Replica Exchange Molecular Dynamics of Diphenylalanine Amyloid Peptides in Electric Fields.

The self-assembling propensity of amyloid peptides such as diphenylalanine (FF) allows them to form ordered, nanoscale structures, with biocompatible properties important for biomedical applications. Moreover, piezoelectric properties allow FF molecules and their aggregates (e.g., FF nanotubes) to be aligned in a controlled way by the application of external electric fields. However, while the behavior of FF nanostructures emerges from the biophysical properties of the monomers, the detailed responses of individual peptides to both temperature and electric fields are not fully understood. Here, we study the temperature-dependent conformational dynamics of FF peptides solvated in explicit water molecules, an environment relevant to biomedical applications, by using an enhanced sampling method, replica exchange molecular dynamics (REMD), in conjunction with applied electric fields. Our simulations highlight and overcome possible artifacts that may occur during the setup of REMD simulations of explicitly solvated peptides in the presence of external electric fields, a problem particularly important in the case of short peptides such as FF. The presence of the external fields could overstabilize certain conformational states in one or more REMD replicas, leading to distortions of the underlying potential energy distributions observed at each temperature. This can be overcome by correcting the REMD initial conditions to include the lower-energy conformations induced by the external field. We show that the converged REMD data can be analyzed using a Markovian description of conformational states and show that a rather complex, 3-state, temperature-dependent conformational dynamics in the absence of electric fields collapses to only one of these states in the presence of the electric fields. These details on the temperature- and electric-field-dependent thermodynamic and kinetic properties of small FF amyloid peptides can be useful in understanding and devising new methods to control their aggregation-prone biophysical properties and, possibly, the structural and biophysical properties of FF molecular nanostructures.

CHARMM36 Lipid Force Field with Explicit Treatment of Long-Range Dispersion: Parametrization and Validation for Phosphatidylethanolamine, Phosphatidylglycerol, and Ether Lipids.

Long-range Lennard-Jones (LJ) interactions have been incorporated into the CHARMM36 (C36) lipid force field (FF) using the LJ particle-mesh Ewald (LJ-PME) method in order to remove the inconsistency of bilayer and monolayer properties arising from the exclusion of long-range dispersion [Yu, Y.; Semi-automated Optimization of the CHARMM36 Lipid Force Field to Include Explicit Treatment of Long-Range Dispersion. J. Chem. Theory Comput. 2021, 10.1021/acs.jctc.0c01326. (preceding article in this issue)]. The new FF is denoted C36/LJ-PME. While the first optimization was based on three phosphatidylcholines (PCs), this work extends the validation and parametrization to more lipids including PC, phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and ether lipids. The agreement with experimental structure data is excellent for PC, PE, and ether lipids. C36/LJ-PME also compares favorably with scattering data of PG bilayers but less so with NMR deuterium order parameters of 1,2-dimyristoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (DMPG) at 303.15 K, indicating a need for future optimization regarding PG-specific parameters. Frequency dependence of NMR T1 spin-lattice relaxation times is well-described by C36/LJ-PME, and the overall agreement with experiment is comparable to C36. Lipid diffusion is slower than C36 due to the added long-range dispersion causing a higher viscosity, although it is still too fast compared to experiment after correction for periodic boundary conditions. When using a 10 Å real-space cutoff, the simulation speed of C36/LJ-PME is roughly equal to C36. While more lipids will be incorporated into the FF in the future, C36/LJ-PME can be readily used for common lipids and extends the capability of the CHARMM FF by supporting monolayers and eliminating the cutoff dependence.

Albumin-chaperoned cyanine dye yields superbright NIR-II fluorophore with enhanced pharmacokinetics.

