An illustration of the systems approach to biology
Systems biology is the computational and mathematical analysis and modeling of complex biological systems. It is a biology-based
interdisciplinary field of study that focuses on complex interactions
within biological systems, using a holistic approach (holism instead of the more traditional reductionism) to biological research.
Particularly from the year 2000 onwards, the concept has been used widely in biology in a variety of contexts. The Human Genome Project is an example of applied systems thinking in biology which has led to new, collaborative ways of working on problems in the biological field of genetics. One of the aims of systems biology is to model and discover emergent properties, properties of cells, tissues and organisms functioning as a system whose theoretical description is only possible using techniques of systems biology. These typically involve metabolic networks or cell signaling networks.
Overview
Systems biology can be considered from a number of different aspects.
As a field of study, particularly, the study of the interactions
between the components of biological systems, and how these interactions
give rise to the function and behavior of that system (for example, the
enzymes and metabolites in a metabolic pathway or the heart beats).
As a paradigm, systems biology is usually defined in antithesis to the so-called reductionist paradigm (biological organisation), although it is consistent with the scientific method. The distinction between the two paradigms is referred to in these quotations: "the reductionist
approach has successfully identified most of the components and many of
the interactions but, unfortunately, offers no convincing concepts or
methods to understand how system properties emerge ... the pluralism of
causes and effects in biological networks is better addressed by
observing, through quantitative measures, multiple components
simultaneously and by rigorous data integration with mathematical
models." (Sauer et al.)
"Systems biology ... is about putting together rather than taking
apart, integration rather than reduction. It requires that we develop
ways of thinking about integration that are as rigorous as our
reductionist programmes, but different. ... It means changing our
philosophy, in the full sense of the term." (Denis Noble)
As a series of operational protocols used for performing research, namely a cycle composed of theory, analytic or computational modelling
to propose specific testable hypotheses about a biological system,
experimental validation, and then using the newly acquired quantitative
description of cells or cell processes to refine the computational model
or theory.
Since the objective is a model of the interactions in a system, the
experimental techniques that most suit systems biology are those that
are system-wide and attempt to be as complete as possible. Therefore, transcriptomics, metabolomics, proteomics and high-throughput techniques are used to collect quantitative data for the construction and validation of models.
As a socioscientific
phenomenon defined by the strategy of pursuing integration of complex
data about the interactions in biological systems from diverse
experimental sources using interdisciplinary tools and personnel.
History
Systems
biology was begun as a new field of science around 2000, when the
Institute for Systems Biology was established in Seattle in an effort to
lure "computational" type people who it was felt were not attracted to
the academic settings of the university. The institute did not have a
clear definition of what the field actually was: roughly bringing
together people from diverse fields to use computers to holistically
study biology in new ways. A Department of Systems Biology at Harvard Medical School was launched in 2003.
In 2006 it was predicted that the buzz generated by the "very
fashionable" new concept would cause all the major universities to need a
systems biology department, thus that there would be careers available
for graduates with a modicum of ability in computer programming and
biology. In 2006 the National Science Foundation put forward a challenge to build a mathematical model of the whole cell. In 2012 the first whole-cell model of Mycoplasma genitalium
was achieved by the Karr Laboratory at the Mount Sinai School of
Medicine in New York. The whole-cell model is able to predict viability
of M. genitalium cells in response to genetic mutations.
An earlier precursor of systems biology, as a distinct discipline, may have been by systems theorist Mihajlo Mesarovic in 1966 with an international symposium at the Case Institute of Technology in Cleveland, Ohio, titled Systems Theory and Biology. Mesarovic predicted that perhaps in the future there would be such as thing as "systems biology".
According to Robert Rosen
in the 1960s, holistic biology had become passé by the early 20th
century, as more empirical science dominated by molecular chemistry had
become popular. Echoing him forty years later in 2006 Kling writes that the success of molecular biology throughout the 20th century had suppressed holistic computational methods. By 2011 the National Institutes of Health had made grant money available to support over ten systems biology centers in the United States,
but by 2012 Hunter writes that systems biology had not lived up to the
hype, having promised more than it achieved, which had caused it to
become a somewhat minor field with few practical applications.
Nonetheless, proponents hoped that it might once prove more useful in
the future.
Shows
trends in systems biology research by presenting the number of articles
out of the top 30 cited systems biology papers during that time which
include a specific topic
An important milestone in the development of systems biology has become the international project Physiome.
