[go: up one dir, main page]

Kuhrova et al., 2016 - Google Patents

Computer folding of RNA tetraloops: identification of key force field deficiencies

Kuhrova et al., 2016

View PDF
Document ID
1836120883569201422
Author
Kuhrova P
Best R
Bottaro S
Bussi G
Sponer J
Otyepka M
Banas P
Publication year
Publication venue
Journal of chemical theory and computation

External Links

Snippet

The computer-aided folding of biomolecules, particularly RNAs, is one of the most difficult challenges in computational structural biology. RNA tetraloops are fundamental RNA motifs playing key roles in RNA folding and RNA–RNA and RNA–protein interactions. Although …
Continue reading at pmc.ncbi.nlm.nih.gov (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/16Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/22Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or SNP [Single-Nucleotide Polymorphism] discovery or sequence alignment
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/18Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/28Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/12Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/24Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/70Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
    • G06F19/701Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds for molecular modelling, e.g. calculation and theoretical details of quantum mechanics, molecular mechanics, molecular dynamics, Monte Carlo methods, conformational analysis or the like
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/70Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
    • G06F19/706Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds for drug design with the emphasis on a therapeutic agent, e.g. ligand-biological target interactions, pharmacophore generation
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12NMICRO-ORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING OR MAINTAINING MICRO-ORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
    • C12N15/00Mutation or genetic engineering; DNA or RNA concerning genetic engineering, vectors, e.g. plasmids, or their isolation, preparation or purification; Use of hosts therefor
    • C12N15/09Recombinant DNA-technology
    • C12N15/11DNA or RNA fragments; Modified forms thereof; Non-coding nucleic acids having a biological activity
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12NMICRO-ORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING OR MAINTAINING MICRO-ORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
    • C12N15/00Mutation or genetic engineering; DNA or RNA concerning genetic engineering, vectors, e.g. plasmids, or their isolation, preparation or purification; Use of hosts therefor
    • C12N15/09Recombinant DNA-technology
    • C12N15/10Processes for the isolation, preparation or purification of DNA or RNA

Similar Documents

Publication Publication Date Title
Kuhrova et al. Computer folding of RNA tetraloops: identification of key force field deficiencies
Kuhrova et al. Improving the performance of the amber RNA force field by tuning the hydrogen-bonding interactions
Sponer et al. Molecular dynamics simulations of nucleic acids. From tetranucleotides to the ribosome
Brown et al. Stacking free energies of all DNA and RNA nucleoside pairs and dinucleoside-monophosphates computed using recently revised AMBER parameters and compared with experiment
Galindo-Murillo et al. Assessing the current state of amber force field modifications for DNA
Zhang et al. AMOEBA polarizable atomic multipole force field for nucleic acids
Condon et al. Stacking in RNA: NMR of four tetramers benchmark molecular dynamics
Cesari et al. Fitting corrections to an RNA force field using experimental data
Bergonzo et al. Highly sampled tetranucleotide and tetraloop motifs enable evaluation of common RNA force fields
Tubbs et al. The nuclear magnetic resonance of CCCC RNA reveals a right-handed helix, and revised parameters for AMBER force field torsions improve structural predictions from molecular dynamics
Banás et al. Performance of molecular mechanics force fields for RNA simulations: stability of UUCG and GNRA hairpins
Kührová et al. Computer folding of RNA tetraloops? Are we there yet?
Haldar et al. Insights into stability and folding of GNRA and UNCG tetraloops revealed by microsecond molecular dynamics and well-tempered metadynamics
Beššeová et al. Simulations of A-RNA duplexes. The effect of sequence, solute force field, water model, and salt concentration
Mlýnský et al. Fine-tuning of the AMBER RNA force field with a new term adjusting interactions of terminal nucleotides
Mlýnský et al. Toward convergence in folding simulations of RNA tetraloops: Comparison of enhanced sampling techniques and effects of force field modifications
Mráziková et al. UUCG RNA tetraloop as a formidable force-field challenge for MD simulations
Spasic et al. The Amber ff99 force field predicts relative free energy changes for RNA helix formation
Sponer et al. Quantum chemical studies of nucleic acids: can we construct a bridge to the RNA structural biology and bioinformatics communities?
Zgarbova et al. Noncanonical α/γ Backbone Conformations in RNA and the Accuracy of Their Description by the AMBER Force Field
Wales et al. Improving computational predictions of single-stranded RNA tetramers with revised α/γ torsional parameters for the amber force field
Zhao et al. Nuclear magnetic resonance spectra and AMBER OL3 and ROC-RNA simulations of UCUCGU reveal force field strengths and weaknesses for single-stranded RNA
Wang et al. Determination of base-flipping free-energy landscapes from nonequilibrium stratification
Zhao et al. Nuclear magnetic resonance of single-stranded RNAs and DNAs of CAAU and UCAAUC as benchmarks for molecular dynamics simulations
Mlynsky et al. Simple adjustment of intranucleotide base-phosphate interaction in the OL3 AMBER force field improves RNA simulations