Ecker · 2015 · Future Medicinal Chemistry
15. Comparison of 0.5% ropivacaine and 0.5% levobupivacaine for infraclavicular brachial plexus block.
    Rhubain Mageswaran, Y C Choy · 2010 · PubMed
16. In silico identification of inhibitors of ribose 5-phosphate isomerase from Trypanosoma cruzi using ligand and structure based approaches
    Vanessa V C Sinatti, Luiz Phillippe R. Baptista, Marcelo Alves-Ferreira, Laurent E. Dardenne, João Hermínio Martins da Silva, Ana Carolina Ramos Guimarães · 2017 · Journal of Molecular Graphics and Modelling
17. Structure-Based Design and Molecular Dynamics Simulations of Pentapeptide AEYTR as a Potential Acetylcholinesterase Inhibitor
    Vivitri Dewi Prasasty, Enade Perdana Istyastono · 2020 · Indonesian Journal of Chemistry
18. Pyrazolopyrimidine fused thiazolidinone hybrids as CDK2 inhibitors: insights from pharmacophore modeling, docking, DFT and molecular dynamics simulations
    Bharath Kumar Chagaleti, Venkatesan Saravanan, Ali Oubella, Saad Hmoud Alotaibi, Ali Altharawi, M. K. Kathiravan · 2025 · Journal of Molecular Structure
19. Benchmarking 3D Structure-Based Molecule Generators
    Natasha Sanjrani, Damien E. Coupry, Péter Pogány, David Scott Palmer, Stephen D. Pickett · 2025 · Journal of Chemical Information and Modeling
20. Electron-density-informed effective and reliable de novo molecular design and optimization with ED2Mol
    Mingyu Li, Kun Song, Jixiao He, Mingzhu Zhao, Gengshu You, Jie Zhong, Mengxi Zhao, Arong Li, Yu Chen, Guobin Li et al. · 2025 · Nature Machine Intelligence
21. A multi-stage virtual screening of FDA-approved drugs reveals potential inhibitors of SARS-CoV-2 main protease
    Yasmine M. Mandour, Darius Paul Zlotos, M. Alaraby Salem · 2020 · Journal of Biomolecular Structure and Dynamics
22. Small molecule superposition: A comprehensive overview on pose scoring of the latest methods
    Sophia M. N. Hönig, Christian Lemmen, Matthias Rarey · 2022 · Wiley Interdisciplinary Reviews Computational Molecular Science
23. A machine learning-integrated stepwise method to discover novel anti-obesity phytochemicals that antagonize the glucocorticoid receptor
    Seo Hyun Shin, Gihyun Hur, Na Ra Kim, Jung Han Yoon Park, Ki Won Lee, Hee Young Yang · 2023 · Food & Function
24. Chemokine Receptors—Structure-Based Virtual Screening Assisted by Machine Learning
    Paulina Dragan, Matthew Merski, Szymon Wiśniewski, Swapnil Ganesh Sanmukh, Dorota Latek · 2023 · Pharmaceutics
25. Steered Molecular Dynamics Simulations Study on FABP4 Inhibitors
    Rosario Tomarchio, Vincenzo Patamia, Chiara Zagni, Letizia Crocetti, Agostino Cilibrizzi, Giuseppe Floresta, Antonio Rescifina · 2023 · Molecules
26. A fragment-based drug discovery developed on ciclopirox for inhibition of Hepatitis B virus core protein: An in silico study
    Alireza Mohebbi, Touba Ghorbanzadeh, Shabnam Naderifar, Fattaneh Khalaj, Fatemeh Sana Askari, Ali Salehnia Sammak · 2023 · PLoS ONE
27. Water Network-Augmented Two-State Model for Protein–Ligand Binding Affinity Prediction
    Xiaoyang Qu, Lina Dong, Ding Luo, Yubing Si, Binju Wang · 2023 · Journal of Chemical Information and Modeling
28. The Impact of Data on Structure-Based Binding Affinity Predictions Using Deep Neural Networks
