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  1. Cosolvent molecular dynamics (MD) simulations are molecular dynamics simulations used to identify preferable locations of small organic fragments on a protein target. Most cosolvent molecular dynamics workflow...

    Authors: Olivier Beyens and Hans De Winter
    Citation: Journal of Cheminformatics 2024 16:23
  2. The conversion of chemical structures into computer-readable descriptors, able to capture key structural aspects, is of pivotal importance in the field of cheminformatics and computer-aided drug design. Molecu...

    Authors: Candida Manelfi, Valerio Tazzari, Filippo Lunghini, Carmen Cerchia, Anna Fava, Alessandro Pedretti, Pieter F. W. Stouten, Giulio Vistoli and Andrea Rosario Beccari
    Citation: Journal of Cheminformatics 2024 16:21
  3. REINVENT 4 is a modern open-source generative AI framework for the design of small molecules. The software utilizes recurrent neural networks and transformer architectures to drive molecule generation. These g...

    Authors: Hannes H. Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Alexey Voronov, Lewis H. Mervin and Ola Engkvist
    Citation: Journal of Cheminformatics 2024 16:20
  4. The rapid increase of publicly available chemical structures and associated experimental data presents a valuable opportunity to build robust QSAR models for applications in different fields. However, the comm...

    Authors: Kamel Mansouri, José T. Moreira-Filho, Charles N. Lowe, Nathaniel Charest, Todd Martin, Valery Tkachenko, Richard Judson, Mike Conway, Nicole C. Kleinstreuer and Antony J. Williams
    Citation: Journal of Cheminformatics 2024 16:19
  5. Cell-penetrating peptides (CPPs) are short chains of amino acids that have shown remarkable potential to cross the cell membrane and deliver coupled therapeutic cargoes into cells. Designing and testing differ...

    Authors: António J. Preto, Ana B. Caniceiro, Francisco Duarte, Hugo Fernandes, Lino Ferreira, Joana Mourão and Irina S. Moreira
    Citation: Journal of Cheminformatics 2024 16:18
  6. Modern data mining techniques using machine learning (ML) and deep learning (DL) algorithms have been shown to excel in the regression-based task of materials property prediction using various materials repres...

    Authors: Vishu Gupta, Youjia Li, Alec Peltekian, Muhammed Nur Talha Kilic, Wei-keng Liao, Alok Choudhary and Ankit Agrawal
    Citation: Journal of Cheminformatics 2024 16:17
  7. As scientific digitization advances it is imperative ensuring data is Findable, Accessible, Interoperable, and Reusable (FAIR) for machine-processable data. Ontologies play a vital role in enhancing data FAIRn...

    Authors: Alexander S. Behr, Hendrik Borgelt and Norbert Kockmann
    Citation: Journal of Cheminformatics 2024 16:16
  8. Mass spectrometry (MS) is an analytical technique for molecule identification that can be used for investigating protein-metal complex interactions. Once the MS data is collected, the mass spectra are usually ...

    Authors: Derek Long, Liam Eade, Matthew P. Sullivan, Katharina Dost, Samuel M. Meier-Menches, David C. Goldstone, Christian G. Hartinger, Jörg S. Wicker and Katerina Taškova
    Citation: Journal of Cheminformatics 2024 16:15
  9. Conventional machine learning (ML) and deep learning (DL) play a key role in the selectivity prediction of kinase inhibitors. A number of models based on available datasets can be used to predict the kinase pr...

    Authors: Jiangxia Wu, Yihao Chen, Jingxing Wu, Duancheng Zhao, Jindi Huang, MuJie Lin and Ling Wang
    Citation: Journal of Cheminformatics 2024 16:13
  10. The drug discovery of G protein-coupled receptors (GPCRs) superfamily using computational models is often limited by the availability of protein three-dimensional (3D) structures and chemicals with experimenta...

    Authors: Wei-Cheng Huang, Wei-Ting Lin, Ming-Shiu Hung, Jinq-Chyi Lee and Chun-Wei Tung
    Citation: Journal of Cheminformatics 2024 16:10
  11. The enantioselective Brønsted acid-catalyzed α-amidoalkylation reaction is a useful procedure is for the production of new drugs and natural products. In this context, Chiral Phosphoric Acid (CPA) catalysts ar...

    Authors: Paula Carracedo-Reboredo, Eider Aranzamendi, Shan He, Sonia Arrasate, Cristian R. Munteanu, Carlos Fernandez-Lozano, Nuria Sotomayor, Esther Lete and Humberto González-Díaz
    Citation: Journal of Cheminformatics 2024 16:9
  12. Within the realm of contemporary medicinal chemistry, bioisosteres are empirically used to enhance potency and selectivity, improve adsorption, distribution, metabolism, excretion and toxicity profiles of drug...