NIR-II fluorescence imaging greatly reduces scattering coefficients for nearly all tissue types at long wavelengths, benefiting deep tissue imaging. However, most of the NIR-II fluorophores suffer from low quantum yields and/or short circulation time that limit the quality of NIR-II imaging. Here, we engineered a supramolecular assembly of protein complex with lodged cyanine dyes to produce a brilliant NIR-II fluorophore, providing a NIR-II quantum yield of 21.2% with prolonged circulation time. Computational modeling revealed the mechanism for fluorescence enhancement and identified key parameters governing albumin complex for NIR-II fluorophores. Our complex afforded high-resolution microvessel imaging, with a 3-hour imaging window compared to 2 min for free dye alone. Furthermore, the complexation strategy was applied to an antibody-derived assembly, offering high-contrast tumor imaging without affecting the targeting ability of the antibody. This study provides a facile strategy for producing high-performance NIR-II fluorophores by chaperoning cyanine dyes with functional proteins.

An Albumin Sandwich Enhances in Vivo Circulation and Stability of Metabolically Labile Peptides.

The effectiveness of numerous molecular drugs is hampered by their poor pharmacokinetics. Different from previous approaches with limited effectiveness, most recently, emerging high-affinity albumin binding moieties (ABMs) for in vivo hitchhiking of endogenous albumin opens up an avenue to chaperone small molecules for long-acting therapeutics. Although several FDA-approved fatty acids have shown prolonged residence and therapeutic effect, an easily synthesized, water-soluble, and high-efficiency ABM with versatile drug loading ability is urgently needed to improve the therapeutic efficacy of short-lived constructs. We herein identified an ideal bivalent Evans blue derivative, denoted as N(tEB)2, as a smart ABM-delivery platform to chaperone short-lived molecules, through both computational modeling screening and efficient synthetic schemes. The optimal N(tEB)2 could reversibly link two molecules of albumin through its two binding heads with a preferable spacer, resulting in significantly extended circulation half-life of a preloaded cargo and water-soluble. Notably, this in situ dimerization of albumin was able to sandwich peptide therapeutics to protect them from proteolysis. As an application, we conjugated N(tEB)2 with exendin-4 for long-acting glucose control in a diabetic mouse model, and it was superior to both previously tested NtEB-exendin-4 (Abextide) and the newly FDA-approved semaglutide, which has been arguably the best commercial weekly formula so far. Hence, this novel albumin binder has excellent clinical potential for next-generation biomimetic drug delivery systems.

Structural Modulation of Human Amylin Protofilaments by Naturally Occurring Mutations.

Human islet amyloid polypeptide (hIAPP), also known as amylin, is a 37-amino-acid peptide, co-secreted with insulin, and widely found in fibril form in type-2 diabetes patients. By using all-atom molecular dynamics simulations, we study hIAPP fibril segments (i.e., fibrillar oligomers) formed with sequences of naturally occurring variants from cat, rat, and pig, presenting different aggregation propensities. We characterize the effect of mutations on the structural dynamics of solution-formed hIAPP fibril models built from solid-state NMR data. Results from this study are in agreement with experimental observations regarding their respective relative aggregation propensities. We analyze in detail the specific structural characteristics and infer mechanisms that modulate the conformational stability of amylin fibrils. Results provide a platform for further studies and the design of new drugs that could interfere with amylin aggregation and its cytotoxicity. One particular mutation, N31K, has fibril-destabilizing properties, and could potentially improve the solubility of therapeutic amylin analogs.

Finding multiple reaction pathways via global optimization of action.

Global searching for reaction pathways is a long-standing challenge in computational chemistry and biology. Most existing approaches perform only local searches due to computational complexity. Here we present a computational approach, Action-CSA, to find multiple diverse reaction pathways connecting fixed initial and final states through global optimization of the Onsager-Machlup action using the conformational space annealing (CSA) method. Action-CSA successfully overcomes large energy barriers via crossovers and mutations of pathways and finds all possible pathways of small systems without initial guesses on pathways. The rank order and the transition time distribution of multiple pathways are in good agreement with those of long Langevin dynamics simulations. The lowest action folding pathway of FSD-1 is consistent with recent experiments. The results show that Action-CSA is an efficient and robust computational approach to study the multiple pathways of complex reactions and large-scale conformational changes.

Enhancing constant-pH simulation in explicit solvent with a two-dimensional replica exchange method.

