TY - GEN
T1 - LCR-BLAST—A New Modification of BLAST to Search for Similar Low Complexity Regions in Protein Sequences
AU - Jarnot, Patryk
AU - Ziemska-Legięcka, Joanna
AU - Grynberg, Marcin
AU - Gruca, Aleksandra
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Low Complexity Regions (LCRs) are fragments of protein sequences that are characterized by a small diversity in amino acid composition. LCRs could play important roles in protein functions or they could be relevant to protein structure. However, for many years, low complexity regions were ignored by the scientific community which resulted in lack of algorithms and tools that could be used to analyze this specific type of protein sequences. Recently, researchers became interested in the so-called dark proteome and studies on such kind of proteins revealed that a vast amount of them include LCRs. Therefore, there is an urgent need to adapt existing methods or develop new ones that could be useful for analysis of LCRs, especially in the context of their functional roles in protein sequences. In this paper, we present LCR-BLAST which is a new modification of BLAST designed to search for similarities among LCRs. This modification consists of the following elements: turning on short sequence parameters, turning off compositional based statistics, applying our own version of identity scoring matrix and replacing E-value with mean-score statistics. In order to evaluate the performance of our new modification, we compare the number of similar pairs found by LCR-BLAST with performance of a standard BLAST tool and of BLAST with a specific set of parameters for compositionally biased and short sequences. We show that our new method provides a robust and balanced solution for searching for similarities among LCRs.
AB - Low Complexity Regions (LCRs) are fragments of protein sequences that are characterized by a small diversity in amino acid composition. LCRs could play important roles in protein functions or they could be relevant to protein structure. However, for many years, low complexity regions were ignored by the scientific community which resulted in lack of algorithms and tools that could be used to analyze this specific type of protein sequences. Recently, researchers became interested in the so-called dark proteome and studies on such kind of proteins revealed that a vast amount of them include LCRs. Therefore, there is an urgent need to adapt existing methods or develop new ones that could be useful for analysis of LCRs, especially in the context of their functional roles in protein sequences. In this paper, we present LCR-BLAST which is a new modification of BLAST designed to search for similarities among LCRs. This modification consists of the following elements: turning on short sequence parameters, turning off compositional based statistics, applying our own version of identity scoring matrix and replacing E-value with mean-score statistics. In order to evaluate the performance of our new modification, we compare the number of similar pairs found by LCR-BLAST with performance of a standard BLAST tool and of BLAST with a specific set of parameters for compositionally biased and short sequences. We show that our new method provides a robust and balanced solution for searching for similarities among LCRs.
KW - BLAST
KW - Low complexity regions
KW - Protein sequences
KW - Sequence similarity
UR - https://www.scopus.com/pages/publications/85075879222
U2 - 10.1007/978-3-030-31964-9_16
DO - 10.1007/978-3-030-31964-9_16
M3 - Conference contribution
AN - SCOPUS:85075879222
SN - 9783030319632
T3 - Advances in Intelligent Systems and Computing
SP - 169
EP - 180
BT - Man-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019
A2 - Gruca, Aleksandra
A2 - Deorowicz, Sebastian
A2 - Harezlak, Katarzyna
A2 - Piotrowska, Agnieszka
A2 - Czachórski, Tadeusz
PB - Springer
T2 - 6th International Conference on Man-Machine Interactions, ICMMI 2019
Y2 - 2 October 2019 through 3 October 2019
ER -