DNA Cryptography using DNA Fragment Assembly and Fragment Key Expansion for Genomic Data

This research proposes a tweaked scheme based on DNA fragment assembly to improve protection over insecure channel. The proposed procedure utilizes binary coding to change over an underlying plaintext into a reference DNA arrangement to deal with the fragmentation. DNA fragment key expansion is applied over the reference DNA sequence to make the short-chain fragments. The redundancy in the long-chain of reference DNA is removed using DNA fragment assembly. A look-up table is generated to store the binary values of overlapped fragments to be reassembled during the encryption and decryption processes to prevent artefacts. Also, it is used in an overlapped sequence to counteract cipher decomposition. The results and comparisons demonstrate that the proposed scheme can balance the three most important characteristics of any DNA masking scheme: payload, capacity, and BPN. Moreover, the potential for cracking the proposed tweaked method is more complex than the current strategies.

A de novo protein structure prediction by iterative partition sampling, topology adjustment, and residue-level distance deviation optimization

Motivation With the great progress of deep learning-based inter-residue contact/distance prediction, the discrete space formed by fragment assembly cannot satisfy the distance constraint well. Thus, the optimal solution of the continuous space may not be achieved. Designing an effective closed-loop continuous dihedral angle optimization strategy that complements the discrete fragment assembly is crucial to improve the performance of the distance-assisted fragment assembly method. Results In this article, we proposed a de novo protein structure prediction method called IPTDFold based on closed-loop iterative partition sampling, topology adjustment and residue-level distance deviation optimization. First, local dihedral angle crossover and mutation operators are designed to explore the conformational space extensively and achieve information exchange between the conformations in the population. Then, the dihedral angle rotation model of loop region with partial inter-residue distance constraints is constructed, and the rotation angle satisfying the constraints is obtained by differential evolution algorithm, so as to adjust the spatial position relationship between the secondary structures. Lastly, the residue distance deviation is evaluated according to the difference between the conformation and the predicted distance, and the dihedral angle of the residue is optimized with biased probability. The final model is generated by iterating the above three steps. IPTDFold is tested on 462 benchmark proteins, 24 FM targets of CASP13, and 20 FM targets of CASP14. Results show that IPTDFold is significantly superior to the distance-assisted fragment assembly method Rosetta_D (Rosetta with distance). In particular, the prediction accuracy of IPTDFold does not decrease as the length of the protein increases. When using the same FastRelax protocol, the prediction accuracy of IPTDFold is significantly superior to that of trRosetta without orientation constraints, and is equivalent to that of the full version of trRosetta. Availability The source code and executable are freely available at https://github.com/iobio-zjut/IPTDFold. Supplementary information Supplementary data are available at Bioinformatics online.

Complementing sequence-derived features with structural information extracted from fragment libraries for protein structure prediction

Background Fragment libraries play a key role in fragment-assembly based protein structure prediction, where protein fragments are assembled to form a complete three-dimensional structure. Rich and accurate structural information embedded in fragment libraries has not been systematically extracted and used beyond fragment assembly. Methods To better leverage the valuable structural information for protein structure prediction, we extracted seven types of structural information from fragment libraries. We broadened the usage of such structural information by transforming fragment libraries into protein-specific potentials for gradient-descent based protein folding and encoding fragment libraries as structural features for protein property prediction. Results Fragment libraires improved the accuracy of protein folding and outperformed state-of-the-art algorithms with respect to predicted properties, such as torsion angles and inter-residue distances. Conclusion Our work implies that the rich structural information extracted from fragment libraries can complement sequence-derived features to help protein structure prediction.

ACES: Analysis of Conservation with Expansive Species

Motivation: An abundance of new reference genomes are becoming available through large-scale sequencing efforts. While the reference FASTA for each genome is available, there is currently no automated mechanism to query a specific sequence across all new reference genomes. Results: We developed ACES (Analysis of Conservation with Expansive Species) as a computational workflow to query specific sequences of interest (e.g., enhancers, promoters, exons) against reference genomes with an available reference FASTA. This automated workflow generates BLAST hits against each of the reference genomes, a multiple sequence alignment file, a graphical fragment assembly file, and a phylogenetic tree file. These data files can then be used by the researcher in several ways to provide key insights into conservation of the query sequence. Availability: ACES is available at https://github.com/TNTurnerLab/ACES

