ArticleInternational journal of molecular sciences2022
Application of the MAHDS Method for Multiple Alignment of Highly Diverged Amino Acid Sequences.
Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Effect of a Comparative Analysis of Different Annotations of the Oryza sativa Rice Genome for In Silico Verification of Predicted Promoter Sequences.Doklady. Biochemistry and biophysics · 2025Article
- In Silico Verification of Predicted Potential Promoter Sequences in the Rice (Plants (Basel, Switzerland) · 2023Article
- Classification of Promoter Sequences from Human Genome.International journal of molecular sciences · 2023Article
- Search for Dispersed Repeats in Bacterial Genomes Using an Iterative Procedure.International journal of molecular sciences · 2023Article
- Detection of tandem repeats in the Capsicum annuum genome.DNA research : an international journal for rapid publication of reports on genes and genomes · 2023Article
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2 authors.
Funding
Abstract
The aim of this work was to compare the multiple alignment methods MAHDS, T-Coffee, MUSCLE, Clustal Omega, Kalign, MAFFT, and PRANK in their ability to align highly divergent amino acid sequences. To accomplish this, we created test amino acid sequences with an average number of substitutions per amino acid (x) from 0.6 to 5.6, a total of 81 sets. Comparison of the performance of sequence alignments constructed by MAHDS and previously developed algorithms using the CS and Z score criteria and the benchmark alignment database (BAliBASE) indicated that, although the quality of the alignments built with MAHDS was somewhat lower than that of the other algorithms, it was compensated by greater statistical significance. MAHDS could construct statistically significant alignments of artificial sequences with x ≤ 4.8, whereas the other algorithms (T-Coffee, MUSCLE, Clustal Omega, Kalign, MAFFT, and PRANK) could not perform that at x > 2.4. The application of MAHDS to align 21 families of highly diverged proteins (identity < 20%) from Pfam and HOMSTRAD databases showed that it could calculate statistically significant alignments in cases when the other methods failed. Thus, MAHDS could be used to construct statistically significant multiple alignments of highly divergent protein sequences, which accumulated multiple mutations during evolution.
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