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

Cited by (1,002)

Items 601–700 of 1,002

1. Targeting Mycobacterium Tuberculosis Enoyl‐Acyl Carrier Protein Reductase Using Computational Tools for Identification of Potential Inhibitor and their Biological Activity
   Jitendra Kuldeep, Sandeep Sharma, Tanuj Sharma, Bhupendra Narain Singh, Mohammad Imran Siddiqi · 2020 · Molecular Informatics
2. Peptidomimetic inhibitors of TMPRSS2 block SARS-CoV-2 infection in cell culture
   Lukas Wettstein, Philip Maximilian Knaff, Christian Kersten, Patrick Müller, Tatjana Weil, Carina Conzelmann, Janis A. Müller, Maximilian Brückner, Markus Hoffmann, Stefan Pöhlmann et al. · 2022 · Communications Biology
3. Protein–ligand binding affinity prediction with edge awareness and supervised attention
   Yuliang Gu, Xiangzhou Zhang, Anqi Xu, Weiqi Chen, Kang Liu, Lijuan Wu, Shenglong Mo, Yong Qiang Hu, Mei Liu, Qichao Luo · 2022 · iScience
4. Virtual screening and molecular dynamics simulation approach for the identification of potential multi-target directed ligands for the treatment of Alzheimer’s disease
   Kailash Jangid, Bharti Devi, Ashrulochan Sahoo, Vijay Kumar, Ashish Ranjan Dwivedi, Suresh Thareja, Rajnish Kumar, Vinod Kumar · 2023 · Journal of Biomolecular Structure and Dynamics
5. Comparative evaluation of several docking tools for docking small molecule ligands to DC-SIGN
   Gregor Jug, Marko Anderluh, Tihomir Tomašič · 2015 · Journal of Molecular Modeling
6. Identification of binding sites and favorable ligand binding moieties by virtual screening and self-organizing map analysis
   Emna Harigua‐Souiai, Isidro Cortés‐Ciriano, Nathan Desdouits, Thérèse E. Malliavin, Ikram Guizani, Michaël Nilges, Arnaud Blondel, Guillaume Bouvier · 2015 · BMC Bioinformatics
7. Identification and Validation of a Potent Dual Inhibitor of the P. falciparum M1 and M17 Aminopeptidases Using Virtual Screening
   Chiara Ruggeri, Nyssa Drinkwater, Komagal Kannan Sivaraman, Rebecca S. Bamert, Sheena McGowan, Alessandro Paiardini · 2015 · PLoS ONE
8. Molecular Docking to Flexible Targets
   Jesper Sørensen, Özlem Demir, Robert V. Swift, Victoria A. Feher, Rommie E. Amaro · 2014 · Methods in molecular biology
9. Novel Agonist Bioisosteres and Common Structure-Activity Relationships for The Orphan G Protein-Coupled Receptor GPR139
   Mohamed A. Shehata, Anne Cathrine Nøhr, Delphine Lissa, Christoph Bisig, Vignir Ísberg, Kirsten Bayer Andersen, Kasper Harpsøe, Fredrik Björkling, Hans Bräuner‐Osborne, David E.I. Gloriam · 2016 · Scientific Reports
10. Identification of new BACE1 inhibitors using Pharmacophore and Molecular dynamics simulations approach
    Anantha Krishnan Dhanabalan, Manish Kesherwani, Devadasan Velmurugan, K. Gunasekaran · 2017 · Journal of Molecular Graphics and Modelling
11. In silico prediction of ROCK II inhibitors by different classification approaches
    Chuipu Cai, Qihui Wu, Yunxia Luo, Huili Ma, Jiangang Shen, Yongbin Zhang, Lei Yang, Yunbo Chen, Zehuai Wen, Qi Wang · 2017 · Molecular Diversity
12. The inhibitory potential of Broussochalcone A for the human cytochrome P450 2J2 isoform and its anti-cancer effects via FOXO3 activation
