Molecular Switching in Proteins
Jie YAN
School of Chemical Engineering, University of Adelaide, Adelaide, SA 5005, Australia
Abstract.
Molecular Switching is a molecule reversibly shifting from one state to another; some environmental stimuli can cause this kind of shifting. And molecular switching is widely used in many fields such as dealing with disease, logical gates and signal transport. However, in the protein, peptide aspect, molecular switching can simply mean the conformational transition (e.g. helix-to-helix transition, helix-to-sheet transition etc.) Through there are ways in studying the molecular switching, the molecular dynamics simulation seems to be a realistic method. In this review we give a brief introduction of the protein and peptide structure and molecular dynamics simulation, and we also show the factors effect molecular switches and the energy change among these switches.
Keywords
Molecular switches. Peptides. Helix. Sheet. Transition. Molecular dynamics simulation.
1. Introduction
Every day we use switches to turn electric appliances on and off, and no appliances would work properly without their switches. Molecular switches work in the same way, changing from one state to another depending on environmental influences. The only difference between normal switches and molecular switches is that the molecular switches are extremely tiny. However, their application in nanotechnology, biomedicine and computer chip design opens up new horizons.
In nature, molecules exploit interaction with their environment to perform complex functionalities on the nanometre length scale. Physical, chemical and/or biological specificity is frequently achieved by the switching of molecules from one state to another state. The examples of this are the energy production in proton pumps of bacteria or the signal conversion in human vision, which rely on switching molecules between different configurations or conformations by external stimuli.
For example, molecular switches are the fundamental building blocks in the field of synthetic biology. The majority of these switches is based on protein-protein, protein-DNA or protein-RNA interaction that responsive towards endogenous metabolites or external stimuli such as small molecules or light. Molecular switches are described as building blocks because they obtain control of biological processes at different cellular levels, they start at the outside of cell at the receptor level, continue to signalling pathway and gene expression control and finally to the regulation of protein degradation.(Hörner and Weber, 2012)
A promising avenue towards emulate nature and develop artificial system with molecule functionalities is partly relying on the molecular switches, which offers new pathways to control functional properties, to apply electrical contacts, or to integrate switches into large systems. This field requires both synthesis and preparation of appropriate molecular systems and control suitable external stimuli, such as light, heat or other conditions. To optimize switching and generate function, it is essential to unravel the geometric structure, the properties and other aspects of molecular switching.
When we talk about molecular switching, it includes all reversible molecular shifting from one state to another. However, in this review, we will focus on the conformational transition of peptides and proteins, which may involve in new nanotechnology, nanomaterial’s and disease control.
Although there are many ways to investigate the molecular switches in proteins and peptides, molecular dynamics simulation seems to provide a more realistic way to do this kind of research for it consider many aspects into account, though there are also some kinds of simplification in molecular dynamics simulation. In this review, we will give some examples in using molecular dynamics simulation to study the conformation of proteins.
Thermodynamics-related concepts
Potential energy: In physics, potential energy is the energy of an object or a system due to the position of the body or the arrangement of the particles of the system.
Internal energy: In thermodynamics, the internal energy is the total energy contained by a thermodynamics system. It is the energy needed to create the system but excludes the energy to displace the system’s surrounding, any energy associated with a move as a whole, or due to external force field.
Free energy: It is the energy in a physical system that can be converted to do work.
Entropy: Entropy is a mathematically-defined thermodynamic quantity that helps to account for the flow of energy through a thermodynamic process. In statistical mechanics, entropy is often related to motions of order and disorder.
Enthalpy: Enthalpy is a measure of the total energy of a thermodynamic system. It includes the internal energy and the amount of energy required to make room for if by displacing its environment and establishing its volume and pressure.
2. The structure of peptides and proteins
Amino acid The term ‘amino acids’ is generally understood to refer to aminoalkanoic acids, it would include all structures carrying amine and acid functional groups(Figure 2.1), including simple aromatic compounds, and would also cover other types of acidic functional groups( such as phosphorus and sulphur oxy-acids).
