Biomedical subjects

Andrew J Doig

Publications and source records attributed to Andrew J Doig.

24 records · Page 2Linked to original sources

PubMed2003

Modulating effect of keratinocyte growth factor on cellular kinetics of murine lung(I).

BACKGROUND & OBJECTIVE: Keratinocyte growth factor (KGF) causes the proliferation of type II pneumocytes in the lungs and confers protection against many external stimulation in the lung. Historically, the kinetic parameters, especially of slowly proliferating normal tissues, such as the lung, were difficult to measure. However, recently developed techniques made it possible to measure accurately the cellular kinetics in normal tissues. Flow cytometric techniques following bromodeoxyuridine (BrdUrd) incorporation into DNA of cells allow the accurate measurement of cellular proliferation. The purpose of this study was to measure the changes of the dynamic kinetics of normal lung tissue after treatment with KGF so as to build up the basis to prevent the occurrence of radiation-induced pneumonitis. METHODS: C3Hf/Kam mice were treated intratracheally (i.t.) with KGF (5 mg/kg) or the control (saline) and were sacrificed at 0, 1, 2, 3, 4, 5, and 7 days. The mice were labeled intraperitoneally (i.p.) with BrdUrd (60 mg/kg) at 20 minutes or 6 hours before sacrifice. Lungs were excised, fixed in 60% ethanol, digested to produce nuclei; and BrdUrd as well the total DNA content were labeled for flow cytometric analysis. The kinetic parameters including the labeling index (LI), duration of S-phase (T(S)), and potential doubling time (T(pot)) were measured by novel analytical methodology. Immunofluorescence staining was used to identify the specific cell type that was proliferating. RESULTS: (1)An optimum route for the administration (i.t.), dose (5 mg/kg), and time course of KGF to stimulate proliferation of type II pneumocytes in the lungs was established. (2)Lung LI control values (0.5%) rose to a maximum (5.5%) at 3 days after KGF treatment and returned to normal level on the 7(th) day. (3)Of the lung tissue, there is a dramatic reduction in T(pot) from 75.5 days to 4.7 days in the KGF-treated mice, while the saline-treated control mice exhibited no change in proliferative parameter values. CONCLUSION: KGF caused the proliferation of type II pneumocytes, followed with the elevated LI and reduced T(pot). This proliferative effect was transient and levels returned to normal level by the 7(th) day. The data obtained from this study would lay the groundwork for future investigation of KGF as a possible radioprotector of the lung in the field of radiation oncology.

Animals↗

PubMed2002

Recent advances in helix-coil theory.

Peptide helices in solution form a complex mixture of all helix, all coil or, most frequently, central helices with frayed coil ends. In order to interpret experiments on helical peptides and make theoretical predictions on helices, it is therefore essential to use a helix-coil theory that takes account of this equilibrium. The original Zimm-Bragg and Lifson-Roig helix-coil theories have been greatly extended in the last 10 years to include additional interactions. These include preferences for the N-cap, N1, N2, N3 and C-cap positions, capping motifs, helix dipoles, side chain interactions and 3(10)-helix formation. These have been applied to determine energies for these preferences from experimental data and to predict the helix contents of peptides. This review discusses these newly recognised structural features of helices and how they have been included in helix-coil models.

Peptides↗

PubMed2002

Stabilizing interactions between aromatic and basic side chains in alpha-helical peptides and proteins. Tyrosine effects on helix circular dichroism.

Here we investigate the structures and energetics of interactions between aromatic (Phe or Tyr) and basic (Lys or Arg) amino acids in alpha-helices. Side chain interaction energies are measured using helical peptides, by quantifying their helicities with circular dichroism at 222 nm and interpreting the results with Lifson-Roig-based helix/coil theory. A difficulty in working with Tyr is that the aromatic ring perturbs the CD spectrum, giving an incorrect helicity. We calculated the effect of Tyr on the CD at 222 nm by deriving the intensities of the bands directly from the electronic and magnetic transition dipole moments through the rotational strengths corresponding to each excited state of the polypeptide. This gives an improved value of the helix preference of Tyr (from 0.48 to 0.35) and a correction to the helicity for the peptides containing Tyr. We find that Phe-Lys, Lys-Phe, Phe-Arg, Arg-Phe, and Tyr-Lys are all stabilizing by -0.10 to -0.18 kcal.mol-1 when placed i, i + 4 on the surface of a helix in aqueous solution, despite the great difference in polarity between these residues. Interactions between these side chains have previously been attributed to cation-pi bonds. A survey of protein structures shows that they are in fact predominantly hydrophobic interactions between the CH2 groups of Lys or Arg and the aromatic rings.