According to the interpretation of systems biology as using large
data sets using interdisciplinary tools, a typical application is metabolomics, which is the complete set of all the metabolic products, metabolites, in the system at the organism, cell, or tissue level.
The molecular interactions within the cell are also studied, this is called interactomics. A discipline in this field of study is protein-protein interactions, although interactomics includes the interactions of other molecules.[citation needed]Neuroelectrodynamics, where the computer's or a brain's computing function as a dynamic system is studied along with its (bio)physical mechanisms; and fluxomics, measurements of the rates of metabolic reactions in a biological system (cell, tissue, or organism).
In approaching a systems biology problem there are two main
approaches. These are the top down and bottom up approach. The top down
approach takes as much of the system into account as possible and relies
largely on experimental results. The RNA-Seq
technique is an example of an experimental top down approach.
Conversely, the bottom up approach is used to create detailed models
while also incorporating experimental data. An example of the bottom up
approach is the use of circuit models to describe a simple gene network.
Various technologies utilized to capture dynamic changes in mRNA, proteins, and post-translational modifications. Mechanobiology, forces and physical properties at all scales, their interplay with other regulatory mechanisms; biosemiotics, analysis of the system of sign relations of an organism or other biosystems; Physiomics, a systematic study of physiome in biology.
Cancer systems biology is an example of the systems biology approach, which can be distinguished by the specific object of study (tumorigenesis and treatment of cancer). It works with the specific data (patient samples, high-throughput data with particular attention to characterizing cancer genome in patient tumour samples) and tools (immortalized cancer cell lines, mouse models of tumorigenesis, xenograft models, high-throughput sequencing methods, siRNA-based gene knocking down high-throughput screenings, computational modeling of the consequences of somatic mutations and genome instability).
The long-term objective of the systems biology of cancer is ability to
better diagnose cancer, classify it and better predict the outcome of a
suggested treatment, which is a basis for personalized cancer medicine and virtual cancer patient
in more distant prospective. Significant efforts in computational
systems biology of cancer have been made in creating realistic
multi-scale in silico models of various tumours.
The systems biology approach often involves the development of mechanistic models, such as the reconstruction of dynamic systems from the quantitative properties of their elementary building blocks. For instance, a cellular network can be modelled mathematically using methods coming from chemical kinetics and control theory.
Due to the large number of parameters, variables and constraints in
cellular networks, numerical and computational techniques are often used
(e.g., flux balance analysis).
Bioinformatics and data analysis
Other aspects of computer science, informatics, and statistics are also used in systems biology. These include new forms of computational models, such as the use of process calculi to model biological processes (notable approaches include stochastic π-calculus, BioAmbients, Beta Binders, BioPEPA, and Brane calculus) and constraint-based modeling; integration of information from the literature, using techniques of information extraction and text mining;
development of online databases and repositories for sharing data and
models, approaches to database integration and software interoperability
via loose coupling
of software, websites and databases, or commercial suits; network-based
approaches for analyzing high dimensional genomic data sets. For
example, weighted correlation network analysis
is often used for identifying clusters (referred to as modules),
modeling the relationship between clusters, calculating fuzzy measures
of cluster (module) membership, identifying intramodular hubs, and for
studying cluster preservation in other data sets; pathway-based methods
for omics data analysis, e.g. approaches to identify and score pathways
with differential activity of their gene, protein, or metabolite
members.
Much of the analysis of genomic data sets also include identifying
correlations. Additionally, as much of the information comes from
different fields, the development of syntactically and semantically
sound ways of representing biological models is needed.
Creating biological models
A
simple three protein negative feedback loop modeled with mass action
kinetic differential equations. Each protein interaction is described by
a Michaelis–Menten reaction.
Researchers begin by choosing a biological pathway and diagramming
all of the protein interactions. After determining all of the
interactions of the proteins, mass action kinetics
is utilized to describe the speed of the reactions in the system. Mass
action kinetics will provide differential equations to model the
biological system as a mathematical model in which experiments can
determine the parameter values to use in the differential equations.
These parameter values will be the reaction rates of each proteins
interaction in the system. This model determines the behavior of certain
proteins in biological systems and bring new insight to the specific
activities of individual proteins. Sometimes it is not possible to
gather all reaction rates of a system. Unknown reaction rates are
determined by simulating the model of known parameters and target
behavior which provides possible parameter values.
The use of constraint-based reconstruction and analysis (COBRA)
methods has become popular among systems biologists to simulate and
predict the metabolic phenotypes, using genome-scale models. One of the
methods is the flux balance analysis (FBA) approach, by which one can
study the biochemical networks and analyze the flow of metabolites
through a particular metabolic network, by maximizing the object of
interest.
