It is well known
that proteins are the essential part of an oragnism and it plays a
vital role in every process within the cells. Proteins are made up
of amino acids arranged in a linear chain and joined together by
peptide bonds between the carboxyl and amino groups. Proteins are
important for structural functions (such as actin and myosin in
muscle),cell signaling, immune responses, cell adhesion, and the
cycle. It is also known that proteins are synthesized in a
different way for many organisms. For example, for prokaryotes it
is synthesized in cytoplasm while cytosol for eukaryotes.Always
bidirectional traffic occurs continuously between the cytosol and
the nucleus. The many proteins that function in the
nucleus—including histones, DNA and RNA polymerases, gene
regulatory proteins, and RNA-processing proteins, are selectively
imported into the nuclear compartment from the cytosol, where they
are made.
But now question is that where proteins should perform their
functions? So, for performing of their desired functions, they must be
localized according to their targeted locations like cell membrane and
extra cellular environment, so that they can perform well.
Determination of the sub-cellular localization of any protein is an
important step towards the understanding of its function in a cellular
context. Proteins must be localized in order to interact with each
other and understand the external stimuli reflect on changes of
activities.
Determination of the sub cellular localization of
a protein is time taking task by experimentally. Now days, there
are several tools which help in prediction of localization of
proteins by computational tool which are fast and their results
are more accurate and it can be done by bioinformatics approaches.
Protein sub cellular localization is crucial for genome
annotation, protein function prediction, and drug discovery.
Protein localization is important for understanding protein
function and is important step in genome annotation (Genome
annotation means giving the biological information to related to
genes). Localization of a protein improves target identification
during the drug discovery process
In other words, we can say like that protein localization is
becoming challenging field and and it has been solving by
bioinformatics soft wares and methods. Some of them are listed for
bacteria and eukaryotes as follows:
1) PSORT: It is the first tool which is used for
prediction of protein localization. It is open for all users.PSORT
represents a portal for protein subcellular localization
predictors. It takes the amino acid sequence as inputs. After
this, it analyses the input information by applying the stored
rules for various sequence features of known protein sorting
signals. Finally, it will report the possibility for the input
protein to be localized at each candidate site with additional
information. In another way, it uses known signal peptide
sequences to analyze and predict what an input sequence is most
likely to cause localization.
2) Proteome Analyst: It is a method for the prediction of protein
localization for both prokaryotes and eukaryotes by using a text
mining approach.
3) Hum-PLoc: It is a challenging problem to predict the
subcellular localization of human proteins, especially when
unknown query proteins do not have significant homology to
proteins of known subcellular locations. To begin the challenge,
protein samples are expressed by hybridizing the gene ontology
(GO) database and amphiphilic pseudo amino acid composition (PseAA).
Based on this fact, Hum-PLoc is developed.
4) PSORTb: Prediction of bacterial protein
localization.
5) BaCelLo: It is the predictor for prediction of eukaryotic
protein subcellular localization. BaCelLo represents Balanced
subCellular Localization predictor
6) TargetP: Prediction of N-terminal sorting signals.
7) SecretomeP: Prediction of eukaryotic proteins.
8) LOCATE: It is a database for membrane organization and sub
cellular localization of mouse and human proteins.
9) PA-GOSUB: It is a database of molecular functions and predicted
sub cellular localizations of more than 107,000 proteins from 10
model organisms.
10) LOC3D: It predicts sub-cellular localization for eukaryotic
proteins of known three-dimensional (3D) structure. There are four
different methods for subcellular localization: predict NLS
(nuclear localization signal), LOChom ( using homology ), LOCkey
(using keywords) and LOC3d (neural network based prediction).
