Publications

Multiple dissipative self-assembly protocols designed to create novel structures or to reduce kinetic traps have recently emerged. Specifically, temporal oscillations of particle interactions have been shown effective at both aims, but investigations thus far have focused on systems of simple colloids or their binary mixtures. In this work, we expand our understanding of the effect of temporally oscillating interactions to a two-dimensional coarse-grained viral capsid-like model that undergoes a self-limited assembly. This model includes multiple intrinsic relaxation times due to the internal structure of the capsid subunits and, under certain interaction regimes, proceeds via a two-step nucleation mechanism. We find that oscillations much faster than the local intrinsic relaxation times can be described via a time averaged inter-particle potential across a wide range of interaction strengths, while oscillations much slower than these relaxation times result in structures that adapt to the attraction strength of the current half-cycle. Interestingly, oscillation periods similar to these relaxation times shift the interaction window over which orderly assembly occurs by enabling error correction during the half-cycles with weaker attractions. Our results provide fundamental insights to non-equilibrium self-assembly on temporally variant energy landscapes.

The sequence of copolymers is of significant importance to their material properties, yet controlling copolymer sequence remains a challenge. Previously, we have shown that polymer chains with sufficient stiffness and intermolecular attractions can undergo an emergent, polymerization-driven nematic alignment of nascent oligomers during a step-growth polymerization process. Both the extent of alignment and the point in the reaction at which it occurs impacts the kinetics and the sequence development of the growing polymer. Of particular interest is the emergence of a characteristic block length in the ensemble of sequences, resulting in unusually peaked block length distributions. Here we explore the emergence of this characteristic block length in time and investigate how changes in activation energy, solution viscosity, and monomer density influence the sequence and block length distributions of stiff copolymers undergoing step-growth polymerization. We find that emergent aggregation and nematic ordering restricts the availability of longer chains to form bonds, thereby altering the propensity of chains to react in a length dependent fashion, which changes as the reaction progresses, and promoting the formation of chains and blocks of a characteristic length. Further, we demonstrate that the characteristic length scale which emerges is sensitive to the relative timescales of reaction kinetics and reactant diffusion, shifting in response to changes in the activation energy of the reaction and the viscosity of the solvent. Our observations suggest the potential for biasing characteristic lengths of sequence repeats in stiff and semi-flexible copolymer systems by targeting specific non-bonded interactions and reaction kinetics through the informed adjustment of reaction conditions and the selection or chemical modification of monomer species.

Phillip L. Geissler made important contributions to the statistical mechanics of biological polymers, heterogeneous materials, and chemical dynamics in aqueous environments. He devised analytical and computational methods that revealed the underlying organization of complex systems at the frontiers of biology, chemistry, and materials science. In this retrospective we celebrate his work at these frontiers.

The phase behavior and material properties of copolymers are intrinsically dependent on their primary comonomer sequences. Achieving precise control over monomer sequence in synthetic copolymerizations is challenging, as sequence determination is influenced not only by the reaction conditions and the properties of the reactants but also by the statistical nature of the copolymerization process itself. Mayo–Lewis reactivity ratios are often used to predict copolymer composition and sequence and are based on ratios of static reactivity constants. However, prior results have demonstrated that in a generic, solution-based step-growth A,B-copolymerization, relatively weak non-bonded attractions between certain monomer pairs induce emergent microphase separations. Such polymerization-driven separations lead to deviations from standard kinetics due to the emergent heterogeneities in reactant concentrations, which can also cause significant shifts in the resulting copolymer sequences. Previously, these effects were observed in systems where the activation energies were equal for all reaction pathways, that is, between all monomer pair combinations. In this work, we explore the combined effects on copolymerization kinetics of differences in both activation energies and non-bonded attractions between monomers and examine the sequences produced within this same step-growth copolymerization model. Our results indicate that altering activation energies influences the kinetics and sequences in a manner that also depends on the non-bonded attractions, showing that these effects may work in concert or in opposition to one another to bias the sequences formed. Non-standard kinetic behaviors and long-range sequence biasing are observed under certain conditions, and the extent of each clearly shifts as the reaction proceeds. These findings provide insight into the complex interplay between sequence and nascent oligomer phase behavior, highlighting the potential for exploiting emergent phase properties in the informed design of advanced sequence-biased materials.

Advanced carbon microelectrodes, including many carbon-nanotube (CNT)-based electrodes, are being developed for the in vivo detection of neurotransmitters such as dopamine (DA). Our prior simulations of DA and dopamine-o-quinone (DOQ) on pristine, flat graphene showed rapid surface diffusion for all adsorbed species, but it is not known how CNT surfaces affect dopamine adsorption and surface diffusivity. In this work, we use molecular dynamics simulations to investigate the adsorbed structures and surface diffusion dynamics of DA and DOQ on CNTs of varying curvature and helicity. In addition, we study DA dynamics in a groove between two aligned CNTs to model the spatial constraints at the junctions within CNT assemblies. We find that the adsorbate diffusion on a solvated CNT surface depends upon curvature. However, this effect cannot be attributed to changes in the surface energy roughness because the lateral distributions of the molecular adsorbates are similar across curvatures, diffusivities on zigzag and armchair CNTs are indistinguishable, and the curvature dependence disappears in the absence of solvent. Instead, adsorbate diffusivities correlate with the vertical placement of the adsorbate’s moieties, its tilt angle, its orientation along the CNT axis, and the number of waters in its first hydration shell, all of which will influence its effective hydrodynamic radius. Finally, DA diffuses into and remains in the groove between a pair of aligned and solvated CNTs, enhancing diffusivity along the CNT axis. These first studies of surface diffusion on a CNT electrode surface are important for understanding the changes in diffusion dynamics of dopamine on nanostructured carbon electrode surfaces.

Carbon microelectrodes enable in vivo detection of neurotransmitters, and new electrodes aim to optimize the carbon surface. However, atomistic detail on the diffusion and orientation of neurotransmitters near these surfaces is lacking. Here, we employ molecular dynamics simulations to investigate the surface diffusion of dopamine (DA), its oxidation product dopamine-o-quinone (DOQ), and their protonated forms on the pristine basal plane of flat graphene. We find that all DA species rapidly adsorb to the surface and remain adsorbed, even without a holding potential or graphene surface defects. We also find that the diffusivities of the adsorbed and the fully solvated DA are similar and that the protonated species diffuse more slowly on the surface than their corresponding neutral forms, while the oxidized species diffuse more rapidly. Structurally, we find that the underlying graphene lattice has little influence over the molecular adsorbate's lateral position, and the vertical placement of the amine group on dopamine is highly dependent upon its charge. Finally, we find that solvation has a large effect on surface diffusivities. These first results from molecular dynamics simulations of dopamine at the aqueous-graphene interface show that dopamine diffuses rapidly on the surface, even without an applied potential, and provide a basis for future simulations of neurotransmitter structure and dynamics on advanced carbon materials electrodes.

Sequence control in synthetic copolymers remains a tantalizing objective in polymer science due to the influence of sequence on material properties and self-organization. A greater understanding of sequence development throughout the polymerization process will aid the design of simple, generalizable methods to control sequence and tune supramolecular assembly. In previous simulations of solution-based step-growth copolymerizations, we have shown that weak, non-bonding attractions between monomers of the same type can produce a microphase separation among the lengthening nascent oligomers and thereby alter sequence. This work explores the phenomenon further, examining how effective attractive interactions, mediated by a solvent selective for one of the reacting species, impact the development of sequence and the supramolecular assembly in a simple A–B copolymerization. We find that as the effective attractions between monomers increase, an emergent self-organization of the reactants causes a shift in reaction kinetics and sequence development. When the solvent-mediated interactions are selective enough, the simple mixture of A and B monomers oligomerize and self-assemble into structures characteristic of amphiphilic copolymers. The composition and morphology of these structures and the sequences of their chains are sensitive to the relative balance of affinities between the comonomer species. Our results demonstrate the impact of differing A–B monomer–solvent affinities on sequence development in solution-based copolymerizations and are of consequence to the informed design of synthetic methods for sequence controlled amphiphilic copolymers and their aggregates.

