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  1. Mohamad SB, Ong AL, Khairuddin RF, Ripen AM
    In Silico Biol. (Gedrukt), 2010;10(3):145-53.
    PMID: 22430288 DOI: 10.3233/ISB-2010-0423
    Laccases are industrially attractive enzymes and their applications have expanded to the field of bioremediation. The challenge of today's biotechnology in enzymatic studies is to design enzymes that not only have a higher activity but are also more stable and could fit well with the condition requirements. Laccases are known to oxidize non-natural substrates like polycyclic aromatic hydrocarbons (PAHs). We suppose by increasing the hydrophobicity of laccase, it would increase the chance of the enzyme to meet the hydrophobic substrates in a contamination site, therefore increasing the bioremediation efficacy of PAHs from environment. In this attempt, the applications of evolutionary trace (ET), molecular surface accessibility and hydrophobicity analysis on laccase sequences and laccase's crystal structure (1KYA) are described for optimal design of an enzyme with higher hydrophobicity. Our analysis revealed that Q23A, Q45I, N141A, Q237V, N262L, N301V, N331A, Q360L and Q482A could be promising exchanges to be tested in mutagenesis experiments.
  2. Magdy Mohamed Abdelaziz Barakat S, Sallehuddin R, Yuhaniz SS, R Khairuddin RF, Mahmood Y
    PeerJ Comput Sci, 2023;9:e1180.
    PMID: 37547391 DOI: 10.7717/peerj-cs.1180
    BACKGROUND: The development of sequencing technology increases the number of genomes being sequenced. However, obtaining a quality genome sequence remains a challenge in genome assembly by assembling a massive number of short strings (reads) with the presence of repetitive sequences (repeats). Computer algorithms for genome assembly construct the entire genome from reads in two approaches. The de novo approach concatenates the reads based on the exact match between their suffix-prefix (overlapping). Reference-guided approach orders the reads based on their offsets in a well-known reference genome (reads alignment). The presence of repeats extends the technical ambiguity, making the algorithm unable to distinguish the reads resulting in misassembly and affecting the assembly approach accuracy. On the other hand, the massive number of reads causes a big assembly performance challenge.

    METHOD: The repeat identification method was introduced for misassembly by prior identification of repetitive sequences, creating a repeat knowledge base to reduce ambiguity during the assembly process, thus enhancing the accuracy of the assembled genome. Also, hybridization between assembly approaches resulted in a lower misassembly degree with the aid of the reference genome. The assembly performance is optimized through data structure indexing and parallelization. This article's primary aim and contribution are to support the researchers through an extensive review to ease other researchers' search for genome assembly studies. The study also, highlighted the most recent developments and limitations in genome assembly accuracy and performance optimization.

    RESULTS: Our findings show the limitations of the repeat identification methods available, which only allow to detect of specific lengths of the repeat, and may not perform well when various types of repeats are present in a genome. We also found that most of the hybrid assembly approaches, either starting with de novo or reference-guided, have some limitations in handling repetitive sequences as it is more computationally costly and time intensive. Although the hybrid approach was found to outperform individual assembly approaches, optimizing its performance remains a challenge. Also, the usage of parallelization in overlapping and reads alignment for genome assembly is yet to be fully implemented in the hybrid assembly approach.

    CONCLUSION: We suggest combining multiple repeat identification methods to enhance the accuracy of identifying the repeats as an initial step to the hybrid assembly approach and combining genome indexing with parallelization for better optimization of its performance.

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