We present a new method for enhanced sampling for constant-pH simulations in explicit water based on a two-dimensional (2D) replica exchange scheme. The new method is a significant extension of our previously developed constant-pH simulation method, which is based on enveloping distribution sampling (EDS) coupled with a one-dimensional (1D) Hamiltonian exchange method (HREM). EDS constructs a hybrid Hamiltonian from multiple discrete end state Hamiltonians that, in this case, represent different protonation states of the system. The ruggedness and heights of the hybrid Hamiltonian's energy barriers can be tuned by the smoothness parameter. Within the context of the 1D EDS-HREM method, exchanges are performed between replicas with different smoothness parameters, allowing frequent protonation-state transitions and sampling of conformations that are favored by the end-state Hamiltonians. In this work, the 1D method is extended to 2D with an additional dimension, external pH. Within the context of the 2D method (2D EDS-HREM), exchanges are performed on a lattice of Hamiltonians with different pH conditions and smoothness parameters. We demonstrate that both the 1D and 2D methods exactly reproduce the thermodynamic properties of the semigrand canonical (SGC) ensemble of a system at a given pH. We have tested our new 2D method on aspartic acid, glutamic acid, lysine, a four residue peptide (sequence KAAE), and snake cardiotoxin. In all cases, the 2D method converges faster and without loss of precision; the only limitation is a loss of flexibility in how CPU time is employed. The results for snake cardiotoxin demonstrate that the 2D method enhances protonation-state transitions, samples a wider conformational space with the same amount of computational resources, and converges significantly faster overall than the original 1D method.

A Virtual Mixture Approach to the Study of Multistate Equilibrium: Application to Constant pH Simulation in Explicit Water.

Chemical and thermodynamic equilibrium of multiple states is a fundamental phenomenon in biology systems and has been the focus of many experimental and computational studies. This work presents a simulation method to directly study the equilibrium of multiple states. This method constructs a virtual mixture of multiple states (VMMS) to sample the conformational space of all chemical states simultaneously. The VMMS system consists of multiple subsystems, one for each state. The subsystem contains a solute and a solvent environment. The solute molecules in all subsystems share the same conformation but have their own solvent environments. Transition between states is implicated by the change of their molar fractions. Simulation of a VMMS system allows efficient calculation of relative free energies of all states, which in turn determine their equilibrium molar fractions. For systems with a large number of state transition sites, an implicit site approximation is introduced to minimize the cost of simulation. A direct application of the VMMS method is for constant pH simulation to study protonation equilibrium. Applying the VMMS method to a heptapeptide of 3 ionizable residues, we calculated the pKas of those residues both with all explicit states and with implicit sites and obtained consistent results. For mouse epidermal growth factor of 9 ionizable groups, our VMMS simulations with implicit sites produced pKas of all 9 ionizable groups and the results agree qualitatively with NMR measurement. This example demonstrates the VMMS method can be applied to systems of a large number of ionizable groups and the computational cost scales linearly with the number of ionizable groups. For one of the most challenging systems in constant pH calculation, SNase Δ+PHS/V66K, our VMMS simulation shows that it is the state-dependent water penetration that causes the large deviation in lysine66's pKa.

Maintain rigid structures in Verlet based cartesian molecular dynamics simulations.

An algorithm is presented to maintain rigid structures in Verlet based cartesian molecular dynamics (MD) simulations. After each unconstrained MD step, the coordinates of selected particles are corrected to maintain rigid structures through an iterative procedure of rotation matrix computation. This algorithm, named as SHAPE and implemented in CHARMM program suite, avoids the calculations of Lagrange multipliers, so that the complexity of computation does not increase with the number of particles in a rigid structure. The implementation of this algorithm does not require significant modification of propagation integrator, and can be plugged into any cartesian based MD integration scheme. A unique feature of the SHAPE method is that it is interchangeable with SHAKE for any object that can be constrained as a rigid structure using multiple SHAKE constraints. Unlike SHAKE, the SHAPE method can be applied to large linear (with three or more centers) and planar (with four or more centers) rigid bodies. Numerical tests with four model systems including two proteins demonstrate that the accuracy and reliability of the SHAPE method are comparable to the SHAKE method, but with much more applicability and efficiency.