Figure 2.1 the basic structure of an amino acid(G.C.Barrett and D.T.Elmore, 1998)
Peptide The term ‘peptides’ has a more restricted meaning and is therefore a less ambiguous term, since it covers polymers formed by the condensation of the respective amino and carboxy groups of amino acids(Figure 2.2). For the structures made up from 2 to 20 amino acids, the term ‘oligopeptide’ is used and a prefix di-, tri-, tetra-, undeca-, dodeca-, etc. is used to in indicate the number of amino-acid residues contained in the compound. And longer polymers are termed ‘proteins’.(G.C.Barrett and D.T.Elmore, 1998)
Figure 2.2 how amino acids form peptides(G.C.Barrett and D.T.Elmore, 1998)
The primary structure of a protein is the sequence of amino acids in it. Secondary structure describes the local conformation of the amino acids in the protein chain. It is stabilised by hydrogen bonds between the amino- groups which carry a positive charge and the keto-groups which carry a negative charge of the peptide bonds(Figure 2.3). It seems that the energy of a hydrogen bond is relatively small, the total energy of all hydrogen bonds in a protein can be considerable. (G.C.Barrett and D.T.Elmore, 1998)
Figure 2.3 the geometry of a peptide bond(G.C.Barrett and D.T.Elmore, 1998)
The conformational details within an amino-acid residue of a polypeptide are must clearly defined as torsion angles for the backbone single bonds. The helices and sheets structures can be in nearly native protein structure.
The α-helix (Figure 2.4(a)) is one of the best-known regular conformational features of the secondary structure of proteins and the is frequently adopted in chains of six or more helicogenic amino acids. The polypeptide chain is wound around an imaginary axis, the average number of amino-acid residues contained in one turn is 3.6, each turn is about 5.4A long, the pitch per amino acid is 1.5A. The angle between successive residues is about 100°, φ =−57°, ψ = −47° The R-groups point outward. The β-sheet (Figure 2.4(b)) is another classical conformational feature of the protein secondary structure. (Dobson, 2003)In addition to the two structures mentioned above, there are other conformations such as the 310-helix(3 residues per turn and a hydrogen bond between residues i and i+3, φ =−50°, ψ = −25° ) and the π-helix(5 residues per turn and a hydrogen bond between residues i and i+5) as well as coil state.
(a) (b)
Figure 2.4 Two classical secondary structures of protein (a) α-helix (b) β-sheet(G.C.Barrett and D.T.Elmore, 1998)
3. Molecular switching in proteins
Molecular switch is a reversible molecular shifting between two or more states. When speaking of proteins and peptides, molecular switching can mean the conformational transition between different structures.
The conformational transition is common for polypeptides and proteins due to the different stability between different states, and it is often caused thermally or caused by the changes of solvents (such as the change of pH or ionic strength or temperature.(Cerpa et al., 1996)
The state a protein adopts under certain condition depends on the relative thermodynamic stabilities of the conformations accessible and the interconversion kinetics.
And some methods have been found to prompt a peptide to switch from one structure to another. The conformational change of peptides made of only natural amino acids can be trigged by pressure, temperature, solvent or pH.
Researchers use circular dichroism (CD) spectroscopy to study the conformation of peptides, for CD spectroscopy has been shown to be quite sensitive to the secondary structure of proteins(Figure 3.1).(A.Comptom and Johnson, 1986) Using the CD spectra, we can predict the effect of different temperature, pH, etc.