Plot
of Concentrations vs time for the simple three protein negative
feedback loop. All parameters are set to either 0 or 1 for initial
conditions. The reaction is allowed to proceed until it hits
equilibrium. This plot is of the change in each protein over time.
Proteins are generally thought to adopt unique structures determined by their amino acid
sequences. However, proteins are not strictly static objects, but
rather populate ensembles of (sometimes similar) conformations.
Transitions between these states occur on a variety of length scales
(tenths of Å to nm) and time scales (ns to s),
and have been linked to functionally relevant phenomena such as allosteric signaling and enzyme catalysis.
The study of protein dynamics is most directly concerned with the transitions between these states,
but can also involve the nature and equilibrium populations of the states themselves.
These two perspectives—kinetics and thermodynamics, respectively—can be conceptually synthesized in an "energy landscape" paradigm:
highly populated states and the kinetics of transitions between them can
be described by the depths of energy wells and the heights of energy
barriers, respectively.
Portions of protein structures often deviate from the equilibrium state.
Some such excursions are harmonic, such as stochastic fluctuations of chemical bonds and bond angles.
Others are anharmonic, such as sidechains that jump between separate discrete energy minima, or rotamers.
Evidence for local flexibility is often obtained from NMR spectroscopy. Flexible and potentially disordered regions of a protein can be detected using the random coil index. Flexibility in folded proteins can be identified by analyzing the spin relaxation of individual atoms in the protein. Flexibility can also be observed in very high-resolution electron density maps produced by X-ray crystallography,
particularly when diffraction data is collected at room temperature
instead of the traditional cryogenic temperature (typically near 100 K).
Information on the frequency distribution and dynamics of local protein
flexibility can be obtained using Raman and optical Kerr-effect
spectroscopy in the terahertz frequency domain.
A
network of alternative conformations in catalase (Protein Data Bank
code: 1gwe) with diverse properties. Multiple phenomena define the
network: van der Waals interactions (blue dots and line segments)
between sidechains, a hydrogen bond (dotted green line) through a
partial-occupancy water (brown), coupling through the locally mobile
backbone (black), and perhaps electrostatic forces between the Lys
(green) and nearby polar residues (blue: Glu, yellow: Asp, purple: Ser).
This particular network is distal from the active site and is therefore
putatively not critical for function.
Many residues are in close spatial proximity in protein structures.
This is true for most residues that are contiguous in the primary sequence,
but also for many that are distal in sequence yet are brought into contact in the final folded structure.
Because of this proximity, these residue's energy landscapes become coupled
based on various biophysical phenomena such as hydrogen bonds, ionic bonds, and van der Waals interactions (see figure).
Transitions between states for such sets of residues therefore become correlated.
This is perhaps most obvious for surface-exposed loops, which
often shift collectively to adopt different conformations in different
crystal structures (see figure). However, coupled conformational
heterogeneity is also sometimes evident in secondary structure. For example, consecutive residues and residues offset by 4 in the primary sequence often interact in α helices. Also, residues offset by 2 in the primary sequence point their sidechains toward the same face of β sheets and are close enough to interact sterically, as are residues on adjacent strands of the same β sheet.
Some of these conformational changes are induced by post-translational
modifications in protein structure, such as phosphorylation and
methylation.
An
"ensemble" of 44 crystal structures of hen egg white lysozyme from the
Protein Data Bank, showing that different crystallization conditions
lead to different conformations for various surface-exposed loops and
termini (red arrows).
When these coupled residues form pathways linking functionally important parts of a protein,
they may participate in allosteric signaling.
For example, when a molecule of oxygen binds to one subunit of the hemoglobin
tetramer,
that information is allosterically propagated to the other three
subunits, thereby enhancing their affinity for oxygen.
In this case, the coupled flexibility in hemoglobin allows for
cooperative oxygen binding,
which is physiologically useful because it allows rapid oxygen loading
in lung tissue and rapid oxygen unloading in oxygen-deprived tissues
(e.g. muscle).
Global flexibility: multiple domains
The presence of multiple domains in proteins gives rise to a great deal of flexibility and mobility, leading to protein domain dynamics.
Domain motions can be inferred by comparing different structures of a protein (as in Database of Molecular Motions), or they can be directly observed using spectra
measured by neutron spin echo spectroscopy.
