Improved Protein Structure Prediction Using a New Multi-Scale Network and Homologous Templates.
Sign Up to like & getrecommendations! Published in 2021 at "Advanced science"
DOI: 10.1002/advs.202102592
Abstract: The accuracy of de novo protein structure prediction has been improved considerably in recent years, mostly due to the introduction of deep learning techniques. In this work, trRosettaX, an improved version of trRosetta for protein… read more here.
Keywords: network; protein structure; scale network; multi scale ... See more keywords
The Combination of Structure Prediction and Experiment for the Exploration of Alkali‐Earth Metal‐Contained Chalcopyrite‐Like IR Nonlinear Optical Material
Sign Up to like & getrecommendations! Published in 2022 at "Advanced Science"
DOI: 10.1002/advs.202106120
Abstract: Design and fabrication of new infrared (IR) nonlinear optical (NLO) materials with balanced properties are urgently needed since commercial chalcopyrite‐like (CL) NLO crystals are suffering from their intrinsic drawbacks. Herein, the first defect‐CL (DCL) alkali‐earth… read more here.
Keywords: structure; nonlinear optical; earth metal; alkali earth ... See more keywords
TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Computer-Aided Molecular Design"
DOI: 10.1007/s10822-017-0047-0
Abstract: Abstract$$\alpha$$α-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in… read more here.
Keywords: transmembrane; bitopic dimers; tmdim improved; structure prediction ... See more keywords
Improving protein secondary structure prediction: the evolutionary optimized classification algorithms
Sign Up to like & getrecommendations! Published in 2019 at "Structural Chemistry"
DOI: 10.1007/s11224-018-1271-5
Abstract: Determining protein structures plays an important role in the field of drug design. Currently, the machine learning methods including artificial neural network (ANN) and support vector machine (SVM) have replaced the experimental techniques to determine… read more here.
Keywords: evolutionary optimized; secondary structure; protein secondary; structure ... See more keywords
Crystal structure prediction of ReN2 under high pressure
Sign Up to like & getrecommendations! Published in 2019 at "Indian Journal of Physics"
DOI: 10.1007/s12648-019-01620-6
Abstract: Three ReN2 phases (Pbcn, C2/m and P4/mbm) are searched to be stable under different pressures by the swarm-intelligence-based CALYPSO method. Pressure-induced phase transitions from Pbcn phase to C2/m phase at 68.5 GPa and C2/m phase to… read more here.
Keywords: crystal structure; prediction ren2; structure prediction; high pressure ... See more keywords
Machine learning in protein structure prediction.
Sign Up to like & getrecommendations! Published in 2021 at "Current opinion in chemical biology"
DOI: 10.1016/j.cbpa.2021.04.005
Abstract: Prediction of protein structure from sequence has been intensely studied for many decades, owing to the problem's importance and its uniquely well-defined physical and computational bases. While progress has historically ebbed and flowed, the past… read more here.
Keywords: machine learning; protein structure; learning protein; structure ... See more keywords
Deep learning methods in protein structure prediction
Sign Up to like & getrecommendations! Published in 2020 at "Computational and Structural Biotechnology Journal"
DOI: 10.1016/j.csbj.2019.12.011
Abstract: Protein Structure Prediction is a central topic in Structural Bioinformatics. Since the ’60s statistical methods, followed by increasingly complex Machine Learning and recently Deep Learning methods, have been employed to predict protein structural information at… read more here.
Keywords: protein structure; deep learning; structure prediction;
A hybrid framework based on genetic algorithm and simulated annealing for RNA structure prediction with pseudoknots
Sign Up to like & getrecommendations! Published in 2020 at "Journal of King Saud University - Computer and Information Sciences"
DOI: 10.1016/j.jksuci.2020.03.005
Abstract: Abstract RNA structure prediction with pseudoknots is an NP-complete problem, in which an optimal RNA structure with minimum energy is to be computed. In past decades, several methods have been developed to predict RNA structure… read more here.
Keywords: prediction pseudoknots; genetic algorithm; structure; rna structure ... See more keywords
Deep learning techniques have significantly impacted protein structure prediction and protein design.
Sign Up to like & getrecommendations! Published in 2021 at "Current opinion in structural biology"
DOI: 10.1016/j.sbi.2021.01.007
Abstract: Protein structure prediction and design can be regarded as two inverse processes governed by the same folding principle. Although progress remained stagnant over the past two decades, the recent application of deep neural networks to… read more here.
Keywords: protein; protein structure; protein design; structure prediction ... See more keywords
RNA modifications in structure prediction - Status quo and future challenges.
Sign Up to like & getrecommendations! Published in 2019 at "Methods"
DOI: 10.1016/j.ymeth.2018.10.019
Abstract: Chemical modifications of RNA nucleotides change their identity and characteristics and thus alter genetic and structural information encoded in the genomic DNA. tRNA and rRNA are probably the most heavily modified genes, and often depend… read more here.
Keywords: rna modifications; prediction status; structure prediction; modifications structure ... See more keywords
Crystal Structure Prediction via Efficient Sampling of the Potential Energy Surface.
Sign Up to like & getrecommendations! Published in 2022 at "Accounts of chemical research"
DOI: 10.1021/acs.accounts.2c00243
Abstract: ConspectusThe crystal structure prediction (CSP) has emerged in recent years as a major theme in research across many scientific disciplines in physics, chemistry, materials science, and geoscience, among others. The central task here is to… read more here.
Keywords: methodology; potential energy; energy; energy surface ... See more keywords