A de novo protein structure prediction by iterative partition sampling, topology adjustment, and residue-level distance deviation optimization

Motivation: With the great progress of deep learning-based inter-residue contact/distance prediction, the discrete space formed by fragment assembly cannot satisfy the distance constraint well. Thus, the optimal solution of the continuous space may not be achieved. Designing an effective closed-loop continuous dihedral angle optimization strategy that complements the discrete fragment assembly is crucial to improve the performance of the distance-assisted fragment assembly method. Results: In this article, we proposed a de novo protein structure prediction method called IPTDFold based on closed-loop iterative partition sampling, topology adjustment and residue-level distance deviation optimization. First, local dihedral angle crossover and mutation operators are designed to explore the conformational space extensively and achieve information exchange between the conformations in the population. Then, the dihedral angle rotation model of loop region with partial inter-residue distance constraints is constructed, and the rotation angle satisfying the constraints is obtained by differential evolution algorithm, so as to adjust the spatial position relationship between the secondary structures. Lastly, the residue distance deviation is evaluated according to the difference between the conformation and the predicted distance, and the dihedral angle of the residue is optimized with biased probability. The final model is generated by iterating the above three steps. IPTDFold is tested on 462 benchmark proteins, 24 FM targets of CASP13, and 20 FM targets of CASP14. Results show that IPTDFold is significantly superior to the distance-assisted fragment assembly method Rosetta_D (Rosetta with distance). In particular, the prediction accuracy of IPTDFold does not decrease as the length of the protein increases. When using the same FastRelax protocol, the prediction accuracy of IPTDFold is significantly superior to that of trRosetta without orientation constraints, and is equivalent to that of the full version of trRosetta.

Limitations of the ABEGO representation: ambiguity between αα-corner and αα-hairpin

SummaryABEGO is a coarse-grained representation for polypeptide backbone dihedral angles. The Ramachandran map is divided into four segments denoted as A, B, E, and G to represent the local conformation of polypeptide chains in the character strings. Although the ABEGO representation is widely used in structural informatics and protein design, it cannot capture minor differences in backbone dihedral angles, which potentially leads to ambiguity between two structurally distinct fragments. Here, we show a nontrivial example of two local motifs that could not be distinguished by their ABEGO representations. We found that two well-known local motifs αα-hairpins and αα-corners are both represented as α-GBB-α and thus indistinguishable in the ABEGO representation, although they show distinct arrangements of the flanking α-helices. We also found that α-GBB-α motifs caused a loss of efficiency in the ABEGO-based fragment-assembly simulations for protein backbone design. Nevertheless, we designed amino-acid sequences that were predicted to fold into the target topologies that contained these α-GBB-α motifs. Our finding that certain local motifs bottleneck the ABEGO-based fragment-assembly simulations for construction of backbone structures suggests that finer representations of backbone torsion angles are required for efficiently generating diverse topologies containing such indistinguishable local motifs.

DNA Fragment Assembly Using Hybridized Catfish PSO

DNA fragment assembly aids in uncovering several aspects of the human DNA, and hence in-turn enables scientists in understanding and curing several hereditary problems. Several computational methods have been proposed to solve this problem. However, the huge size and the NP-hard nature of the problem poses several challenges in proposing a time effective system for fragment assembly. This paper proposes a hybridized catfish PSO model for the process of fragment assembly. PSO algorithm is enhanced by incorporating the catfish particles to enable the model to get out of the local optimal solutions. Further, the local search process has been hybridized to incorporate simulated annealing, such that the model performs faster selection of solutions. This has enabled the proposed model to provide effective results with low computational requirements. Experiments were performed with 10 benchmark instances from GenFrag. The results were compared with state-of-the-art models in literature, and it was identified that the proposed model exhibits high performance in comparatively shorter time.

RNA fragment assembly with experimental restraints

ABSTRACTWe present RNA Masonry, a computer program and a web service for a fully automated assembly of RNA fragments into geometrically plausible models fulfilling user-provided secondary structure constraints and restraints on tertiary contacts and Small Angle X-ray Scattering (SAXS) data. We illustrate the method description with its recent application to structural studies of viral RNAs with SAXS restraints. The program web server is available at http://iimcb.genesilico.pl/[email protected]