DNA-base radicals. Their base pairing abilities as calculated by DFTElectronic supplementary information (ESI) available: Single-point energies, zero-point energies and BSSE corrections for guanine, 7,8-dihydro-8-oxoguanine, their radicals and base pairs. See http://www.rsc.org/suppdata/cp/b2/b204842f/

2002 ◽  
Vol 4 (21) ◽  
pp. 5346-5352 ◽  
Author(s):  
J??hannes Reynisson ◽  
Steen Steenken
Keyword(s):  
Single Point ◽  
Zero Point ◽  
Supplementary Information ◽  
Base Pairing ◽  
Base Pairs ◽  
Dna Base ◽  
Bsse Corrections

Improved RNA secondary structure and tertiary base-pairing prediction using evolutionary profile, mutational coupling and two-dimensional transfer learning

2021 ◽  
Author(s):  
Jaswinder Singh ◽  
Kuldip Paliwal ◽  
Tongchuan Zhang ◽  
Jaspreet Singh ◽  
Thomas Litfin ◽  
...  
Keyword(s):  
High Resolution ◽  
Secondary Structure ◽  
Transfer Learning ◽  
Rna Secondary Structure ◽  
Computational Prediction ◽  
Supplementary Information ◽  
Base Pairing ◽  
Base Pairs ◽  
Homologous Sequences ◽  
Non Coding Rnas

Abstract Motivation The recent discovery of numerous non-coding RNAs (long non-coding RNAs, in particular) has transformed our perception about the roles of RNAs in living organisms. Our ability to understand them, however, is hampered by our inability to solve their secondary and tertiary structures in high resolution efficiently by existing experimental techniques. Computational prediction of RNA secondary structure, on the other hand, has received much-needed improvement, recently, through deep learning of a large approximate data, followed by transfer learning with gold-standard base-pairing structures from high-resolution 3-D structures. Here, we expand this single-sequence-based learning to the use of evolutionary profiles and mutational coupling. Results The new method allows large improvement not only in canonical base-pairs (RNA secondary structures) but more so in base-pairing associated with tertiary interactions such as pseudoknots, non-canonical and lone base-pairs. In particular, it is highly accurate for those RNAs of more than 1000 homologous sequences by achieving >0.8 F1-score (harmonic mean of sensitivity and precision) for 14/16 RNAs tested. The method can also significantly improve base-pairing prediction by incorporating artificial but functional homologous sequences generated from deep mutational scanning without any modification. The fully automatic method (publicly available as server and standalone software) should provide the scientific community a new powerful tool to capture not only the secondary structure but also tertiary base-pairing information for building three-dimensional models. It also highlights the future of accurately solving the base-pairing structure by using a large number of natural and/or artificial homologous sequences. Availability and implementation Standalone-version of SPOT-RNA2 is available at https://github.com/jaswindersingh2/SPOT-RNA2. Direct prediction can also be made at https://sparks-lab.org/server/spot-rna2/. The datasets used in this research can also be downloaded from the GITHUB and the webserver mentioned above. Supplementary information Supplementary data are available at Bioinformatics online.

Metal-Mediated DNA Base Pairing: Alternatives to Hydrogen-Bonded Watson–Crick Base Pairs

2012 ◽  
Vol 45 (12) ◽  
pp. 2066-2076 ◽  
Author(s):  
Yusuke Takezawa ◽  
Mitsuhiko Shionoya
Keyword(s):  
Base Pairing ◽  
Base Pairs ◽  
Dna Base ◽  
Hydrogen Bonded

New 2-Oxopyridine/2-Thiopyridine Derivatives Tethered to a Benzotriazole with Cytotoxicity on MCF7 Cell Lines and with Antiviral Activities

2020 ◽  
Vol 17 (2) ◽  
pp. 124-137 ◽  
Author(s):  
Adel Mahmoud Attia ◽  
Ahmed Ibrahin Khodair ◽  
Eman Abdelnasser Gendy ◽  
Mohammed Abu El-Magd ◽  
Yaseen Ali Mosa Mohamed Elshaier
Keyword(s):  
Dna Damage ◽  
Anticancer Agents ◽  
Active Compound ◽  
Docking Study ◽  
Base Pairs ◽  
Dna Base ◽  
Dna Base Pairs ◽  
Antiviral Activities ◽  
Active Methylene ◽  
Damage Study

Background:Perturbation of nucleic acids structures and confirmation by small molecules through intercalation binding is an intriguing application in anticancer therapy. The planar aromatic moiety of anticancer agents was inserted between DNA base pairs leading to change in the DNA structure and subsequent functional arrest.Objective:The final scaffold of the target compounds was annulated and linked to a benzotriazole ring. These new pharmacophoric features were examined as antiviral and anticancer agents against MCF7 and their effect on DNA damage was also assessed.Methods:A new series of fully substituted 2-oxopyridine/2-thioxopyridine derivatives tethered to a benzotriazole moiety (4a-h) was synthesized through Michael cyclization of synthesized α,β- unsaturated compounds (3a-e) with appropriate active methylene derivatives. The DNA damage study was assessed by comet assay. In silico DNA molecular docking was performed using Open Eye software to corroborate the experimental results and to understand molecule interaction at the atomic level.Results:The highest DNA damage was observed in Doxorubicin, followed by 4h, then, 4b, 4g, 4f, 4e, and 4d. The docking study showed that compound 4h formed Hydrogen Bonds (HBs) as a standard ligand with GSK-3. Compound 4h was the most active compound against rotavirus Wa, HAVHM175, and HSV strains with a reduction of 30%, 40%, and 70%, respectively.Conclusion:Compound 4h was the most active compound and could act as a prospective lead molecule for anticancer agent.