Replica exchanging self-guided Langevin dynamics for efficient and accurate conformational sampling.

This work presents a replica exchanging self-guided Langevin dynamics (RXSGLD) simulation method for efficient conformational searching and sampling. Unlike temperature-based replica exchanging simulations, which use high temperatures to accelerate conformational motion, this method uses self-guided Langevin dynamics (SGLD) to enhance conformational searching without the need to elevate temperatures. A RXSGLD simulation includes a series of SGLD simulations, with simulation conditions differing in the guiding effect and/or temperature. These simulation conditions are called stages and the base stage is one with no guiding effect. Replicas of a simulation system are simulated at the stages and are exchanged according to the replica exchanging probability derived from the SGLD partition function. Because SGLD causes less perturbation on conformational distribution than high temperatures, exchanges between SGLD stages have much higher probabilities than those between different temperatures. Therefore, RXSGLD simulations have higher conformational searching ability than temperature based replica exchange simulations. Through three example systems, we demonstrate that RXSGLD can generate target canonical ensemble distribution at the base stage and achieve accelerated conformational searching. Especially for large systems, RXSGLD has remarkable advantages in terms of replica exchange efficiency, conformational searching ability, and system size extensiveness.

Simulation of multiphase systems utilizing independent force fields to control intraphase and interphase behavior.

Fixed-charge empirical force fields have been developed and widely used over the past three decades for all-atom molecular simulations. Most simulation programs providing these methods enable only one set of force field parameters to be used for the entire system. Whereas this is generally suitable for single-phase systems, the molecular environment at the interface between two phases may be sufficiently different from the individual phases to require a different set of parameters to be used to accurately represent the system. Recently published simulations of peptide adsorption to material surfaces using the CHARMM force field have clearly demonstrated this issue by revealing that calculated values of adsorption free energy substantially differ from experimental results. Whereas nonbonded parameters could be adjusted to correct this problem, this cannot be done without also altering the conformational behavior of the peptide in solution, for which CHARMM has been carefully tuned. We have developed a dual-force-field approach (Dual-FF) to address this problem and implemented it in the CHARMM simulation package. This Dual-FF method provides the capability to use two separate sets of nonbonded force field parameters within the same simulation: one set to represent intraphase interactions and a separate set to represent interphase interactions. Using this approach, we show that interfacial parameters can be adjusted to correct errors in peptide adsorption free energy without altering peptide conformational behavior in solution. This program thus provides the capability to enable both intraphase and interphase molecular behavior to be accurately and efficiently modeled in the same simulation.

Effects of pH on proteins: predictions for ensemble and single-molecule pulling experiments.

Protein conformations change among distinct thermodynamic states as solution conditions (temperature, denaturants, pH) are altered or when they are subjected to mechanical forces. A quantitative description of the changes in the relative stabilities of the various thermodynamic states is needed to interpret and predict experimental outcomes. We provide a framework based on the Molecular Transfer Model (MTM) to account for pH effects on the properties of globular proteins. The MTM utilizes the partition function of a protein calculated from molecular simulations at one set of solution conditions to predict protein properties at another set of solution conditions. To take pH effects into account, we utilized experimentally measured pK(a) values in the native and unfolded states to calculate the free energy of transferring a protein from a reference pH to the pH of interest. We validate our approach by demonstrating that the native-state stability as a function of pH is accurately predicted for chymotrypsin inhibitor 2 (CI2) and protein G. We use the MTM to predict the response of CI2 and protein G subjected to a constant force (f) and varying pH. The phase diagrams of CI2 and protein G as a function of f and pH are dramatically different and reflect the underlying pH-dependent stability changes in the absence of force. The calculated equilibrium free energy profiles as functions of the end-to-end distance of the two proteins show that, at various pH values, CI2 unfolds via an intermediate when subjected to f. The locations of the two transition states move toward the more unstable state as f is changed, which is in accord with the Hammond-Leffler postulate. In sharp contrast, force-induced unfolding of protein G occurs in a single step. Remarkably, the location of the transition state with respect to the folded state is independent of f, which suggests that protein G is mechanically brittle. The MTM provides a natural framework for predicting the outcomes of ensemble and single-molecule experiments for a wide range of solution conditions.

