Tuning self-assembled nanostructures through enzymatic degradation of a peptide amphiphile

The enzymatic cleavage of a peptide amphiphile (PA) is investigated. The self-assembly of the cleaved products is distinct from that of the PA substrate. The PA C16-KKFFVLK is cleaved by α-chymotrypsin at two sites leading to products C16-KKF with FVLK and C16-KKFF with VLK. The PA C16-KKFFVLK forms nanotubes and helical ribbons at room temperature. Both PAs C16-KKF and C16-KKFF corresponding to cleavage products instead self-assemble into 5-6 nm diameter spherical micelles, while peptides FVLK and VLK do not adopt well-defined aggregate structures. The secondary structures of the PAs and peptides are examined by FTIR and circular dichroism spectroscopy and X-ray diffraction. Only C16-KKFFVLK shows substantial β-sheet secondary structure, consistent with its self-assembly into extended aggregates, based on PA layers containing hydrogen-bonded peptide headgroups. This PA also exhibits a thermoreversible transition to twisted tapes on heating.

Self-assembly of amphiphilic peptides

The self-assembly of amphiphilic peptides is reviewed. The review covers surfactant-like peptides with amphiphilicity arising from the sequence of natural amino acids, and also peptide amphiphiles (PAs) in which lipid chains are attached to hydrophilic peptide sequences containing charged residues. The influence of the secondary structure on the self-assembled structure and vice versa is discussed. For surfactant-like peptides structures including fibrils, nanotubes, micelles and vesicles have been reported. A particularly common motif for PAs is beta-sheet based fibrils, although other structures have been observed. In these structures, the peptide epitope is presented at the surface of the nanostructure, providing remarkable bioactivity. Recent discoveries of potential, and actual, applications of these materials in biomedicine and bionanotechnology are discussed.

Protein structure prediction servers at University College London

A number of state-of-the-art protein structure prediction servers have been developed by researchers working in the Bioinformatics Unit at University College London. The popular PSIPRED server allows users to perform secondary structure prediction, transmembrane topology prediction and protein fold recognition. More recent servers include DISOPRED for the prediction of protein dynamic disorder and DomPred for domain boundary prediction.

The PSIPRED protein structure prediction server

The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method.

Self-assembly of palmitoyl lipopeptides used in skin care products

The self-assembly of three cosmetically active peptide amphiphiles C16-GHK, C16-KT, and C16-KTTKS (C16 denotes a hexadecyl, palmitoyl chain) used in commercial skin care products is examined. A range of spectroscopic, microscopic, and X-ray scattering methods is used to probe the secondary structure, aggregate morphology, and the nanostructure. Peptide amphiphile (PA) C16-KTTKS forms flat tapes and extended fibrillar structures with high β-sheet content. In contrast, C16-KT and C16-GHK exhibit crystal-like aggregates with, in the case of the latter PA, lower β-sheet content. All three PA samples show spacings from bilayer structures in small-angle X-ray scattering profiles, and all three have similar critical aggregation concentrations, this being governed by the lipid chain length. However, only C16-KTTKS is stained by Congo red, a diagnostic dye used to detect amyloid formation, and this PA also shows a highly aligned cross-β X-ray diffraction pattern consistent with the high β-sheet content in the self-assembled aggregates. These findings may provide important insights relevant to the role of self-assembled aggregates on the reported collagen-stimulating properties of these PAs.

Layer-by-layer electrostatic entrapment of protein molecules on superparamagnetic nanoparticle: new strategy to enhance adsorption capacity and maintain biological activity

There is a recent interest to use inorganic-based magnetic nanoparticles as a vehicle to carry biomolecules for various biophysical applications, but direct attachment of the molecules is known to alter their conformation leading to attenuation in activity. In addition, surface immobilization has been limited to monolayer coverage. It is shown that alternate depositions of negatively charged protein molecules, typically bovine serum albumin (BSA) with a positively charged aminocarbohydrate template such as glycol chitosan (GC) on magnetic iron oxide nanoparticle surface as a colloid, are carried out under pH 7.4. Circular dichroism (CD) clearly reveals that the secondary structure of the entrapped BSA sequential depositions in this manner remains totally unaltered which is in sharp contrast to previous attempts. Probing the binding properties of the entrapped BSA using small molecules (Site I and Site II drug compounds) confirms for the first time the full retention of its biological activity as compared with native BSA, which also implies the ready accessibility of the entrapped protein molecules through the porous overlayers. This work clearly suggests a new method to immobilize and store protein molecules beyond monolayer adsorption on a magnetic nanoparticle surface without much structural alteration. This may find applications in magnetic recoverable enzymes or protein delivery.