They can also be suggested by sampling in extensive molecular dynamics trajectories and principal component analysis. Domain motions are important for:
One of the largest observed domain motions is the 'swivelling' mechanism in pyruvate phosphate dikinase.
The phosphoinositide domain swivels between two states in order to
bring a phosphate group from the active site of the nucleotide binding
domain to that of the phosphoenolpyruvate/pyruvate domain.
The phosphate group is moved over a distance of 45 Å involving a domain
motion of about 100 degrees around a single residue. In enzymes, the
closure of one domain onto another captures a substrate by an induced
fit, allowing the reaction to take place in a controlled way. A detailed
analysis by Gerstein led to the classification of two basic types of
domain motion; hinge and shear.
Only a relatively small portion of the chain, namely the inter-domain
linker and side chains undergo significant conformational changes upon
domain rearrangement.
Hinges by secondary structures
A study by Hayward
found that the termini of α-helices and β-sheets form hinges in a large
number of cases. Many hinges were found to involve two secondary
structure elements acting like hinges of a door, allowing an opening and
closing motion to occur. This can arise when two neighbouring strands
within a β-sheet situated in one domain, diverge apart as they join the
other domain. The two resulting termini then form the bending regions
between the two domains. α-helices that preserve their hydrogen bonding
network when bent are found to behave as mechanical hinges, storing
`elastic energy' that drives the closure of domains for rapid capture of
a substrate.
Helical to extended conformation
The
interconversion of helical and extended conformations at the site of a
domain boundary is not uncommon. In calmodulin, torsion angles change
for five residues in the middle of a domain linking α-helix. The helix
is split into two, almost perpendicular, smaller helices separated by
four residues of an extended strand.
Shear motions
Shear
motions involve a small sliding movement of domain interfaces,
controlled by the amino acid side chains within the interface. Proteins
displaying shear motions often have a layered architecture: stacking of
secondary structures. The interdomain linker has merely the role of
keeping the domains in close proximity.
Domain motion and functional dynamics in enzymes
The
analysis of the internal dynamics of structurally different, but
functionally similar enzymes
has highlighted a common relationship between the positioning of the
active site and the two principal protein sub-domains. In fact, for
several members of the hydrolase superfamily, the catalytic site is
located close to the interface separating the two principal quasi-rigid
domains.[13]
Such positioning appears instrumental for maintaining the precise
geometry of the active site, while allowing for an appreciable
functionally oriented modulation of the flanking regions resulting from
the relative motion of the two sub-domains.
Implications for macromolecular evolution
Evidence suggests that protein dynamics are important for function, e.g. enzyme catalysis in DHFR,
yet they are also posited to facilitate the acquisition of new functions by molecular evolution.
This argument suggests that proteins have evolved to have stable, mostly unique folded structures,
but the unavoidable residual flexibility leads to some degree of functional promiscuity,
which can be amplified/harnessed/diverted by subsequent mutations.
However, there is growing awareness that intrinsically unstructured proteins are quite prevalent in eukaryotic genomes,
casting further doubt on the simplest interpretation of Anfinsen's dogma:
"sequence determines structure (singular)".
In effect, the new paradigm is characterized by the addition of two
caveats: "sequence and cellular environment determine structural
ensemble".
In biology, cell signaling (cell signalling in British English) or cell communication is the ability of a cell to receive, process, and transmit signals with its environment and with itself. It is a fundamental property of all cells in every living organism such as bacteria, plants, and animals. Signals that originate from outside a cell (or extracellular signals) can be physical agents like mechanical pressure, voltage, temperature, light, or chemical signals (e.g., small molecules, peptides,
or gas). Chemical signals can be hydrophobic or hydrophillic. Cell
signaling can occur over short or long distances, and as a result can be
classified as autocrine, juxtacrine, intracrine, paracrine, or endocrine. Signaling molecules can be synthesized from various biosynthetic pathways and released through passive or active transports, or even from cell damage.
Receptors
play a key role in cell signaling as they are able to detect chemical
signals or physical stimuli. Receptors are generally proteins located on
the cell surface or within the interior of the cell such as the cytoplasm, organelles, and nucleus. Cell surface receptors usually bind with extracellular signals (or ligands), which causes a conformational change in the receptor that leads it to initiate enzymic activity, or to open or close ion channel activity. Some receptors do not contain enzymatic or channel-like domains but are instead linked to enzymes or transporters. Other receptors like nuclear receptors have a different mechanism such as changing their DNA binding properties and cellular localization to the nucleus.