    Pierre-Yves Libouban, Samia Aci‐Sèche, José Carlos Gómez-Tamayo, Gary Tresadern, Pascal Bonnet · 2023 · International Journal of Molecular Sciences
29. Identification of novel potential cathepsin-B inhibitors through pharmacophore-based virtual screening, molecular docking, and dynamics simulation studies for the treatment of Alzheimer’s disease
    Jatin Jangra, Nilesh Gajanan Bajad, Ravi Singh, Ashok Kumar, Sushil Kumar Singh · 2024 · Molecular Diversity
30. Retrospective Ensemble Docking of Allosteric Modulators in an Adenosine G-Protein-Coupled Receptor
    Apurba Bhattarai, Jinan Wang, Yinglong Miao · 2020 · Biochimica et Biophysica Acta (BBA) - General Subjects
31. Learning the Edit Costs of Graph Edit Distance Applied to Ligand-Based Virtual Screening
    Carlos Garcia-Hernandez, Alberto Fernández, Francesc Serratosa · 2020 · Current Topics in Medicinal Chemistry
32. Virtual screening and structure-based 3D pharmacophore approach to identify small-molecule inhibitors of SARS-CoV-2 Mpro
    Samia A. Elseginy · 2021 · Journal of Biomolecular Structure and Dynamics
33. In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of Mycobacterium tuberculosis
    Tatiana F. Vieira, F. Martins, joel. moreira, T. Barbosa, S. Sousa · 2021 · Molecules
34. Small-molecule modulators of TRMT2A decrease PolyQ aggregation and PolyQ-induced cell death
    Michael A. Margreiter, Monika Witzenberger, Yasmine Wasser, Elena Davydova, Robert Janowski, Jonas Metz, Pardes Habib, Sabri E. M. Sahnoun, Carina Sobisch, Benedetta Poma et al. · 2021 · Computational and Structural Biotechnology Journal
35. Combinatorial Consensus Scoring for Ligand-Based Virtual Fragment Screening: A Comparative Case Study for Serotonin 5-HT3A, Histamine H1, and Histamine H4Receptors
    Sabine Schultes, Albert J. Kooistra, Henry F. Vischer, Saskia Nijmeijer, Eric E. J. Haaksma, Rob Leurs, Iwan J. P. de Esch, Chris de Graaf · 2015 · Journal of Chemical Information and Modeling
36. Prediction of the endocrine disruption profile of pesticides
    James Devillers, Elisabeth Bro, Florian Millot · 2015 · SAR and QSAR in environmental research
37. An Algorithm to Identify Target-Selective Ligands – A Case Study of 5-HT7/5-HT1A Receptor Selectivity
    Rafał Kurczab, Vittorio Canale, Paweł Zajdel, Andrzej Jacek Bojarski · 2016 · PLoS ONE
38. Simplified AutoDock force field for hydrated binding sites
    Marek Wojciechowski · 2017 · Journal of Molecular Graphics and Modelling
39. Identification of potential histone deacetylase1 (HDAC1) inhibitors using multistep virtual screening approach including SVM model, pharmacophore modeling, molecular docking and biological evaluation
    Shagun Krishna, Amar Deep Lakra, Nidhi Shukla, Saman Khan, Durga Prasad Mishra, Shakil Ahmed, Mohammad Imran Siddiqi · 2019 · Journal of Biomolecular Structure and Dynamics
40. Signals in the Cells: Multimodal and Contextualized Machine Learning Foundations for Therapeutics
    Alejandro Velez-Arce, Xiang Lin, Michelle M. Li, Kexin Huang, Wenhao Gao, Tianfan Fu, Bradley L. Pentelute, M Kellis, Marinka Žitnik · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
41. Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth
    Rui Zhou, Ziqian Liu, Tongtong Wu, Xianwei Pan, Tongtong Li, Kaiting Miao, Yuru Li, Xiaohui Hu, Haigang Wu, Andrew M. Hemmings et al. · 2024 · Cell Communication and Signaling