Benchmarking consensus model quality assessment for protein fold recognition

Background: Selecting the highest quality 3D model of a protein structure from a number of alternatives remains an important challenge in the field of structural bioinformatics. Many Model Quality Assessment Programs (MQAPs) have been developed which adopt various strategies in order to tackle this problem, ranging from the so called "true" MQAPs capable of producing a single energy score based on a single model, to methods which rely on structural comparisons of multiple models or additional information from meta-servers. However, it is clear that no current method can separate the highest accuracy models from the lowest consistently. In this paper, a number of the top performing MQAP methods are benchmarked in the context of the potential value that they add to protein fold recognition. Two novel methods are also described: ModSSEA, which based on the alignment of predicted secondary structure elements and ModFOLD which combines several true MQAP methods using an artificial neural network. Results: The ModSSEA method is found to be an effective model quality assessment program for ranking multiple models from many servers, however further accuracy can be gained by using the consensus approach of ModFOLD. The ModFOLD method is shown to significantly outperform the true MQAPs tested and is competitive with methods which make use of clustering or additional information from multiple servers. Several of the true MQAPs are also shown to add value to most individual fold recognition servers by improving model selection, when applied as a post filter in order to re-rank models. Conclusion: MQAPs should be benchmarked appropriately for the practical context in which they are intended to be used. Clustering based methods are the top performing MQAPs where many models are available from many servers; however, they often do not add value to individual fold recognition servers when limited models are available. Conversely, the true MQAP methods tested can often be used as effective post filters for re-ranking few models from individual fold recognition servers and further improvements can be achieved using a consensus of these methods.

Use of a novel Hill-climbing genetic algorithm in protein folding simulations

We have developed a novel Hill-climbing genetic algorithm (GA) for simulation of protein folding. The program (written in C) builds a set of Cartesian points to represent an unfolded polypeptide's backbone. The dihedral angles determining the chain's configuration are stored in an array of chromosome structures that is copied and then mutated. The fitness of the mutated chain's configuration is determined by its radius of gyration. A four-helix bundle was used to optimise simulation conditions, and the program was compared with other, larger, genetic algorithms on a variety of structures. The program ran 50% faster than other GA programs. Overall, tests on 100 non-redundant structures gave comparable results to other genetic algorithms, with the Hill-climbing program running from between 20 and 50% faster. Examples including crambin, cytochrome c, cytochrome B and hemerythrin gave good secondary structure fits with overall alpha carbon atom rms deviations of between 5 and 5.6 Angstrom with an optimised hydrophobic term in the fitness function. (C) 2003 Elsevier Ltd. All rights reserved.

Use of essential and molecular dynamics to study gamma B-crystallin unfolding after non-enzymic post-translational modifications

Essential and Molecular Dynamics (ED/MD) have been used to model the conformational changes of a protein implicated in a conformational disease-cataract, the largest cause of blindness in the world-after non-enzymic post-translational modification. Cyanate modification did not significantly alter flexibility, while the Schiff's base adduct produced a more flexible N-terminal domain, and intra-secondary structure regions, than either the cyanate adduct or the native structure. Glycation also increased linker flexibility and disrupted the charge network. A number of post-translational adducts showed structural disruption around Cys15 and increased linker flexibility; this may be important in subsequent protein aggregation. Our modelling results are in accord with experimental evidence, and show that ED/MD is a useful tool in modelling conformational changes in proteins implicated in disease processes. (C) 2003 Published by Elsevier Ltd.

Interactions of bovine serum albumin with ethylene oxide/butylene oxide copolymers in aqueous solution

The interactions of bovine serum albumin (BSA) with three ethylene oxide/butylene oxide (E/B) copolymers having different block lengths and varying molecular architectures is examined in this study in aqueous solutions. Dynamic light scattering (DLS) indicates the absence of BSA-polymer binding in micellar systems of copolymers with lengthy hydrophilic blocks. On the contrary, stable protein-polyrner aggregates were observed in the case of E18B10 block copolymer. Results from DLS and SAXS suggest the dissociation of E/B copolymer micelles in the presence of protein and the absorption of polymer chains to BSA surface. At high protein loadings, bound BSA adopts a more compact conformation in solution. The secondary structure of the protein remains essentially unaffected even at high polymer concentrations. Raman spectroscopy was used to give insight to the configurations of the bound molecules in concentrated solutions. In the vicinity of the critical gel concentration of E18B10 introduction of BSA can dramatically modify the phase diagram, inducing a gel-sol-gel transition. The overall picture of the interaction diagram of the E18B10-BSA reflects the shrinkage of the suspended particles due to destabilization of micelles induced by BSA and the gelator nature of the globular protein. SAXS and rheology were used to further characterize the structure and flow behavior of the polymer-protein hybrid gels and sols.

