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  1. Drug design is an important area of study for pharmaceutical businesses. However, low efficacy, off-target delivery, time consumption, and high cost are challenges and can create barriers that impact this proc...

    Authors: Maryam Abbasi, Beatriz P. Santos, Tiago C. Pereira, Raul Sofia, Nelson R. C. Monteiro, Carlos J. V. Simões, Rui Brito, Bernardete Ribeiro, José L. Oliveira and Joel P. Arrais
    Citation: Journal of Cheminformatics 2022 14:40
  2. Predicting transition state geometries is one of the most challenging tasks in computational chemistry, which often requires expert-based knowledge and permanent human intervention. This short communication re...

    Authors: Bienfait K. Isamura and Kevin A. Lobb
    Citation: Journal of Cheminformatics 2022 14:39
  3. As an alternative to one drug-one target approaches, systems biology methods can provide a deeper insight into the holistic effects of drugs. Network-based approaches are tools of systems biology, that can rep...

    Authors: Barbara Füzi, Rahuman S. Malik-Sheriff, Emma J. Manners, Henning Hermjakob and Gerhard F. Ecker
    Citation: Journal of Cheminformatics 2022 14:37
  4. The translation of images of chemical structures into machine-readable representations of the depicted molecules is known as optical chemical structure recognition (OCSR). There has been a lot of progress over...

    Authors: Henning Otto Brinkhaus, Achim Zielesny, Christoph Steinbeck and Kohulan Rajan
    Citation: Journal of Cheminformatics 2022 14:36
  5. Facing the continuous emergence of new psychoactive substances (NPS) and their threat to public health, more effective methods for NPS prediction and identification are critical. In this study, the pharmacolog...

    Authors: Kedan He
    Citation: Journal of Cheminformatics 2022 14:35

    The Correction to this article has been published in Journal of Cheminformatics 2022 14:42

  6. As efforts to computationally describe and simulate the biochemical world become more commonplace, computer programs that are capable of in silico chemistry play an increasingly important role in biochemical r...

    Authors: Barbara R. Terlouw, Sophie P. J. M. Vromans and Marnix H. Medema
    Citation: Journal of Cheminformatics 2022 14:34
  7. Retention time information is used for metabolite annotation in metabolomic experiments. But its usefulness is hindered by the availability of experimental retention time data in metabolomic databases, and by ...

    Authors: Constantino A. García, Alberto Gil-de-la-Fuente, Coral Barbas and Abraham Otero
    Citation: Journal of Cheminformatics 2022 14:33
  8. Recently, imputation techniques have been adapted to predict activity values among sparse bioactivity matrices, showing improvements in predictive performance over traditional QSAR models. These models are abl...

    Authors: Moritz Walter, Luke N. Allen, Antonio de la Vega de León, Samuel J. Webb and Valerie J. Gillet
    Citation: Journal of Cheminformatics 2022 14:32
  9. The development of deep learning-based optical chemical structure recognition (OCSR) systems has led to a need for datasets of chemical structure depictions. The diversity of the features in the training data ...

    Authors: Henning Otto Brinkhaus, Kohulan Rajan, Achim Zielesny and Christoph Steinbeck
    Citation: Journal of Cheminformatics 2022 14:31
  10. Natural products (NPs) are a valuable source for anti-inflammatory drug discovery. However, they are limited by the unpredictability of the structures and functions. Therefore, computational and data-driven pr...

    Authors: Ruihan Zhang, Shoupeng Ren, Qi Dai, Tianze Shen, Xiaoli Li, Jin Li and Weilie Xiao
    Citation: Journal of Cheminformatics 2022 14:30
  11. Integration of medicinal chemistry data from numerous public resources is an increasingly important part of academic drug discovery and translational research because it can bring a wealth of important knowled...

    Authors: Daniela Dolciami, Eloy Villasclaras-Fernandez, Christos Kannas, Mirco Meniconi, Bissan Al-Lazikani and Albert A. Antolin
    Citation: Journal of Cheminformatics 2022 14:28
  12. Unpredicted drug safety issues constitute the majority of failures in the pharmaceutical industry according to several studies. Some of these preclinical safety issues could be attributed to the non-selective ...