Extracellular complexes of the hematopoietic human and mouse CSF-1 receptor are driven by common assembly principles.

The hematopoietic colony stimulating factor-1 receptor (CSF-1R or FMS) is essential for the cellular repertoire of the mammalian immune system. Here, we report a structural and mechanistic consensus for the assembly of human and mouse CSF-1:CSF-1R complexes. The EM structure of the complete extracellular assembly of the human CSF-1:CSF-1R complex reveals how receptor dimerization by CSF-1 invokes a ternary complex featuring extensive homotypic receptor contacts and striking structural plasticity at the extremities of the complex. Studies by small-angle X-ray scattering of unliganded hCSF-1R point to large domain rearrangements upon CSF-1 binding, and provide structural evidence for the relevance of receptor predimerization at the cell surface. Comparative structural and binding studies aiming to dissect the assembly principles of human and mouse CSF-1R complexes, including a quantification of the CSF-1/CSF-1R species cross-reactivity, show that bivalent cytokine binding to receptor coupled to ensuing receptor-receptor interactions are common denominators in extracellular complex formation.

pH replica-exchange method based on discrete protonation states.

We propose a new algorithm for obtaining proton titration curves of ionizable residues. The algorithm is a pH replica-exchange method (PHREM), which is based on the constant pH algorithm of Mongan et al. (J Comput Chem 2004;25:2038-2048). In the original replica-exchange method, simulations of different replicas are performed at different temperatures, and the temperatures are exchanged between the replicas. In our PHREM, simulations of different replicas are performed at different pH values, and the pHs are exchanged between the replicas. The PHREM was applied to a blocked amino acid and to two protein systems (snake cardiotoxin and turkey ovomucoid third domain), in conjunction with a generalized Born implicit solvent. The performance and accuracy of this algorithm and the original constant pH method (PHMD) were compared. For a single set of simulations at different pHs, the use of PHREM yields more accurate Hill coefficients of titratable residues. By performing multiple sets of constant pH simulations started with different initial states, the accuracy of predicted pK(a) values and Hill coefficients obtained with PHREM and PHMD methods becomes comparable. However, the PHREM algorithm exhibits better samplings of the protonation states of titratable residues and less scatter of the titration points and thus better precision of measured pK(a) values and Hill coefficients. In addition, PHREM exhibits faster convergence of individual simulations than the original constant pH algorithm.

Efficient Calculation of QM/MM Frequencies with the Mobile Block Hessian.

The calculation of the analytical second derivative matrix (Hessian) is the bottleneck for vibrational analysis in QM/MM systems when an electrostatic embedding scheme is employed. Even with a small number of QM atoms in the system, the presence of MM atoms increases the computational cost dramatically: the long-range Coulomb interactions require that additional coupled perturbed self-consistent field (CPSCF) equations need to be solved for each MM atom displacement. This paper presents an extension to the Mobile Block Hessian (MBH) formalism for QM/MM calculations with blocks in the MM region and its implementation in a parallel version of the Q-Chem/CHARMM interface. MBH reduces both the CPU time and the memory requirements compared to the standard full Hessian QM/MM analysis, without the need to use a cutoff distance for the electrostatic interactions. Special attention is given to the treatment of link atoms which are usually present when the QM/MM border cuts through a covalent bond. Computational efficiency improvements are highlighted using a reduced chorismate mutase enzyme system, consisting of 24 QM atoms and 306 MM atoms, as a test example. In addition, the drug bortezomib, used for cancer treatment of myeloma, has been studied as a test case with multiple MBH block choices and both a QM and QM/MM description. The accuracy of the calculated Hessians is quantified by imposing Eckart constraints, which allows for the assessment of numerical errors in second derivative procedures. The results show that MBH within the QM/MM description not only is a computationally attractive method but also produces accurate results.

