Zanxia Cao

Effects of pH and Temperature on the Structural and Thermodynamic Character of a-syn12 Peptide in Aqueous Solution

Abstract The structural and thermodynamic characters of α-syn12 peptide in aqueous solution at different pH and temperatures have been investigated through temperature replica exchange molecular dynamics (T-REMD) simulations with GROMOS 43A1 force field. The two independent T-REMD simulations were completed at pH = 7.0 and 10.0, respectively. Each replica was run for 300 ns. The structural and thermodynamic characters of α-syn12 peptide were studied based on the distributions of backbone dihedral angles, the free energy surface, and the stability of different type structure and the favorite conformations of the peptide. The results showed that the simulation at pH = 10.0 produced more sampling in α region than the simulation at pH = 7.0. The temperature changes from 283 K to 308 K result in negligible effects on the distributions of backbone dihedral angle. The β hairpin conformation with Turn9-6 and four hydrogen bonds (HB4-11, HB6-9, HB9-6 and HB11-4) is the lowest free energy state in the simulation at pH = 7.0. However, for the simulation at pH = 10.0, the lowest free energy state corresponds to a structure with Turn9-6 and two hydrogen bonds (HB6-10 and HB10-6) induced by an overly strong residue-residue interaction effect between lysine residues. For the simulation at pH = 7.0, the free energy change of the α-syn12 peptide from the unfolded state to the β hairpin state was in good agreement with the experiments and molecular dynamics simulation results for the other β-peptides, the β hairpin state of the α-syn12 peptide included the conformations that not only the Turn9-6 is formed, but also the terminus are closed together in space. However, the subtle balances between lysine-lysine interactions and lysine-solvent interaction are disrupted in the simulation at pH = 10.0, which induced the assembly of lysine residues, the β hairpin conformation is destabilized by the deprotonation of the Lys side chain. This study can help us to understand the conformation changes and the thermodynamic character of α-syn12 peptide at atomic level induced by changing pH and temperature, which is propitious to reveal the nosogenesis of Parkinson disease. In our knowledge, this is the first report to study the influence of pH and temperature on isolated α-syn12 peptide in water by T-REMD.

Novel Strategies for Drug Discovery Based on Intrinsically Disordered Proteins (IDPs)

Intrinsically disordered proteins (IDPs) are proteins that usually do not adopt well-defined native structures when isolated in solution under physiological conditions. Numerous IDPs have close relationships with human diseases such as tumor, Parkinson disease, Alzheimer disease, diabetes, and so on. These disease-associated IDPs commonly play principal roles in the disease-associated protein-protein interaction networks. Most of them in the disease datasets have more interactants and hence the size of the disease-associated IDPs interaction network is simultaneously increased. For example, the tumor suppressor protein p53 is an intrinsically disordered protein and also a hub protein in the p53 interaction network; α-synuclein, an intrinsically disordered protein involved in Parkinson diseases, is also a hub of the protein network. The disease-associated IDPs may provide potential targets for drugs modulating protein-protein interaction networks. Therefore, novel strategies for drug discovery based on IDPs are in the ascendant. It is dependent on the features of IDPs to develop the novel strategies. It is found out that IDPs have unique structural features such as high flexibility and random coil-like conformations which enable them to participate in both the “one to many” and “many to one” interaction. Accordingly, in order to promote novel strategies for drug discovery, it is essential that more and more features of IDPs are revealed by experimental and computing methods.

Molecular Dynamics Simulations of Intrinsically Disordered Proteins in Human Diseases

Recent structural and genomic studies have clearly shown that many proteins contain long regions that do not adopt any globular structures under native conditions. These regions are termed intrinsically disordered or unstructured, and the proteins with intrinsically disordered regions are called intrinsically disordered proteins (IDPs). Current studies estimate that one third of eukaryotic proteins contain stretches of at least 30 contiguous disordered residues, the predictions are even higher in cancer-associated and signaling proteins (80% and 67%, respectively). IDPs play crucial roles in many aspects of molecular and cell biology and numerous IDPs are associated with human diseases such as cancer, cardiovascular disease, amyloidoses, neurodegenerative diseases, diabetes and others. IDPs such as tumor suppressor P53, BRCA1, Parkinsons protein α-synuclein, Alzheimer disease protein tau and many other diseaseassociated hub proteins represent attractive targets for drugs modulating protein-protein interactions. The structures and dynamics of the disordered proteins are the basis for the novel drug discovery. IDPs are lack of stable tertiary and /or secondary structure under physiological conditions in vitro. It is difficult to obtain accurate experimental measurements for the structures and dynamics of the disordered proteins. Molecular dynamics simulations provide available powerful tools to calculate the structures and their related dynamics of IDPs. In this paper, we focus on structural and dynamics insights of disease-associated disordered proteins by molecular dynamics simulations.