    Authors: Doha Naga, Wolfgang Muster, Eunice Musvasva and Gerhard F. Ecker
    Citation: Journal of Cheminformatics 2022 14:27
  13. Chemical structure generators are used in cheminformatics to produce or enumerate virtual molecules based on a set of boundary conditions. The result can then be tested for properties of interest, such as adhe...

    Authors: Brendan D. McKay, Mehmet Aziz Yirik and Christoph Steinbeck
    Citation: Journal of Cheminformatics 2022 14:24
  14. Drug–drug interaction (DDI) often causes serious adverse reactions and thus results in inestimable economic and social loss. Currently, comprehensive DDI evaluation has become a major challenge in pharmaceutic...

    Authors: Ning-Ning Wang, Xiang-Gui Wang, Guo-Li Xiong, Zi-Yi Yang, Ai-Ping Lu, Xiang Chen, Shao Liu, Ting-Jun Hou and Dong-Sheng Cao
    Citation: Journal of Cheminformatics 2022 14:23
  15. We present several workflows for protein-ligand docking and free energy calculation for use in the workflow management system Galaxy. The workflows are composed of several widely used open-source tools, includ...

    Authors: Simon Bray, Tim Dudgeon, Rachael Skyner, Rolf Backofen, Björn Grüning and Frank von Delft
    Citation: Journal of Cheminformatics 2022 14:22
  16. The introduction of machine learning to small molecule research– an inherently multidisciplinary field in which chemists and data scientists combine their expertise and collaborate - has been vital to making s...

    Authors: Christina Humer, Henry Heberle, Floriane Montanari, Thomas Wolf, Florian Huber, Ryan Henderson, Julian Heinrich and Marc Streit
    Citation: Journal of Cheminformatics 2022 14:21
  17. Chemical space exploration is a major task of the hit-finding process during the pursuit of novel chemical entities. Compared with other screening technologies, computational de novo design has become a popula...

    Authors: Chong Lu, Shien Liu, Weihua Shi, Jun Yu, Zhou Zhou, Xiaoxiao Zhang, Xiaoli Lu, Faji Cai, Ning Xia and Yikai Wang
    Citation: Journal of Cheminformatics 2022 14:19
  18. Molecular optimization aims to improve the drug profile of a starting molecule. It is a fundamental problem in drug discovery but challenging due to (i) the requirement of simultaneous optimization of multiple...

    Authors: Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum and Ola Engkvist
    Citation: Journal of Cheminformatics 2022 14:18
  19. Structure-based drug repositioning has emerged as a promising alternative to conventional drug development. Regardless of the many success stories reported over the past years and the novel breakthroughs on th...

    Authors: Melissa F. Adasme, Sarah Naomi Bolz, Ali Al-Fatlawi and Michael Schroeder
    Citation: Journal of Cheminformatics 2022 14:17
  20. The Janus kinase (JAK) family plays a pivotal role in most cytokine-mediated inflammatory and autoimmune responses via JAK/STAT signaling, and administration of JAK inhibitors is a promising therapeutic strate...

    Authors: Yimeng Wang, Yaxin Gu, Chaofeng Lou, Yuning Gong, Zengrui Wu, Weihua Li, Yun Tang and Guixia Liu
    Citation: Journal of Cheminformatics 2022 14:16
  21. Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-tar...

    Authors: Junjie Wang, NaiFeng Wen, Chunyu Wang, Lingling Zhao and Liang Cheng
    Citation: Journal of Cheminformatics 2022 14:14
  22. Chemical–genetic interaction profiling is a genetic approach that quantifies the susceptibility of a set of mutants depleted in specific gene product(s) to a set of chemical compounds. With the recent advances...

    Authors: Chengyou Liu, Andrew M. Hogan, Hunter Sturm, Mohd Wasif Khan, Md. Mohaiminul Islam, A. S. M. Zisanur Rahman, Rebecca Davis, Silvia T. Cardona and Pingzhao Hu
    Citation: Journal of Cheminformatics 2022 14:12
  23. Graph based methods are increasingly important in chemistry and drug discovery, with applications ranging from QSAR to molecular generation. Combining graph neural networks and deep metric learning concepts, w...

    Authors: Damien E. Coupry and Peter Pogány
    Citation: Journal of Cheminformatics 2022 14:11
  24. Deep learning’s automatic feature extraction has been a revolutionary addition to computational drug discovery, infusing both the capabilities of learning abstract features and discovering complex molecular pa...