42. Structural insight into TNF-α inhibitors through combining pharmacophore-based virtual screening and molecular dynamic simulation
    Hina Qaiser, Maria Saeed, Dmitry Nerukh, Zaheer Ul‐Haq · 2020 · Journal of Biomolecular Structure and Dynamics
43. Analyzing Kinase Similarity in Small Molecule and Protein Structural Space to Explore the Limits of Multi-Target Screening
    Denis Schmidt, Magdalena M. Scharf, Dominique Sydow, Eva Aßmann, Maria Martí-Solano, Marina Keul, Andrea Volkamer, Peter Kolb · 2021 · Molecules
44. CHARMM-GUI Ligand Designer for Template-Based Virtual Ligand Design in a Binding Site
    Hugo Guterres, Sang‐Jun Park, Yiwei Cao, Wonpil Im · 2021 · Journal of Chemical Information and Modeling
45. Identification of Novel Natural Product Inhibitors against Matrix Metalloproteinase 9 Using Quantum Mechanical Fragment Molecular Orbital-Based Virtual Screening Methods
    Hocheol Lim, Hansol Hong, Seonik Hwang, Song Ja Kim, Sung Yum Seo, Kyoung Tai No · 2022 · International Journal of Molecular Sciences
46. Structural Modeling of TRPA1 Ion Channel—Determination of the Binding Site for Antagonists
    Alicja Gawalska, Marcin Kołaczkowski, Adam Bucki · 2022 · Molecules
47. Computational repurposing approach for targeting the critical spike mutations in B.1.617.2 (delta), AY.1 (delta plus) and C.37 (lambda) SARS-CoV-2 variants using exhaustive structure-based virtual screening, molecular dynamic simulations and MM-PBSA methods
    Maryam Ebrahimi, Leila Karami, Mahdi Alijanianzadeh · 2022 · Computers in Biology and Medicine
48. Multi-stage virtual screening of natural products against p38α mitogen-activated protein kinase: predictive modeling by machine learning, docking study and molecular dynamics simulation
    Ruoqi Yang, Xuan Zha, Xingyi Gao, Kangmin Wang, Bin Cheng, Bin Yan · 2022 · Heliyon
49. Structure-Based Discovery of Negative Allosteric Modulators of the Metabotropic Glutamate Receptor 5
    Stefanie Kampen, David J. Rodriguez, Morten Jørgensen, Monika Kruszyk-Kujawa, Xinyan Huang, Michael Collins, Noel Boyle, Damien Maurel, Axel Rudling, Guillaume Lebon et al. · 2022 · ACS Chemical Biology
50. Towards Effective Consensus Scoring in Structure-Based Virtual Screening
    Nhat Phuong, Darren R. Flower, Subhagata Chattopadhyay, Amit Kumar Chattopadhyay · 2022 · Interdisciplinary Sciences Computational Life Sciences
51. Identifying novel and potent inhibitors of EGFR protein for the drug development against the breast cancer
    Arif Jamal Siddiqui, Sadaf Jahan, Mitesh B. Patel, Abdelmushin Abdelgadir, Wael Alturaiki, Fevzi Bardakçi, Manojkumar Sachidanandan, Riadh Badraoui, Mejdi Snoussi, Mohd Adnan · 2023 · Journal of Biomolecular Structure and Dynamics
52. Hic Sunt Dracones: Molecular Docking in Uncharted Territories with Structures from AlphaFold2 and RoseTTAfold
    Christian Kersten, Steven Clower, Fabian Barthels · 2023 · Journal of Chemical Information and Modeling
53. ProfhEX: AI-based platform for small molecules liability profiling
    Filippo Lunghini, Anna Fava, Vincenzo Pisapia, Francesco Maria Sacco, Daniela Iaconis, Andrea R. Beccari · 2023 · Journal of Cheminformatics
54. Ligand binding affinity prediction with fusion of graph neural networks and 3D structure-based complex graph