Figure 3.2 Secondary structure spectra for major secondary structures from 178 to
260nm: α-helix(_), antiparallel β-sheet(﹍), parallel β-sheet(﹎), β
-turn(_﹍_), other structure(…)(A.Comptom and Johnson, 1986)
3.1 Pressure effects
It is reported that at high pressure can cause a polypeptide consisting of 20 alanine residues transiting from the coil state to the helix state (Figure 3.2).In this research ,we assume that the coil state is random coiled and the helix state is totally α-helix. And the structure transition is due to the different conformational stability, while this kind stability is determined by entropy change between the solvent-entropy gain and the conformational-entropy loss during the transition. While the solvent-entropy gain is an increasing function of the pressure and the conformational-entropy loss is almost remaining constant only becomes smaller with the pressure increase.
Thus, at low pressure, the solvent-entropy gain is smaller than the conformational-entropy loss, which makes the coil state more stable. With the increase of the pressure, the solvent-entropy gain becomes larger and finally larger than the conformational-entropy loss, which makes the helix state more stable. So the increase of pressure leads to the transition from coil state to helix state.(Yoshidome and Kinoshita, 2009)
Figure 3.2 the conformational transition due to the pressure(Yoshidome and Kinoshita, 2009)
3.2 Temperature effects
Peptides are sensitive to the change of temperature, and the increase of temperature can cause their secondary structure unfolding and lead to the disruption of the function.(Hansen et al., 2009)
Researchers use a solution of peptide: (acetyl-ETATKAELLAKZEATHK-amide) at the concentration of 75µM in a buffer solution of NaCl at the concentration of 100mM, pH 2.2 to study the effect of temperature (Figure 3.3).
Figure 3.3 CD spectra at different temperature, 75µM peptide concentration in
100mM buffer solution: 50°C(_), 70°C(…..), cooling back to 5°C(﹍) (Cerpa et al., 1996)
From Figure 3.3, we can learn that, even at 70°C, β-sheet structure still can be found in the solution, when the solution cooled back to 5°C, the spectrum shows the characteristics of α-helix. However, after several months, the spectrum gradually changes back to the characteristics of β-sheet.(Cerpa et al., 1996)
3.3 pH effect
To study the effect of pH, researchers use two kinds of peptides:
Peptide I, acetyl-ETATKAELLAKYEATHK-amide
peptide II, acetyl-ETATKAELLAKZEATHK-amide
For Peptide I, at the peptide concentration at 100µM, the CD spectra (Figure 3.4) shows that from pH 2 to pH 4, the helical signal is slightly increasing, then come to a rapid drop from pH 4 to pH 5, and the helical signal keeps decreasing as the pH increases.
Figure3.4 CD spectra of Peptide I at 100µM peptide concentration. pH 2(_);
pH 4(﹍); pH 6(…); pH 8(..▲..)(Cerpa et al., 1996)
For peptide II, at the peptide concentration at 300 µM, in distilled water, the CD spectra (Figure 3.5) indicates that as pH increases, more α-helix conversion to β-sheet.(Cerpa et al., 1996)
Figure 3.5 CD spectra of peptide II at 300 µM peptide concentration. pH 2.5(﹍);
pH 7.8(…); pH 5.5(_) (Cerpa et al., 1996)
From the statement above, we can say that peptides display more β-sheet character at pH value of 5 or higher.
3.4 Peptide concentration effect
Researchers use a series of solutions of peptide: (acetyl-ETATKAELLAKZEATHK-amide) at different concentrations in a buffer solution of NaCl at the concentration of 100mM, pH 2.2 to study the effect of peptide concentration.
The CD spectra of different concentrations of the peptide are shown in Figure 3.6, from the spectra, we can find that at higher peptide concentrations, the spectra show the characteristic of β-sheet. Only at low concentration, we can see the appearance of α-helix.