    See‐Hyoung Park, Jongsung Lee, Jong Cheol Shon, Nguyen Minh Phuc, Jun Goo Jee, Kwang‐Hyeon Liu · 2018 · Phytomedicine
13. Pharmacoinformatics and molecular dynamic simulation studies to identify potential small-molecule inhibitors of WNK-SPAK/OSR1 signaling that mimic the RFQV motifs of WNK kinases
    Mubarak A. Alamri · 2020 · Arabian Journal of Chemistry
14. Combining Virtual Screening Protocol and In Vitro Evaluation towards the Discovery of BACE1 Inhibitors
    Judite R M Coimbra, S. J. Baptista, T. Dinis, M. C. Silva, P. Moreira, A. Santos, Jorge A. R. Salvador · 2020 · Biomolecules
15. Reliability of AlphaFold2 Models in Virtual Drug Screening: A Focus on Selected Class A GPCRs
    Nada K. Alhumaid, Essam A. Tawfik · 2024 · International Journal of Molecular Sciences
16. Discovery of natural MCL1 inhibitors using pharmacophore modelling, QSAR, docking, ADMET, molecular dynamics, and DFT analysis
    Uddalak Das, Tathagata Chanda, Jitendra Kumar, Anitha Peter · 2025 · Computational Biology and Chemistry
17. Application of target repositioning and in silico screening to exploit fatty acid binding proteins (FABPs) from Echinococcus multilocularis as possible drug targets
    Julián A. Bélgamo, Lucas N. Alberca, Jorge Luis Pórfido, Franco N. Caram Romero, Santiago Rodrı́guez, Alan Talevi, Betina Córsico, Gisela Raquel Franchini · 2020 · Journal of Computer-Aided Molecular Design
18. Prioritisation of Compounds for 3CLpro Inhibitor Development on SARS-CoV-2 Variants
    Marko Jukič, Blaž Škrlj, Gašper Tomšič, Sebastian Pleško, Črtomir Podlipnik, Urban Bren · 2021 · Molecules
19. Novel B, C-ring truncated deguelin derivatives reveals as potential inhibitors of cyclin D1 and cyclin E using molecular docking and molecular dynamic simulation
    Kiran Bharat Lokhande, Payel Ghosh, Shuchi Nagar, K. Venkateswara Swamy · 2021 · Molecular Diversity
20. Discovery of Cobimetinib as a novel A-FABP inhibitor using machine learning and molecular docking-based virtual screening
    Shilun Yang, Simeng Li, Junlei Chang · 2022 · RSC Advances
21. LIDeB Tools: A Latin American resource of freely available, open-source cheminformatics apps
    Denis N. Prada Gori, Lucas N. Alberca, Santiago Rodrı́guez, Juan I. Alice, Manuel A. Llanos, Carolina L. Bellera, Alan Talevi · 2022 · Artificial Intelligence in the Life Sciences
22. TB-IECS: an accurate machine learning-based scoring function for virtual screening
    Xujun Zhang, Chao Shen, Dejun Jiang, Jintu Zhang, Qing Ye, Lei Xu, Tingjun Hou, Peichen Pan, Yu Kang · 2023 · Journal of Cheminformatics
23. Identification of Compounds with Potential Antibacterial Activity against Mycobacterium through Structure-Based Drug Screening
    Tomohiro Kinjo, Yuji Koseki, Maiko Kobayashi, Atsumi Yamada, Koji Morita, Kento Yamaguchi, Ryoya Tsurusawa, Gülçin Gülten, Hideyuki Komatsu, Hiroshi Sakamoto et al. · 2013 · Journal of Chemical Information and Modeling
24. Identification of new anti- Candida compounds by ligand-based pharmacophore virtual screening