Amino Acid Sequence↗

PubMed2002

Information-theoretic analysis of protein sequences shows that amino acids self-cluster.

We analyse for each of 20 amino acids X the statistics of spacings between consecutive occurrences of X within the well-characterized Saccharomyces cerevisiae genome. The occurrences of amino acids may exhibit near random, clustered or smoothed out behaviour, like one-dimensional stochastic processes along the protein chain. If amino acids are distributed randomly within a sequence, then they follow a Poisson process, and a histogram of the number of observations of each gap size would asymptotically follow a negative exponential distribution. The novelty of the present approach lies in the use of differential geometric methods to quantify information on sequencing of amino acids and groups of amino acids, via the sequences of intervals between their occurrences. The differential geometry arises from an information-theoretic distance function on the two-dimensional space of stochastic processes subordinate to gamma distributions-which latter include the random process as a special case. We find that maximum-likelihood estimates of parametric statistics show that all 20 amino acids tend to cluster, some substantially. In other words, the frequencies of short gap lengths tend to be higher and the variance of the gap lengths is greater than expected by chance. This may be because localizing amino acids with the same properties may favour secondary structure formation or transmembrane domains. Gap sizes of 1 or 2 are generally disfavoured, 1 strongly so. The only exceptions to this are Gln and Ser, as a result of poly(Gln) or poly(Ser) sequences. There are preferences for gaps of 4 and 7 that can be attributed to alpha -helices. In particular, a favoured gap of 7 for Leu is found in coiled coils. Our method contributes to the characterization of whole sequences by extracting and quantifying stable stochastic features.

Amino Acids↗

PubMed2002

Effect of phosphorylation on alpha-helix stability as a function of position.

We have investigated the effect of placing phosphoserine at the N-cap, N1, N2, N3, and interior position in alanine-based alpha-helical peptides. Helix contents of each peptide were measured by CD spectroscopy and titrations performed to determine pK(a) values. Data were analyzed with modified Lifson-Roig theory to determine helix-coil parameters (n, n(1), n(2), n(3), and w) and free energy changes for phosphoserine at each helical position. Results are given for a -1 and -2 phosphoserine charge state. Results show that phosphoserine stabilizes at the N-terminal positions by as much as 2.3 kcal.mol(-1), while destabilizes in the helix interior by 1.2 kcal.mol(-1), relative to serine. The rank order of free energies relative to serine at each position is N2 > N3 > N1 > N-cap > interior. Moreover, -2 phosphoserine is the most preferred residue known at each of these N-terminal positions. Experimental pK(a) values for the -1 to -2 phosphoserine transition are in the order N2 < N-cap < N1 < N3 < interior. This order agrees well with electrostatics calculations carried out with phosphoserine at the N-terminal positions and interior positions. Combining these with calculations at the C3, C2, C1, and C-cap positions gives results for phosphoserine along the length of the helix. We see a transition from phosphoserine stabilization at the N-terminus to destabilization at the C-terminus and can explain this in terms of the balance of protein solvation, favorable interactions, and dehydration. These results give insight into the phosphorylatable control of biological systems through positive or negative changes in stability.

Amino Acid Sequence↗

PubMed2002

A critical assessment of the secondary structure alpha-helices and their termini in proteins.

Secondary structure prediction from amino acid sequence is a key component of protein structure prediction, with current accuracy at approximately 75%. We analysed two state-of-the-art secondary structure prediction methods, PHD and JPRED, comparing predictions with secondary structure assigned by the algorithms DSSP and STRIDE. The specific focus of our study was alpha-helix N-termini, as empirical free energy scales are available for residue preferences at N-terminal positions. Although these prediction methods perform well in general at predicting the alpha-helical locations and length distributions in proteins, they perform less well at predicting the correct helical termini. For example, although most predicted alpha-helices overlap a real alpha-helix (with relatively few completely missed or extra predicted helices), only one-third of JPRED and PHD predictions correctly identify the N-terminus. Analysis of neighbouring N-terminal sequences to predicted helical N-termini shows that the correct N-terminus is often within one or two residues. More importantly, the true N-terminal motif is, on average, more favourable as judged by our experimentally measured free energies. This suggests a simple, but powerful, strategy to improve secondary structure prediction using empirically derived energies to adjust the predicted output to a more favourable N-terminal sequence.

Algorithms↗