Synthetic copolymer sequences remain challenging to control, and there are features of even simple one-pot, solution-based copolymerizations that are not yet fully understood. In previous simulations on step-growth copolymerizations in solution, we demonstrated that modest variations in the attractions between type A and B monomers could significantly influence copolymer sequence through an emergent aggregation and phase separation initiated by the lengthening of nascent oligomers. Here we investigate how one aspect of a copolymer’s geometry─its flexibility─can modulate those effects. Our simulations show the onset of strand alignment within the polymerization-induced aggregates as chain stiffness increases and demonstrate that this alignment can influence the resulting copolymer sequences. For less flexible copolymers, with persistence lengths ≥10 monomers, modest nonbonded attractions of ∼k_BT between monomers of the same type yield A and B blocks of a characteristic length and result in a polydispersity index that grows rapidly, peaks, and then diminishes as the reaction proceeds. These results demonstrate that for copolymer systems with modest variations in intermonomer attractions and physically realistic flexibilities a nascent copolymer’s persistence length can influence its own sequence.

In the outer membrane of Gram-negative bacteria, membrane proteins are thought to be organized into domains or islands that play a role in the segregation, movement, and turnover of membrane components. However, there is presently limited information on the structure of these domains or the molecular interactions that mediate domain formation. In the present work, the Escherichia coli outer membrane vitamin B₁₂ transporter, BtuB, was spin-labeled, and double electron–electron resonance was used to measure the distances between proteins in intact cells. These data together with Monte Carlo simulations provide evidence for the presence of specific intermolecular contacts between BtuB monomers that could drive the formation of string-like oligomers. Moreover, the EPR data provide evidence for the location of the interacting interfaces and indicate that lipopolysaccharide mediates the contacts between BtuB monomers.

The sequential ordering of different monomers within synthetic copolymers is remarkably difficult to control. Our understanding of the determinants of and variations within copolymer sequences, even in simple step-growth reactions, remains limited. In this work, we perform simulations on a generic model of irreversible step-growth copolymerization between two types of monomers, A and B, in solution. Our results demonstrate that relatively weak attractions among nascent oligomers can exert considerable influence over the sequential arrangement of monomers in the final set of copolymers, even when identical reaction barriers exist between all monomer pairs. The observed effects cannot be fully accounted for within conventional polymerization theories due to a breakdown in Flory’s principle of equal reactivity that occurred in some cases. Nonetheless, these anomalous results can be readily explained by the Flory–Huggins theory, as a phase separation between A-rich and B-rich segments can emerge from and also be limited by the copolymerization process itself. This observation suggests that new routes for the one-pot synthesis of sequence-biased copolymers may be available through the coupling of step-growth copolymerizations and emergent phase separations.

Nanoparticles (NPs) protected with a ligand monolayer hold promise for a wide variety of applications, from photonics and catalysis to drug delivery and biosensing. Monolayers that include a mixture of ligand types can have multiple chemical functionalities and may also self-assemble into advantageous patterns. Previous work has shown that both chemical and length mismatches among these surface ligands influence phase separation. In this work, we examine the interplay between these driving forces, first by using our previously-developed configurationally-biased Monte Carlo (CBMC) algorithm to predict, then by using our matrix assisted laser desorption/ionization mass spectrometry (MALDI-MS) technique to experimentally probe, the surface morphologies of a series of two-ligand mixtures on the surfaces of ultrasmall silver NPs. Specifically, we examine three such mixtures, each of which has the same chemical mismatch (consisting of a hydrophobic alkanethiol and a hydrophilic mercapto-alcohol), but varying degrees of chain-length mismatch. This delicate balance between chemical and length mismatches provides a challenging test for our CBMC prediction algorithm. Even so, the simulations are able to quantitatively predict the MALDI-MS results for all three ligand mixtures, while also providing atomic-scale details from the equilibrated ligand structures, such as patch sizes and co-crystallization patterns. The resulting monolayer morphologies range from randomly-mixed to Janus-like, demonstrating that chain-length modifications are an effective way to tune monolayer morphology without needing to alter chemical functionalities.

Detection of monolayer morphology on nanoparticles smaller than 10 nm has proven difficult with traditional visualization techniques. Here matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) is used in conjunction with atomistic simulations to detect the formation of Janus-like monolayers on noble metal nanoparticles. Silver metal nanoparticles were synthesized with a monolayer consisting of dodecanethiol (DDT) and mercaptoethanol (ME) at varying ratios. The nanoparticles were then analyzed using MALDI-MS, which gives information on the local ordering of ligands on the surface. The MALDI-MS analysis showed large deviations from random ordering, suggesting phase separation of the DDT/ME monolayers. Atomistic Monte Carlo (MC) calculations were then used to simulate the nanoscale morphology of the DDT/ME monolayers. In order to quantitatively compare the computational and experimental results, we developed a method for determining an expected MALDI-MS spectrum from the atomistic simulation. Experiments and simulations show quantitative agreement, and both indicate that the DDT/ME ligands undergo phase separation, resulting in Janus-like nanoparticle monolayers with large, patchy domains.

Optogenetics and photopharmacology are powerful approaches to investigating biochemical systems. While the former is based on genetically encoded photoreceptors that utilize abundant chromophores, the latter relies on synthetic photoswitches that are either freely diffusible or covalently attached to specific bioconjugation sites, which are often native or engineered cysteines. The identification of suitable cysteine sites and appropriate linkers for attachment is generally a lengthy and cumbersome process. Herein, we describe an in silico screening approach that is designed to propose a small number of optimal combinations. By applying this computational approach to human carbonic anhydrase and a set of three photochromic tethered ligands, the number of potential site-ligand combinations was narrowed from over 750 down to 6, which we then evaluated experimentally. Two of these six combinations resulted in light-responsive human Carbonic Anhydrases (LihCAs), which were characterized with enzymatic activity assays, mass spectrometry, and X-ray crystallography. Our study also provides insights into the reactivity of cysteines toward maleimides and the hydrolytic stability of the adducts obtained.

A one-step postpolymerization modification that converts three high bandgap poly(arylene ethynylene)s into low bandgap donor–acceptor copolymers is described. The strategy relies on a palladium-catalyzed cyclopentannulation reaction between the main-chain ethynylene functionality and a small molecule aryl bromide (6-bromo-1,2-dimethylaceanthrylene). The reaction installs new cyclopenta[hi]aceanthrylene electron-accepting groups between the electron rich arylenes along the polymer backbone. The modified polymers include poly(9,9-didodecyl-fluorene-2,7-ethynylene), poly(9-dodecyl-carbazole-2,7-ethynylene), and poly(2,5-dioctyloxyphenylene-1,4-ethynylene). The functionalization efficiency was evaluated via isotopic ¹³C labeling of the polymeric ethynylene carbons and then monitoring the chemical environment of those carbons via NMR spectroscopy. Near complete conversion of the sp carbon species to sp² carbon species was observed, which demonstrates the high efficiency of the modification strategy. Gel permeation chromatography shows that the hydrodynamic radius of the polymers is reduced considerably going from linear to kinked polymer morphology upon functionalization, and molecular dynamics simulations illustrate the underlying morphological change. The newly formed donor–acceptor polymers showed dramatically different optical and electrochemical properties from the precursor poly(arylene ethynylene) polymers. A new absorption band centered at ∼650 nm represents a red-shift of >300 nm for the onset of absorption compared with that of precursor polymers and cyclic voltammetry shows two new low-lying reduction peaks that coincide with the cyclopenta[hi]aceanthrylene moiety.

Conspectus

Folded protein structures are both stable and dynamic. Historically, our clearest window into these structures came from X-ray crystallography, which generally provided a static image of each protein’s singular “folded state”, highlighting its stability. Deviations away from that crystallographic structure were difficult to quantify, and as a result, their potential functional consequences were often neglected. However, several dynamical and statistical studies now highlight the structural variability that is present within the protein’s folded state. Here we review mounting evidence of the importance of these structural rearrangements; both experiment and computation indicate that folded proteins undergo substantial fluctuations that can greatly influence their function.

Crucially, recent studies have shown that structural elements of proteins, especially their side-chain degrees of freedom, fluctuate in ways that generate significant conformational heterogeneity. The entropy associated with these motions contributes to the folded structure’s thermodynamic stability. In addition, since these fluctuations can shift in response to perturbations such as ligand binding, they may play an important role in the protein’s capacity to respond to environmental cues. In one compelling example, the entropy associated with side-chain fluctuations contributes significantly to regulating the binding of calmodulin to a set of peptide ligands.

The neglect of fluctuations within proteins’ native states was often justified by the dense packing within folded proteins, which has inspired comparisons with crystalline solids. Many liquids, however, can achieve similarly dense packing yet fluidity is maintained through correlated molecular motions. Indeed, the studies we discuss favor comparison of folded proteins not with solids but instead with dense liquids, where the internal side chain fluidity is facilitated by collective motions that are correlated over long distances. These correlated rearrangements can enable allosteric communication between different parts of a protein, through subtle and varied channels. Such long-range correlations appear to be an innate feature of proteins in general, manifest even in molecules lacking known allosteric regulators and arising robustly from the physical nature of their internal environment. Given their ubiquity, it is only to be expected that, over time, nature has refined some subset of these correlated motions and put them to use.

