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- Volume 29, Issue 5, 2022
Current Medicinal Chemistry - Volume 29, Issue 5, 2022
Volume 29, Issue 5, 2022
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A Survey for Predicting ATP Binding Residues of Proteins Using Machine Learning Methods
Authors: Yu-He Yang, Jia-Shu Wang, Shi-Shi Yuan, Meng-Lu Liu, Wei Su, Hao Lin and Zhao-Yue ZhangProtein-ligand interactions are necessary for majority protein functions. Adenosine- 5’-triphosphate (ATP) is one such ligand that plays vital role as a coenzyme in providing energy for cellular activities, catalyzing biological reaction and signaling. Knowing ATP binding residues of proteins is helpful for annotation of protein function and drug design. However, due to the huge amounts of protein sequences influx into databases in the Read More
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The Development of Machine Learning Methods in Discriminating Secretory Proteins of Malaria Parasite
Authors: Ting Liu, Jiamao Chen, Qian Zhang, Kyle Hippe, Cassandra Hunt, Thu Le, Renzhi Cao and Hua TangMalaria caused by Plasmodium falciparum is one of the major infectious diseases in the world. It is essential to exploit an effective method to predict secretory proteins of malaria parasites to develop effective cures and treatment. Biochemical assays can provide details for accurate identification of the secretory proteins, but these methods are expensive and time-consuming. In this paper, we summarized the machi Read More
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Research Progress in Predicting DNA Methylation Modifications and the Relation with Human Diseases
Authors: Chunyan Ao, Lin Gao and Liang YuDNA methylation is an important mode of regulation in epigenetic mechanisms, and it is one of the research foci in the field of epigenetics. DNA methylation modification affects a series of biological processes, such as eukaryotic cell growth, differentiation, and transformation mechanisms, by regulating gene expression. In this review, we systematically summarized the DNA methylation databases, prediction tools for DNA m Read More
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Non-coding RNAs as Novel Biomarkers in Cancer Drug Resistance
Authors: Haixiu Yang, Changlu Qi, Boyan Li and Liang ChengChemotherapy is often the primary and most effective anticancer treatment; however, drug resistance remains a major obstacle to it being curative. Recent studies have demonstrated that non-coding RNAs (ncRNAs), especially microRNAs and long non-coding RNAs, are involved in drug resistance of tumor cells in many ways, such as modulation of apoptosis, drug efflux and metabolism, epithelial-to-mesenchymal transiti Read More
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Review and Comparative Analysis of Machine Learning-based Predictors for Predicting and Analyzing Anti-angiogenic Peptides
Cancer is one of the leading causes of death worldwide and the underlying angiogenesis represents one of the hallmarks of cancer. Efforts are already under way for the discovery of anti-angiogenic peptides (AAPs) as a promising therapeutic route, which tackle the formation of new blood vessels. As such, the identification of AAPs constitutes a viable path for understanding their mechanistic properties pertinent for the disc Read More
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Recent Development of Bioinformatics Tools for microRNA Target Prediction
MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of gene expression. Binding of miRNAs to target mRNAs can repress their translation by inducing the degradation or by inhibiting the translation of the target mRNAs. Highthroughput experimental approaches for miRNA target identification are costly and timeconsuming, depending on various factors. It is vitally important to develo Read More
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Better Performance with Transformer: CPPFormer in the Precise Prediction of Cell-penetrating Peptides
Authors: Yuyang Xue, Xiucai Ye, Lesong Wei, Xin Zhang, Tetsuya Sakurai and Leyi WeiOwing to its superior performance, the Transformer model, based on the 'Encoder- Decoder' paradigm, has become the mainstream model in natural language processing. However, bioinformatics has embraced machine learning and has led to remarkable progress in drug design and protein property prediction. Cell-penetrating peptides (CPPs) are a type of permeable protein that is a convenient 'postman' in drug pen Read More
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Recent Development of Machine Learning Methods in Sumoylation Sites Prediction
Authors: Yi-Wei Zhao, Shihua Zhang and Hui DingSumoylation of proteins is an important reversible post-translational modification of proteins and mediates a variety of cellular processes. Sumo-modified proteins can change their subcellular localization, activity, and stability. In addition, it also plays an important role in various cellular processes such as transcriptional regulation and signal transduction. The abnormal sumoylation is involved in many diseases, including n Read More
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Methicillin-Resistant Staphylococcus Aureus (MRSA) Pyruvate Kinase (PK) Inhibitors and their Antimicrobial Activities
Authors: Jingjing Jia, Yang Luo, Xue Zhong and Ling HeResistance to antibiotics has existed in the health care and community settings. Thus, developing novel antibiotics is urgent. Methicillin-resistant Staphylococcus aureus (MRSA) pyruvate kinase (PK) is crucial for the survival of bacteria, making it a novel antimicrobial target. In the past decade, the most commonly reported PK inhibitors include indole, flavonoid, phenazine derivatives from natural products’ small molecules or the Read More
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The Role of FTO in Tumors and Its Research Progress
More LessBackground: Malignant tumor is a disease that seriously threatens human health. At present, more and more research results show that the pathogenesis of different tumors is very complicated, and the methods of clinical treatment are also diverse. This review analyzes and summarizes the role of fat mass and obesity associated (FTO) gene in different tumors, and provides a reference value for research and drug treatm Read More
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Research Progress on Natural Compounds Exerting an Antidepressant Effect through Anti-inflammatory
Authors: Caixia Yuan, Yucen Yao, Tao Liu, Ying Jin, Chunrong Yang, Xian J. Loh and Zibiao LiDepression is a common mental illness that belongs to the category of emotional disorders that causes serious damage to the health and life of patients, while inflammation is considered to be one of the important factors that cause depression. In this case, it might be important to explore the possible therapeutic approach by using natural compounds exerting an anti-inflammatory and antidepressant effect, which has not Read More
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Volumes & issues
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Volume 32 (2025)
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Volume 31 (2024)
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Volume 30 (2023)
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Volume 29 (2022)
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Volume 28 (2021)
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Volume 27 (2020)
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Volume 26 (2019)
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Volume 25 (2018)
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Volume 24 (2017)
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Volume 23 (2016)
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Volume 22 (2015)
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Volume 21 (2014)
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Volume 20 (2013)
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Volume 19 (2012)
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Volume 18 (2011)
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Volume 17 (2010)
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Volume 16 (2009)
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Volume 15 (2008)
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Volume 14 (2007)
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Volume 13 (2006)
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Volume 12 (2005)
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Volume 11 (2004)
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Volume 10 (2003)
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Volume 9 (2002)
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Volume 8 (2001)
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Volume 7 (2000)
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