Fatih Yaşar

In silico cross seeding of Aβ and amylin fibril-like oligomers.

Recent epidemiological data have shown that patients suffering from Type 2 Diabetes Mellitus have an increased risk to develop Alzheimers disease and vice versa. A possible explanation is the cross-sequence interaction between Aβ and amylin. Because the resulting amyloid oligomers are difficult to probe in experiments, we investigate stability and conformational changes of Aβ-amylin heteroassemblies through molecular dynamics simulations. We find that Aβ is a good template for the growth of amylin and vice versa. We see water molecules permeate the β-strand-turn-β-strand motif pore of the oligomers, supporting a commonly accepted mechanism for toxicity of β-rich amyloid oligomers. Aiming for a better understanding of the physical mechanisms of cross-seeding and cell toxicity of amylin and Aβ aggregates, our simulations also allow us to identify targets for the rational design of inhibitors against toxic fibril-like oligomers of Aβ and amylin oligomers.

Multicanonical procedure for continuum peptide models

The multicanonical (Muca) Monte Carlo method enables simulating a system over a wide range of temperatures and thus has become an efficient tool for studying spin glasses, first‐order phase transitions, the helix–coil transition of polypeptides, and protein folding. However, implementation of the method requires calculating the multicanonical weights by an iterative procedure that is not straightforward and is a stumbling block for newcomers. A recursive procedure that takes into account the statistical errors of all previous iterations and thus enables an automatic calculation of the weights without the need for human intervention after each iteration has been proposed. This procedure, which has already been tested successfully for lattice systems, is extended here to continuum models of peptides and proteins. The method is examined in detail and tested for models of the pentapeptide Leu‐enkephalin (Tyr‐Gly‐Gly‐Phe‐Leu) described by the potential energy function ECEPP. Because of the great interest in the structural mapping of the low‐energy region of biomolecules, the energy of structures selected from the Muca trajectory is minimized. The extent of conformational coverage provided by the method is examined and found to be very satisfactory.

Sampling of Protein Folding Transitions: Multicanonical Versus Replica Exchange Molecular Dynamics

We compare the efficiency of multicanonical and replica exchange molecular dynamics for the sampling of folding/unfolding events in simulations of proteins with end-to-end β-sheet. In Go-model simulations of the 75-residue MNK6, we observe improvement factors of 30 in the number of folding/unfolding events of multicanonical molecular dynamics over replica exchange molecular dynamics. As an application, we use this enhanced sampling to study the folding landscape of the 36-residue DS119 with an all-atom physical force field and implicit solvent. Here, we find that the rate-limiting step is the formation of the central helix that then provides a scaffold for the parallel β-sheet formed by the two chain ends.

Efficiency of the multicanonical simulation method as applied to peptides of increasing size: The heptapeptide deltorphin

The advantage of the multicanonical (MUCA) simulation method of Berg and coworkers over the conventional Metropolis method is in its ability to move a system effectively across energy barriers thereby providing results for a wide range of temperatures. However, a MUCA simulation is based on weights (related to the density of states) that should be determined prior to a production run and their calculation is not straightforward. To overcome this difficulty a procedure has been developed by Berg that calculates the MUCA weights automatically. In a previous article (Yaşar et al. J Comput Chem 2000, 14, 1251–1261) we extended this procedure to continuous systems and applied it successfully to the small pentapeptide Leu‐enkephalin. To investigate the performance of the automated MUCA procedure for larger peptides, we apply it here to deltorphin, a linear heptapeptide with bulky side chains (H‐Tyr1‐D‐Met2‐Phe3‐His4‐Leu5‐Met6‐Asp7‐NH2). As for Leu‐enkephalin, deltorphin is modeled in vacuum by the potential energy function ECEPP. MUCA is found to perform well. A weak second peak is seen for the specific heat, which is given a special attention. By minimizing the energy of structures along the trajectory it is found that MUCA provides a good conformational coverage of the low energy region of the molecule. These latter results are compared with conformational coverage obtained by the Monte Carlo minimization method of Li and Scheraga.

Softening of Phase Transition in 2D Potts Model Under Quenched Bond Randomness

We have simulated, by using cluster algorithm, the

Thermodynamic and structural analysis of interactions between peptide ligands and SEB.

q=8

Replica-exchange-with-tunneling for fast exploration of protein landscapes

state Potts model in two-dimension with varying amount of quenched bond randomness. We have shown that there exist a finite size dependent threshold value of the introduced quenched bond randomness for rounding the first-order phase transition and this threshold value becomes smaller as the system size increased.

Enhancing the affinity of SEB‐binding peptides by repeating their sequence

Staphylococcal enterotoxin B (SEB) is an exotoxin produced by Staphylococcus aureus and commonly associated with food poisoning. In this study, SEB‐binding peptides were identified by screening a phage displayed peptide library. The binding of peptides to SEB was tested with isothermal titration calorimetry (ITC) and of the five selected peptides, three showed affinity to SEB, with one measured to have the highest affinity constant (105 M−1). ITC revealed that the interaction of peptide ligands with SEB was driven entropically and the binding was dominated by hydrophobic interactions. Circular dichroism (CD) measurements and molecular dynamics (MD) simulations, together, give a structural insight into the interaction of peptides with SEB. While SEB binding peptides showed random coil structure before binding, after complex formation they had more ordered structures. The peptide with highest affinity to SEB showed stable conformation during MD simulation. Taken together, our approach about thermodynamic and structural characterization of peptide ligands can be used to develop aptamers, with high affinity and selectivity, for biosensor applications. Copyright

Multicanonical simulations of some peptides

While the use of replica-exchange molecular dynamics in protein simulations has become ubiquitous, its utility is limited in many practical applications. We propose to overcome some shortcomings that hold back its use in settings such as multi-scale or explicit solvent simulations by integrating ideas of hybrid MC/MD into the replica-exchange protocol. This Replica-Exchange-with-Tunneling method is tested by simulating the Trp-cage protein, a system often used in molecular biophysics for testing sampling techniques.

Short-time dynamics of cluster growth in the Potts model

The utilization of peptide ligands in biosensors and bioassays is dependent on achieving high affinity of these peptides toward their targets. In a previous report, we identified 12‐mer peptides that could selectively bind to Staphylococcal enterotoxin B (SEB) using a phage‐display library. In this study, we explore for new modification approaches to enhance the affinity of two different SEB‐binding peptides. In order to identify the binding regions of selected peptides, the charged residues and the ones, critical for the structure of peptide, were replaced with alanine. However, a specific binding region could not be suggested as all mutant peptides have lost their affinities toward SEB completely. The modifications for the affinity enhancement were done by repeating the 12‐mer peptide sequences. A 10‐fold increase was observed in the binding affinity of one of the two‐repeated peptides, while this modification did not affect the affinity of the other tested peptide. The peptide, with enhanced affinity, was further modified as three repeats; however the affinity of the peptide decreased. The structural basis of the affinity difference between modified peptides was examined by molecular dynamics simulation. The results showed that the conformational differences hold the key for affinity of peptides modified by repeating the sequence. This high affinity peptide with increased affinity is a promising molecular recognition agent to be used in the detection of SEB to be utilized in biosensing systems.