Search PubMed⌕ Search

Biomedical subjects

Andrew J Doig

Publications and source records attributed to Andrew J Doig.

At least 19 recordsLinked to original sources
PubMed2006

N-Methylated peptide inhibitors of beta-amyloid aggregation and toxicity. Optimization of the inhibitor structure.

The key pathogenic event in the onset of Alzheimer's disease (AD) is believed to be the aggregation of the beta-amyloid (Abeta) peptide into toxic oligomers. Molecules that interfere with this process may therefore act as therapeutic agents for the treatment of AD. N-Methylated peptides (meptides) are a general class of peptide aggregation inhibitors that act by binding to one face of the aggregating peptide but are unable to hydrogen bond on the other face, because of the N-methyl group replacing a backbone NH group. Here, we optimize the structure of meptide inhibitors of Abeta aggregation, starting with the KLVFF sequence that is known to bind to Abeta. We varied the meptide length, N-methylation sites, acetylation, and amidation of the N and C termini, side-chain identity, and chirality, via five compound libraries. Inhibitor activity was tested by thioflavin T binding, affinity chromatography, electron microscopy, and an 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide toxicity assay. We found that inhibitors should have all d chirality, have a free N terminus but an amidated C terminus, and have large, branched hydrophobic side chains at positions 1-4, while the side chain at position 5 was less important. A single N-methyl group was necessary and sufficient. The most active compound, d-[(chGly)-(Tyr)-(chGly)-(chGly)-(mLeu)]-NH(2), was more active than all previously reported peptide inhibitors. Its related non-N-methylated analogues were insoluble and toxic.

Amino Acid Sequence↗
PubMed2006

A study of the regional effects of alpha-synuclein on the organization and stability of phospholipid bilayers.

Associations between the protein alpha-synuclein (alpha-syn) and presynaptic vesicles have been implicated in synaptic plasticity and neurotransmitter release and may also affect how the protein aggregates into fibrils found in Lewy bodies, the cellular inclusions associated with neurodegenerative diseases. This work investigated how alpha-syn interacts with model phospholipid membranes and examined what effect protein binding has upon the physical properties of lipid bilayers. Wide line 2H and 31P NMR spectra of phospholipid vesicles revealed that alpha-syn associates with membranes containing lipids with anionic headgroups and can disrupt the integrity of the lipid bilayer, but the protein has little effect on membranes of zwitterionic phosphatidylcholine. A peptide, alpha-syn(10-48), which corresponds to the lysine-rich N-terminal region of alpha-syn, was found to associate with lipid headgroups with a preference for a negative membrane surface charge. Another peptide, alpha-syn(120-140), which corresponds to the glutamate-rich C-terminal region, also associates weakly with lipid headgroups but with a slightly higher affinity for membranes with no net surface charge than for negatively charged membrane surfaces. Binding of alpha-syn(10-48) and alpha-syn(120-140) to the lipid vesicles did not disrupt the lamellar structure of the membranes, but both peptides appeared to induce the lateral segregation of the lipids into clusters of acidic lipid-enriched and acidic lipid-deficient domains. From these findings, it is speculated that the N-terminal and C-terminal domains of full-length alpha-syn might act in concert to organize the membrane components during normal protein function and perhaps play a role in presynaptic vesicle synthesis, maintenance, and fusion.

Amino Acid Sequence↗
PubMed2006

The CXXC motif at the N terminus of an alpha-helical peptide.

An active site containing a CXXC motif is always found in the thiol-disulphide oxidoreductase superfamily. A survey of crystal structures revealed that the CXXC motif had a very high local propensity (26.3 +/- 6.2) for the N termini of alpha-helices. A helical peptide with the sequence CAAC at the N terminus was synthesized to examine the helix-stabilizing capacity of the CXXC motif. Circular dichroism was used to confirm the helical nature of the peptide and study behavior under titration with various species. With DTT, a redox potential of E(o) = -230 mV was measured, indicating that the isolated peptide is reducing in nature and similar to native human thioredoxin. The pK(a) values of the individual Cys residues could not be separated in the titration of the reduced state, giving a single transition with an apparent pK(a) of 6.74 (+/-0.06). In the oxidized state, the N-terminal pK(a) is 5.96 (+/-0.05). Analysis of results with the modified helix-coil theory indicated that the disulfide bond stabilized the alpha-helical structure by 0.5 kcal/mol. Reducing the disulfide destabilizes the helix by 0.9 kcal/mol.

Amino Acid Motifs↗
PubMed2006

Structure and stability of the alpha-helix: lessons for design.