Computational investigation of the oxidative deboronation of boroglycine, H2N-CH2-B(OH)2, Using H2O and H2O2.

We report results from a computational investigation of the oxidative deboronation of boroglycine, H2N-CH2-B(OH)2, using H2O and H2O2 as the reactive oxygen species (ROS) to yield aminomethanol, H2N-CH2-OH; these results complement our study on the protodeboronation of boroglycine to produce methylamine, H2N-CH3 (Larkin et al. J. Phys. Chem. A 2007, 111, 6489-6500). Second-order Møller-Plesset (MP2) perturbation theory with Dunning-Woon correlation-consistent (cc) basis sets were used for the calculations with comparisons made to results from density functional theory (DFT) at the PBE1PBE/6-311++G(d,p)(cc-pVDZ) levels. The effects of a bulk aqueous environment were also incorporated into the calculations employing PCM and CPCM methodology. Using H2O as the ROS, the reaction H2O + H2N-CH2-B(OH)2 --> H2N-CH2-OH + H-B(OH)2 was calculated to be endothermic; the value of DeltaH(298)(0) was +12.0 kcal/mol at the MP2(FC)/cc-pVTZ computational level in vacuo and +13.7 kcal/mol in PCM aqueous media; the corresponding value for the activation barrier, DeltaH(double dagger), was +94.3 kcal/mol relative to the separated reactants in vacuo and +89.9 kcal/mol in PCM aqueous media. In contrast, the reaction H2O2 + H2N-CH2-B(OH)2 --> H2N-CH2-OH + B(OH)3 was calculated to be highly exothermic with an DeltaH(298)(0) value of -100.9 kcal/mol at the MP2(FC)/cc-pVTZ computational level in vacuo and -99.6 kcal/mol in CPCM aqueous media; the highest-energy transition state for the multistep process associated with this reaction involved the rearrangement of H2N-CH2-B(OH)(OOH) to H2N-CH2-O-B(OH)2 with a DeltaH(double dagger) value of +23.2 kcal/mol in vacuo relative to the separated reactants. These computational results for boroglycine are in accord with the experimental observations for the deboronation of the FDA approved anticancer drug bortezomib (Velcade, PS-341), where it was found to be the principle deactivation pathway (Labutti et al. Chem. Res. Toxicol. 2006, 19, 539-546).

Thermodynamic perspective on the dock-lock growth mechanism of amyloid fibrils.

The mechanism of addition of a soluble unstructured monomer to a preformed ordered amyloid fibril is a complex process. On the basis of the kinetics of monomer disassociation of Abeta(1-40) from the amyloid fibril, it has been suggested that deposition is a multistep process involving a rapid reversible association of the unstructured monomer to the fibril surface (docking) followed by a slower conformational rearrangement leading to the incorporation onto the underlying fibril lattice (locking). By exploiting the vast time scale separation between the dock and lock processes and using molecular dynamics simulation of deposition of the disordered peptide fragment (35)MVGGVV(40) from the Abeta peptide onto the fibril with known crystal structure, we provide a thermodynamic basis for the dock-lock mechanism of fibril growth. Free energy profiles, computed using implicit solvent model and enhanced sampling methods with the distance (delta(C)) between the center of mass of the peptide and the fibril surface as the order parameter, show three distinct basins of attraction. When delta(C) is large, the monomer is compact and unstructured and the favorable interactions with the fibril results in stretching of the peptide at delta(C) approximately 13 A. As delta(C) is further decreased, the peptide docks onto the fibril surface with a structure that is determined by a balance between intrapeptide and peptide fibril interactions. At delta(C) approximately 4 A, a value that is commensurate with the spacing between beta-strands in the fibril, the monomer expands and locks onto the fibril. Using simulations with implicit solvent model and all atom molecular dynamics in explicit water, we show that the locked monomer, which interacts with the underlying fibril, undergoes substantial conformational fluctuations and is not stable. The cosolutes urea and TMAO destabilize the unbound phase and stabilize the docked phase. Interestingly, small crowding particles enhance the stability of the fibril-bound monomer only marginally. We predict that the experimentally measurable critical monomer concentration, C(R), at which the soluble unbound monomer is in equilibrium with the ordered fibril, increases sharply as temperature is increased under all solution conditions.