    Maria Concetta Gidaro, Stefano Alcaro, Daniela Secci, Daniela Rivanera, Adriano Mollica, Mariangela Agamennone, Letizia Giampietro, Simone Carradori · 2016 · Journal of Enzyme Inhibition and Medicinal Chemistry
25. Identification of Novel Smoothened Ligands Using Structure-Based Docking
    Celine Lacroix, Inbar Fish, Hayarpi Torosyan, Pranavan Parathaman, John J. Irwin, Brian K. Shoichet, Stéphane Angers · 2016 · PLoS ONE
26. Drug-induced diabetes type 2: In silico study involving class B GPCRs
    Dorota Latek, Ewelina E. Rutkowska, Szymon Niewieczerzał, Judyta Cielecka‐Piontek · 2019 · PLoS ONE
27. Virtual Screening of Human Class-A GPCRs Using Ligand Profiles Built on Multiple Ligand–Receptor Interactions
    Wallace K. B. Chan, Yang Zhang · 2020 · Journal of Molecular Biology
28. Integrated virtual screening, molecular modeling and machine learning approaches revealed potential natural inhibitors for epilepsy
    Faez Falah Alshehri · 2023 · Saudi Pharmaceutical Journal
29. Discovery of dual kinase inhibitors targeting VEGFR2 and FAK: structure-based pharmacophore modeling, virtual screening, and molecular docking studies
    Marwa A. Fouad, Alaa A. Osman, Noha M. Abdelhamid, Mai W. Rashad, Ashrakat Y. Nabawy, Ahmed Mahmoud El Kerdawy · 2024 · BMC Chemistry
30. AlphaFold and what is next: bridging functional, systems and structural biology
    Kacper Szczepski, Łukasz Jaremko · 2025 · Expert Review of Proteomics
31. Navigating structure-based drug discovery with emerging innovations in physics- and knowledge-based approaches
    Jordy Homing Lam, Vsevolod Katritch · 2025 · npj Drug Discovery.
32. Strategies for Improved Modeling of GPCR-Drug Complexes: Blind Predictions of Serotonin Receptors Bound to Ergotamine
    David J. Rodriguez, Anirudh Ranganathan, Jens Carlsson · 2014 · Journal of Chemical Information and Modeling
33. Roles for Ordered and Bulk Solvent in Ligand Recognition and Docking in Two Related Cavities
    Sarah Barelier, Sarah E. Boyce, Inbar Fish, Marcus M. Fischer, David B. Goodin, Brian K. Shoichet · 2013 · PLoS ONE
34. Toward a Benchmarking Data Set Able to Evaluate Ligand- and Structure-based Virtual Screening Using Public HTS Data
    Martin Lindh, Fredrik Svensson, Wesley Schaal, Jin Zhang, Christian Sköld, Peter Brandt, Anders Karlén · 2015 · Journal of Chemical Information and Modeling
35. Design of novel lead molecules against RhoG protein as cancer target – a computational study
    Thirupathi Dasari, Bhargavi Kondagari, Ramasree Dulapalli, Aboubakr Haredi Abdelmonsef, Thirupathi Mukkera, Lavanya Souda Padmarao, Vasavi Malkhed, Uma Vuruputuri · 2016 · Journal of Biomolecular Structure and Dynamics
36. Spectrophores as one-dimensional descriptors calculated from three-dimensional atomic properties: applications ranging from scaffold hopping to multi-target virtual screening
    Rafaela Gladysz, Fábio Mendes dos Santos, Wilfried Langenaeker, Gert Thijs, Koen Augustyns, Hans L. De Winter · 2018 · Journal of Cheminformatics
37. In silico identification and evaluation of potential interaction of Azadirachta indica phytochemicals with Plasmodium falciparum heat shock protein 90.