Signal transduction begins with the transformation (or transduction) of a signal into a chemical one, which can directly activate an ion channel (ligand-gated ion channel) or initiate a second messenger system
cascade that propagates the signal through the cell. Second messenger
systems can amplify a signal, in which activation of a few receptors
results in multiple secondary messengers being activated, thereby
amplifying the initial signal (the first messenger). The downstream effects of these signaling pathways may include additional enzymatic activities such as proteolytic cleavage, phosphorylation, methylation, and ubiquitinylation.
In many small organisms such as bacteria, quorum sensing
enables individuals to begin an activity only when the population is
sufficiently large. This signaling between cells was first observed in
the marine bacterium Aliivibrio fischeri, which produces light when the population is dense enough.
The mechanism involves the production and detection of a signaling
molecule, and the regulation of gene transcription in response. Quorum
sensing operates in both gram-positive and gram-negative bacteria, and
both within and between species.
In slime moulds,
individual cells known as amoebae aggregate together to form fruiting
bodies and eventually spores, under the influence of a chemical signal,
originally named acrasin. The individuals move by chemotaxis, i.e. they are attracted by the chemical gradient. Some species use cyclic AMP as the signal; others such as Polysphondylium violaceum use other molecules, in its case N-propionyl-gamma-L-glutamyl-L-ornithine-delta-lactam ethyl ester, nicknamed glorin.
In plants and animals, signaling between cells occurs either through release into the extracellular space, divided in paracrine signaling (over short distances) and endocrine signaling (over long distances), or by direct contact, known as juxtacrine signaling (e.g., notch signaling). Autocrine
signaling is a special case of paracrine signaling where the secreting
cell has the ability to respond to the secreted signaling molecule. Synaptic signaling is a special case of paracrine signaling (for chemical synapses) or juxtacrine signaling (for electrical synapses) between neurons and target cells.
Extracellular signal
Synthesis and release
Different types of extracellular signaling
Many cell signals are carried by molecules that are released by one
cell and move to make contact with another cell. Signaling molecules can
belong to several chemical classes: lipids, phospholipids, amino acids, monoamines, proteins, glycoproteins, or gases. Signaling molecules binding surface receptors are generally large and hydrophilic (e.g. TRH, Vasopressin, Acetylcholine), while those entering the cell are generally small and hydrophobic (e.g. glucocorticoids, thyroid hormones, cholecalciferol, retinoic acid),
but important exceptions to both are numerous, and a same molecule can
act both via surface receptors or in an intracrine manner to different
effects.
In animal cells, specialized cells release these hormones and send them
through the circulatory system to other parts of the body. They then
reach target cells, which can recognize and respond to the hormones and
produce a result. This is also known as endocrine signaling. Plant
growth regulators, or plant hormones, move through cells or by diffusing
through the air as a gas to reach their targets. Hydrogen sulfide
is produced in small amounts by some cells of the human body and has a
number of biological signaling functions. Only two other such gases are
currently known to act as signaling molecules in the human body: nitric oxide and carbon monoxide.
Exocytosis
Exocytosis is the process by which a cell transports molecules such as neurotransmitters and proteins out of the cell. As an active transport mechanism, exocytosis requires the use of energy to transport material. Exocytosis and its counterpart, endocytosis, are used by all cells because most chemical substances important to them are large polar molecules that cannot pass through the hydrophobic portion of the cell membrane by passive
means. Exocytosis is the process by which a large amount of molecules
are released; thus it is a form of bulk transport. Exocytosis occurs via
secretory portals at the cell plasma membrane called porosomes. Porosomes
are permanent cup-shaped lipoprotein structure at the cell plasma
membrane, where secretory vesicles transiently dock and fuse to release
intra-vesicular contents from the cell.
In exocytosis, membrane-bound secretory vesicles are carried to the cell membrane, where they dock and fuse at porosomes and their contents (i.e., water-soluble molecules) are secreted into the extracellular environment. This secretion is possible because the vesicle transiently fuses with the plasma membrane. In the context of neurotransmission, neurotransmitters are typically released from synaptic vesicles into the synaptic cleft via exocytosis; however, neurotransmitters can also be released via reverse transport through membrane transport proteins.
Forms
Autocrine
Differences between autocrine and paracrine signaling
Autocrine signaling involves a cell secreting a hormone or chemical
messenger (called the autocrine agent) that binds to autocrine receptors
on that same cell, leading to changes in the cell itself. This can be contrasted with paracrine signaling, intracrine signaling, or classical endocrine signaling.
