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Relevant bibliographies by topics / Cheminformatics database analysis

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Journal articles

Academic literature on the topic 'Cheminformatics database analysis'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Cheminformatics database analysis"

1

Tiwari, Amit Kumar, Dipika Jaspal, Shradha Deshmukh, and Preeti Mulay. "Cheminformatics: A Patentometric Analysis." French-Ukrainian Journal of Chemistry 10, no. 1 (2022): 13–29. http://dx.doi.org/10.17721/fujcv10i1p13-29.

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Cheminformatics has entrenched itself as a core discipline within chemistry, biology, and allied sciences, more particularly in the field of Drug Design Discovery and Development. The article begins with a patent analysis of the progressing field of cheminformatics from 1996 to early 2021 using the Relecura and Lens patent database. It proceeds with a description of patents in various domains and aspects. The eye-catching mind map shows the landscape of cheminformatics patent search. The results reveal the star rating-wise patent counts and the trends in the sub-technological research areas. A

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2

Vivek-Ananth, R. P., Ajaya Kumar Sahoo, Kavyaa Kumaravel, Karthikeyan Mohanraj, and Areejit Samal. "MeFSAT: a curated natural product database specific to secondary metabolites of medicinal fungi." RSC Advances 11, no. 5 (2021): 2596–607. http://dx.doi.org/10.1039/d0ra10322e.

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3

Xue, Mengzhu, Shoude Zhang, Chaoqian Cai, et al. "Predicting the Drug Safety for Traditional Chinese Medicine through a Comparative Analysis of Withdrawn Drugs Using Pharmacological Network." Evidence-Based Complementary and Alternative Medicine 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/256782.

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As the major issue to limit the use of drugs, drug safety leads to the attrition or failure in clinical trials of drugs. Therefore, it would be more efficient to minimize therapeutic risks if it could be predicted before large-scale clinical trials. Here, we integrated a network topology analysis with cheminformatics measurements on drug information from the DrugBank database to detect the discrepancies between approved drugs and withdrawn drugs and give drug safety indications. Thus, 47 approved drugs were unfolded with higher similarity measurements to withdrawn ones by the same target and c

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4

Williams, Tova N., Melaine A. Kuenemann, George A. Van Den Driessche, Antony J. Williams, Denis Fourches, and Harold S. Freeman. "Toward the Rational Design of Sustainable Hair Dyes Using Cheminformatics Approaches: Step 1. Database Development and Analysis." ACS Sustainable Chemistry & Engineering 6, no. 2 (2018): 2344–52. http://dx.doi.org/10.1021/acssuschemeng.7b03795.

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5

Yu, Tianshi, Tianyang Huang, Leiye Yu, et al. "Exploring the Chemical Space of CYP17A1 Inhibitors Using Cheminformatics and Machine Learning." Molecules 28, no. 4 (2023): 1679. http://dx.doi.org/10.3390/molecules28041679.

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Cytochrome P450 17A1 (CYP17A1) is one of the key enzymes in steroidogenesis that produces dehydroepiandrosterone (DHEA) from cholesterol. Abnormal DHEA production may lead to the progression of severe diseases, such as prostatic and breast cancers. Thus, CYP17A1 is a druggable target for anti-cancer molecule development. In this study, cheminformatic analyses and quantitative structure–activity relationship (QSAR) modeling were applied on a set of 962 CYP17A1 inhibitors (i.e., consisting of 279 steroidal and 683 nonsteroidal inhibitors) compiled from the ChEMBL database. For steroidal inhibito

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6

Liang, Jihao, Yang Zheng, Xin Tong, Naixue Yang, and Shaoxing Dai. "In Silico Identification of Anti-SARS-CoV-2 Medicinal Plants Using Cheminformatics and Machine Learning." Molecules 28, no. 1 (2022): 208. http://dx.doi.org/10.3390/molecules28010208.