Figure 3.6 CD spectra of peptide of different peptide concentration, in buffer solution of NaCl at 100mM. 376µM(_); 75µM(﹍); 7.5µM(…)(Cerpa et al., 1996)
It is also found that in vacuo, β-sheet structures are stable for neutral peptides; however, they can be disrupted by a charge. At the same time, no helix conformation have been observed for neutral peptides, charges play a critical role in the stability of the helices conformation.(Jarrold, 2007)
3.5 molecular switches at solid surface
Surface energy is the excess energy at the surface of a material compared to the bulk. Surface energy quantifies the disruption of intermolecular bonds that occur when a surface is created. In the physics of solids, surfaces must be intrinsically less energetically favourable than the bulk of a material, means the molecules on the surface have more energy compared with the molecules in the bulk of the material, or otherwise there would be a driving force for surface to be created, removing the bulk of the material.
Researchers investigated the conformation of polyalanine at a smooth uncharged solid surface considering the surface energy and number of residues.(Mijajlovic and Biggs, 2007) They found that molecules tend to be adsorbed parallel to the surface.(Biggs and Mijajlovic, 2008) It is also found that the structure change of polyalanine with the surface energy isn’t continuous, but change suddenly at specific surface energies. They said that for 6-alanine peptide, on [1 1 1] gold surface, the conformation change with the surface energy, and from figure 3.7, we can tell that the variation of the root-mean-square deviation (RMSD) changes when the surface energy changes, also, from this figure we can learn that the conformation of 6-alanine polypeptide changes as steps with no gradient and the changes only take place at specific surface energy Es=0.878Eg and Es=2.158Eg. (Mijajlovic and Biggs, 2007)
Figure 3.7 The variation of the root-mean-square deviation (RMSD) change with the
surface energy change for 6-alanine polypeptide(Mijajlovic and Biggs, 2007)
The “root-mean-square deviation (RMSD)” is a frequently used measurement of the differences between values predicted by a model or an estimator and the values actually observed. These individual differences are called residuals when the calculations are performed over the data sample that was used for estimation, and are called prediction errors when computed out-of sample. The RMSD serves to aggregate the magnitudes of the errors in prediction for various times into a single measurement of predictive power, RMSD is a good measure of accuracy, but only to compare forecasting errors of different models for a particular variable and root between variables, as it is scale-dependent.(Hyndman et al., 2006)
Figure 3.8 shows the three different conformations observed for 6-alanine polypeptide as the surface energy increases.
Figure 3.8 Three different conformations observed for 6-alanine polypeptide with the increase of surface energy. (a) α-helix; (b)310-helix; (c)27-helix(Mijajlovic and Biggs, 2007)
From Figure 3.8, we can see that there three different conformations as the surface energy increase, when Es is less than 0.878Eg the conformation is α-helix, when Es increases greater than 0.878 Eg while less than 2.158Eg, the conformation is 310-helix, as Es increases to 2.158Eg and greater, the conformation is 27-helix. So there are two conformational switches observed (1) α-helix to 310-helix and (2)310-helix to 27-helix.(Mijajlovic and Biggs, 2007)
It is also observed that the conformational switches in the peptide lead to step changes in the length of the peptide. It is said that the α-helix to 310-helix switch cause a length increase of approximately 24%, while the 310-helix to 27-helix switch is accompanied by an even greater length increase, the length of 27-helix is about 73% longer than the gas phase α-helix. (Biggs and Mijajlovic, 2008)
4. Using Molecular Dynamics to Study Protein Conformations
Molecular dynamic is computer simulation with atoms and or molecules interacting using some basic laws of physics. It provides the methodology for detailed microscopic modeling on the molecular scale. It can be used in the study of fundamental studies, phase transitions, collective behavior, complex fluids, polymers, solids, fluid dynamics as well as biomolecules.(Norberg and Nilsson, 2003)
However, there are also some limits of molecular dynamics simulation, such as chemical reactions are not described; the poor description of H-atoms (proton-transfer); the poor description of low temperature effects; the electrostatic model and the force fields are simplified.
However, molecular dynamics simulation is an efficient way to study the conformational transition in proteins. And the 310-helix/α-helix transition serves a good model for studying the conformational changes in proteins.
Using molecular dynamics simulation, researchers use the following peptides to study the conformational transition between α-helix and 310-helix.