    M. O. Daniyan, O. Ojo · 2019 · Journal of Molecular Graphics and Modelling
38. Applying Machine Learning to Ultrafast Shape Recognition in Ligand-Based Virtual Screening
    Etienne Bonanno, Jean-Paul Ebejer · 2020 · Frontiers in Pharmacology
39. Discovery of Potential Chemical Probe as Inhibitors of CXCL12 Using Ligand-Based Virtual Screening and Molecular Dynamic Simulation
    Sajjad Haider, Assem Barakat, Zaheer Ul‐Haq · 2020 · Molecules
40. Best Practices for Docking-Based Virtual Screening
    Bruno J. Neves, Melina Mottin, José Teófilo Moreira‐Filho, Bruna Katiele de Paula Sousa, Sabrina Silva Mendonça, Carolina Horta Andrade · 2021 · Elsevier eBooks
41. Structure-based in silico approaches for drug discovery against Mycobacterium tuberculosis
    A. Kingdon, L. Alderwick · 2021 · Computational and Structural Biotechnology Journal
42. Discovery of Novel Acetylcholinesterase Inhibitors by Virtual Screening, In Vitro Screening, and Molecular Dynamics Simulations
    C. Johan van der Westhuizen, André Stander, Darren Lyall Riley, Jenny‐Lee Panayides · 2022 · Journal of Chemical Information and Modeling
43. Machine intelligence-driven framework for optimized hit selection in virtual screening
    Neeraj Kumar, Vishal Acharya · 2022 · Journal of Cheminformatics
44. DeepBindBC: A practical deep learning method for identifying native-like protein-ligand complexes in virtual screening
    Haiping Zhang, Tingting Zhang, Konda Mani Saravanan, Linbu Liao, Hao Wu, Hai‐Shan Zhang, Huiling Zhang, Yi Feng Pan, Xuli Wu, Yanjie Wei · 2022 · Methods
45. Using filters in virtual screening: A comprehensive guide to minimize errors and maximize efficiency
    Radwa E. Mahgoub, Noor Atatreh, Mohammad A. Ghattas · 2022 · Annual reports in medicinal chemistry
46. Improving drug-target affinity prediction via feature fusion and knowledge distillation
    Ruiqiang Lu, Jun Wang, Pengyong Li, Yuquan Li, Shuoyan Tan, Yiting Pan, Huanxiang Liu, Peng Gao, Guotong Xie, Xiaojun Yao · 2023 · Briefings in Bioinformatics
47. Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels
    Palina Pliushcheuskaya, Georg Künze · 2023 · International Journal of Molecular Sciences
48. Structure-based design of eugenol analogs as potential estrogen receptor antagonists
    Yulia Anita, Muhammad Radifar, Leonardus B. S. Kardono, Muhammad Hanafi, Enade Perdana Istyastono · 2012 · Bioinformation
49. In silico identification of novel kinase inhibitors targeting wild-type and T315I mutant ABL1 from FDA-approved drugs
    Huailong Xu, Zijie Wang, Xiaomeng Liang, Xin Li, Zheng Shi, Nan Zhou, Jinku Bao · 2014 · Molecular BioSystems
50. Fragment-Based Discovery of Subtype-Selective Adenosine Receptor Ligands from Homology Models
    Anirudh Ranganathan, Leigh A. Stoddart, Stephen John Hill, Jens Carlsson · 2015 · Journal of Medicinal Chemistry
51. In silico study of subtilisin-like protease 1 (SUB1) from different Plasmodium species in complex with peptidyl-difluorostatones and characterization of potent pan-SUB1 inhibitors
    Simone Brogi, Simone Giovani, Margherita Brindisi, Sandra Gemma, Ettore Novellino, Giuseppe Campiani, Michael J. Blackman, Stefania Butini · 2016 · Journal of Molecular Graphics and Modelling
52. Enhancing Virtual Screening Performance of Protein Kinases with Molecular Dynamics Simulations
    Tavina L. Offutt, Robert V. Swift, Rommie E. Amaro · 2016 · Journal of Chemical Information and Modeling
53. Integrated machine learning, molecular docking and 3D-QSAR based approach for identification of potential inhibitors of trypanosomal N -myristoyltransferase
    Nidhi Singh, Priyanka Shah, Hemlata Dwivedi‐Agnihotri, Shikha Mishra, Renu Tripathi, Amogh A. Sahasrabuddhe, Mohammad Imran Siddiqi · 2016 · Molecular BioSystems