The alpha-helix is the most abundant secondary structure in proteins. We now have an excellent understanding of the rules for helix formation because of experimental studies of helices in isolated peptides and within proteins, examination of helices in crystal structures, computer modeling and simulations, and theoretical work. Here we discuss structural features that are important for designing peptide helices, including amino acid preferences for interior and terminal positions, side chain interactions, disulfide bonding, metal binding, and phosphorylation. The solubility and stability of a potential design can be predicted with helical wheels and helix/coil theory, respectively. The helical content of a peptide is most often quantified by circular dichroism, so its use is discussed in detail.

Circular Dichroism↗
PubMed2005

Anticooperativity in a Glu-Lys-Glu salt bridge triplet in an isolated alpha-helical peptide.

Salt bridges between oppositely charged side chains are well-known to stabilize protein structure, though their contributions vary considerably. Here we study Glu-Lys and Lys-Glu salt bridges, formed when the residues are spaced i, i + 4 surface of an isolated alpha-helix in aqueous solution. Both are stabilizing by -0.60 and -1.02 kcal/mol, respectively, when the interacting residues are fully charged. When the side chains are spaced i, i + 4, i + 8, forming a Glu-Lys-Glu triplet, the second salt bridge provides no additional stabilization to the helix. We attribute this to the inability of the central Lys to form two salt bridges simultaneously. Analysis of these salt bridges in protein structures shows that the Lys-Glu interaction is dominant, with the side chains of the Glu-Lys pair far apart.

Amino Acid Sequence↗
PubMed2005

A phosphoserine-lysine salt bridge within an alpha-helical peptide, the strongest alpha-helix side-chain interaction measured to date.

Phosphorylation is ubiquitous in control of protein activity, yet its effects on protein structure are poorly understood. Here we investigate the effect of serine phosphorylation in the interior of an alpha-helix when a salt bridge is present between the phosphate group and a positively charged side chain (in this case lysine) at i,i + 4 spacing. The stabilization of the helix is considerable and can overcome the intrinsically low preference of phosphoserine for the interior of the helix. The effect is pH dependent, as both the lysine and phosphate groups are titratable, and so calculations are given for several charge combinations. These results, with our previous work, highlight the different, context-dependent effects of phosphorylation in the alpha-helix. The interaction between the phosphate(2)(-) group and the lysine side chain is the strongest yet recorded in helix-coil studies. The results are of interest both in de novo design of peptides and in understanding the structural modes of control by phosphorylation.

Amino Acid Sequence↗
PubMed2005

Pairwise coupling in an Arg-Phe-Met triplet stabilizes alpha-helical peptide via shared rotamer preferences.

The hydrophobic Arg-Phe and Phe-Met side chain interactions stabilize the alpha-helix by -0.29 and -0.59 kcal/mol, respectively, when placed i, i + 4 in an alanine-based peptide. When both interactions are present simultaneously, however, they stabilize the helix by an additional -0.75 kcal/mol, nearly as much as the sum of its parts. We attribute this coupling to a shared rotamer preference, as the central Phe is t in both bonds. The energetic cost of restricting the Phe residue into a t conformation is only paid once in the triplet, rather than twice when the interactions are separate. Coupling is thus demonstrated to have large effects on protein stability.

Amino Acid Sequence↗
PubMed2005

Predicting enzyme class from protein structure without alignments.

Methods for predicting protein function from structure are becoming more important as the rate at which structures are solved increases more rapidly than experimental knowledge. As a result, protein structures now frequently lack functional annotations. The majority of methods for predicting protein function are reliant upon identifying a similar protein and transferring its annotations to the query protein. This method fails when a similar protein cannot be identified, or when any similar proteins identified also lack reliable annotations. Here, we describe a method that can assign function from structure without the use of algorithms reliant upon alignments. Using simple attributes that can be calculated from any crystal structure, such as secondary structure content, amino acid propensities, surface properties and ligands, we describe each enzyme in a non-redundant set. The set is split according to Enzyme Classification (EC) number. We combine the predictions of one-class versus one-class support vector machine models to make overall assignments of EC number to an accuracy of 35% with the top-ranked prediction, rising to 60% accuracy with the top two ranks. In doing so we demonstrate the utility of simple structural attributes in protein function prediction and shed light on the link between structure and function. We apply our methods to predict the function of every currently unclassified protein in the Protein Data Bank.

Algorithms↗
PubMed2004

Improved prediction for N-termini of alpha-helices using empirical information.

