title: MSAIndelFR: a scheme for multiple protein sequence alignment using information on indel flanking regions.
abstract: BACKGROUND
  The alignment of multiple protein sequences is one of the most commonly performed tasks in bioinformatics. In spite of considerable research and efforts that have been recently deployed for improving the performance of multiple sequence alignment (MSA) algorithms, finding a highly accurate alignment between multiple protein sequences is still a challenging problem.
  
  
  RESULTS
  We propose a novel and efficient algorithm called, MSAIndelFR, for multiple sequence alignment using the information on the predicted locations of IndelFRs and the computed average log-loss values obtained from IndelFR predictors, each of which is designed for a different protein fold. We demonstrate that the introduction of a new variable gap penalty function based on the predicted locations of the IndelFRs and the computed average log-loss values into the proposed algorithm substantially improves the protein alignment accuracy. This is illustrated by evaluating the performance of the algorithm in aligning sequences belonging to the protein folds for which the IndelFR predictors already exist and by using the reference alignments of the four popular benchmarks, BAliBASE 3.0, OXBENCH, PREFAB 4.0, and SABRE (SABmark 1.65).
  
  
  CONCLUSIONS
  We have proposed a novel and efficient algorithm, the MSAIndelFR algorithm, for multiple protein sequence alignment incorporating a new variable gap penalty function. It is shown that the performance of the proposed algorithm is superior to that of the most-widely used alignment algorithms, Clustal W2, Clustal Omega, Kalign2, MSAProbs, MAFFT, MUSCLE, ProbCons and Probalign, in terms of both the sum-of-pairs and total column metrics.
authors.affiliation: Department of Electrical and Computer Engineering, Concordia University, 1455 De Maisonneuve Blvd. W., Montreal, H3G 1M8, Quebec, Canada. m_alshat@ece.concordia.ca.
authors.forename: Mufleh
authors.initials: M
authors.lastname: Al-Shatnawi
authors.affiliation: Department of Electrical and Computer Engineering, Concordia University, 1455 De Maisonneuve Blvd. W., Montreal, H3G 1M8, Quebec, Canada. omair@ece.concordia.ca.
authors.forename: M Omair
authors.initials: MO
authors.lastname: Ahmad
authors.affiliation: Department of Electrical and Computer Engineering, Concordia University, 1455 De Maisonneuve Blvd. W., Montreal, H3G 1M8, Quebec, Canada. swamy@ece.concordia.ca.
authors.forename: M N S
authors.initials: MN
authors.lastname: Swamy
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D054643:INDEL Mutation / Q000235:genetics*; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins