Simulations of Protein Aggregation: Insights from Atomistic and Coarse-Grained Models

Amyloid growth and membrane damage: Current themes and emerging perspectives from theory and experiments on Aβ and hIAPP

Alzheimer's Disease (AD) and Type 2 diabetes mellitus (T2DM) are two incurable diseases both hallmarked by an abnormal deposition of the amyloidogenic peptides Aβ and Islet Amyloid Polypeptide (IAPP) in affected tissues. Epidemiological data demonstrate that patients suffering from diabetes are at high risk of developing AD, thus making the search for factors common to the two pathologies of special interest for the design of new therapies. Accumulating evidence suggests that the toxic properties of both Aβ or IAPP are ascribable to their ability to damage the cell membrane. However, the molecular details describing Aβ or IAPP interaction with membranes are poorly understood. This review focuses on biophysical and in silico studies addressing these topics. Effects of calcium, cholesterol and membrane lipid composition in driving aberrant Aβ or IAPP interaction with the membrane will be specifically considered. The cross correlation of all these factors appears to be a key issue not only to shed light in the countless and often controversial reports relative to this area but also to gain valuable insights into the central events leading to membrane damage caused by amyloidogenic peptides. This article is part of a Special Issue entitled: Protein Aggregation and Misfolding at the Cell Membrane Interface edited by Ayyalusamy Ramamoorthy.

Molecular simulation aspects of amyloid peptides at membrane interface

The interactions of amyloid peptides with cell membranes play an important role in maintaining the integrity and functionality of cell membrane. A thorough molecular-level understanding of the structure, dynamics, and interactions between amyloid peptides and cell membranes is critical to amyloid aggregation and toxicity mechanisms for the bench-to-bedside applications. Here we review the most recent computational studies of amyloid peptides at model cell membranes. Different mechanisms of action of amyloid peptides on/in cell membranes, targeted by different computational techniques at different lengthscales and timescales, are rationally discussed. Finally, we have proposed some new insights into the remaining challenges and perspectives for future studies to improve our understanding of the activity of amyloid peptides associated with protein-misfolding diseases. This article is part of a Special Issue entitled: Protein Aggregation and Misfolding at the Cell Membrane Interface edited by Ayyalusamy Ramamoorthy.

Effects of forcefield and sampling method in all-atom simulations of inherently disordered proteins: Application to conformational preferences of human amylin

Although several computational modelling studies have investigated the conformational behaviour of inherently disordered protein (IDP) amylin, discrepancies in identifying its preferred solution conformations still exist between various forcefields and sampling methods used. Human islet amyloid polypeptide has long been a subject of research, both experimentally and theoretically, as the aggregation of this protein is believed to be the lead cause of type-II diabetes. In this work, we present a systematic forcefield assessment using one of the most advanced non-biased sampling techniques, Replica Exchange with Solute Tempering (REST2), by comparing the secondary structure preferences of monomeric amylin in solution. This study also aims to determine the ability of common forcefields to sample a transition of the protein from a helical membrane bound conformation into the disordered solution state of amylin. Our results demonstrated that the CHARMM22* forcefield showed the best ability to sample multiple conformational states inherent for amylin. It is revealed that REST2 yielded results qualitatively consistent with experiments and in quantitative agreement with other sampling methods, however far more computationally efficiently and without any bias. Therefore, combining an unbiased sampling technique such as REST2 with a vigorous forcefield testing could be suggested as an important step in developing an efficient and robust strategy for simulating IDPs.

Molecular simulations of peptide amphiphiles

This review describes recent progress in the area of molecular simulations of peptide assemblies, including peptide-amphiphiles and drug-amphiphiles. The ability to predict the structure and stability of peptide self-assemblies from the molecular level up is vital to the field of nanobiotechnology. Computational methods such as molecular dynamics offer the opportunity to characterize intermolecular forces between peptide-amphiphiles that are critical to the self-assembly process. Furthermore, these computational methods provide the ability to computationally probe the structure of these supramolecular assemblies at the molecular level, which is a challenge experimentally. Herein, we briefly highlight progress in the areas of all-atomistic and coarse-grained simulation studies investigating the self-assembly process of short peptides and peptide amphiphiles. We also discuss recent all-atomistic and coarse-grained simulations of the self-assembly of a drug-amphiphile into elongated filaments. Next, we discuss how these computational methods can provide further insight into the pathway of cylindrical nanofiber formation and predict their biocompatibility by studying the interaction of these peptide-amphiphile nanostructures with model cell membranes.

