We describe a novel freely available web server Base of Bioisosterically Exchangeable Replacements (BoBER), which implements an interface to a database of bioisosteric and scaffold hopping replacements. Bioisosterism and scaffold hopping are key concepts in drug design and optimization, and can be defined as replacements of biologically active compound's fragments with other fragments to improve activity, reduce toxicity, change bioavailability or to diversify the scaffold space. Our web server enables fast and user-friendly searches for bioisosteric and scaffold replacements which were obtained by mining the whole Protein Data Bank. The working of the web server is presented on an existing MurF inhibitor as example. BoBER web server enables medicinal chemists to quickly search for and get new and unique ideas about possible bioisosteric or scaffold hopping replacements that could be used to improve hit or lead drug-like compounds.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5727005 | PMC |
http://dx.doi.org/10.1186/s13321-017-0251-x | DOI Listing |
HardwareX
March 2025
INRAE - French National Research Institute for Agriculture, Food and Environment, REVERSAAL Research Unit, 5 rue de la Doua, CS 20244, 69625 Villeurbanne Cedex, France.
Sensors play an important role in both the continuous monitoring and intermittent analyses, which are essential for the study of wastewater treatment plant management and conducting related research. Given the significant environmental impact of the issues involved, accurate measurement of the volume of water flowing into and out of treatment plants is a key parameter for plant management, ecotoxicological studies and academic research programs. Traditionally, flow measurements have been based on calibrated weirs or venturi flumes, using water level measurements for conversion into flow, according to established relationships.
View Article and Find Full Text PDFBioinformatics
January 2025
Biocomputing Group, University of Bologna, Italy.
Motivation: The knowledge of protein stability upon residue variation is an important step for functional protein design and for understanding how protein variants can promote disease onset. Computational methods are important to complement experimental approaches and allow a fast screening of large datasets of variations.
Results: In this work we present DDGemb, a novel method combining protein language model embeddings and transformer architectures to predict protein ΔΔG upon both single- and multi-point variations.
Brief Bioinform
November 2024
Institute of Clinical Science, Zhongshan Hospital, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Intelligent Medicine Institute, School of Life Sciences, Fudan University, No. 180 Fenglin Road, Shanghai 200032, China.
Nuclear receptors (NRs) are a class of essential proteins that regulate the expression of specific genes and are associated with multiple diseases. In silico methods for prescreening potential NR binders with predictive binding ability are highly desired for NR-related drug development but are rarely reported. Here, we present the PbsNRs (Predicting binders and scaffolds for Nuclear Receptors), a user-friendly web server designed to predict the potential NR binders and scaffolds through proteochemometric modeling.
View Article and Find Full Text PDFMethods
January 2025
Department of Physiology, Ajou University School of Medicine, Suwon 16499 Republic of Korea; Department of Molecular Science and Technology, Ajou University, Suwon 16499 Republic of Korea. Electronic address:
Pancreatic α-amylase breaks down starch into isomaltose and maltose, which are further hydrolyzed by α-glucosidase in the intestine into monosaccharides, rapidly raising blood sugar levels and contributing to type 2 diabetes mellitus (T2DM). Synthetic inhibitors of carbohydrate-digesting enzymes are used to manage T2DM but may harm organ function over time. Bioactive peptides offer a safer alternative, avoiding such adverse effects.
View Article and Find Full Text PDFExpert Rev Proteomics
January 2025
Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA.
Introduction: Molecular recognition features (MoRFs) are regions in protein sequences that undergo induced folding upon binding partner molecules. MoRFs are common in nature and can be predicted from sequences based on their distinctive sequence signatures.
Areas Covered: We overview twenty years of progress in the sequence-based prediction of MoRFs which resulted in the development of 25 predictors of MoRFs that interact with proteins, peptides and lipids.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!