Ala10: Ac-AAAAAAAAAA-NMe
Ala10-G:Ac-AAAAAAAGAA-NMe
Ala14:Ac-AAAAAAAAAAAAAA-NMe
Ala14-G:Ac-AAAAAAAAAGAAAA-NMe
Aib10:Ac-BBBBBBBBBB-NMe
(A=Ala, B=Aib, Ac=acetyl, G=Gly, NMe=N-methyl)
Molecular dynamics simulations were carried out using al-atom representation, and the simulations were under constant pressure (1 atm), and mean temperature of 300K.
During the study, they found that in the vacuo simulations, Ala10 is mainly α-helix while Aib10 can maintain quite well the 310-helix, and in the transition, Ala10 change into α-helix from 310-helix in 15ps, while Aib10 starting from α-helical conformation change into 310-helix in 10ps.While in solvated system, the conformational transition between the two types of helices take much more time. With the help of molecular dynamics simulation, they also studied the free energy difference during the transition, which show the same result that α-helix is popular in Ala10 while 310-helix is favourable in Aib10.(Zhang and Hermans, 1994)
Another researcher also use molecular dynamics simulation to study conformational transition between α-helix and β-sheet. And with the help of molecular dynamics simulation, they are able to provide a critical geometrical condition of the α-helix/β-sheet transition and associated molecular-level effects. And with the help of molecular dynamics simulation, they provide an evidence for a critical filament length scale, and that maybe used to explain other structure transitions, stability, and flexibility in proteins.(Palencˇár and Bleha, 2013)
There is another example of using molecular dynamics simulation to study the conformation of proteins. In this study, researchers use the Amber force fields to study the long chain of polyalanine, they found that after cooling long polyalanine chain to 303K, the straight α-helix become shorter pieces organizing into helical bundles. The straight α-helix becomes unstable in polypeptides of the length n~55. And with the help of molecular dynamics simulation, they studied the temperature dependency of helicity and stabilization energy of bundles.(Qin and Buehler, 2010)
Conclusion
From this review we can learn that molecular switches can be driven by pressure, temperature, pH, charge and concentration. We can learn that the increase of pressure can drive protein conformational transition from coil state to helix state. And the increase can make the protein tend to be in sheet state.at the same time, pH increase also drive protein conformation to form the sheet state instead of helix state. What’s more, the increase of peptide concentration also promotes the structure to transit to sheet state. However, charges can drive proteins to form helix sate; even one single charge can disrupt the sheet state.
We can also learn from the literature that at solid surface, peptides undergo step conformational changes, in our case, the 6-alanine polypeptide at [1 1 1] gold surface undergo three conformations, two switches with the increase of the surface energy.
From this literature review, we can also learn that molecular dynamics simulation is an efficient way to study the conformations of proteins, and therefore, molecular dynamics simulation may provide a new way to study the molecular switches in proteins from energy, structure and other aspects.
Without switches, we can never turn a computer or a light on or off; no electric applications can work without switches. Just like normal switches, molecular switches also play an important role in science and technology; it plays as the fundamental building blocks in several scientific fields. During the past few decades, a huge diversity of molecular switches have been engineered and characterized, new areas of fast and reversible control have been opened up. At the same time, protein plays an important role in human life and different parts of science; therefore, it is of great importance to study the molecular switches in proteins. It is certain that with the development of research technologies, we will learn more about molecular switches and proteins and of course get to know the molecular switches in proteins better, and we can make better use of it in dealing with disease such as Alzheimer’s disease whose cause is said to be the improper conformational transition of certain protein in brain, and we can develop new nanomaterial in logical gate control, and signal transport. So there is no doubt that the study of molecular switches has a promising future.
And we can say that with the development molecular dynamics simulation, we can make our simulation more realistic and more and more conditions will be taken into consideration, which will lead our simulation more close to reality, and the result will be more accurate and more reliable.
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