Conformational Ensembles of the Wild-Type and S8C Aβ1-42 Dimers

We characterized the dimer of the amyloid-β wild-type (WT) peptide, Aβ, of 42 residues and its disulfide-bond-locked double mutant (S8C) by replica exchange molecular dynamics simulations. Aβ dimers are known to be the smallest toxic species in Alzheimer's disease, and the S8C mutant has been shown experimentally to form an exclusive homogeneous and neurotoxic dimer. Our 50 μs all-atom simulations reveal similar secondary structures and collision cross-sections but very different intramolecular and intermolecular conformations upon double S8C mutation. Both dimers are very dynamic with hundreds of free-energy minima that differ from the U-shape and S-shape conformations of the peptides in the fibrils. The only common structural feature, shared by both species with a probability of 4% in WT and 12% in S8C-S8C, is a three-stranded β-sheet spanning the 17-23, 29-36, and 39-41 residues, which does not exist in the Aβ40 WT dimers.

Performance Comparison of Systematic Methods for Rigorous Definition of Coarse-Grained Sites of Large Biomolecules

Construction of coarse-grained (CG) models for large biomolecules used for multiscale simulations demands a rigorous definition of CG sites for them. Several coarse-graining methods such as the simulated annealing and steepest descent (SASD) based on the essential dynamics coarse-graining (ED-CG) or the stepwise local iterative optimization (SLIO) based on the fluctuation maximization coarse-graining (FM-CG), were developed to do it. However, the practical applications of these methods such as SASD based on ED-CG are subject to limitations because they are too expensive. In this work, we extend the applicability of ED-CG by combining it with the SLIO algorithm. A comprehensive comparison of optimized results and accuracy of various algorithms based on ED-CG show that SLIO is the fastest as well as the most accurate algorithm among them. ED-CG combined with SLIO could give converged results as the number of CG sites increases, which demonstrates that it is another efficient method for coarse-graining large biomolecules. The construction of CG sites for Ras protein by using MD fluctuations demonstrates that the CG sites derived from FM-CG can reflect the fluctuation properties of secondary structures in Ras accurately.

Computer Simulations of Intrinsically Disordered Proteins

The investigation of intrinsically disordered proteins (IDPs) is a new frontier in structural and molecular biology that requires a new paradigm to connect structural disorder to function. Molecular dynamics simulations and statistical thermodynamics potentially offer ideal tools for atomic-level characterizations and thermodynamic descriptions of this fascinating class of proteins that will complement experimental studies. However, IDPs display sensitivity to inaccuracies in the underlying molecular mechanics force fields. Thus, achieving an accurate structural characterization of IDPs via simulations is a challenge. It is also daunting to perform a configuration-space integration over heterogeneous structural ensembles sampled by IDPs to extract, in particular, protein configurational entropy. In this review, we summarize recent efforts devoted to the development of force fields and the critical evaluations of their performance when applied to IDPs. We also survey recent advances in computational methods for protein configurational entropy that aim to provide a thermodynamic link between structural disorder and protein activity.

Hydrodynamic effects on β-amyloid (16-22) peptide aggregation

Computer simulations based on simplified representations are routinely used to explore the early steps of amyloid aggregation. However, when protein models with implicit solvent are employed, these simulations miss the effect of solvent induced correlations on the aggregation kinetics and lifetimes of metastable states. In this work, we apply the multi-scale Lattice Boltzmann Molecular Dynamics technique (LBMD) to investigate the initial aggregation phases of the amyloid Aβ16-22 peptide. LBMD includes naturally hydrodynamic interactions (HIs) via a kinetic on-lattice representation of the fluid kinetics. The peptides are represented by the flexible OPEP coarse-grained force field. First, we have tuned the essential parameters that control the coupling between the molecular and fluid evolutions in order to reproduce the experimental diffusivity of elementary species. The method is then deployed to investigate the effect of HIs on the aggregation of 100 and 1000 Aβ16-22 peptides. We show that HIs clearly impact the aggregation process and the fluctuations of the oligomer sizes by favouring the fusion and exchange dynamics of oligomers between aggregates. HIs also guide the growth of the leading largest cluster. For the 100 Aβ16-22 peptide system, the simulation of ∼300 ns allowed us to observe the transition from ellipsoidal assemblies to an elongated and slightly twisted aggregate involving almost the totality of the peptides. For the 1000 Aβ16-22 peptides, a system of unprecedented size at quasi-atomistic resolution, we were able to explore a branched disordered fibril-like structure that has never been described by other computer simulations, but has been observed experimentally.

A Protocol for the Design of Protein and Peptide Nanostructure Self-Assemblies Exploiting Synthetic Amino Acids

In recent years there has been increasing interest in nanostructure design based on the self-assembly properties of proteins and polymers. Nanodesign requires the ability to predictably manipulate the properties of the self-assembly of autonomous building blocks, which can fold or aggregate into preferred conformational states. The design includes functional synthetic materials and biological macromolecules. Autonomous biological building blocks with available 3D structures provide an extremely rich and useful resource. Structural databases contain large libraries of protein molecules and their building blocks with a range of sizes, shapes, surfaces, and chemical properties. The introduction of engineered synthetic residues or short peptides into these building blocks can greatly expand the available chemical space and enhance the desired properties. Herein, we summarize a protocol for designing nanostructures consisting of self-assembling building blocks, based on our recent works. We focus on the principles of nanostructure design with naturally occurring proteins and synthetic amino acids, as well as hybrid materials made of amyloids and synthetic polymers.

Simulations of disordered proteins and systems with conformational heterogeneity

Intrinsically disordered proteins (IDPs) and protein regions can facilitate a wide variety of complex physiological processes such as binding, signaling, and formation of membraneless organelles. They can however also play pathological roles by aggregating into cytotoxic oligomers and fibrils. Characterizing the structure and function of disordered proteins is an onerous task, primarily because these proteins adopt transient structures, which are difficult to capture in experiments. Simulations have emerged as a powerful tool for interpreting and augmenting experimental measurements of IDPs. In this review we focus on computer simulations of disordered protein structures, functions, assemblies, and emerging questions that, taken together, give an overview of the field as it exists today.

Multiscale simulation of molecular processes in cellular environments

We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.

Protein Aggregation and Molecular Crowding: Perspectives From Multiscale Simulations

Cells are extremely crowded environments, thus the use of diluted salted aqueous solutions containing a single protein is too simplistic to mimic the real situation. Macromolecular crowding might affect protein structure, folding, shape, conformational stability, binding of small molecules, enzymatic activity, interactions with cognate biomolecules, and pathological aggregation. The latter phenomenon typically leads to the formation of amyloid fibrils that are linked to several lethal neurodegenerative diseases, but that can also play a functional role in certain organisms. The majority of molecular simulations performed before the last few years were conducted in diluted solutions and were restricted both in the timescales and in the system dimensions by the available computational resources. In recent years, several computational solutions were developed to get close to physiological conditions. In this review we summarize the main computational techniques used to tackle the issue of protein aggregation both in a diluted and in a crowded environment.

Protein Polymerization into Fibrils from the Viewpoint of Nucleation Theory

The assembly of various proteins into fibrillar aggregates is an important phenomenon with wide implications ranging from human disease to nanoscience. Using general kinetic results of nucleation theory, we analyze the polymerization of protein into linear or helical fibrils in the framework of the Oosawa-Kasai (OK) model. We show that while within the original OK model of linear polymerization the process does not involve nucleation, within a modified OK model it is nucleation-mediated. Expressions are derived for the size of the fibril nucleus, the work for fibril formation, the nucleation barrier, the equilibrium and stationary fibril size distributions, and the stationary fibril nucleation rate. Under otherwise equal conditions, this rate decreases considerably when the short (subnucleus) fibrils lose monomers much more frequently than the long (supernucleus) fibrils, a feature that should be born in mind when designing a strategy for stymying or stimulating fibril nucleation. The obtained dependence of the nucleation rate on the concentration of monomeric protein is convenient for experimental verification and for use in rate equations accounting for nucleation-mediated fibril formation. The analysis and the results obtained for linear fibrils are fully applicable to helical fibrils whose formation is describable by a simplified OK model.