Molecular origin of constant m-values, denatured state collapse, and residue-dependent transition midpoints in globular proteins.

Experiments show that for many two-state folders the free energy of the native state, DeltaG(ND)([C]), changes linearly as the denaturant concentration, [C], is varied. The slope {m = [dDeltaG(ND)([C])]/(d[C])}, is nearly constant. According to the transfer model, the m-value is associated with the difference in the surface area between the native (N) and denatured (D) state, which should be a function of DeltaR(g)(2), the difference in the square of the radius of gyration between the D and N states. Single-molecule experiments show that the R(g) of the structurally heterogeneous denatured state undergoes an equilibrium collapse transition as [C] decreases, which implies m also should be [C]-dependent. We resolve the conundrum between constant m-values and [C]-dependent changes in R(g) using molecular simulations of a coarse-grained representation of protein L, and the molecular transfer model, for which the equilibrium folding can be accurately calculated as a function of denaturant (urea) concentration. In agreement with experiment, we find that over a large range of denaturant concentration (>3 M) the m-value is a constant, whereas under strongly renaturing conditions (<3 M), it depends on [C]. The m-value is a constant above [C] > 3 M because the [C]-dependent changes in the surface area of the backbone groups, which make the largest contribution to m, are relatively narrow in the denatured state. The burial of the backbone and hydrophobic side chains gives rise to substantial surface area changes below [C] < 3 M, leading to collapse in the denatured state of protein L. Dissection of the contribution of various amino acids to the total surface area change with [C] shows that both the sequence context and residual structure are important. There are [C]-dependent variations in the surface area for chemically identical groups such as the backbone or Ala. Consequently, the midpoints of transition of individual residues vary significantly (which we call the Holtzer effect) even though global folding can be described as an all-or-none transition. The collapse is specific in nature, resulting in the formation of compact structures with appreciable populations of nativelike secondary structural elements. The collapse transition is driven by the loss of favorable residue-solvent interactions and a concomitant increase in the strength of intrapeptide interactions with a decreasing [C]. The strength of these interactions is nonuniformly distributed throughout the structure of protein L. Certain secondary structure elements have stronger [C]-dependent interactions than others in the denatured state.

Computational validation of protein nanotubes.

We present a novel generic computational method to assess protein nanotubes with variable diameter sizes at the atomic level given their low resolution protomeric structures. The method is based on the symmetrical assembly of a repeating protein subunit into a nanotube. Given the protein unit-cell, and the tube diameter and helicity, we carry out all-atom molecular dynamics simulations, combined with a unique mathematical transformation. This allows us to mimic nanotubes of even huge sizes without end or edge effects. All our simulation setups attempt to explicitly adhere to the conditions under which the experiments were conducted. Thus, we are able to obtain high resolution atomic-scale structures at reasonable computational costs. We expect that our approach would prove useful in assessing protein nanotubes, as well as in silico constructions of novel nanobiomaterials.

Vibrational subsystem analysis: A method for probing free energies and correlations in the harmonic limit.

A new vibrational subsystem analysis (VSA) method is presented for coupling global motion to a local subsystem while including the inertial effects of the environment. The premise of the VSA method is a partitioning of a system into a smaller region of interest and a usually larger part referred to as environment. This method allows the investigation of local-global coupling, a more accurate estimation of vibrational free energy contribution for parts of a large system, and the elimination of the "tip effect" in elastic network model calculations. Additionally, the VSA method can be used as a probe of specific degrees of freedom that may contribute to free energy differences. The VSA approach can be employed in many ways, but it will likely be most useful for estimating activation free energies in QM/MM reaction path calculations. Four examples are presented to demonstrate the utility of this method.