Review
Oncology
Yuhao Zhao, Mao Yang, Shijia Wang, Sk Jahir Abbas, Junzhe Zhang, Yongsheng Li, Rong Shao, Yingbin Liu
Summary: This review focuses on the mechanistic insights of DNA, histone, and RNA methylation in regulating the progression of pancreatic cancer. The roles of methylation regulators in modulating gene expression associated with cell proliferation, invasion, and apoptosis are discussed. Recent clinical trials on methylation drug targeting are also explored. Understanding the novel regulatory mechanisms of methylation modification may offer alternative opportunities to improve therapeutic efficacy in combating this devastating disease.
FRONTIERS IN ONCOLOGY
(2022)
Review
Biochemistry & Molecular Biology
Sarah S. Wang, Jihao Xu, Keely Y. Ji, Chang-Il Hwang
Summary: Pancreatic cancer, particularly pancreatic ductal adenocarcinoma (PDA), is a significant cause of cancer-related deaths in the United States. While genetic mutations driving PDA initiation and progression have been identified, the mechanisms underlying PDA metastasis remain elusive. It is suggested that epigenetic fluctuations may play a critical role in driving PDA metastasis.
Article
Biochemistry & Molecular Biology
Yan Sun, Xin Jin, Junpeng Meng, Feng Guo, Taoyu Chen, Xiaoyan Zhao, Heshui Wu, Dianyun Ren
Summary: PRMT5 contributes to the inactivation of the Hippo signaling pathway in pancreatic cancer by blocking the homodimerization of MST2 through symmetrical dimethylation. Inhibitors of PRMT5 can reactivate the dysregulated Hippo signaling pathway and inhibit the growth of pancreatic cancer.
Article
Biochemistry & Molecular Biology
Hua Huang, Huan Li, Ruining Pan, Sijia Wang, Xinhui Liu
Summary: The discovery of m6A has led to increasing interest in RNA epitranscriptomics. tRNAs play a crucial role in cellular function and their abnormal modifications can lead to diseases. Changes in tRNA modifications are associated with human cancers, including pancreatic cancer, suggesting potential therapeutic targets.
ARCHIVES OF BIOCHEMISTRY AND BIOPHYSICS
(2021)
Article
Gastroenterology & Hepatology
Shounak Majumder, William R. Taylor, Patrick H. Foote, Brianna J. Gysbers, Xiaoming Cao, Douglas W. Mahoney, Kelli N. Burger, Karen A. Doering, Rondell P. Graham, Fergus J. Couch, Gloria M. Petersen, John B. Kisiel
Summary: This study compares the distribution of MDMs in tissue samples from PDAC cases carrying germline mutations with non-carriers, demonstrating high discrimination similar to sporadic PDAC. These results provide a scientific rationale for studying plasma MDMs in high-risk individuals with the aim of developing a minimally-invasive early detection test.
Article
Chemistry, Medicinal
Jianan Li, Keisuke Yanagisawa, Masatake Sugita, Takuya Fujie, Masahito Ohue, Yutaka Akiyama
Summary: Recently, the development of membrane-permeable peptides has been a challenge in discovering cyclic peptide drugs. To address this issue, researchers have constructed CycPeptMPDB, the first web-accessible database for cyclic peptide membrane permeability. This database contains comprehensive information on 7334 cyclic peptides, including their structures and experimentally measured membrane permeability. CycPeptMPDB provides various functions such as online visualization, data analysis, and downloading, making it a valuable platform for membrane permeability research on cyclic peptides.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Medicinal
Jianan Li, Keisuke Yanagisawa, Masatake Sugita, Takuya Fujie, Masahito Ohue, Yutaka Akiyama
Summary: Recently, cyclic peptides have been recognized as breakthrough drugs due to their ability to target undruggable intracellular protein-protein interactions. However, the development of membrane-permeable cyclic peptides remains a challenge. In this study, we constructed CycPeptMPDB, the first web-accessible database of cyclic peptide membrane permeability. The database includes information on 7334 cyclic peptides collected from published papers and pharmaceutical patents. CycPeptMPDB is expected to provide valuable support for membrane permeability research on cyclic peptides.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Review
Chemistry, Multidisciplinary
Zeyu Zhang, Xiu-Jie Wang
Summary: The development of chemical methods has allowed scientists to study the distribution and functions of RNA modifications. N-6-methyladenosine (m(6)A) is the most abundant internal modification on mRNAs in eukaryotic cells and has been extensively studied. Unlike DNA methylation, m(6)A modification on mRNA is reversible and highly dynamic, influenced by various factors. It plays important roles in biological processes.
ACCOUNTS OF CHEMICAL RESEARCH
(2023)
Article
Oncology
Yuki Sunagawa, Masamichi Hayashi, Suguru Yamada, Hiroshi Tanabe, Keisuke Kurimoto, Nobutake Tanaka, Fuminori Sonohara, Yoshikuni Inokawa, Hideki Takami, Mitsuro Kanda, Chie Tanaka, Goro Nakayama, Masahiko Koike, Yasuhiro Kodera
Summary: The study applied molecular surgical margin (MSM) analysis to improve the detection sensitivity of tiny cancerous cells on the surgical specimen surface after pancreatic cancer surgery. Results showed that MSM-positive patients had worse recurrence-free survival and overall survival, while a significant proportion of MSM-negative patients had received neoadjuvant chemotherapy.