Coarse Master Equations for Binding Kinetics of Amyloid Peptide Dimers

We characterize the kinetics of dimer formation of the short amyloid microcrystal-forming tetrapeptides NNQQ by constructing coarse master equations for the conformational dynamics of the system, using temperature replica-exchange molecular dynamics (REMD) simulations. We minimize the effects of Kramers-type recrossings by assigning conformational states based on their sequential time evolution. Transition rates are further estimated from short-time state propagators by maximizing the likelihood that the extracted rates agree with the observed atomistic trajectories without any a priori assumptions about their temperature dependence. Here, we evaluate the rates for both continuous replica trajectories that visit different temperatures and for discontinuous data corresponding to each REMD temperature. While the binding-unbinding kinetic process is clearly Markovian, the conformational dynamics of the bound NNQQ dimer has a complex character. Our kinetic analysis allows us to discriminate between short-lived encounter pairs and strongly bound conformational states. The conformational dynamics of NNQQ dimers supports a kinetically driven aggregation mechanism, in agreement with the polymorphic character reported for amyloid aggregates such as microcrystals and fibrils.

Protein Domain-Swapping Can Be a Consequence of Functional Residues

Monomer topology has been implicated in domain-swapping, a potential first step on the route to disease-causing protein aggregation. Despite having the same topology (β1-α1-β2-β3-β4-β5), the cysteine protease inhibitor stefin-B domain swaps more readily than a single-chain variant of the heterodimeric sweet protein monellin (scMn). Here, we computationally study the folding of stefin-B and scMn in order to understand the molecular basis for the difference in their domain-swapping propensities. In agreement with experiments, our structure-based simulations show that scMn folds cooperatively without the population of an intermediate while stefin-B populates an equilibrium intermediate state. Since the simulation intermediate has only one domain structured (β3-β4-β5), it can directly lead to domain-swapping. Using computational variants of stefin-B, we show that the population of this intermediate is caused by regions of stefin-B that have been implicated in protease inhibition. We also find that the protease-binding regions are located on two structural elements and localized in space. In contrast, the residues that contribute to the sweetness of monellin are not localized to a few structural elements but are distributed over the protein fold. We conclude that the distributed functional residues of monellin do not induce large local perturbations in the protein structure, eliminating the formation of folding intermediates and in turn domain-swapping. On the other hand, the localized protease-binding regions of stefin-B promote the formation of a folding intermediate which can lead to domain-swapping. Thus, domain-swapping can be a direct consequence of the constraints that function imposes on the protein structure.

Thermodynamics of amyloid formation and the role of intersheet interactions

The self-assembly of proteins into β-sheet-rich amyloid fibrils has been observed to occur with sigmoidal kinetics, indicating that the system initially is trapped in a metastable state. Here, we use a minimal lattice-based model to explore the thermodynamic forces driving amyloid formation in a finite canonical (NVT) system. By means of generalized-ensemble Monte Carlo techniques and a semi-analytical method, the thermodynamic properties of this model are investigated for different sets of intersheet interaction parameters. When the interactions support lateral growth into multi-layered fibrillar structures, an evaporation/condensation transition is observed, between a supersaturated solution state and a thermodynamically distinct state where small and large fibril-like species exist in equilibrium. Intermediate-size aggregates are statistically suppressed. These properties do not hold if aggregate growth is one-dimensional.

Fe(2+) binding on amyloid β-peptide promotes aggregation

The metal ions Zn(2+) , Cu(2+) , and Fe(2+) play a significant role in the aggregation mechanism of Aβ peptides. However, the nature of binding between metal and peptide has remained elusive; the detailed information on this from the experimental study is very difficult. Density functional theory (dft) (M06-2X/6-311++G (2df,2pd) +LANL2DZ) has employed to determine the force field resulting due to metal and histidine interaction. We performed 200 ns molecular dynamics (MD) simulation on Aβ1-42 -Zn(2+) , Aβ1-42 -Cu(2+) , and Aβ1-42 -Fe(2+) systems in explicit water with different combination of coordinating residues including the three Histidine residues in the N-terminal. The present investigation, the Aβ1-42 -Zn(2+) system possess three turn conformations separated by coil structure. Zn(2+) binding caused the loss of the helical structure of N-terminal residues which transformed into the S-shaped conformation. Zn(2+) has reduced the coil and increases the turn content of the peptide compared with experimental study. On the other hand, the Cu(2+) binds with peptide, β sheet formation is observed at the N-terminal residues of the peptide. Fe(2+) binding is to promote the formation of Glu22-Lys28 salt-bridge which stabilized the turn conformation in the Phe19-Gly25 residues, subsequently β sheets were observed at His13-Lys18 and Gly29-Gly37 residues. The turn conformation facilitates the β sheets are arranged in parallel by enhancing the hydrophobic contact between Gly25 and Met35, Lys16 and Met35, Leu17 and Leu34, Val18 and Leu34 residues. The Fe(2+) binding reduced the helix structure and increases the β sheet content in the peptide, which suggested, Fe(2+) promotes the oligomerization by enhancing the peptide-peptide interaction. Proteins 2016; 84:1257-1274. © 2016 Wiley Periodicals, Inc.