The prediction of the secondary structure of proteins from their amino acid sequences remains a key component of many approaches to the protein folding problem. The most abundant form of regular secondary structure in proteins is the alpha-helix, in which specific residue preferences exist at the N-terminal locations. Propensities derived from these observed amino acid frequencies in the Protein Data Bank (PDB) database correlate well with experimental free energies measured for residues at different N-terminal positions in alanine-based peptides. We report a novel method to exploit this data to improve protein secondary structure prediction through identification of the correct N-terminal sequences in alpha-helices, based on existing popular methods for secondary structure prediction. With this algorithm, the number of correctly predicted alpha-helix start positions was improved from 30% to 38%, while the overall prediction accuracy (Q3) remained the same, using cross-validated testing. Although the algorithm was developed and tested on multiple sequence alignment-based secondary structure predictions, it was also able to improve the predictions of start locations by methods that use single sequences to make their predictions. Furthermore, the residue frequencies at N-terminal positions of the improved predictions better reflect those seen at the N-terminal positions of alpha-helices in proteins. This has implications for areas such as comparative modeling, where a more accurate prediction of the N-terminal regions of alpha-helices should benefit attempts to model adjacent loop regions. The algorithm is available as a Web tool, located at http://rocky.bms.umist.ac.uk/elephant.

Databases, Protein↗
PubMed2004

Prediction of Saccharomyces cerevisiae protein functional class from functional domain composition.

MOTIVATION: A key goal of genomics is to assign function to genes, especially for orphan sequences. RESULTS: We compared the clustered functional domains in the SBASE database to each protein sequence using BLASTP. This representation for a protein is a vector, where each of the non-zero entries in the vector indicates a significant match between the sequence of interest and the SBASE domain. The machine learning methods nearest neighbour algorithm (NNA) and support vector machines are used for predicting protein functional classes from this information. We find that the best results are found using the SBASE-A database and the NNA, namely 72% accuracy for 79% coverage. We tested an assigning function based on searching for InterPro sequence motifs and by taking the most significant BLAST match within the dataset. We applied the functional domain composition method to predict the functional class of 2018 currently unclassified yeast open reading frames. AVAILABILITY: A program for the prediction method, that uses NNA called Functional Class Prediction based on Functional Domains (FCPFD) is available and can be obtained by contacting Y.D.Cai at y.cai@umist.ac.uk

Algorithms↗
PubMed2004

Cellular kinetics of murine lung: model system to determine basis for radioprotection with keratinocyte growth factor.

PURPOSE: Normal tissue toxicity remains a dose limitation for cancer radiotherapy and chemoradiotherapy. Growth factors offer a novel means of mitigating normal tissue radiotoxicity. In particular, keratinocyte growth factor (rHuKGF), whose proliferative activity is restricted to epithelial cells, holds promise on the basis of the findings of preclinical models of epithelial cytoprotection and the clinical developments to date. We report the radioprotection of murine lung by an increase in tissue cellularity after rHuKGF-induced proliferation. METHODS AND MATERIALS: Flow cytometric and image analysis techniques after bromodeoxyuridine labeling were used to estimate proliferative parameters. Our specialized analytical methods measure not only labeling indexes, but also the durations of S and G(2)+M phases, potential doubling times, and the net cell production rate. Image analysis techniques were used to identify the specific cell types that were proliferating (type II pneumocytes). RESULTS: Lung labeling index control values (0.5%) rose to a maximum (5.5%) at 3 days after intratracheal rHuKGF, returning to normal by Day 7. The potential doubling time fell from 66 days to 4.4 days. The net cell production rate rose from a control value of 1%/d to >15%/d by Day 3. This resulted in a nearly twofold increase in alveolar epithelial cellularity, which remained significantly elevated on Day 7. Saline-treated control animals exhibited no significant changes in the proliferative parameter values or cellularity. On the basis of these data, mice were irradiated, solely to the thorax, with ranges of single doses of 250 kVp X-rays 7 days after either intratracheal administration of 5 mg/kg rHuKGF or phospate-buffered saline. This interval was chosen because the proliferative response of the type II cells was finished but the cellularity of the lung remained increased. Pretreatment with rHuKGF extended the latent period before onset of pneumonitis after all radiation doses. rHuKGF treatment 7 days before thoracic irradiation significantly protected against pneumonitis (median effective dose 13.7 Gy, 95% confidence limit 13.4-14.0) compared with the control pretreatment with phosphate-buffered saline (median effective dose 12.8 Gy, 95% confidence limit 12.6-13.1). CONCLUSION: The data showed that an increase in tissue cellularity, caused by rHuKGF treatment before irradiation, protected the lung from damage due to pneumonitis.

Algorithms↗
PubMed2004

Effect of the N3 residue on the stability of the alpha-helix.

N3 is the third position from the N terminus in the alpha-helix with helical backbone dihedral angles. All 20 amino acids have been placed in the N3 position of a synthetic helical peptide (CH(3)CO-[AAX AAAAKAAAAKAGY]-NH(2)) and the helix content measured by circular dichroism spectroscopy at 273 K. The dependence of peptide helicity on N3 residue identity has been used to determine a free energy scale by analysis with a modified Lifson-Roig helix coil theory that includes a parameter for the N3 energy (n3). The most stabilizing residues at N3 in rank order are Ala, Glu, Met/Ile, Leu, Lys, Ser, Gln, Thr, Tyr, Phe, Asp, His, and Trp. Free energies for the most destabilizing residues (Cys, Gly, Asn, Arg, and Pro) could not be fitted. The results correlate with N1, N2, and helix interior energies and not at all with N-cap preferences. This completes our work on studying the structural and energetic preferences of the amino acids for the N-terminal positions of the alpha-helix. These results can be used to rationally modify protein stability, help design helices, and improve prediction of helix location and stability.