Native state fluctuations increasingly appear to be vital for proteins’ natural functions. Understanding the diversity, origin, and range of these rearrangements may provide novel routes for rationally manipulating biomolecular activity.

Previous methods for determining whether a uniform region of a sample is crystalline or isotropic—what we call the “state of internal orientation” 𝒮S—require a priori knowledge of properties of the purely crystalline and purely isotropic states. In addition, these methods can be ambiguous in their determination of state 𝒮S for particular materials and, for a given material, the spectral methods can be ambiguous when using particular peaks. Using first-principles Raman theory, we have discovered a simple, non-resonance, polarized Raman method for determining the state 𝒮S that requires no information a priori and will work unambiguously for any material using any vibrational mode. Similar to the concept behind “magic angle spinning” in NMR, we have found that for a special set of incident/analyzed polarizations and scattering angle, the dependence of the Raman modulation depth M on the sample composition—and, for crystalline regions, the unit cell orientation—falls out completely, leaving dependence on only whether the region is crystalline (M = 1) or isotropic (M = 0). Further, upon scanning between homogeneous regions or domains within a heterogeneous sample, our signal M is a clear detector of the region boundaries, so that when combined with methods for determining the orientations of the crystalline domains, our method can be used to completely characterize the molecular structure of an entire heterogeneous sample to a very high certainty. Interestingly, our method can also be used to determine when a given mode is vibrationally degenerate. While simulations on realistic terthiophene systems are included to illustrate our findings, our method should apply to any type of material, including thin films, molecular crystals, and semiconductors. Finally, our discovery of these relationships required derivations of Raman intensity formulas that are at least as general as any we have found, and herein we present our comprehensive formulas for both the crystalline and isotropic states.

We have measured the single-molecule conductance of a family of bithiophene derivatives terminated with methyl sulfide gold-binding linkers using a scanning tunneling microscope based break-junction technique. We find a broad distribution in the single-molecule conductance of bithiophene compared with that of a methyl sulfide terminated biphenyl. Using a combination of experiments and calculations, we show that this increased breadth in the conductance distribution is explained by the difference in 5-fold symmetry of thiophene rings as compared to the 6-fold symmetry of benzene rings. The reduced symmetry of thiophene rings results in a restriction on the torsion angle space available to these molecules when bound between two metal electrodes in a junction, causing each molecular junction to sample a different set of conformers in the conductance measurements. In contrast, the rotations of biphenyl are essentially unimpeded by junction binding, allowing each molecular junction to sample similar conformers. This work demonstrates that the conductance of bithiophene displays a strong dependence on the conformational fluctuations accessible within a given junction configuration, and that the symmetry of such small molecules can significantly influence their conductance behaviors.

Single-molecule excitation polarization anisotropy and molecular dynamics simulations reveal that the folding of polymers composed of conjugated phenylene vinylene (PPV) oligomers joined by flexible linkers can be influenced by the length of the conjugated segments. By varying the number of PPV repeat units from three to five to seven, both the structure and the spectral properties of the polymer can be controlled at the synthetic level. The stronger interactions between longer conjugated units of the polymers lead to more ordered conformations. The mean modulation depth of a septamer containing PPV (M = 0.75) was found to be even higher than that of the traditional homopolymer MEH-PPV (M = 0.66), which suggests that these new polymers provide access to highly aligned nanostructures not typically found in homopolymer systems.

The modeling of the conformational properties of conjugated polymers entails a unique challenge for classical force fields. Conjugation imposes strong constraints upon bond rotation. Planar configurations are favored, but the concomitantly shortened bond lengths result in moieties being brought into closer proximity than usual. The ensuing steric repulsions are particularly severe in the presence of side chains, straining angles, and stretching bonds to a degree infrequently found in nonconjugated systems. We herein demonstrate the resulting inaccuracies by comparing the LMP2-calculated inter-ring torsion potentials for a series of substituted stilbenes and bithiophenes to those calculated using standard classical force fields. We then implement adjustments to the OPLS-2005 force field in order to improve its ability to model such systems. Finally, we show the impact of these changes on the dihedral angle distributions, persistence lengths, and conjugation length distributions observed during molecular dynamics simulations of poly[2-methoxy-5-(2′-ethylhexyloxy)-p-phenylene vinylene] (MEH-PPV) and poly 3-hexylthiophene (P3HT), two of the most widely used conjugated polymers.