On the change of the order od stability of DNA base pairs as a result of the methylation of guanine

1988 ◽  
Vol 53 (9) ◽  
pp. 1943-1945
Author(s):  
Pavel Hobza ◽  
Camille Sandorfy
Keyword(s):  
Ab Initio ◽  
Base Pairs ◽  
Dispersion Energy ◽  
Dna Base ◽  
Dna Base Pairs

The interaction of the 6-O methylguanine cation with cytosine and thymine was studied using the ab initio SCF method in combination with a London type expression for dispersion energy. The structure of the complex formed with cytosine differs from that found previously with guanine itself.

scholarly journals RNA Delivery via DNA-Inspired Janus Base Nanotubes for Extracellular Matrix Penetration

MRS Advances ◽  
2020 ◽  
Vol 5 (16) ◽  
pp. 815-823
Author(s):  
Ian Sands ◽  
Jinhyung Lee ◽  
Wuxia Zhang ◽  
Yupeng Chen
Keyword(s):  
Extracellular Matrix ◽  
Small Rnas ◽  
Base Pairs ◽  
Major Barrier ◽  
Dna Base ◽  
Dna Base Pairs ◽  
Negative Surface ◽  
Negative Surface Charge ◽  
Delivery Vehicles ◽  
Low Cell Density

AbstractRNA delivery into deep tissues with dense extracellular matrix (ECM) has been challenging. For example, cartilage is a major barrier for RNA and drug delivery due to its avascular structure, low cell density and strong negative surface charge. Cartilage ECM is comprised of collagens, proteoglycans, and various other noncollagneous proteins with a spacing of 20nm. Conventional nanoparticles are usually spherical with a diameter larger than 50-60nm (after cargo loading). Therefore, they presented limited success for RNA delivery into cartilage. Here, we developed Janus base nanotubes (JBNTs, self-assembled nanotubes inspired from DNA base pairs) to assemble with small RNAs to form nano-rod delivery vehicles (termed as “Nanopieces”). Nanopieces have a diameter of ∼20nm (smallest delivery vehicles after cargo loading) and a length of ∼100nm. They present a novel breakthrough in ECM penetration due to the reduced size and adjustable characteristics to encourage ECM and intracellular penetration.

scholarly journals Apollo: a sequencing-technology-independent, scalable and accurate assembly polishing algorithm

2020 ◽  
Vol 36 (12) ◽  
pp. 3669-3679 ◽  
Author(s):  
Can Firtina ◽  
Jeremie S Kim ◽  
Mohammed Alser ◽  
Damla Senol Cali ◽  
A Ercument Cicek ◽  
...  
Keyword(s):  
Genome Analysis ◽  
Supplementary Information ◽  
Third Generation ◽  
Sequencing Technology ◽  
Base Pairs ◽  
Sequencing Technologies ◽  
Third Generation Sequencing ◽  
Long Reads ◽  
Generation Sequencing ◽  
Large Genomes

Abstract Motivation Third-generation sequencing technologies can sequence long reads that contain as many as 2 million base pairs. These long reads are used to construct an assembly (i.e. the subject’s genome), which is further used in downstream genome analysis. Unfortunately, third-generation sequencing technologies have high sequencing error rates and a large proportion of base pairs in these long reads is incorrectly identified. These errors propagate to the assembly and affect the accuracy of genome analysis. Assembly polishing algorithms minimize such error propagation by polishing or fixing errors in the assembly by using information from alignments between reads and the assembly (i.e. read-to-assembly alignment information). However, current assembly polishing algorithms can only polish an assembly using reads from either a certain sequencing technology or a small assembly. Such technology-dependency and assembly-size dependency require researchers to (i) run multiple polishing algorithms and (ii) use small chunks of a large genome to use all available readsets and polish large genomes, respectively. Results We introduce Apollo, a universal assembly polishing algorithm that scales well to polish an assembly of any size (i.e. both large and small genomes) using reads from all sequencing technologies (i.e. second- and third-generation). Our goal is to provide a single algorithm that uses read sets from all available sequencing technologies to improve the accuracy of assembly polishing and that can polish large genomes. Apollo (i) models an assembly as a profile hidden Markov model (pHMM), (ii) uses read-to-assembly alignment to train the pHMM with the Forward–Backward algorithm and (iii) decodes the trained model with the Viterbi algorithm to produce a polished assembly. Our experiments with real readsets demonstrate that Apollo is the only algorithm that (i) uses reads from any sequencing technology within a single run and (ii) scales well to polish large assemblies without splitting the assembly into multiple parts. Availability and implementation Source code is available at https://github.com/CMU-SAFARI/Apollo. Supplementary information Supplementary data are available at Bioinformatics online.

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