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of COVID-19, is spreading rapidly and has caused hundreds of millions of infections and millions of deaths worldwide. Due to the lack of specific vaccines and effective treatments for COVID-19, there is an urgent need to identify effective drugs. Traditional Chinese medicine (TCM) is a valuable resource for identifying novel anti-SARS-CoV-2 drugs based on the important contribution of TCM and its potential benefits in COVID-19 treatment. Herein, we aimed to discover novel anti-SARS-CoV-2 compounds and medicina

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7

Ebejer, Jean-Paul, Michael H. Charlton, and Paul W. Finn. "Are the physicochemical properties of antibacterial compounds really different from other drugs?" Journal of Cheminformatics 8, no. 1 (2016): 30. https://doi.org/10.1186/s13321-016-0143-5.

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<strong>Background: </strong>It is now widely recognized that there is an urgent need for new antibacterial drugs, with novel mechanisms of action, to combat the rise of multi-drug resistant bacteria. However, few new compounds are reaching the market. Antibacterial drug discovery projects often succeed in identifying potent molecules in biochemical assays but have been beset by difficulties in obtaining antibacterial activity. A commonly held view, based on analysis of marketed antibacterial compounds, is that antibacterial drugs possess very different physicochemical properties to other drug

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8

Li, Yuze, Zhe Wang, Shengyao Ma, Xiaowen Tang, and Hanting Zhang. "Chemical Space Exploration and Machine Learning-Based Screening of PDE7A Inhibitors." Pharmaceuticals 18, no. 4 (2025): 444. https://doi.org/10.3390/ph18040444.

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Background/Objectives: Phosphodiesterase 7 (PDE7), a member of the PDE superfamily, selectively catalyzes the hydrolysis of cyclic adenosine 3′,5′-monophosphate (cAMP), thereby regulating the intracellular levels of this second messenger and influencing various physiological functions and processes. There are two subtypes of PDE7, PDE7A and PDE7B, which are encoded by distinct genes. PDE7 inhibitors have been shown to exert therapeutic effects on neurological and respiratory diseases. However, FDA-approved drugs based on the PDE7A inhibitor are still absent, highlighting the need for novel com

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9

Srivastava, Neha, Bhartendu Nath Mishra, and Prachi Srivastava. "In-Silico Identification of Drug Lead Molecule Against Pesticide Exposed-neurodevelopmental Disorders Through Network-Based Computational Model Approach." Current Bioinformatics 14, no. 5 (2019): 460–67. http://dx.doi.org/10.2174/1574893613666181112130346.

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Background: Neurodevelopmental Disorders (NDDs) are impairment of the growth and development of the brain or central nervous system, which occurs at the developmental stage. This can include developmental brain dysfunction, which can manifest as neuropsychiatric problems or impaired motor function, learning, language or non-verbal communication. These include the array of disorder, including: Autism Spectrum Disorders (ASD), Attention Deficit Hyperactivity Disorders (ADHD) etc. There is no particular diagnosis and cure for NDDs. These disorders seem to be result from a combination of genetic,

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10

Chitsazi, Rezvan, Phillip W. Gingrich, James P. Long, Chong Wu, and Bissan Al-Lazikani. "Abstract 4460: OpencanSARchem: chemistry registration and standardization pipeline for FAIR integration of bioassay data." Cancer Research 85, no. 8_Supplement_1 (2025): 4460. https://doi.org/10.1158/1538-7445.am2025-4460.

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Abstract Introduction: The rapid growth of medicinal chemistry and bioactivity data has driven AI advancements but inconsistencies in chemical representation across databases make bioactivity-focused data integration challenging. Tautomerism, a key challenge, complicates chemical registration due to the existence of multiple interchangeable molecular forms, significantly impacting database uniqueness and separating bioactivity data across tautomeric forms. We previously developed a standalone, fully deployable solution to address these challenges (Dolciami et al. 2022), now a core component of

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