Natural protein sequences are more intrinsically disordered than random sequences

Most natural protein sequences have resulted from millions or even billions of years of evolution. How they differ from random sequences is not fully understood. Previous computational and experimental studies of random proteins generated from noncoding regions yielded inclusive results due to species-dependent codon biases and GC contents. Here, we approach this problem by investigating 10,000 sequences randomized at the amino acid level. Using well-established predictors for protein intrinsic disorder, we found that natural sequences have more long disordered regions than random sequences, even when random and natural sequences have the same overall composition of amino acid residues. We also showed that random sequences are as structured as natural sequences according to contents and length distributions of predicted secondary structure, although the structures from random sequences may be in a molten globular-like state, according to molecular dynamics simulations. The bias of natural sequences toward more intrinsic disorder suggests that natural sequences are created and evolved to avoid protein aggregation and increase functional diversity.

Effects of Different Force Fields and Temperatures on the Structural Character of Abeta (12–28) Peptide in Aqueous Solution

The aim of this work is to investigate the effects of different force fields and temperatures on the structural character of Aβ (12–28) peptide in aqueous solution. Moreover, the structural character of Aβ (12–28) peptide is compared with other amyloid peptides (such as H1 and α-syn12 peptide). The two independent temperature replica exchange molecular dynamics (T-REMD) simulations were completed by using two different models (OPLS-AA/TIP4P and GROMOS 43A1/SPC). We compared the models by analyzing the distributions of backbone dihedral angles, the secondary structure propensity, the free energy surface and the formation of β-hairpin. The results show that the mostly populated conformation state is random coil for both models. The population of β-hairpin is below 8 percent for both models. However, the peptide modeled by GROMOS 43A1 form β-hairpin with turn located at residues F19-E22, while the peptide modeled by OPLS-AA form β-hairpin with turn located at residues L17-F20.

Why the OPLS-AA force field cannot produce the β-hairpin structure of H1 peptide in solution when comparing with the GROMOS 43A1 force field?

Abstract The optimal combination of force field and water model is an essential problem that is able to increase molecular dynamics simulation quality for different types of proteins and peptides. In this work, an attempt has been made to explore the problem by studying H1 peptide using four different models based on different force fields, water models and electrostatic schemes. The driving force for H1 peptide conformation transition and the reason why the OPLS-AA force field cannot produce the β-hairpin structure of H1 peptide in solution while the GROMOS 43A1 force field can do were investigated by temperature replica exchange molecular dynamics simulation (T-REMD). The simulation using the GROMOS 43A1 force field preferred to adopt a β-hairpin structure, which was in good agreement with the several other simulations and the experimental evidences. However, the simulation using the OPLS-AA force field has a significant difference from the simulations with the GROMOS 43A1 force field simulation. The results show that the driving force in H1 peptide conformation transition is solvent exposure of its hydrophobic residues. However, the subtle balances between residue-residue interactions and residue-solvent interaction are disrupted by using the OPLS-AA force field, which induced the reduction in the number of residue-residue contact. Similar solvent exposure of the hydrophobic residues is observed for all the conformations sampled using the OPLS-AA force field. For H1 peptide which exhibits large solvent exposure of the hydrophobic residues, the GROMOS 43A1 force field with the SPC water model can provide more accurate results.