    Authors: Tinghao Zhang, Shaohua Sun, Runzhou Wang, Ting Li, Bicheng Gan and Yuezhou Zhang
    Citation: Journal of Cheminformatics 2024 16:7
  13. Probing the surface of proteins to predict the binding site and binding affinity for a given small molecule is a critical but challenging task in drug discovery. Blind docking addresses this issue by performin...

    Authors: Sadettin Y. Ugurlu, David McDonald, Huangshu Lei, Alan M. Jones, Shu Li, Henry Y. Tong, Mark S. Butler and Shan He
    Citation: Journal of Cheminformatics 2024 16:5
  14. Evaluation of chemical drug-likeness is essential for the discovery of high-quality drug candidates while avoiding unwarranted biological and clinical trial costs. A high-quality drug candidate should have pro...

    Authors: Yaxin Gu, Yimeng Wang, Keyun Zhu, Weihua Li, Guixia Liu and Yun Tang
    Citation: Journal of Cheminformatics 2024 16:4
  15. The prediction of molecular properties is a crucial aspect in drug discovery that can save a lot of money and time during the drug design process. The use of machine learning methods to predict molecular prope...

    Authors: Łukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gaiński, Jacek Tabor, Igor Podolak, Paweł Morkisz and Stanisław Jastrzębski
    Citation: Journal of Cheminformatics 2024 16:3
  16. Safety is one of the important factors constraining the distribution of clinical drugs on the market. Drug-induced liver injury (DILI) is the leading cause of safety problems produced by drug side effects. The...

    Authors: Soyeon Lee and Sunyong Yoo
    Citation: Journal of Cheminformatics 2024 16:1
  17. Identifying bioactive conformations of small molecules is an essential process for virtual screening applications relying on three-dimensional structure such as molecular docking. For most small molecules, con...

    Authors: Benoit Baillif, Jason Cole, Ilenia Giangreco, Patrick McCabe and Andreas Bender
    Citation: Journal of Cheminformatics 2023 15:124
  18. Knowledge about the 3-dimensional structure, orientation and interaction of chemical compounds is important in many areas of science and technology. X-ray crystallography is one of the experimental techniques ...

    Authors: Antanas Vaitkus, Andrius Merkys, Thomas Sander, Miguel Quirós, Paul A. Thiessen, Evan E. Bolton and Saulius Gražulis
    Citation: Journal of Cheminformatics 2023 15:123
  19. This publication introduces a novel open-access 31P Nuclear Magnetic Resonance (NMR) shift database. With 14,250 entries encompassing 13,730 distinct molecules from 3,648 references, this database offers a compre...

    Authors: Jasmin Hack, Moritz Jordan, Alina Schmitt, Melissa Raru, Hannes Sönke Zorn, Alex Seyfarth, Isabel Eulenberger and Robert Geitner
    Citation: Journal of Cheminformatics 2023 15:122
  20. With the increasingly more important role of machine learning (ML) models in chemical research, the need for putting a level of confidence to the model predictions naturally arises. Several methods for obtaini...

    Authors: Maria H. Rasmussen, Chenru Duan, Heather J. Kulik and Jan H. Jensen
    Citation: Journal of Cheminformatics 2023 15:121
  21. Developing compounds with novel structures is important for the production of new drugs. From an intellectual perspective, confirming the patent status of newly developed compounds is essential, particularly f...

    Authors: Yugo Shimizu, Masateru Ohta, Shoichi Ishida, Kei Terayama, Masanori Osawa, Teruki Honma and Kazuyoshi Ikeda
    Citation: Journal of Cheminformatics 2023 15:120
  22. Time-split cross-validation is broadly recognized as the gold standard for validating predictive models intended for use in medicinal chemistry projects. Unfortunately this type of data is not broadly availabl...

    Authors: Gregory A. Landrum, Maximilian Beckers, Jessica Lanini, Nadine Schneider, Nikolaus Stiefl and Sereina Riniker
    Citation: Journal of Cheminformatics 2023 15:119
  23. The solubility of proteins stands as a pivotal factor in the realm of pharmaceutical research and production. Addressing the imperative to enhance production efficiency and curtail experimental costs, the dema...

    Authors: Long Chen, Rining Wu, Feixiang Zhou, Huifeng Zhang and Jian K. Liu
    Citation: Journal of Cheminformatics 2023 15:118
  24. While the Protein Data Bank (PDB) contains a wealth of structural information on ligands bound to macromolecules, their analysis can be challenging due to the large amount and diversity of data. Here, we prese...

    Authors: Ibrahim Roshan Kunnakkattu, Preeti Choudhary, Lukas Pravda, Nurul Nadzirin, Oliver S. Smart, Qi Yuan, Stephen Anyango, Sreenath Nair, Mihaly Varadi and Sameer Velankar
    Citation: Journal of Cheminformatics 2023 15:117
  25. This paper presents a novel approach called Pharmacophore Activity Delta for extracting outstanding pharmacophores from a chemogenomic dataset, with a specific focus on a kinase target known as BCR-ABL. The me...

