Canan Baysal

Elucidating the structural mechanisms for biological activity of the chemokine family.

Chemokines are a family of proteins involved in inflammatory and immune response. They share a common fold, made up of a three‐stranded β‐sheet, and an overlaying α‐helix. Chemokines are mainly categorized into two subfamilies distinguished by the presence or absence of a residue between two conserved cysteines in the N‐terminus. Although dimers and higher‐order quaternary structures are common in chemokines, they are known to function as monomers. Yet, there is quite a bit of controversy on how the actual function takes place. The mechanisms of binding and activation in the chemokine family are investigated using the gaussian network model of proteins, a low‐resolution model that monitors the collective motions in proteins. It is particularly suitable for elucidating the global dynamic characteristics of large proteins or the common properties of a group of related proteins such as the chemokine family presently investigated. A sample of 16 proteins that belong to the CC, CXC, or CX3C subfamilies are inspected. Local packing density and packing order of residues are used to determine the type and range of motions on a global scale, such as those occurring between various loop regions. The 30s‐loop, although not directly involved in the binding interface like the N‐terminus and the N‐loop, is identified as having a prominent role in both binding/activation and dimerization. Two mechanisms are distinguished based on the communication among the three flexible regions. In these two‐step mechanisms, the 30s‐loop assists either the N‐loop or the N‐terminus during binding and activation. The findings are verified by molecular mechanics and molecular dynamics simulations carried out on the detailed structure of representative proteins from each mechanism type. A basis for the construction of hybrids of chemokines to bind and/or activate various chemokine receptors is presented. Proteins 2001;43:150–160.

Relaxation Kinetics and the Glassiness of Proteins: The Case of Bovine Pancreatic Trypsin Inhibitor

Folded proteins may be regarded as soft active matter under physiological conditions. The densely packed hydrophobic interior, the relatively molten hydrophilic exterior, and the spacer connecting these put together a large number of locally homogeneous regions. For the case of the bovine pancreatic trypsin inhibitor, with the aid of molecular dynamics simulations, we have demonstrated that the kinetics of the relaxation of the internal motions is highly concerted, manifesting the proteins heterogeneity, which may arise from variations in density, local packing, or the local energy landscape. This behavior is characterized in a stretched exponential decay described by an exponent of approximately 0.4 at physiological temperatures. Due to the trapped conformations, configurational entropy becomes smaller, and the associated stretch exponent drops to half of its value below the glass transition range. The temperature dependence of the inverse relaxation time closely follows the Vogel-Tamman-Fulcher expression when the protein is biologically active.

Coordination topology and stability for the native and binding conformers of chymotrypsin inhibitor 2.

We demonstrate that the stabilization of the binding region is accomplished at the expense of a loss in the stability of the rest of the protein. A novel molecular mechanics (MM) approach is introduced to distinguish residue stabilities of proteins in a given conformation. As an example, the relative stabilities of folded chymotrypsin inhibitor 2 (CI2) in unbound form, and CI2 in complex with subtilisin novo is investigated. The conformation of the molecule in the two states is almost identical, with an ∼0.6‐Å root‐mean‐square deviation (RMSD) of the Cα atoms. On binding, the packing density changes only at the binding loop. However, residue fluctuations in the rest of the protein are greatly altered solely due to those contacts, indicating the effective propagation of perturbation and the presence of remotely controlling residues. To quantify the interplay between packing density, packing order, residue fluctuations, and residue stability, we adopt an MM approach whereby small displacements are inserted at selected residues, followed by energy minimization; the displacement of each residue in response to such perturbations are organized in a perturbation‐response matrix L. We define residue stability λi = ∑jLij/∑j Lji as the ratio of the amount of change to which the residue is amenable, to the ability of a given residue to induce change. We then define the free energy associated with residue stability, ΔGλ = −RT ln λ. ΔGλ intrinsically selects the residues that are in the folding core. Upon complexation, the binding loop becomes more resistant to perturbation, in contrast to the α‐helix that favors change. Although the two forms of CI2 are structurally similar, residue fluctuations differ vastly, and the stability of many residues is altered upon binding. The decrease in entropy introduced by binding is thus compensated by these changes. Proteins 2001;45:62–70.