Raman spectra were recorded experimentally and calculated theoretically for bithiophene, terthiophene, and quaterthiophene samples as a function of excitation polarization. Distinct spectral signatures were assigned and correlated to the molecular/unit cell orientation as determined by X-ray diffraction. The ability to predict molecular/unit cell orientation within organic crystals using polarized Raman spectroscopy was evaluated by predicting the unit cell orientation in a simulated terthiophene crystal given a random set of simulated polarized Raman spectra. Polarized Raman spectroscopy offers a promising tool to quickly and economically determine the unit cell orientation in known organic crystals and crystalline thin films. Implications of our methodologies for studying individual molecule conformations are discussed.

Allosteric regulation is a key component of cellular communication, but the way in which information is passed from one site to another within a folded protein is not often clear. While backbone motions have long been considered essential for long-range information conveyance, side-chain motions have rarely been considered. In this work, we demonstrate their potential utility using Monte Carlo sampling of side-chain torsional angles on a fixed backbone to quantify correlations amongst side-chain inter-rotameric motions. Results indicate that long-range correlations of side-chain fluctuations can arise independently from several different types of interactions: steric repulsions, implicit solvent interactions, or hydrogen bonding and salt-bridge interactions. These robust correlations persist across the entire protein (up to 60 Å in the case of calmodulin) and can propagate long-range changes in side-chain variability in response to single residue perturbations.

The Horner method was used to synthesize random copolymers of poly(2-methoxy-5-(2′-ethylhexyloxy)-p-phenylene vinylene) (MEH-PPV) that incorporated different backbone-directing monomers. Single-molecule polarization absorption studies of these new polymers demonstrate that defects that preserve the linear backbone of PPV-type polymers assume the highly anisotropic configurations found in defect-free MEH-PPV. Rigid defects that are bent lower the anisotropy of the single chain, and saturated defects that provide rotational freedom for the chain backbone allow for a wide variety of possible configurations. Molecular dynamics simulations of model defect PPV oligomers in solution demonstrate that defect-free and linearly defected oligomers remain extended while the bent and saturated defects tend toward more folded, compact structures.

Despite the high density within a typical protein fold, the ensemble of sterically permissible side-chain repackings is vast. Here, we examine the extent of this variability that survives energetic biases due to van der Waals interactions, hydrogen bonding, salt bridges, and solvation. Monte Carlo simulations of an atomistic model exhibit thermal fluctuations among a diverse set of side-chain arrangements, even with the peptide backbone fixed in its crystallographic conformation. We have quantified the torsional entropy of this native-state ensemble, relative to that of a noninteracting reference system, for 12 small proteins. The reduction in entropy per rotatable bond due to each kind of interaction is remarkably consistent across this set of molecules. To assess the biophysical importance of these fluctuations, we have estimated side-chain entropy contributions to the binding affinity of several peptide ligands with calmodulin. Calculations for our fixed-backbone model correlate very well with experimentally determined binding entropies over a range spanning more than 80 kJ/(mol·308 K).

Increasing evidence indicates that many peptides and proteins can be converted in vitro into highly organised amyloid structures, provided that the appropriate experimental conditions can be found. In this work, we define intrinsic propensities for the aggregation of individual amino acids and develop a method for identifying the regions of the sequence of an unfolded peptide or protein that are most important for promoting amyloid formation. This method is applied to the study of three polypeptides associated with neurodegenerative diseases, Aβ42, α-synuclein and tau. In order to validate the approach, we compare the regions of proteins that are predicted to be most important in driving aggregation, either intrinsically or as the result of mutations, with those determined experimentally. The knowledge of the location and the type of the “sensitive regions” for aggregation is important both for rationalising the effects of sequence changes on the aggregation of polypeptide chains and for the development of targeted strategies to combat diseases associated with amyloid formation.