Algorithms↗
PubMed2004

Prediction of protein function in the absence of significant sequence similarity.

Tremendous progress in DNA sequencing has yielded the genomes of a host of important organisms. The utilisation of these resources requires understanding of the function of each gene. Standard methods of functional assignment involve sequence alignment to a gene of known function; however such methods often fail to find any significant matches. Here we discuss a number of recent alternative methods that may be of use when sequence alignment fails. Function can be defined in a number of ways including E.C. number and MIPS and KEGG functional classes. Phylogenetic profiles show the pattern of presence or absence of a protein between genomes. Protein-protein interactions can be identified by searching for interacting pairs of proteins that are fused to a single protein chain in another organism. The gene neighbour method uses the observation that if the genes that encode two proteins are close on a chromosome, the proteins tend to be functionally related. More general methods use sequence properties such as amino acid composition, mean hydrophobicity, predicted secondary structure and post-translational modification sites. Data mining methods devise rules in the form of IF... THEN statements that make predictions of function using sequence based attributes, predicted secondary structure and sequence similarity. Finally, structural features can be used, after modelling the structure of a protein from its sequence or solving its structure. Protein fold class can be strongly indicative of function, while other structural features, such as secondary structure content, cleft size and 3D structural motifs are also useful.

Computer Simulation↗
PubMed2003

Distinguishing enzyme structures from non-enzymes without alignments.

The ability to predict protein function from structure is becoming increasingly important as the number of structures resolved is growing more rapidly than our capacity to study function. Current methods for predicting protein function are mostly reliant on identifying a similar protein of known function. For proteins that are highly dissimilar or are only similar to proteins also lacking functional annotations, these methods fail. Here, we show that protein function can be predicted as enzymatic or not without resorting to alignments. We describe 1178 high-resolution proteins in a structurally non-redundant subset of the Protein Data Bank using simple features such as secondary-structure content, amino acid propensities, surface properties and ligands. The subset is split into two functional groupings, enzymes and non-enzymes. We use the support vector machine-learning algorithm to develop models that are capable of assigning the protein class. Validation of the method shows that the function can be predicted to an accuracy of 77% using 52 features to describe each protein. An adaptive search of possible subsets of features produces a simplified model based on 36 features that predicts at an accuracy of 80%. We compare the method to sequence-based methods that also avoid calculating alignments and predict a recently released set of unrelated proteins. The most useful features for distinguishing enzymes from non-enzymes are secondary-structure content, amino acid frequencies, number of disulphide bonds and size of the largest cleft. This method is applicable to any structure as it does not require the identification of sequence or structural similarity to a protein of known function.

Algorithms↗
PubMed2003

Design strategies for anti-amyloid agents.

Numerous diseases have been linked to a common pathogenic process called amyloidosis, whereby proteins or peptides clump together in the brain or body to form toxic soluble oligomers and/or insoluble fibres. An attractive strategy to develop therapies for these diseases is therefore to inhibit or reverse protein/peptide aggregation. A diverse range of small organic ligands have been found to act as aggregation inhibitors. Alternatively, the wild-type peptide can be derivatised so that it still binds to the amyloid target, but prevents further aggregation. This can be achieved by adding a bulky group or charged amino acid to either end of the peptide, or by incorporating proline residues or N-methylated amide groups.

Amyloid beta-Peptides↗
PubMed2003

Length preferences and periodicity in beta-strands. Antiparallel edge beta-sheets are more likely to finish in non-hydrogen bonded rings.

We analysed the length distributions of different types of beta-strand in a high resolution, non-homologous set of 500 protein structures, finding differences in their mean lengths. Antiparallel edge strands in strand-turn-strand motifs show a preference for an even number of residues. This propensity is enhanced if the length is corrected for beta-bulges, which insert an extra residue into the strand. Residues in antiparallel edge beta-strands alternate between being in hydrogen bonded and non-hydrogen bonded rings. Antiparallel edges with an even number of residues are more likely to have their final beta residue in a non-hydrogen bonded ring. This suggests that non-hydrogen bonded rings are intrinsically more stable than hydrogen bonded rings, perhaps because its side chain packing is closer. Therefore, we suggest that a simple way to increase beta-hairpin stability, or the stability of an antiparallel edge strand, is to have a non-hydrogen bonded ring at the end of the strand.

Computational Biology↗