54. Maximizing gain in high-throughput screening using conformal prediction
    Fredrik Svensson, Avid M. Afzal, Ulf Norinder, Andreas Bender · 2018 · Journal of Cheminformatics
55. In Silico Workflow for the Discovery of Natural Products Activating the G Protein-Coupled Bile Acid Receptor 1
    Benjamin Kirchweger, Jadel Muller Kratz, Angela Ladurner, Ulrike Grienke, Thierry Langer, Verena Maria Dirsch, Judith Maria Rollinger · 2018 · Frontiers in Chemistry
56. The Current Limits in Virtual Screening and Property Prediction
    Michael Christopher Hutter · 2018 · Future Medicinal Chemistry
57. Identification of dual Sigma1 receptor modulators/acetylcholinesterase inhibitors with antioxidant and neurotrophic properties, as neuroprotective agents
    Marta Rui, Giacomo Rossino, Stefania Coniglio, Stefania Monteleone, Arianna Scuteri, Alessio Malacrida, Daniela Rossi, Laura Catenacci, Milena Sorrenti, Mayra Paolillo et al. · 2018 · European Journal of Medicinal Chemistry
58. Computer-Driven Development of an in Silico Tool for Finding Selective Histone Deacetylase 1 Inhibitors
    Hajar Sirous, Giuseppe Campiani, Simone Brogi, Vincenzo Calderone, Giulia Chemi · 2020 · Molecules
59. Unveiling the “invisible” druggable conformations of GDP-bound inactive Ras
    Dan Liu, Yunyun Mao, Xue Gu, Yang Zhou, Dong Long · 2021 · Proceedings of the National Academy of Sciences
60. Identification and Molecular Interaction Studies of Thyroid Hormone Receptor Disruptors among Household Dust Contaminants
    Jin Zhang, Yaozong Li, Arun A. Gupta, Kwangho Nam, Patrik L. Andersson · 2016 · Chemical Research in Toxicology
61. Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
    Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, Sung Ju Hwang · 2021 · arXiv (Cornell University)
62. Advances in machine-learning approaches to RNA-targeted drug design
    Yuanzhe Zhou, Shi‐Jie Chen · 2024 · Artificial Intelligence Chemistry
63. Insight into Janus kinases specificity: From molecular architecture to cancer therapeutics
    Tian‐Hua Wei, Meng‐Yi Lu, Si‐Hui Yao, Yu‐Qi Hong, Jin Yang, Meng‐Yuan Zhang, Yu‐Qi Yin, Yu‐Jie Han, Qingqing Li, Zixuan Wang et al. · 2024 · MedComm – Oncology
64. Knowledge-guided diffusion model for 3D ligand-pharmacophore mapping
    Jun-Lin Yu, Zhou Cong, Xiang-Li Ning, Jun Mou, Fan-Bo Meng, Jing-Wei Wu, Yi-Ting Chen, Biao-Dan Tang, X.F. Liu, Guo‐Bo Li · 2025 · Nature Communications
65. A survey on deep learning for drug-target binding prediction: models, benchmarks, evaluation, and case studies
    Kusal Debnath, Pratip Rana, Preetam Ghosh · 2025 · Briefings in Bioinformatics
66. A computational chemistry perspective on the current status and future direction of hepatitis B antiviral drug discovery
    Dante Morgnanesi, Eric Heinrichs, Anthony R. Mele, Sean R. Wilkinson, Suzanne Zhou, John L. Kulp · 2015 · Antiviral Research
67. The application of molecular modelling in the safety assessment of chemicals: A case study on ligand-dependent PPARγ dysregulation
    Merilin Al Sharif, Ivanka Tsakovska, Ilza K. Pajeva, Petko Alov, Elena Fioravanzo, Arianna Bassan, Simona Kovarich, Chihae Yang, Aleksandra Mostrąg, Vessela Vitcheva et al. · 2016 · Toxicology
68. Effect of Binding Pose and Modeled Structures on SVMGen and GlideScore Enrichment of Chemical Libraries
    David Daqiang Xu, Samy O. Meroueh · 2016 · Journal of Chemical Information and Modeling
69. In Silico Identification of Piperidinyl-amine Derivatives as Novel Dual Binders of Oncogene c-myc/c-Kit G-quadruplexes