    Authors: Arash Keshavarzi Arshadi, Milad Salem, Arash Firouzbakht and Jiann Shiun Yuan
    Citation: Journal of Cheminformatics 2022 14:10
  25. A key concept in drug design is how natural variants, especially the ones occurring in the binding site of drug targets, affect the inter-individual drug response and efficacy by altering binding affinity. The...

    Authors: Ammar Ammar, Rachel Cavill, Chris Evelo and Egon Willighagen
    Citation: Journal of Cheminformatics 2022 14:8
  26. In this work we explore the properties which make many real-life global optimization problems extremely difficult to handle, and some of the common techniques used in literature to address them. We then introd...

    Authors: Michael Freitas Gustavo and Toon Verstraelen
    Citation: Journal of Cheminformatics 2022 14:7
  27. In the era of data science, data-driven algorithms have emerged as powerful platforms that can consolidate bioisosteric rules for preferential modifications on small molecules with a common molecular scaffold....

    Authors: Hadar Grimberg, Vinay S. Tiwari, Benjamin Tam, Lihi Gur-Arie, Daniela Gingold, Lea Polachek and Barak Akabayov
    Citation: Journal of Cheminformatics 2022 14:4
  28. Given an objective function that predicts key properties of a molecule, goal-directed de novo molecular design is a useful tool to identify molecules that maximize or minimize said objective function. Nonethel...

    Authors: Alan Kerstjens and Hans De Winter
    Citation: Journal of Cheminformatics 2022 14:3
  29. Human oral bioavailability (HOB) is a key factor in determining the fate of new drugs in clinical trials. HOB is conventionally measured using expensive and time-consuming experimental tests. The use of comput...

    Authors: Min Wei, Xudong Zhang, Xiaolin Pan, Bo Wang, Changge Ji, Yifei Qi and John Z. H. Zhang
    Citation: Journal of Cheminformatics 2022 14:1
  30. In this work, we introduce TorsiFlex, a user-friendly software written in Python 3 and designed to find all the torsional conformers of flexible acyclic molecules in an automatic fashion. For the mapping of the t...

    Authors: David Ferro-Costas, Irea Mosquera-Lois and Antonio Fernández-Ramos
    Citation: Journal of Cheminformatics 2021 13:100

    The Correction to this article has been published in Journal of Cheminformatics 2022 14:13

  31. The thermal shift assay (TSA)—also known as differential scanning fluorimetry (DSF), thermofluor, and Tm shift—is one of the most popular biophysical screening techniques used in fragment-based ligand discovery (...

    Authors: Errol L. G. Samuel, Secondra L. Holmes and Damian W. Young
    Citation: Journal of Cheminformatics 2021 13:99
  32. Chemical patents are a commonly used channel for disclosing novel compounds and reactions, and hence represent important resources for chemical and pharmaceutical research. Key chemical data in patents is ofte...

    Authors: Zenan Zhai, Christian Druckenbrodt, Camilo Thorne, Saber A. Akhondi, Dat Quoc Nguyen, Trevor Cohn and Karin Verspoor
    Citation: Journal of Cheminformatics 2021 13:97
  33. With the increase in applications of machine learning methods in drug design and related fields, the challenge of designing sound test sets becomes more and more prominent. The goal of this challenge is to hav...

    Authors: Jaak Simm, Lina Humbeck, Adam Zalewski, Noe Sturm, Wouter Heyndrickx, Yves Moreau, Bernd Beck and Ansgar Schuffenhauer
    Citation: Journal of Cheminformatics 2021 13:96
  34. Predicting compound–protein interactions (CPIs) is of great importance for drug discovery and repositioning, yet still challenging mainly due to the sparse nature of CPI matrixes, resulting in poor generalizat...

    Authors: Xinyu Bai and Yuxin Yin
    Citation: Journal of Cheminformatics 2021 13:95
  35. As safety is one of the most important properties of drugs, chemical toxicology prediction has received increasing attentions in the drug discovery research. Traditionally, researchers rely on in vitro and in ...

    Authors: Jiarui Chen, Yain-Whar Si, Chon-Wai Un and Shirley W. I. Siu
    Citation: Journal of Cheminformatics 2021 13:93
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