An Account of Amyloid Oligomers: Facts and Figures Obtained from Experiments and Simulations

The deposition of amyloid in brain tissue in the context of neurodegenerative diseases involves the formation of intermediate species-termed oligomers-of lower molecular mass and with structures that deviate from those of mature amyloid fibrils. Because these oligomers are thought to be primarily responsible for the subsequent disease pathogenesis, the elucidation of their structure is of enormous interest. Nevertheless, because of the high aggregation propensity and the polydispersity of oligomeric species formed by the proteins or peptides in question, the preparation of appropriate samples for high-resolution structural methods has proven to be rather difficult. This is why theoretical approaches have been of particular importance in gaining insights into possible oligomeric structures for some time. Only recently has it been possible to achieve some progress with regard to the experimentally based structural characterization of defined oligomeric species. Here we discuss how theory and experiment are used to determine oligomer structures and what can be done to improve the integration of the two disciplines.

Advances in the Simulation of Protein Aggregation at the Atomistic Scale

Protein aggregation into highly structured amyloid fibrils is associated with various diseases including Alzheimer's disease, Parkinson's disease, and type II diabetes. Amyloids can also have normal biological functions and, in the future, could be used as the basis for novel nanoscale materials. However, a full understanding of the physicochemical forces that drive protein aggregation is still lacking. Such understanding is crucial for the development of drugs that can effectively inhibit aberrant amyloid aggregation and for the directed design of functional amyloids. Atomistic simulations can help understand protein aggregation. In particular, atomistic simulations can be used to study the initial formation of toxic oligomers which are hard to characterize experimentally and to understand the difference in aggregation behavior between different amyloidogenic peptides. Here, we review the latest atomistic simulations of protein aggregation, concentrating on amyloidogenic protein fragments, and provide an outlook for the future in this field.

A Monte Carlo Study of the Early Steps of Functional Amyloid Formation

In addition to their well-known roles in neurodegenerative diseases and amyloidoses, amyloid structures also assume important functional roles in the cell. Although functional amyloid shares many physiochemical properties with its pathogenic counterpart, it is evolutionarily optimized to avoid cytotoxicity. This makes it an interesting study case for aggregation phenomenon in general. One of the most well-known examples of a functional amyloid, E. coli curli, is an essential component in the formation of bacterial biofilm, and is primarily formed by aggregates of the protein CsgA. Previous studies have shown that the minor sequence variations observed in the five different subrepeats (R1-R5), which comprise the CsgA primary sequence, have a substantial influence on their individual aggregation propensities. Using a recently described diffusion-optimized enhanced sampling approach for Monte Carlo simulations, we here investigate the equilibrium properties of the monomeric and dimeric states of these subrepeats, to probe whether structural properties observed in these early stage oligomers are decisive for the characteristics of the resulting aggregate. We show that the dimerization propensities of these peptides have strong correlations with their propensity for amyloid formation, and provide structural insights into the inter- and intramolecular contacts that appear to be essential in this process.

Amyloid Fibril Solubility

It is well established that amyloid fibril solubility is protein specific, but how solubility depends on the interactions between the fibril building blocks is not clear. Here we use a simple protein model and perform Monte Carlo simulations to directly measure the solubility of amyloid fibrils as a function of the interaction between the fibril building blocks. Our simulations confirms that the fibril solubility depends on the fibril thickness and that the relationship between the interactions and the solubility can be described by a simple analytical formula. The results presented in this study reveal general rules how side-chain-side-chain interactions, backbone hydrogen bonding, and temperature affect amyloid fibril solubility, which might prove to be a powerful tool to design protein fibrils with desired solubility and aggregation properties in general.