Paracrine
In
paracrine signaling, a cell produces a signal to induce changes in
nearby cells, altering the behaviour of those cells. Signaling molecules
known as paracrine factors diffuse over a relatively short distance
(local action), as opposed to cell signaling by endocrine factors, hormones which travel considerably longer distances via the circulatory system; juxtacrine interactions; and autocrine signaling. Cells that produce paracrine factors secrete them into the immediate extracellular
environment. Factors then travel to nearby cells in which the gradient
of factor received determines the outcome. However, the exact distance
that paracrine factors can travel is not certain.
Paracrine signals such as retinoic acid target only cells in the vicinity of the emitting cell. Neurotransmitters represent another example of a paracrine signal.
Some signaling molecules can function as both a hormone and a neurotransmitter. For example, epinephrine and norepinephrine can function as hormones when released from the adrenal gland and are transported to the heart by way of the blood stream. Norepinephrine can also be produced by neurons to function as a neurotransmitter within the brain. Estrogen can be released by the ovary and function as a hormone or act locally via paracrine or autocrine signaling.
Although paracrine signaling elicits a diverse array of responses
in the induced cells, most paracrine factors utilize a relatively
streamlined set of receptors and pathways. In fact, different organs
in the body - even between different species - are known to utilize a
similar sets of paracrine factors in differential development. The highly conserved receptors and pathways can be organized into four major families based on similar structures: fibroblast growth factor (FGF) family, Hedgehog family, Wnt family, and TGF-β superfamily. Binding of a paracrine factor to its respective receptor initiates signal transduction cascades, eliciting different responses.
Endocrine
Endocrine signals are called hormones. Hormones are produced by endocrine cells and they travel through the blood
to reach all parts of the body. Specificity of signaling can be
controlled if only some cells can respond to a particular hormone.
Endocrine signaling involves the release of hormones by internal glands of an organism directly into the circulatory system, regulating distant target organs. In vertebrates, the hypothalamus is the neural control center for all endocrine systems. In humans, the major endocrine glands are the thyroid gland and the adrenal glands. The study of the endocrine system and its disorders is known as endocrinology.
Juxtacrine
Figure 2. Notch-mediated juxtacrine signal between adjacent cells.
Juxtacrine signaling is a type of cell–cell or cell–extracellular matrix signaling in multicellular organisms that requires close contact. There are three types:
Additionally, in unicellular organisms such as bacteria, juxtacrine signaling means interactions by membrane contact. Juxtacrine signaling has been observed for some growth factors, cytokine and chemokine cellular signals, playing an important role in the immune response.
Cells receive information from their neighbors through a class of proteins known as receptors.
Receptors may bind with some molecules (ligands) or may interact with
physical agents like light, mechanical temperature, pressure, etc.
Reception occurs when the target cell (any cell with a receptor protein specific to the signal molecule)
detects a signal, usually in the form of a small, water-soluble
molecule, via binding to a receptor protein on the cell surface, or once
inside the cell, the signaling molecule can bind to intracellular receptors, other elements, or stimulate enzyme activity (e.g. gasses), as in intracrine signaling.
Cell surface receptors play an essential role in the biological
systems of single- and multi-cellular organisms and malfunction or
damage to these proteins is associated with cancer, heart disease, and
asthma. These trans-membrane receptors are able to transmit information from outside the cell to the inside because they change conformation when a specific ligand binds to it. There are three major types: Ion channel linked receptors, G protein–coupled receptors, and enzyme-linked receptors.
Ion channel linked receptors
The AMPA receptor bound to a glutamate antagonist showing the amino terminal, ligand binding, and transmembrane domain, PDB 3KG2
Ion channel linked receptors are a group of transmembraneion-channel proteins which open to allow ions such as Na+, K+, Ca2+, and/or Cl− to pass through the membrane in response to the binding of a chemical messenger (i.e. a ligand), such as a neurotransmitter.
When a presynaptic neuron is excited, it releases a neurotransmitter from vesicles into the synaptic cleft. The neurotransmitter then binds to receptors located on the postsynaptic neuron.
If these receptors are ligand-gated ion channels, a resulting
conformational change opens the ion channels, which leads to a flow of
ions across the cell membrane. This, in turn, results in either a depolarization, for an excitatory receptor response, or a hyperpolarization, for an inhibitory response.