    Lina Dong, Shuai Shi, Xiaoyang Qu, Ding Luo, Binju Wang · 2023 · Physical Chemistry Chemical Physics
55. Accelerating Molecular Docking using Machine Learning Methods
    Abdulsalam Yazıd Bande, Sefer Baday · 2024 · Molecular Informatics
56. Accelerating drug discovery and repurposing by combining transcriptional signature connectivity with docking
    Alexander William Thorman, James K. Reigle, Somchai Chutipongtanate, Juechen Yang, Behrouz Shamsaei, Marcin Pilarczyk, Mehdi Fazel‐Najafabadi, Rafał Adamczak, Michal Kouril, Surbhi Bhatnagar et al. · 2024 · Science Advances
57. Structure based virtual screening to identify inhibitors against MurE Enzyme of Mycobacterium tuberculosis using AutoDock Vina
    Shilpi Singh, Urmi Bajpai, Andrew Michael Lynn · 2014 · Bioinformation
58. A Large and Phylogenetically Diverse Class of Type 1 Opsins Lacking a Canonical Retinal Binding Site
    Erin Becker, Andrew I. Yao, Phillip Seitzer, Tobias Kind, Ting Wang, Rich Eigenheer, Katie S. Y. Shao, Vladimir M. Yarov-Yarovoy, Marc T. Facciotti · 2016 · PLoS ONE
59. A D3R prospective evaluation of machine learning for protein-ligand scoring
    Jocelyn Sunseri, Matthew Ragoza, Jasmine Collins, David Ryan Koes · 2016 · Journal of Computer-Aided Molecular Design
60. Prediction of Protein Kinase–Ligand Interactions through 2.5D Kinochemometrics
    Nicolas Bosc, Berthold Wroblowski, Christophe Meyer, Pascal Bonnet · 2016 · Journal of Chemical Information and Modeling
61. Towards a critical evaluation of an empirical and volume-based solvation function for ligand docking
    Heloisa dos Santos Muniz, Alessandro Silva Nascimento · 2017 · PLoS ONE
62. Similarity search combined with docking and molecular dynamics for novel hAChE inhibitor scaffolds
    Nádia M. Borges, G. Sartori, Jean F. R. Ribeiro, Josmar Rodrigues da Rocha, João B. L. Martins, Carlos Alberto Montanari, Ricardo Gargano · 2018 · Journal of Molecular Modeling
63. Anthranilic Acid Inhibitors of Undecaprenyl Pyrophosphate Synthase (UppS), an Essential Enzyme for Bacterial Cell Wall Biosynthesis
    Marko Jukič, Kaja Rožman, Matej Sova, Hélène Barreteau, Stanislav Gobec · 2019 · Frontiers in Microbiology
64. Binding site comparisons for target-centered drug discovery
    Janez Konc · 2019 · Expert Opinion on Drug Discovery
65. Evaluation and Identification of the Neuroprotective Compounds of Xiaoxuming Decoction by Machine Learning: A Novel Mode to Explore the Combination Rules in Traditional Chinese Medicine Prescription
    Shilun Yang, Yanjia Shen, Wendan Lu, Yinglin Yang, Haigang Wang, Li Li, Chunfu Wu, Guanhua Du · 2019 · BioMed Research International
66. New strategy for identifying potential natural HIV-1 non-nucleoside reverse transcriptase inhibitors against drug-resistance: anin silicostudy
    Yanjing Wang, Xiangeng Wang, Yi Xiong, Aman Chandra Kaushik, Muhammad Junaid, Abbas Khan, Hao Dai, Dong‐Qing Wei · 2019 · Journal of Biomolecular Structure and Dynamics
67. Toward a Computational Ecotoxicity Assay
    Natasha Kamerlin, Mickaël G. Delcey, Sergio Manzetti, David van der Spoel · 2020 · Journal of Chemical Information and Modeling
68. Predicting target–ligand interactions with graph convolutional networks for interpretable pharmaceutical discovery