Exploring the role of hydration and confinement in the aggregation of amyloidogenic peptides Aβ(16-22) and Sup35(7-13) in AOT reverse micelles

Knowledge of how intermolecular interactions of amyloid-forming proteins cause protein aggregation and how those interactions are affected by sequence and solution conditions is essential to our understanding of the onset of many degenerative diseases. Of particular interest is the aggregation of the amyloid-β (Aβ) peptide, linked to Alzheimer's disease, and the aggregation of the Sup35 yeast prion peptide, which resembles the mammalian prion protein linked to spongiform encephalopathies. To facilitate the study of these important peptides, experimentalists have identified small peptide congeners of the full-length proteins that exhibit amyloidogenic behavior, including the KLVFFAE sub-sequence, Aβ16-22, and the GNNQQNY subsequence, Sup357-13. In this study, molecular dynamics simulations were used to examine these peptide fragments encapsulated in reverse micelles (RMs) in order to identify the fundamental principles that govern how sequence and solution environment influence peptide aggregation. Aβ16-22 and Sup357-13 are observed to organize into anti-parallel and parallel β-sheet arrangements. Confinement in the sodium bis(2-ethylhexyl) sulfosuccinate (AOT) reverse micelles is shown to stabilize extended peptide conformations and enhance peptide aggregation. Substantial fluctuations in the reverse micelle shape are observed, in agreement with earlier studies. Shape fluctuations are found to facilitate peptide solvation through interactions between the peptide and AOT surfactant, including direct interaction between non-polar peptide residues and the aliphatic surfactant tails. Computed amide I IR spectra are compared with experimental spectra and found to reflect changes in the peptide structures induced by confinement in the RM environment. Furthermore, examination of the rotational anisotropy decay of water in the RM demonstrates that the water dynamics are sensitive to the presence of peptide as well as the peptide sequence. Overall, our results demonstrate that the RM is a complex confining environment where substantial direct interaction between the surfactant and peptides plays an important role in determining the resulting ensemble of peptide conformations. By extension the results suggest that similarly complex sequence-dependent interactions may determine conformational ensembles of amyloid-forming peptides in a cellular environment.

On the lack of polymorphism in Aβ-peptide aggregates derived from patient brains

The amyloid beta (Aβ) oligomers and fibrils that are found in neural tissues of patients suffering from Alzheimer's disease may either cause or contribute to the pathology of the disease. In vitro, these Aβ-aggregates are characterized by structural polymorphism. However, recent solid state NMR data of fibrils acquired post mortem from the brains of two Alzheimer's patients indicate presence of only a single, patient-specific structure. Using enhanced molecular dynamic simulations we investigate the factors that modulate the stability of Aβ-fibrils. We find characteristic differences in molecular flexibility, dynamics of interactions, and structural behavior between the brain-derived Aβ-fibril structure and in vitro models. These differences may help to explain the lack of polymorphism in fibrils collected from patient brains, and have to be taken into account when designing aggregation inhibitors and imaging agents for Alzheimer's disease.

Interfacial interaction and lateral association of cross-seeding assemblies between hIAPP and rIAPP oligomers

Cross-sequence interactions between different amyloid peptides are important not only for fundamental understanding of amyloid aggregation and polymorphism mechanisms, but also for probing a potential molecular link between different amyloid diseases.

A polarizable coarse-grained protein model for dissipative particle dynamics

We present a new coarse-grained polarizable protein model for the dissipative particle dynamics (DPD) method.

Disorder in cholesterol-binding functionality of CRAC peptides: a molecular dynamics study

The cholesterol recognition/interaction amino acid consensus (CRAC) motif is a primary structure pattern used to identify regions that may be responsible for preferential cholesterol binding in many proteins. The leukotoxin LtxA, which is produced by a pathogenic bacterium, contains two CRAC seqences, only one of which is responsible for cholesterol binding, and the binding is required for cytotoxicity. The factors, in addition to the CRAC definition, that may be responsible for cholesterol-binding functionality and atomistic interactions between the CRAC region and cholesterol are as yet unknown. This study uses molecular dynamics simulations to identify structural characteristics and specific interactions of the two LtxA CRAC peptides with both pure phospholipid and binary cholesterol-phospholipid bilayers. We have identified changes in the secondary structure of these peptides that occur upon cholesterol binding, which are not seen when it is associated with a cholesterol-devoid membrane, and which show salient coupling of structural disorder and function. Additionally, the central tyrosine residue of the CRAC motif was found to play a significant role in cholesterol binding, though residues outside of the CRAC motif also influence membrane interactions and functionality of the CRAC region.