These receptor proteins are typically composed of at least two
different domains: a transmembrane domain which includes the ion pore,
and an extracellular domain which includes the ligand binding location
(an allosteric
binding site). This modularity has enabled a 'divide and conquer'
approach to finding the structure of the proteins (crystallising each
domain separately). The function of such receptors located at synapses is to convert the chemical signal of presynaptically released neurotransmitter directly and very quickly into a postsynaptic electrical signal. Many LICs are additionally modulated by allostericligands, by channel blockers, ions, or the membrane potential. LICs are classified into three superfamilies which lack evolutionary relationship: cys-loop receptors, ionotropic glutamate receptors and ATP-gated channels.
G protein–coupled receptors
A G Protein-coupled receptor within the plasma membrane.
G protein-coupled receptors are a large group of evolutionarily-related proteins that are cell surface receptors that detect molecules outside the cell and activate cellular responses. Coupling with G proteins, they are called seven-transmembrane receptors because they pass through the cell membrane seven times.
Ligands can bind either to extracellular N-terminus and loops (e.g.
glutamate receptors) or to the binding site within transmembrane
helices (Rhodopsin-like family). They are all activated by agonists although a spontaneous auto-activation of an empty receptor can also be observed.
There are two principal signal transduction pathways involving the G protein-coupled receptors: cAMP signal pathway and phosphatidylinositol signal pathway. When a ligand binds to the GPCR it causes a conformational change in the GPCR, which allows it to act as a guanine nucleotide exchange factor (GEF). The GPCR can then activate an associated G protein by exchanging the GDP bound to the G protein for a GTP.
The G protein's α subunit, together with the bound GTP, can then
dissociate from the β and γ subunits to further affect intracellular
signaling proteins or target functional proteins directly depending on
the α subunit type (Gαs, Gαi/o, Gαq/11, Gα12/13).
G protein-coupled receptors are an important drug target and approximately 34%
of all Food and Drug Administration (FDA) approved drugs target 108
members of this family. The global sales volume for these drugs is
estimated to be 180 billion US dollars as of 2018.
It is estimated that GPCRs are targets for about 50% of drugs currently
on the market, mainly due to their involvement in signaling pathways
related to many diseases i.e. mental, metabolic including
endocrinological disorders, immunological including viral infections,
cardiovascular, inflammatory, senses disorders, and cancer. The long ago
discovered association between GPCRs and many endogenous and exogenous
substances, resulting in e.g. analgesia, is another dynamically
developing field of pharmaceutical research.
Enzyme-linked receptors
VEGF receptors are a type of enzyme-coupled receptors, specifically tyrosine kinase receptors
They have two important domains, an extra-cellular ligand binding
domain and an intracellular domain, which has a catalytic function; and
a single transmembrane helix.
The signaling molecule binds to the receptor on the outside of the
cell and causes a conformational change on the catalytic function
located on the receptor inside the cell. Examples of the enzymatic
activity include:
Figure 3. Key components of a signal transduction pathway (MAPK/ERK pathway shown)
When binding to the signaling molecule, the receptor protein changes
in some way and starts the process of transduction, which can occur in a
single step or as a series of changes in a sequence of different
molecules (called a signal transduction pathway). The molecules that
compose these pathways are known as relay molecules. The multistep
process of the transduction stage is often composed of the activation of
proteins by addition or removal of phosphate groups or even the release
of other small molecules or ions that can act as messengers. The
amplifying of a signal is one of the benefits to this multiple step
sequence. Other benefits include more opportunities for regulation than
simpler systems do and the fine- tuning of the response, in both
unicellular and multicellular organism.
In some cases, receptor activation caused by ligand binding to a
receptor is directly coupled to the cell's response to the ligand. For
example, the neurotransmitter GABA can activate a cell surface receptor that is part of an ion channel. GABA binding to a GABAA receptor on a neuron opens a chloride-selective ion channel that is part of the receptor. GABAA
receptor activation allows negatively charged chloride ions to move
into the neuron, which inhibits the ability of the neuron to produce action potentials.
However, for many cell surface receptors, ligand-receptor interactions
are not directly linked to the cell's response. The activated receptor
must first interact with other proteins inside the cell before the
ultimate physiological
effect of the ligand on the cell's behavior is produced. Often, the
behavior of a chain of several interacting cell proteins is altered
following receptor activation. The entire set of cell changes induced by
receptor activation is called a signal transduction mechanism or pathway.