    Roberta Rocca, Federica Moraca, Giosuè Costa, Carmine Talarico, Francesco Ortuso, Silvia Da Ros, Giulia Nicoletto, Claudia Sissi, Stefano Alcaro, Anna Artese · 2018 · ACS Medicinal Chemistry Letters
70. Assessing the public landscape of clinical-stage pharmaceuticals through freely available online databases
    Rebekah H. Griesenauer, Constantino Schillebeeckx, Michael S. Kinch · 2019 · Drug Discovery Today
71. BCL::MolAlign: Three-Dimensional Small Molecule Alignment for Pharmacophore Mapping
    Benjamin P. Brown, Jeffrey Mendenhall, Jens Meiler · 2019 · Journal of Chemical Information and Modeling
72. Identification of Tyrosinase Inhibitors and Their Structure-Activity Relationships via Evolutionary Chemical Binding Similarity and Structure-Based Methods
    Prasannavenkatesh Durai, Young‐Joon Ko, Jin‐Chul Kim, Cheol‐Ho Pan, Keunwan Park · 2021 · Molecules
73. Combination of consensus and ensemble docking strategies for the discovery of human dihydroorotate dehydrogenase inhibitors
    Garri Chilingaryan, Narek Abelyan, Arsen Sargsyan, Karen Nazaryan, Andre Serobian, Hovakim S. Zakaryan · 2021 · Scientific Reports
74. SidechainNet : An all‐atom protein structure dataset for machine learning
    Jonathan Edward King, David Ryan Koes · 2021 · Proteins Structure Function and Bioinformatics
75. Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents
    Kushagra Kashyap, Mohammad Imran Siddiqi · 2021 · Molecular Diversity
76. Virtual Screening and Biological Activity Evaluation of New Potent Inhibitors Targeting LRRK2 Kinase Domain
    Shuoyan Tan, Xiaoqing Gong, Huanxiang Liu, Xiaojun Yao · 2021 · ACS Chemical Neuroscience
77. Novel and Potential Small Molecule Scaffolds as DYRK1A Inhibitors by Integrated Molecular Docking-Based Virtual Screening and Dynamics Simulation Study
    Mir Mohammad Shahroz, Hemant Kumar Sharma, Abdulmalik Saleh Alfawaz Altamimi, Mubarak A. Alamri, Abuzer Ali, Amena Ali, Safar M. Alqahtani, Ali Altharawi, Alhumaidi B. Alabbas, Manal Abdullah Alossaimi et al. · 2022 · Molecules
78. AI-based prediction of new binding site and virtual screening for the discovery of novel P2X3 receptor antagonists
    Koon Mook Kang, Ingoo Lee, Hojung Nam, Yong‐Chul Kim · 2022 · European Journal of Medicinal Chemistry
79. Bioengineering of the Marine Diatom Phaeodactylum tricornutum with Cannabis Genes Enables the Production of the Cannabinoid Precursor, Olivetolic Acid
    Fatima Awwad, Elisa Ines Fantino, Marianne Héneault, Aracely Maribel Diaz-Garza, Natacha Mérindol, Alexandre Custeau, Sarah‐Eve Gélinas, Fatma Meddeb‐Mouelhi, Jessica Li, Jean-François Lemay et al. · 2023 · International Journal of Molecular Sciences
80. Structure-based discovery of novel P-glycoprotein inhibitors targeting the nucleotide binding domains
    Laust Moesgaard, Maria L. Pedersen, Carsten Uhd Nielsen, Jacob Kongsted · 2023 · Scientific Reports
81. AutoMolDesigner for Antibiotic Discovery: An AI-Based Open-Source Software for Automated Design of Small-Molecule Antibiotics
    Tao Shen, Jiale Guo, Zunsheng Han, Gao Zhang, Qingxin Liu, Xinxin Si, Dongmei Wang, Song Wu, Jie Xia · 2024 · Journal of Chemical Information and Modeling
82. Electrostatic Similarities between Protein and Small Molecule Ligands Facilitate the Design of Protein-Protein Interaction Inhibitors
    Arnout R. D. Voet, Francois Berenger, Kam Y. J. Zhang · 2013 · PLoS ONE
83. Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles
    Robert V. Swift, Siti Azma Jusoh, Tavina L. Offutt, Eric S. Li, Rommie E. Amaro · 2016 · Journal of Chemical Information and Modeling
84. Assessing GPCR homology models constructed from templates of various transmembrane sequence identities: Binding mode prediction and docking enrichment