    Paola Ruiz Puentes, Laura Rueda-Gensini, Natalia Valderrama, Isabela Hernández, Cristina González, Laura Alexandra Daza, Carolina Muñoz-Camargo, Juan C. Cruz, Pablo Arbeláez · 2022 · Scientific Reports
69. kinCSM : Using graph‐based signatures to predict small molecule CDK2 inhibitors
    Yunzhuo Zhou, Raghad Al‐Jarf, Azadeh Alavi, Thanh Nguyen, Carlos H. M. Rodrigues, Douglas E. V. Pires, David Benjamin Ascher · 2022 · Protein Science
70. Identification of potential ATP-competitive cyclin-dependent kinase 1 inhibitors: De novo drug generation, molecular docking, and molecular dynamics simulation
    Fengming He, Xiumei Wang, Qiaoqiong Wu, Shun-Zhi Liu, Yin Cao, Xiaodan Guo, Sihang Yin, Na Yin, Baicun Li, Meijuan Fang · 2023 · Computers in Biology and Medicine
71. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach
    Shengqi Wang, Liangjun Xie, Hui Wang, Bing Zhu, Ai-qin Niu · 2016 · Drug Design Development and Therapy
72. Multiple machine learning based descriptive and predictive workflow for the identification of potential PTP1B inhibitors
    Sharat Chandra, Jyotsana Pandey, Akhilesh Kumar Tamrakar, Mohammad Imran Siddiqi · 2016 · Journal of Molecular Graphics and Modelling
73. Pharmacophore analysis of positive allosteric modulators of AMPA receptors
    Dmitry S. Karlov, Mstislav Igorevich Lavrov, Vladimir A. Palyulin, N. S. Zefirov · 2016 · Russian Chemical Bulletin
74. In-silico profiling of the biological activities of Amaryllidaceae alkaloids
    Eman Shawky · 2017 · Journal of Pharmacy and Pharmacology
75. Discrete Fourier Transform-Based Multivariate Image Analysis: Application to Modeling of Aromatase Inhibitory Activity
    Stephen J. Barigye, Matheus P. Freitas, Priscila Ausina, Patrícia Zancan, Mauro Sola‐Penna, Juan A. Castillo‐Garit · 2018 · ACS Combinatorial Science
76. Privileged substructures for anti-sickling activity via cheminformatic analysis
    Chuleeporn Phanus‐umporn, Watshara Shoombuatong, Veda Prachayasittikul, Nuttapat Anuwongcharoen, Chanin Nantasenamat · 2018 · RSC Advances
77. Protein Binding Pocket Optimization for Virtual High-Throughput Screening (vHTS) Drug Discovery
    Dimitris Gazgalis, Mehreen Zaka, Bilal Haider Abbasi, Diomedes E. Logothetis, Mihaly Mezei, Meng Cui · 2020 · ACS Omega
78. Current methods and challenges for deep learning in drug discovery
    Stefan Schroedl · 2019 · Drug Discovery Today Technologies
79. Repurposing FDA-approved drugs to target G-quadruplexes in breast cancer.
    F. Moraca, Valentina Arciuolo, Simona Marzano, F. Napolitano, Giuliano Castellano, Federica D'Aria, Anna Di Porzio, Laura Landolfi, B. Catalanotti, Antonio Randazzo et al. · 2025 · European journal of medicinal chemistry
80. A human metabolic map of pharmacological perturbations reveals drug modes of action
    Laurentz Schuhknecht, Karin Ortmayr, Jürgen Jänes, Martina Bläsi, Eleni Panoussis, Sebastian Bors, Terézia Dorčaková, Tobias Fuhrer, Pedro Beltrão, Mattia Zampieri · 2025 · Nature Biotechnology
81. Pharmacophore screening, molecular docking, and MD simulations for identification of VEGFR-2 and c-Met potential dual inhibitors
    Junmin Dong, Xiaohua Hao · 2025 · Frontiers in Pharmacology
82. Discovery of Covalent Ligands with AlphaFold3
    Yoav Shamir, Ronen Gabizon, Adi Rogel, David Yin-wei Lin, Amy Hamilton Andreotti, Nir London · 2026 · Journal of the American Chemical Society