CLINICAL EPIGENETICS
(2021)
Review
Gastroenterology & Hepatology
Xing-Yu Liu, Chuan-Hao Guo, Zhi-Yuan Xi, Xin-Qi Xu, Qing-Yang Zhao, Li-Sha Li, Ying Wang
Summary: In pancreatic cancer research, histone methylation plays a crucial role, with writers and erasers potentially serving as therapeutic targets, while further research on reader domains is needed.
WORLD JOURNAL OF GASTROENTEROLOGY
(2021)
Article
Biochemistry & Molecular Biology
Yuyang Hong, Leiqin Liu, Yan Feng, Zhiqiang Zhang, Rui Hou, Qiong Xu, Jiantao Shi
Summary: mHapBrowser is a comprehensive database for visualizing and analyzing DNA methylation haplotypes, providing various functionalities and tools for studying gene expression and classifying tumors based on methylation patterns.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Qingyuan Zheng, Xiao Yu, Qiyao Zhang, Yuting He, Wenzhi Guo
Summary: This study analyzed the genetic characteristics and prognostic value of m1A regulators in pancreatic cancer, finding that changes in these genes are related to clinical stage and can be used as prognostic markers for patients with pancreatic cancer. Additionally, low expression of the ALKBH1 gene is associated with poor prognosis in pancreatic cancer patients, with potential involvement in the mTOR and ErbB signaling pathway.
BIOSCIENCE REPORTS
(2021)
Article
Biochemical Research Methods
Chunting Liu, Jiangning Song, Hiroyuki Ogata, Tatsuya Akutsu
Summary: The study introduces a novel lightweight neural network called MSNet-4mC, which can effectively identify 4mC sites in DNA sequences, achieving significant performance improvement and outperforming other state-of-the-art methods.
Review
Pharmacology & Pharmacy
Chaithanya Ganji, Batoul Farran
Summary: This review focuses on dysregulated genes associated with epigenetic mechanisms in pancreatic cancer progression and resistance, as well as current clinical trials for epigenetic drugs. Combining epigenetic drugs with targeted therapies might represent a promising approach for treating pancreatic cancer.
DRUG DISCOVERY TODAY
(2022)
Article
Oncology
Xiaoli Yin, Lingming Kong, Peng Liu
Summary: This study established prognosis-related molecular subgroups based on DNA methylation signature for pancreatic cancer, developed a five CpG sites model for prognostic prediction, and constructed a nomogram model, which may contribute to precision medicine development, therapeutic efficacy prediction, and clinical decision guidance.
CLINICAL EPIGENETICS
(2021)
Article
Biochemistry & Molecular Biology
Mohini Jaiswal, Ajeet Singh, Shailesh Kumar
Summary: This study developed models based on multiple peptide features to predict plant-derived antimicrobial peptides (AMPs) and integrated these models into a web server called PTPAMP. The web server is capable of classifying queried peptide sequences into four functional activities. The results of the study showed that the performance of the method was superior to current methods, and also identified some features of plant-derived AMPs.
Article
Biochemical Research Methods
Nishant Kumar, Sumeet Patiyal, Shubham Choudhury, Ritu Tomer, Anjali Dhall, Gajendra P. S. Raghava
Summary: In this study, a high-precision method for predicting, designing, and scanning T1DM associated peptides was developed. By using alignment and machine learning techniques, this method provides accurate results. A web server and standalone server were also developed for practical use.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Sumeet Patiyal, Anjali Dhall, Khushboo Bajaj, Harshita Sahu, Gajendra P. S. Raghava
Summary: This paper describes a method called Pprint2 for predicting RNA-interacting residues in proteins. The study found that positively charged amino acids are more prominent in these residues. By using evolutionary profiles and convolutional neural network, the researchers developed a final model that performed well on the validation dataset.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Multidisciplinary Sciences
Shafaque Zahra, Ajeet Singh, Shailesh Kumar
Summary: This article introduces a tool called "tncRNA Toolkit" for accurately identifying tncRNAs and provides detailed information about its functions and features. By using this tool, multiple tncRNA subclasses can be identified, and relevant information is provided, facilitating further exploration of the role of this class of non-coding RNAs in living organisms.