Free energy based populations of interconverting microstates of a cyclic peptide lead to the experimental NMR data

Analysis of nuclear Overhauser enhancement (NOE) intensities data of interconverting microstates of a peptide is a difficult problem in nmr. A new statistical mechanics methodology has been proposed recently, consisting of several steps: (1) potential energy wells on the energy surface of the molecule are identified (the corresponding regions are called wide microstates); (2) each wide microstate is then spanned by a Monte Carlo (MC) or molecular dynamics simulation starting from a representative structure, and the corresponding relative populations are obtained from the free energy calculated with the local states method; and (3) the overall NOEs and 3J coupling constants are obtained as averages over the corresponding contributions of the samples, weighted by the populations. Extending this methodology to cyclic peptides, we are treating here the hexapeptide cyclo(D-Pro1-Phe2-Ala3-Ser4-Phe5-Phe6) in DMSO, which was studied by Kessler et al. using nmr (Journal of the American Chemical Society, 1992, Vol. 114, pp. 4805-4818). They found that at least two structures are required to explain their NOE data, a conclusion also corroborated by our analysis (Journal of the American Chemical Society, 1998, Vol. 120, pp. 800-812) and led to a novel derivation of atomic solvation parameters (ASPs) for DMSO. Thus, the overall interactions within the peptide-solvent system are described approximately by Etot = EGRO + summation operator sigmaiAi, where EGRO is the energy of the GROMOS force field, Ai is the solvent-accessible surface area of atom i, and sigmai is the ASP. In the present paper the validity of these ASPs within the framework of the entire methodology is verified. This requires taking into account 23 microstates. A very good agreement is obtained between experimental and calculated NOEs and 3J coupling constants. The free energy based populations lead to the best results, which means that entropic effects should not be ignored. We have also studied the behavior of the internal angular fluctuations of the proton-proton vectors and discovered that they have a negligible effect on the calculated NOEs; this is due to the relatively concentrated wide microstates spanned by the MC simulations. The applicability of our ASPs to other cyclic peptides in DMSO is being studied in another work and preliminary results are discussed.

New conformational search method based on local torsional deformations for cyclic molecules, loops in proteins, and dense polymer systems

We propose a conformational search method, based on local torsional deformations (LTD) for locating the low energy structures of cyclic peptides, loops in proteins or dense polymer systems. LTD is applied preliminarily to cycloundecane modeled by the MM2 force field, and is found to be more efficient than other techniques.

Efficiency of simulated annealing for peptides with increasing geometrical restrictions

Simulated annealing (SA) is a popular global minimizer that can conveniently be applied to complex macromolecular systems. Thus, a molecular dynamics or a Monte Carlo simulation starts at high temperature, which is decreased gradually, and the system is expected to reach the low‐energy region on the potential energy surface of the molecule. However, in many cases this process is not efficient. Alternatively, the low‐energy region can be reached more effectively by minimizing the energy of selected molecular structures generated along the simulation pathway. The efficiency of SA to locate energy‐minimized structures within 5 kcal/mol above the global energy minimum is studied as applied to three peptide models with increasing geometrical restrictions: (1) The linear pentapeptide Leu‐enkephalin described by the ECEPP potential, (2) a cyclic hexapeptide described by the GROMOS force field energy EGRO alone, and (3) the same cyclic peptide with EGRO combined with a restraining potential based on 31 proton–proton restraints obtained from nuclear magnetic resonance (NMR) experiments. The efficiency of SA is compared to that of the Monte Carlo minimization (MCM) method of Li and Scheraga, and to our local torsional deformations (LTD) method for the conformational search of cyclic molecules. The results for the linear peptide show that SA provides a relatively weak guidance towards the most stable energy region; as expected, this guidance increases for the cyclic peptide and the cyclic peptide with NMR restraints. However, in general, MCM and LTD are significantly more efficient than SA as generators of low‐energy minimized structures. This suggests that LTD might provide a better search tool than SA in structure determination of protein regions for which a relatively small number of restraints are provided by NMR. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1659–1670, 1999

Ab initio prediction of the solution structures and populations of a cyclic pentapeptide in DMSO based on an implicit solvation model