    Authors: Etienne Lehembre, Johanna Giovannini, Damien Geslin, Alban Lepailleur, Jean-Luc Lamotte, David Auber, Abdelkader Ouali, Bruno Cremilleux, Albrecht Zimmermann, Bertrand Cuissart and Ronan Bureau
    Citation: Journal of Cheminformatics 2023 15:116
  26. The discovery and utilization of natural products derived from endophytic microorganisms have garnered significant attention in pharmaceutical research. While remarkable progress has been made in this field ea...

    Authors: Hong-Quan Xu, Huan Xiao, Jin-Hui Bu, Yan-Feng Hong, Yu-Hong Liu, Zi-Yue Tao, Shu-Fan Ding, Yi-Tong Xia, E Wu, Zhen Yan, Wei Zhang, Gong-Xing Chen, Feng Zhu and Lin Tao
    Citation: Journal of Cheminformatics 2023 15:115
  27. Prediction of chemical shift in NMR using machine learning methods is typically done with the maximum amount of data available to achieve the best results. In some cases, such large amounts of data are not ava...

    Authors: Herman Rull, Markus Fischer and Stefan Kuhn
    Citation: Journal of Cheminformatics 2023 15:114
  28. While a multitude of deep generative models have recently emerged there exists no best practice for their practically relevant validation. On the one hand, novel de novo-generated molecules cannot be refuted by r...

    Authors: Koichi Handa, Morgan C. Thomas, Michiharu Kageyama, Takeshi Iijima and Andreas Bender
    Citation: Journal of Cheminformatics 2023 15:112
  29. In chemistry-related disciplines, a vast repository of molecular structural data has been documented in scientific publications but remains inaccessible to computational analyses owing to its non-machine-reada...

    Authors: Chong Zhou, Wei Liu, Xiyue Song, Mengling Yang and Xiaowang Peng
    Citation: Journal of Cheminformatics 2023 15:111
  30. BBPs have the potential to facilitate the delivery of drugs to the brain, opening up new avenues for the development of treatments targeting diseases of the central nervous system (CNS). The obstacle faced in ...

    Authors: Ansar Naseem, Fahad Alturise, Tamim Alkhalifah and Yaser Daanial Khan
    Citation: Journal of Cheminformatics 2023 15:110
  31. The discovery of both distinctive lead molecules and novel drug targets is a great challenge in drug discovery, which particularly accounts for orphan diseases. Huntington’s disease (HD) is an orphan, neurodeg...

    Authors: Sven Marcel Stefan, Jens Pahnke and Vigneshwaran Namasivayam
    Citation: Journal of Cheminformatics 2023 15:109
  32. Plants are one of the primary sources of natural products for drug development. However, despite centuries of research, only a limited region of the phytochemical space has been studied. To understand the scop...

    Authors: Daniel Domingo-Fernández, Yojana Gadiya, Sarah Mubeen, David Healey, Bryan H. Norman and Viswa Colluru
    Citation: Journal of Cheminformatics 2023 15:107
  33. Deep learning models have proven to be a powerful tool for the prediction of molecular properties for applications including drug design and the development of energy storage materials. However, in order to le...

    Authors: Tianzhixi Yin, Gihan Panapitiya, Elizabeth D. Coda and Emily G. Saldanha
    Citation: Journal of Cheminformatics 2023 15:105
  34. Identifying the molecular formula and fragmentation reactions of an unknown compound from its mass spectrum is crucial in areas such as natural product chemistry and metabolomics. We propose a method for ident...

    Authors: Sean Li, Björn Bohman, Gavin R. Flematti and Dylan Jayatilaka
    Citation: Journal of Cheminformatics 2023 15:104
  35. Docking of large compound collections becomes an important procedure to discover new chemical entities. Screening of large sets of compounds may also occur in de novo design projects guided by molecular dockin...

    Authors: Guzel Minibaeva, Aleksandra Ivanova and Pavel Polishchuk
    Citation: Journal of Cheminformatics 2023 15:102
  36. Science and art have been connected for centuries. With the development of new computational methods, new scientific disciplines have emerged, such as computational chemistry, and related fields, such as chemi...

    Authors: Daniela Gaytán-Hernández, Ana L. Chávez-Hernández, Edgar López-López, Jazmín Miranda-Salas, Fernanda I. Saldívar-González and José L. Medina-Franco
    Citation: Journal of Cheminformatics 2023 15:100
  37. A reliable and practical determination of a chemical species’ solubility in water continues to be examined using empirical observations and exhaustive experimental studies alone. Predictions of chemical solubi...

    Authors: Arash Tayyebi, Ali S Alshami, Zeinab Rabiei, Xue Yu, Nadhem Ismail, Musabbir Jahan Talukder and Jason Power
    Citation: Journal of Cheminformatics 2023 15:99