Prediction of Protein Metal Binding Sites Using Deep Neural Networks
Sign Up to like & getrecommendations! Published in 2019 at "Molecular Informatics"
DOI: 10.1002/minf.201800169
Abstract: Metals have crucial roles for many physiological, pathological and diagnostic processes. Metal binding proteins or metalloproteins are important for metabolism functions. The proteins that reach the three‐dimensional structure by folding show which vital function is… read more here.
Keywords: metal binding; prediction protein; metal; binding sites ... See more keywords
The computational prediction of protein assemblies.
Sign Up to like & getrecommendations! Published in 2017 at "Current opinion in structural biology"
DOI: 10.1016/j.sbi.2017.10.006
Abstract: The function of proteins in the cell is almost always mediated by their interaction with different partners, including other proteins, nucleic acids or small organic molecules. The ability of identifying all of them is an… read more here.
Keywords: protein; protein assemblies; prediction protein; computational prediction ... See more keywords
Machine Learning for Efficient Prediction of Protein Redox Potential: The Flavoproteins Case
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Chemical Information and Modeling"
DOI: 10.1021/acs.jcim.2c00858
Abstract: Determining the redox potentials of protein cofactors and how they are influenced by their molecular neighborhoods is essential for basic research and many biotechnological applications, from biosensors and biocatalysis to bioremediation and bioelectronics. The laborious… read more here.
Keywords: redox potential; protein redox; machine learning; prediction protein ... See more keywords
Prediction of Protein Configurational Entropy (Popcoen).
Sign Up to like & getrecommendations! Published in 2018 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.7b01079
Abstract: A knowledge-based method for configurational entropy prediction of proteins is presented; this methodology is extremely fast, compared to previous approaches, because it does not involve any type of configurational sampling. Instead, the configurational entropy of… read more here.
Keywords: entropy; prediction protein; protein configurational; popcoen prediction ... See more keywords
Prediction of protein structures, functions and interactions using the IntFOLD7, MultiFOLD and ModFOLDdock servers.
Sign Up to like & getrecommendations! Published in 2023 at "Nucleic acids research"
DOI: 10.1093/nar/gkad297
Abstract: The IntFOLD server based at the University of Reading has been a leading method over the past decade in providing free access to accurate prediction of protein structures and functions. In a post-AlphaFold2 world, accurate… read more here.
Keywords: protein structures; prediction protein; modfolddock; structures functions ... See more keywords
Detailed prediction of protein sub-nuclear localization
Sign Up to like & getrecommendations! Published in 2019 at "BMC Bioinformatics"
DOI: 10.1186/s12859-019-2790-9
Abstract: BackgroundSub-nuclear structures or locations are associated with various nuclear processes. Proteins localized in these substructures are important to understand the interior nuclear mechanisms. Despite advances in high-throughput methods, experimental protein annotations remain limited. Predictions of… read more here.
Keywords: protein; nuclear localization; prediction protein; sub nuclear ... See more keywords
FALCON2: a web server for high-quality prediction of protein tertiary structures
Sign Up to like & getrecommendations! Published in 2021 at "BMC Bioinformatics"
DOI: 10.1186/s12859-021-04353-8
Abstract: Background Accurate prediction of protein tertiary structures is highly desired as the knowledge of protein structures provides invaluable insights into protein functions. We have designed two approaches to protein structure prediction, including a template-based modeling… read more here.
Keywords: protein; high quality; prediction protein; structure ... See more keywords
Ten quick tips for sequence-based prediction of protein properties using machine learning
Sign Up to like & getrecommendations! Published in 2022 at "PLOS Computational Biology"
DOI: 10.1371/journal.pcbi.1010669
Abstract: The ubiquitous availability of genome sequencing data explains the popularity of machine learning-based methods for the prediction of protein properties from their amino acid sequences. Over the years, while revising our own work, reading submitted… read more here.
Keywords: sequence based; prediction protein; machine; machine learning ... See more keywords
Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Bioengineering and Biotechnology"
DOI: 10.3389/fbioe.2020.00635
Abstract: The G Protein-Coupled Receptor (GPCR) family consists of more than 800 different members. In this article, we attempt to use the physicochemical properties of Composition, Transition, Distribution (CTD) to represent GPCRs. The dimensionality reduction method… read more here.
Keywords: protein; reduction; mrmd2; prediction protein ... See more keywords
ProTstab2 for Prediction of Protein Thermal Stabilities
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Molecular Sciences"
DOI: 10.3390/ijms231810798
Abstract: The stability of proteins is an essential property that has several biological implications. Knowledge about protein stability is important in many ways, ranging from protein purification and structure determination to stability in cells and biotechnological… read more here.
Keywords: protein thermal; protstab2 prediction; prediction protein; stability ... See more keywords