Using a recently developed statistical mechanics methodology, the solution structures and populations of the cyclic pentapeptide cyclo(D‐Pro1–Ala2–Ala3–Ala4–Ala5) in DMSO are obtained ab initio, i.e., without using experimental restraints. An important ingredient of this methodology is a novel optimization of implicit solvation parameters, which in our previous publication [Baysal, C.; Meirovitch, H. J Am Chem Soc 1998, 120, 800–812] has been applied to a cyclic hexapeptide in DMSO. The molecule has been described by the simplified energy function Etot = EGRO + ∑k σkAk, where EGRO is the GROMOS force‐field energy, σk and Ak are the atomic solvation parameter (ASP) and the solvent accessible surface area of atom k. This methodology, which relies on an extensive conformational search, Monte Carlo simulations, and free energy calculations, is applied here with Etot based on the ASPs derived in our previous work, and for comparison also with EGRO alone. For both models, entropy effects are found to be significant. For Etot, the theoretical values of proton–proton distances and 3J coupling constants agree very well with the NMR results [Mierke, D. F.; Kurz, M.; Kessler, H. J Am Chem Soc 1994, 116, 1042–1049], while the results for EGRO are significantly worse. This suggests that our ASPs might be transferrable to other cyclic peptides in DMSO as well, making our methodology a reliable tool for an ab initio structure prediction; obviously, if necessary, parts of this methodology can also be incorporated in a best‐fit analysis where experimental restraints are used.

Conformational features of poly(1,1-dihydroperfluorooctyl acrylate) and poly(vinyl acetate) diblock oligomers in supercritical carbon dioxide

We report detailed molecular dynamics calculations of single chain diblocks of poly(1,1- dihydroperfluorooctyl acrylate) (PFOA) and poly(vinyl acetate) (PVAc) in supercritical carbon dioxide, SCCO2. At the critical micelle concentration, this system exhibits self-assembly into micellar structures due to the solvent specific selectivity of the blocks. Although the intermolecular factors determining micelle formation are well studied for this system, the intramolecular single chain conformational features of the molecules have not yet been investigated in the literature. The specific aim of the present work is to study the conformational properties of the single diblock chains in supercritical carbon dioxide at 65 °C, and at four different pressures by molecular dynamics simulations. Fluctuations in the shapes of the PVAc and PFOA blocks are observed to be strongly dependent on pressure. The rate of approach of an initially rodlike chain to its equilibrium conformational space is likewise found to depend st...

New surfactants design for CO2 applications: Molecular dynamics simulations of fluorocarbon–hydrocarbon oligomers

Novel block co-oligomers are designed as candidate surfactants in near-supercritical CO2 environment, with the CO2–phobic block consisting of ethyl propionate and ten different types of ethylene monomers, flanked on either side by eight repeat unit fluorinated CO2–philic blocks. Single chain molecular dynamics simulations are performed to understand their conformational and dynamic properties. Depending on the side chain type, the CO2–phobic blocks are prone to shrinkage in the CO2 environment, while the CO2–philic blocks preserve their vacuum dimensions. The overall chains form U-shaped planar structures with flapping motion of the fluorinated arms; thus, we expect bilayer micelle formation under these conditions. The origin of the CO2–oligomer interactions is investigated and van der Waals interactions are found to dominate over electrostatic interactions in the CO2 environment. Calculations of the radial distribution function for the solvent molecules around the oligomer backbone show a solvation shell...

Performance of Efficient Minimization Algorithms as Applied to Models of Peptides and Proteins

We test the efficiency of three minimization algorithms as applied to models of peptides and proteins. These include: the limited memory quasi‐Newton (L‐BFGS) of Liu and Nocedal; the truncated Newton (TN) with automatic preconditioner of Nash; and the nonlinear conjugate gradients (CG) of Shanno and Phua. The molecules are modeled by two energy functions, one is the Gromos87 united atoms force field (defining the energy EGRO), which takes into account the intramolecular interactions only; the second is defined by the energy Etot=EGRO+Esolv, where Esolv is an implicit solvation free every term based on the solvent‐accessible surface area of the atoms. The molecules studied are cyclo‐(d‐Pro1–Ala2–Ala3–Ala4–Ala5) (31 atoms), axinastatin 2 [cyclo‐(Asn1–Pro2–Phe3–Val4–Leu5–Pro6–Val7), 62 atoms], and the protein bovine pancreatic trypsin inhibitor (58 residues, 568 atoms). With EGRO, the performance of TN with respect to the CPU time is found to be ∼1.2 to 2 times better than that of both L‐BFGS and CG, whereas, with Etot, L‐BFGS outperforms TN by a factor of 1.5 to 2.5, and CG by a larger factor. Still, the quality of the solution in terms of the value of the minimized energy and the gradient norm, obtained with TN, is always equivalent to, or better than, those obtained with L‐BFGS and CG. The performance is analyzed in terms of criteria outlined by Nash and Nocedal. We find the distribution of the Hessian eigenvalues to be a reliable predictor of efficiency. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 354–364, 1999