    Jason Siau Ee Loo, Abigail L. Emtage, Kar Weng Ng, Alene S.J. Yong, Stephen W. Doughty · 2017 · Journal of Molecular Graphics and Modelling
85. Homology Modeling Informs Ligand Discovery for the Glutamine Transporter ASCT2
    Rachel‐Ann A. Garibsingh, Nicholas James Otte, Elias Ndaru, Claire Colas, Christof T. Grewer, Jeff Holst, Avner Schlessinger · 2018 · Frontiers in Chemistry
86. METADOCK 2: a high-throughput parallel metaheuristic scheme for molecular docking
    Baldomero Imbernón, Antonio Serrano, Andrés Bueno-Crespo, José Luis Abellán, Horacio Pérez‐Sánchez, José Maria Cecilia · 2020 · Bioinformatics
87. Learning from Docked Ligands: Ligand-Based Features Rescue Structure-Based Scoring Functions When Trained on Docked Poses
    Fergus Boyles, Charlotte Mary Deane, Garrett M. Morris · 2021 · Journal of Chemical Information and Modeling
88. Epidermal growth factor receptor ( EGFR ) structure‐based bioactive pharmacophore models for identifying next‐generation inhibitors against clinically relevant EGFR mutations
    Pooja S. Panicker, Anu Rohit Melge, Lalitha Biswas, Keechilat Pavithran, C. Gopi Mohan · 2017 · Chemical Biology & Drug Design
89. Concepts and Applications of Conformal Prediction in Computational Drug Discovery
    Isidro Cortés‐Ciriano, Andreas Bender · 2019 · arXiv (Cornell University)
90. Report on an NIH Workshop on Ultralarge Chemistry Databases
    Wendy A. Warr · 2021 · ChemRxiv
91. Machine learning accelerates pharmacophore-based virtual screening of MAO inhibitors
    Marcin Cieślak, Tomasz Danel, Olga I. Krzysztynska‐Kuleta, Justyna Kalinowska‐Tłuścik · 2024 · Scientific Reports
92. Accurate prediction of protein–ligand interactions by combining physical energy functions and graph-neural networks
    Yi-Yu Hong, Junsu Ha, Jaemin Sim, C. Lim, Kwang-Seok Oh, Ramakrishnan Chandrasekaran, Bomin Kim, Jieun Choi, Jun-Su Ko, Woong-Hee Shin et al. · 2024 · Journal of Cheminformatics
93. Guided multi-objective generative AI to enhance structure-based drug design
    Amit Kadan, Kevin Ryczko, Erika Lloyd, Adrián E. Roitberg, Takeshi Yamazaki · 2025 · Chemical Science
94. Multimodal fusion with relational learning for molecular property prediction
    Zhengyang Zhou, Yunrui Li, Pengyu Hong, Hao Xu · 2025 · Communications Chemistry
95. Discovery of InhA inhibitors with anti-mycobacterial activity through a matched molecular pair approach
    Hironori Kanetaka, Yuji Koseki, Junichi Taira, Tomohiro Umei, Hideyuki Komatsu, Hiroshi Sakamoto, Gülçin Gülten, James C. Sacchettini, Mitsuru Kitamura, Shunsuke Aoki · 2015 · European Journal of Medicinal Chemistry
96. Strategies of Virtual Screening in Medicinal Chemistry
    Giovanna Ilaria Passeri, Daniela Trisciuzzi, Domenico Alberga, Lydia Siragusa, Francesco Leonetti, Giuseppe Felice Mangiatordi, Orazio Nicolotti · 2017 · International Journal of Quantitative Structure-Property Relationships
97. Combined pharmacophore, virtual screening and molecular dynamics studies to identify Bruton’s tyrosine kinase inhibitors
    Seethalakshmi Sakthivel, Habeeb Shaik Mohideen · 2018 · Journal of Biomolecular Structure and Dynamics
98. Natural products repurposing of the H5N1-based lead compounds for the most fit inhibitors against 3C-like protease of SARS-CoV-2
    Arli Aditya Parikesit, Rizky Nurdiansyah · 2021 · Journal of Pharmacy & Pharmacognosy Research
99. Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing
    Panagiotis I. Koukos, Manon F. Réau, Alexandre M. J. J. Bonvin · 2021 · Journal of Chemical Information and Modeling
100. pdCSM-GPCR: predicting potent GPCR ligands with graph-based signatures
     João Paulo Linhares Velloso, David Benjamin Ascher, Douglas E. V. Pires · 2021 · Bioinformatics Advances