Computational methods are required for prediction of non-coding RNAs (ncRNAs), which are involved in many biological processes, especially at post-transcriptional level. Among these ncRNAs, miRNAs have been largely studied and biologists need efficient and fast tools for their identification. In particular, ab initio methods are usually required when predicting novel miRNAs. Here we present a web server dedicated for miRNA precursors identification at a large scale in genomes. It is based on an algorithm called miRNAFold that allows predicting miRNA hairpin structures quickly with high sensitivity. miRNAFold is implemented as a web server with an intuitive and user-friendly interface, as well as a standalone version. The web server is freely available at: http://EvryRNA.ibisc.univ-evry.fr/miRNAFold.
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http://dx.doi.org/10.1093/nar/gkw459 | DOI Listing |
J Chem Inf Model
January 2025
Department of Grain Science and Industry, Kansas State University, Manhattan, Kansas 66506, United States.
Cell-penetrating peptides (CPPs) are short peptides capable of penetrating cell membranes, making them valuable for drug delivery and intracellular targeting. Accurate prediction of CPPs can streamline experimental validation in the lab. This study aims to assess pretrained protein language models (pLMs) for their effectiveness in representing CPPs and develop a reliable model for CPP classification.
View Article and Find Full Text PDFPLoS One
January 2025
Special Infectious Agents Unit-BSL3, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
The ongoing increase in the prevalence and mutation rate of the influenza virus remains a critical global health issue. A promising strategy for antiviral drug development involves targeting the RNA-dependent RNA polymerase, specifically the PB2-cap binding domain of Influenza A H5N1. This study employs an in-silico approach to inhibit this domain, crucial for viral replication, using potential inhibitors derived from marine bacterial compounds.
View Article and Find Full Text PDFAsian Pac J Cancer Prev
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Cachar Cancer Hospital and Research Center, NS Avenue, Meherpur, Silchar, Assam, India.
Objective: Cancer remains a leading cause of morbidity and mortality globally, with India experiencing a significant cancer burden. Effective population-based cancer screening is crucial for early detection and reduction of cancer-related deaths. This study aims to develop a mobile application-based Cancer Screening and Surveillance System (CSMS) to enhance the efficiency and effectiveness of population-based cancer screening by community health workers (CHWs).
View Article and Find Full Text PDFInnovation (Camb)
January 2025
AIM Center, College of Life Sciences and Technology, Beijing University of Chemical Technology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Predicting free energy changes (ΔΔG) is essential for enhancing our understanding of protein evolution and plays a pivotal role in protein engineering and pharmaceutical development. While traditional methods offer valuable insights, they are often constrained by computational speed and reliance on biased training datasets. These constraints become particularly evident when aiming for accurate ΔΔG predictions across a diverse array of protein sequences.
View Article and Find Full Text PDFActa Pharmacol Sin
January 2025
Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
Computational target identification plays a pivotal role in the drug development process. With the significant advancements of deep learning methods for protein structure prediction, the structural coverage of human proteome has increased substantially. This progress inspired the development of the first genome-wide small molecule targets scanning method.
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