The adsorbed conformation of globular proteins at the air/water interface

External reflection FTIR spectroscopy and surface pressure measurements were used to compare conformational changes in the adsorbed structures of three globular proteins at the air/water interface. Of the three proteins studied, lysozyme, bovine serum albumin and P-lactoglobulin, lysozyme was unique in its behaviour. Lysozyme adsorption was slow, taking approximately 2.5 h to reach a surface pressure plateau (from a 0.07 mM solution), and led to significant structural change. The FTIR spectra revealed that lysozyme formed a highly networked adsorbed layer of unfolded protein with high antiparallel beta-sheet content and that these changes occurred rapidly (within 10 min). This non-native secondary structure is analogous to that of a 3D heat-set protein gel, suggesting that the adsorbed protein formed a highly networked interfacial layer. Albumin and P-lactoglobulin adsorbed rapidly (reaching a plateau within 10 min) and with little chance to their native secondary structure.

Complex formation of bovine serum albumin with a poly(ethylene glycol) lipid conjugate

In this work, we report the formation of complexes by self-assembly of bovine serum albumin (BSA) with a poly(ethylene glycol) lipid conjugate (PEG(2000)-PE) in phosphate saline buffer solution (pH 7.4). Three different sets of samples have been studied. The BSA concentration remained fixed (1, 0.01, or 0.001 wt % BSA) within each set of samples, while the PEG(2000)-PE concentration was varied. Dynamic light scattering (DLS), rheology, and small-angle X-ray scattering (SAXS) were used to study samples with 1 wt % BSA. DLS showed that BSA/PEG(2000)-PE aggregates have a size intermediate between a BSA monomer and a PEG(2000)-PE micelle. Rheology suggested that BSA/PEG(2000)-PE complexes might be surrounded by a relatively compact PEG-lipid shell, while SAXS results showed that depletion forces do not take an important role in the stabilization of the complexes. Samples containing 0.01 wt % BSA were studied by circular dichroism (CD) and ultraviolet fluorescence spectroscopy (UV). UV results showed that at low concentrations of PEG-lipid, PEG(2000)-PE binds to tryptophan (Trp) groups in BSA, while at high concentrations of PEG-lipid the Trp groups are exposed to water. CD results showed that changes in Trp environment take place with a minimal variation of the BSA secondary structure elements. Finally, samples containing 0.001 wt % BSA were studied by zeta-potential experiments. Results showed that steric interactions might play an important role in the stabilization of the BSA/PEG(2000)-PE complexes.

Prediction of novel and analogous folds using fragment assembly and fold recognition

A number of new and newly improved methods for predicting protein structure developed by the Jones–University College London group were used to make predictions for the CASP6 experiment. Structures were predicted with a combination of fold recognition methods (mGenTHREADER, nFOLD, and THREADER) and a substantially enhanced version of FRAGFOLD, our fragment assembly method. Attempts at automatic domain parsing were made using DomPred and DomSSEA, which are based on a secondary structure parsing algorithm and additionally for DomPred, a simple local sequence alignment scoring function. Disorder prediction was carried out using a new SVM-based version of DISOPRED. Attempts were also made at domain docking and “microdomain” folding in order to build complete chain models for some targets.

The DISOPRED server for the prediction of protein disorder

Dynamically disordered regions appear to be relatively abundant in eukaryotic proteomes. The DISOPRED server allows users to submit a protein sequence, and returns a probability estimate of each residue in the sequence being disordered. The results are sent in both plain text and graphical formats, and the server can also supply predictions of secondary structure to provide further structural information.

Improvement of the GenTHREADER method for genomic fold recognition

Motivation: In order to enhance genome annotation, the fully automatic fold recognition method GenTHREADER has been improved and benchmarked. The previous version of GenTHREADER consisted of a simple neural network which was trained to combine sequence alignment score, length information and energy potentials derived from threading into a single score representing the relationship between two proteins, as designated by CATH. The improved version incorporates PSI-BLAST searches, which have been jumpstarted with structural alignment profiles from FSSP, and now also makes use of PSIPRED predicted secondary structure and bi-directional scoring in order to calculate the final alignment score. Pairwise potentials and solvation potentials are calculated from the given sequence alignment which are then used as inputs to a multi-layer, feed-forward neural network, along with the alignment score, alignment length and sequence length. The neural network has also been expanded to accommodate the secondary structure element alignment (SSEA) score as an extra input and it is now trained to learn the FSSP Z-score as a measurement of similarity between two proteins. Results: The improvements made to GenTHREADER increase the number of remote homologues that can be detected with a low error rate, implying higher reliability of score, whilst also increasing the quality of the models produced. We find that up to five times as many true positives can be detected with low error rate per query. Total MaxSub score is doubled at low false positive rates using the improved method.