Article
Biology
Anjali Dhall, Sumeet Patiyal, Shubham Choudhury, Shipra Jain, Kashish Narang, Gajendra P. S. Raghava
Summary: Tumor Necrosis Factor alpha (TNF-a) is a pleiotropic pro-inflammatory cytokine that plays a crucial role in immune cell signaling pathways. This study aimed to predict and design TNF-a inducing epitopes using an in silico tool. The proposed models achieved high predictive performance in identifying TNF-a inducing peptides in both human and mouse hosts. Additionally, potential TNF-a inducing peptides were identified in proteins of HIV-1, HIV-2, SARS-CoV-2, and human insulin.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biology
Leimarembi Devi Naorem, Neelam Sharma, Gajendra P. S. Raghava
Summary: This study aims to develop a model for accurately predicting IL-5 inducing antigenic regions in proteins. The study identified certain residues, such as Ile, Asn, and Tyr, that dominate IL-5 inducing peptides. Alignment-based methods provided high precision but limited coverage, while alignment-free methods, including machine learning models, improved performance. The hybrid model combining alignment-based and alignment-free methods achieved excellent results on the validation dataset.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Review
Pharmacology & Pharmacy
Sadhana Tripathi, Neelam Sharma, Leimarembi Devi Naorem, Gajendra P. S. Raghava
Summary: Over the years, numerous vaccines have been developed against viral infections, but a comprehensive database providing detailed information on viral vaccines has been lacking. In this review, we introduce our freely accessible database ViralVacDB, which includes details of viral vaccines, their types, routes of administration, and approving agencies. This repository systematically covers additional information on 422 viral vaccines, including 145 approved vaccines and 277 in clinical trials. We believe that this database will greatly benefit researchers and professionals in pharmaceuticals and immuno-informatics.
DRUG DISCOVERY TODAY
(2023)
Article
Endocrinology & Metabolism
Dashleen Kaur, Akanksha Arora, Sumeet Patiyal, Gajendra Pal Singh Raghava
Summary: Hmrbase2 is a comprehensive platform that provides extensive information on hormones, which is essential for the therapeutics and diagnostics of hormonal diseases.
HORMONES-INTERNATIONAL JOURNAL OF ENDOCRINOLOGY AND METABOLISM
(2023)
Article
Multidisciplinary Sciences
Srija Chakraborty, Rashmi Gangwar, Shafaque Zahra, Nikita Poddar, Amarjeet Singh, Shailesh Kumar
Summary: This study identifies and characterizes the OSCA genes in legumes, providing insights into their role in the interaction between hormone signaling pathways and stress signaling pathways, as well as their involvement in plant growth and development. The expression levels of OSCAs vary under different stress conditions in a tissue-specific manner.
SCIENTIFIC REPORTS
(2023)
Article
Microbiology
Suchet Aggarwal, Anjali Dhall, Sumeet Patiyal, Shubham Choudhury, Akanksha Arora, Gajendra P. S. Raghava
Summary: Phage therapy is a viable alternative to antibiotics for treating drug-resistant bacterial infections. This study aims to accurately predict phage-host interactions to identify potential bacteriophage candidates for treatment. Various models, including alignment-based, alignment-free, hybrid, and ensemble models, were developed and achieved high accuracy rates, with the ensemble model reaching up to 93.5% accuracy on the validation dataset.
FRONTIERS IN MICROBIOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Supriya P. Swain, Shahzaib Ahamad, Nikhil Samarth, Shailza Singh, Dinesh Gupta, Shailesh Kumar
Summary: In this study, three potential natural compounds were identified to combat drug-resistant Mycobacterium tuberculosis. These compounds showed promising results in molecular docking and simulation experiments and could be used in the development of therapies against drug-resistant strains of M.tb.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Biochemistry & Molecular Biology
Mohini Jaiswal, Shailesh Kumar
Summary: The study developed a method called smAMPsTK to identify hidden small open reading frames (smORFs) encoding antimicrobial peptides (AMPs) in the transcriptome data of five different angiosperms. AMPs with diverse functional activities were discovered and found to be widely distributed across the plant kingdom. Domain analysis revealed that almost all AMPs have chitin-binding ability, indicating their potential as antifungal agents.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Review
Biochemistry & Molecular Biology
Nishant Kumar, Nisha Bajiya, Sumeet Patiyal, Gajendra P. S. Raghava
Summary: This paper provides a comprehensive review of the identification of B-cell epitopes (BCEs), covering experimental techniques, historical perspectives, and computational methods. The overall challenge of identifying BCEs is also discussed.
Article
Biochemical Research Methods
Akanksha Arora, Sumeet Patiyal, Neelam Sharma, Naorem Leimarembi Devi, Dashleen Kaur, Gajendra P. S. Raghava
Summary: Non-invasive diagnostics and therapies are important for minimizing patient discomfort. Exosomal proteins are identified as potential biomarkers. This study presents a model for predicting exosomal proteins based on machine learning and sequence motifs. The hybrid model outperforms existing methods and a web server and standalone software have been developed for researchers to predict and discover exosomal proteins.
Article
Biochemistry & Molecular Biology
Ajeet Singh, A. T. Vivek, Kanika Gupta, Shruti Sharma, Shailesh Kumar
Summary: This study constructed a user-friendly database, CoNCRAtlas, by incorporating large-scale RNA-seq and small RNA-seq datasets, and systematically collected lncRNAs and miRNAs from G. hirsutum and G. barbadense. The database provides extensive annotation and is expected to accelerate the study of ncRNAs and inform future breeding programs for cotton improvement.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