Protein aggregation is associated with a variety of pathological conditions, including Alzheimer s and Creutzfeldt-Jakob diseases and type II diabetes. Such degenerative disorders result from the conversion of the normal soluble state of specific proteins into aggregated states that can ultimately form the characteristic amyloid fibrils found in diseased tissue. Under appropriate conditions it appears that many, perhaps all, proteins can be converted in vitro into amyloid fibrils. The aggregation propensities of different polypeptide chains have, however, been observed to vary substantially. Here, we describe an approach that uses the knowledge of the amino acid sequence and of the experimental conditions to reproduce, with a correlation coefficient of 0.92 and over five orders of magnitude, the in vitro aggregation rates of a wide range of unstructured peptides and proteins. These results indicate that the formation of protein aggregates can be rationalised to a considerable extent in terms of simple physico-chemical parameters that describe the properties of polypeptide chains and their environment.

Paramagnetic metal centers [such as Fe^III found within ferriprotoporphyrin IX heme (FPIX)] exert through space effects on the relaxation rate of nearby proton spins that depend critically on the metal−proton distance. We have measured these effects for all protons of several antimalarial drugs that bind to FPIX by systematically varying the drug:heme molar ratio in high field NMR experiments. These measurements allow us to determine precise FPIX Fe−drug H distances for the solution structures of noncovalent complexes formed between FPIX μ-oxo dimers and the antimalarial drugs chloroquine (CQ), quinine (QN), and quinidine (QD). Using these distances, we then performed distance restraint calculations to determine the lowest-energy solution structures of these complexes. Structures were solved for neutral, monoprotic (+1), and diprotic (+2) forms of the drugs. Analysis of these structures allows us to visualize for the first time the stereospecific differences between QN and QD binding to FPIX and the differences in populations of QN and QD solution structures upon changes in digestive vacuolar pH for drug resistant malarial parasites [Dzekunov, S. M., et al. (2000) Mol. Biochem. Parasitol. 110, 107−124]. The data indicate a previously unrecognized key role for the CQ aliphatic chain in stabilizing FPIX−CQ complexes, and suggest how lengthening or shortening the chain might perturb stability. We also define FPIX:drug stoichiometries of 2:1 for the complexes formed at physiological FPIX concentrations, in contrast to the 4:1 and 5:1 stoichiometries previously determined at higher FPIX concentrations [Dorn, A., et al. (1998) Biochem. Pharmacol. 55, 727−736]. These atomic resolution antimalarial drug−heme structures should help elucidate how these drugs inhibit formation of hemozoin during metabolism of heme within the malarial parasite Plasmodium falciparum and assist ongoing development of strategies for circumventing antimalarial drug resistance.

Recently, we measured a more acid digestive vacuolar pH for drug resistant Plasmodium falciparum [Dzekunov S, Ursos LMB, Roepe PD. Mol Biochem Parasitol 2000;in press; Ursos LMB, Dzekunov S, Roepe PD. Mol Biochem Parasitol 2000;in press]. We suggested this acidification contributes to drug resistance via the profound effects that pH has on the solubility of unpolymerized heme found in the vacuole (ferriprotoporphyrin IX μ oxo dimers). In this report, we measure how FPIX concentration, time, NaCl concentration, and several antimalarial drugs affect FPIX pH dependent solubility. Aggregation is essentially instantaneous below pH 5.3, but at vacuolar pH previously measured for HB3 parasites [Dzekunov S, Ursos LMB, Roepe PD. Mol Biochem Parasitol 2000;in press] can increase to several minutes as NaCl is lowered. As FPIX is decreased, the midpoint of the pH dependent solubility curve shifts to higher values. Addition of antimalarial drugs also increases the midpoint of the pH dependent FPIX solubility curve, with the net shift proportional to the relative affinity of the drug for FPIX. Surprisingly, however, for all drugs tested shifts of essentially identical magnitude are found at all drug: FPIX molar ratios inspected, spanning eight orders of magnitude (to as low as 0.0000001:1). This suggests that changes in pH dependent FPIX solubility by addition of antimalarial drugs is via previously unrecognized drug/FPIX nucleation phenomena. These data could have important implications for understanding the role of previously observed changes in pHvac [Dzekunov S, Ursos LMB, Roepe PD. Mol Biochem Parasitol 2000;in press; Ursos LMB, Dzekunov S, Roepe PD. Mol Biochem Parasitol 2000;in press] upon development of antimalarial drug resistance.