83. Rescoring of docking poses under Occam’s Razor: are there simpler solutions?
    Michael Zhenin, Malkeet Singh Bahia, Gilles Marcou, Alexandre A. Varnek, Hanoch Senderowitz, Dragos Horvath · 2018 · Journal of Computer-Aided Molecular Design
84. Collaborative Approach between Explainable Artificial Intelligence and Simplified Chemical Interactions to Explore Active Ligands for Cyclin-Dependent Kinase 2
    Tomomi Shimazaki, Masanori Tachikawa · 2022 · ACS Omega
85. Improved Molecular Docking of MAO-B Inhibitors with Glide
    2022 · Biointerface Research in Applied Chemistry
86. Exploration of N-Arylsulfonyl-indole-2-carboxamide Derivatives as Novel Fructose-1,6-bisphosphatase Inhibitors by Molecular Simulation
    Yilan Zhao, Honghao Yang, Fengshou Wu, Xiaogang Luo, Qi Sun, Weiliang Feng, Xiu-Lian Ju, Genyan Liu · 2022 · International Journal of Molecular Sciences
87. Combining structure-based pharmacophore modeling and machine learning for the identification of novel BTK inhibitors
    Tanuj Sharma, Venu Venkatarame Gowda Saralamma, Duk‐Chul Lee, Mohammad Azhar Imran, Jaehyuk Choi, Mohammad Hassan Baig, Jae-June Dong · 2022 · International Journal of Biological Macromolecules
88. Advances in Deep Learning Assisted Drug Discovery Methods: A Self-review
    Haiping Zhang, Konda Mani Saravanan · 2024 · Current Bioinformatics
89. Machine learning for predicting protein properties: A comprehensive review
    Yizhen Wang, Yanyun Zhang, Xuhui Zhan, Yuhao He, Yongfu Yang, Li Cheng, Daniyal Alghazzawi · 2024 · Neurocomputing
90. Discovery of potent LRRK2 inhibitors by ensemble virtual screening strategy and bioactivity evaluation
    Xiaoqing Gong, Shuli Li, Junli Huang, Shuoyan Tan, Qianqian Zhang, Yanan Tian, Qin Li, Lingling Wang, Henry H. Y. Tong, Xiaojun Yao et al. · 2024 · European Journal of Medicinal Chemistry
91. Deciphering quinazoline derivatives’ interactions with EGFR: a computational quest for advanced cancer therapy through 3D-QSAR, virtual screening, and MD simulations
    Sirajudheen Anwar, Jowaher Alanazi, Nafees Ahemad, Shafaq Raza, Tahir Ali Chohan, Hammad Saleem · 2024 · Frontiers in Pharmacology
92. Collecting and Assessing Human Lactate Dehydrogenase-A Conformations for Structure-Based Virtual Screening
    Rosa Buonfiglio, Mariarosaria Ferraro, Federico Falchi, Andrea Cavalli, Matteo Masetti, Maurizio Recanatini · 2013 · Journal of Chemical Information and Modeling
93. SPOT‐Ligand: Fast and effective structure‐based virtual screening by binding homology search according to ligand and receptor similarity
    Yuedong Yang, Jian Zhan, Yaoqi Zhou · 2016 · Journal of Computational Chemistry
94. Novel FXa Inhibitor Identification through Integration of Ligand- and Structure-Based Approaches
    Carlos F. Lagos, Gerardine F Segovia, Nicolás Núñez-Navarro, Mario Faúndez, Flavia C. M. Zacconi · 2017 · Molecules
95. Consensus queries in ligand-based virtual screening experiments
    Francois Berenger, Oanh Vu, Jens Meiler · 2017 · Journal of Cheminformatics
96. On the discovery of a potential survivin inhibitor combining computational tools and cytotoxicity studies
    Patricia A. Quispe, Martín J. Lavecchia, Ignácio E. León · 2019 · Heliyon
97. Ranking the synthesizability of hypothetical zeolites with the sorting hat
    Benjamin A. Helfrecht, Giovanni Pireddu, Rocío Semino, Scott M. Auerbach, Michele Ceriotti · 2022 · Digital Discovery
98. Discovery of New Estrogen-Related Receptor α Agonists via a Combination Strategy Based on Shape Screening and Ensemble Docking
    Dongping Li, Kexin Jiang, Dan Teng, Zengrui Wu, Weihua Li, Yun Tang, Rui Wang, Guixia Liu · 2022 · Journal of Chemical Information and Modeling
99. In Silico Analysis of the Multi-Targeted Mode of Action of Ivermectin and Related Compounds
    Maral Aminpour, Marco Cannariato, Jordane Preto, M. Ehsan Safaeeardebili, Alexia Moracchiato, Domiziano Doria, Francesca Donato, Eric Adriano Zizzi, Marco A. Deriu, David E. Scheim et al. · 2022 · Computation
100. Expanding the Accessible Chemical Space of SIRT2 Inhibitors through Exploration of Binding Pocket Dynamics
     Nemanja Djoković, D. Ružić, M. Rahnasto-Rilla, T. Srdić-Rajić, M. Lahtela-Kakkonen, Katarina M. Nikolic · 2022 · Journal of Chemical Information and Modeling