Structural and thermodynamics characters of isolated α-syn12 peptide: long-time temperature replica-exchange molecular dynamics in aqueous solution

The structural and thermodynamics characters of α-syn12 (residues 1-12 of the human α-synuclein protein) peptide in aqueous solution were investigated through temperature replica-exchange molecular dynamics (T-REMD) simulations with the GROMOS 43A1 force field. The two independent T-REMD simulations were completed starting from an initial conformational α-helix and an irregular structure, respectively. Each replica was run for 300 ns. The structural and thermodynamics characters were studied based on parameters such as distributions of backbone dihedral angles, free energy surface, stability of folded β-hairpin structure, and favorite conformations. The results showed that the isolated α-syn12 peptide in water adopted four different conformational states: the first state was a β-hairpin ensemble with Turn(9-6) and four hydrogen bonds, the second state was a β-hairpin ensemble with two turns (Turn(9-6) and Turn(5-2)) and three hydrogen bonds, the third state was a disordered structure with both Turn(8-5) and Turn(5-2), and the last state was a π-helix ensemble. Meanwhile, we studied the free energy change of α-syn12 peptide from the unfolded state to the β-hairpin state, which was in good agreement with the experiments and molecular dynamics simulations for some other peptides. We also analyzed the driving force of the peptide transition. The results indicated that the driving forces were high solvent exposure of hydrophobic Leu8 and hydrophobic residues in secondary structure. To our knowledge, this was the first report to study the isolated α-syn12 peptide in water by T-REMD.

Studying the unfolding process of protein G and protein L under physical property space

BackgroundThe studies on protein folding/unfolding indicate that the native state topology is an important determinant of protein folding mechanism. The folding/unfolding behaviors of proteins which have similar topologies have been studied under Cartesian space and the results indicate that some proteins share the similar folding/unfolding characters.ResultsWe construct physical property space with twelve different physical properties. By studying the unfolding process of the protein G and protein L under the property space, we find that the two proteins have the similar unfolding pathways that can be divided into three types and the one which with the umbrella-shape represents the preferred pathway. Moreover, the unfolding simulation time of the two proteins is different and protein L unfolding faster than protein G. Additionally, the distributing area of unfolded state ensemble of protein L is larger than that of protein G.ConclusionUnder the physical property space, the protein G and protein L have the similar folding/unfolding behaviors, which agree with the previous results obtained from the studies under Cartesian coordinate space. At the same time, some different unfolding properties can be detected easily, which can not be analyzed under Cartesian coordinate space.

Turn-directed α-β conformational transition of α-syn12 peptide at different pH revealed by unbiased molecular dynamics simulations.

The transition from α-helical to β-hairpin conformations of α-syn12 peptide is characterized here using long timescale, unbiased molecular dynamics (MD) simulations in explicit solvent models at physiological and acidic pH values. Four independent normal MD trajectories, each 2500 ns, are performed at 300 K using the GROMOS 43A1 force field and SPC water model. The most clustered structures at both pH values are β-hairpin but with different turns and hydrogen bonds. Turn9-6 and four hydrogen bonds (HB9-6, HB6-9, HB11-4 and HB4-11) are formed at physiological pH; turn8-5 and five hydrogen bonds (HB8-5, HB5-8, HB10-3, HB3-10 and HB12-1) are formed at acidic pH. A common folding mechanism is observed: the formation of the turn is always before the formation of the hydrogen bonds, which means the turn is always found to be the major determinant in initiating the transition process. Furthermore, two transition paths are observed at physiological pH. One of the transition paths tends to form the most-clustered turn and improper hydrogen bonds at the beginning, and then form the most-clustered hydrogen bonds. Another transition path tends to form the most-clustered turn, and turn5-2 firstly, followed by the formation of part hydrogen bonds, then turn5-2 is extended and more hydrogen bonds are formed. The transition path at acidic pH is as the same as the first path described at physiological pH.

Bias-Exchange Metadynamics Simulation of Membrane Permeation of 20 Amino Acids

Thermodynamics of the permeation of amino acids from water to lipid bilayers is an important first step for understanding the mechanism of cell-permeating peptides and the thermodynamics of membrane protein structure and stability. In this work, we employed bias-exchange metadynamics simulations to simulate the membrane permeation of all 20 amino acids from water to the center of a dipalmitoylphosphatidylcholine (DPPC) membrane (consists of 256 lipids) by using both directional and torsion angles for conformational sampling. The overall accuracy for the free energy profiles obtained is supported by significant correlation coefficients (correlation coefficient at 0.5–0.6) between our results and previous experimental or computational studies. The free energy profiles indicated that (1) polar amino acids have larger free energy barriers than nonpolar amino acids; (2) negatively charged amino acids are the most difficult to enter into the membrane; and (3) conformational transitions for many amino acids during membrane crossing is the key for reduced free energy barriers. These results represent the first set of simulated free energy profiles of membrane crossing for all 20 amino acids.