A more complex signal transduction pathway is shown in Figure 3. This pathway involves changes of protein–protein interactions
inside the cell, induced by an external signal. Many growth factors
bind to receptors at the cell surface and stimulate cells to progress
through the cell cycle and divide. Several of these receptors are kinases that start to phosphorylate themselves and other proteins when binding to a ligand. This phosphorylation
can generate a binding site for a different protein and thus induce
protein–protein interaction. In Figure 3, the ligand (called epidermal growth factor, or EGF) binds to the receptor (called EGFR). This activates the receptor to phosphorylate itself. The phosphorylated receptor binds to an adaptor protein (GRB2),
which couples the signal to further downstream signaling processes. For
example, one of the signal transduction pathways that are activated is
called the mitogen-activated protein kinase
(MAPK) pathway. The signal transduction component labeled as "MAPK" in
the pathway was originally called "ERK," so the pathway is called the MAPK/ERK pathway. The MAPK protein is an enzyme, a protein kinase that can attach phosphate to target proteins such as the transcription factorMYC
and, thus, alter gene transcription and, ultimately, cell cycle
progression. Many cellular proteins are activated downstream of the
growth factor receptors (such as EGFR) that initiate this signal
transduction pathway.
Some signaling transduction pathways respond differently,
depending on the amount of signaling received by the cell. For instance,
the hedgehog protein activates different genes, depending on the amount of hedgehog protein present.
Complex multi-component signal transduction pathways provide
opportunities for feedback, signal amplification, and interactions
inside one cell between multiple signals and signaling pathways.
A specific cellular response is the result of the transduced
signal in the final stage of cell signaling. This response can
essentially be any cellular activity that is present in a body. It can
spur the rearrangement of the cytoskeleton, or even as catalysis by an
enzyme. These three steps of cell signaling all ensure that the right
cells are behaving as told, at the right time, and in synchronization
with other cells and their own functions within the organism. At the
end, the end of a signal pathway leads to the regulation of a cellular
activity. This response can take place in the nucleus or in the
cytoplasm of the cell. A majority of signaling pathways control protein
synthesis by turning certain genes on and off in the nucleus.
In unicellular organisms such as bacteria, signaling can be used to 'activate' peers from a dormant state, enhance virulence, defend against bacteriophages, etc. In quorum sensing,
which is also found in social insects, the multiplicity of individual
signals has the potentiality to create a positive feedback loop,
generating coordinated response. In this context, the signaling
molecules are called autoinducers. This signaling mechanism may have been involved in evolution from unicellular to multicellular organisms. Bacteria also use contact-dependent signaling, notably to limit their growth.
Signaling molecules used by multicellular organisms are often called pheromones. They can have such purposes as alerting against danger, indicating food supply, or assisting in reproduction.
Short-term cellular responses
Brief overview of some signaling pathways (based on receptor families) that result in short-acting cellular responses
Receptor Family
Example of Ligands/ activators (Bracket: receptor for it)
Notch is a cell surface protein that functions as a receptor. Animals have a small set of genes
that code for signaling proteins that interact specifically with Notch
receptors and stimulate a response in cells that express Notch on their
surface. Molecules that activate (or, in some cases, inhibit) receptors
can be classified as hormones, neurotransmitters, cytokines, and growth factors, in general called receptor ligands.
Ligand receptor interactions such as that of the Notch receptor
interaction, are known to be the main interactions responsible for cell
signaling mechanisms and communication. notch
acts as a receptor for ligands that are expressed on adjacent cells.
While some receptors are cell-surface proteins, others are found inside
cells. For example, estrogen is a hydrophobic molecule that can pass through the lipid bilayer of the membranes. As part of the endocrine system, intracellular estrogen receptors from a variety of cell types can be activated by estrogen produced in the ovaries.
In the case of Notch-mediated signaling, the signal transduction
mechanism can be relatively simple. As shown in Figure 2, the activation
of Notch can cause the Notch protein to be altered by a protease. Part of the Notch protein is released from the cell surface membrane and takes part in gene regulation.
Cell signaling research involves studying the spatial and temporal
dynamics of both receptors and the components of signaling pathways that
are activated by receptors in various cell types.
Emerging methods for single-cell mass-spectrometry analysis promise to
enable studying signal transduction with single-cell resolution.
In notch signaling, direct contact between cells allows for precise control of cell differentiation during embryonic development. In the worm Caenorhabditis elegans, two cells of the developing gonad
each have an equal chance of terminally differentiating or becoming a
uterine precursor cell that continues to divide. The choice of which
cell continues to divide is controlled by competition of cell surface
signals. One cell will happen to produce more of a cell surface protein
that activates the Notch receptor on the adjacent cell. This activates a feedback loop
or system that reduces Notch expression in the cell that will
differentiate and that increases Notch on the surface of the cell that
continues as a stem cell.
