Biomedical subjects

Parvez I Haris

Publications and source records attributed to Parvez I Haris.

12 recordsLinked to original sources

PubMed2006

Effect of fasting on the pattern of urinary arsenic excretion.

Millions of people in some of the poorest regions of the world are exposed to high levels of arsenic through drinking contaminated water. It has been reported that development of cancer caused by arsenic exposure in such populations is dependent on dietary and nutritional factors which can modulate arsenic metabolism. Many people in arsenic exposed regions of Bangladesh and India practice fasting for at least one month every year when they refrain from consumption of food and fluid during daylight hours. How such practices may modulate arsenic metabolism has not been previously investigated. This study investigated this issue by determining total arsenic and its species in urine samples from a group of 29 unexposed volunteers at the beginning of the fasting and at the end of approximately 12 h of fasting period. Inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) coupled with ICP-MS was used to measure the total arsenic and arsenic speciation in the urine samples, respectively. The mean total levels of arsenic at the beginning of fasting (18.3 microg g(-1) creatinine) and at the end of approximately 12 h of fasting (17.7 microg g(-1) creatinine) did not differ significantly (p > 0.05). However, the percentages of urinary arsenic as the methylated arsenic species methylarsonate (MA) were found to be significantly different (p < 0.05) and this species was observed more frequently at the end of fasting, although its overall concentration was similar. There were no significant differences (p > 0.05) in both the concentrations and percentages of other urinary arsenic species detected, namely arsenobetaine (AB) and dimethylarsinate (DMA). Arsenite (As(III)) and arsenate (As(V)) were also analyzed, but were not detected. We conclude that fasting for a period of 12 h results in a significant increase in the percentage of urinary arsenic as MA, and its frequency of detection in the volunteers at the end of the fasting period is almost nine fold higher. This suggests that metabolism of arsenic is altered by fasting.

Adult↗

PubMed2006

Understanding arsenic metabolism through a comparative study of arsenic levels in the urine, hair and fingernails of healthy volunteers from three unexposed ethnic groups in the United Kingdom.

Very little is known about arsenic (As) metabolism in healthy populations that are not exposed to high concentrations of As in their food or water. Here we present a study with healthy volunteers from three different ethnic groups, residing in Leicester, UK, which reveals statistically significant differences in the levels of total As in urine and fingernail samples. Urine (n = 63), hair (n = 36) and fingernail (n = 36) samples from Asians, Somali Black-Africans and Whites were analysed using inductively coupled plasma mass spectrometry (ICP-MS) and graphite furnace atomic absorption spectroscopy (GF-AAS). The results clearly show that the total concentrations of As in urine and fingernail samples of a Somali Black-African population (urine 7.2 microg/g creatinine; fingernails 723.1 microg/kg) are significantly (P < 0.05) different from the Asian (urine 24.5 microg/g creatinine; fingernails 153.9 microg/kg) and White groups (urine 20.9 microg/g creatinine; fingernails 177.0 microg/kg). The chemical speciation of As in the urine of the three groups was also measured using high performance liquid chromatography coupled to ICP-MS. This showed that the proportion of the total urinary As present as dimethylarsenate (DMA) was higher for the Somali Black-African group (50%) compared to the Asians (16%) and Whites (22%). However, there was no significant difference (P > 0.05) in the level of As in the hair samples from these three groups; Somali Black-Africans (116.0 microg/kg), Asians (117.4 microg/kg) and Whites (141.2 microg/kg). Significantly different levels of total As in fingernail and urine and a higher percentage of urinary DMA in the Somali Black-Africans are suggestive of a different pattern of As metabolism in this ethnic group.

Adult↗

PubMed2005

A biomaterial based approach for arsenic removal from water.

We demonstrate that the non-living, dried roots of the water hyacinth plant [Eichhornia crassipes(Mart.) Solms] can rapidly remove arsenic from water. Atomic absorption spectrometry was used to demonstrate that more than 93% of arsenite (As(iii)) and 95% of arsenate (As(v)) were removed from a solution containing 200 microg As l(-1) within 60 minutes of exposure to a powder produced from dried roots. No difference in removal efficiency was observed between the two oxidation states of As studied. The amount of arsenic remaining in solution was found to be less than 10 microg l(-1) which is the WHO guideline limit value for As in drinking water. The presence of arsenic in drinking water in a number of countries in the developing world has been found to be much higher than the WHO level, affecting the health of millions of people. In this paper, we show that a biomaterial produced from dried water hyacinth roots, a plant that is found in abundant supply in many parts of the world, can provide a simple, effective and yet cheap method for removing arsenic from contaminated water.

Arsenic↗

PubMed2004

Using artificially generated spectral data to improve protein secondary structure prediction from Fourier transform infrared spectra of proteins.

Secondary structures of proteins have been predicted using neural networks from their Fourier transform infrared spectra. To improve the generalization ability of the neural networks, the training data set has been artificially increased by linear interpolation. The leave-one-out approach has been used to demonstrate the applicability of the method. Bayesian regularization has been used to train the neural networks and the predictions have been further improved by the maximum-likelihood estimation method. The networks have been tested and standard error of prediction (SEP) of 4.19% for alpha helix, 3.49% for beta sheet, and 3.15% for turns have been achieved. The results indicate that there is a significant decrease in the SEP for each type of structure parameter compared to previous works.

Algorithms↗

PubMed2004

Towards developing a protein infrared spectra databank (PISD) for proteomics research.

Fourier transform infrared (FTIR) spectroscopy is an attractive tool for proteomics research as it can be used to rapidly characterize protein secondary structure in aqueous solution. Recently, a number of secondary structure prediction methods based on reference sets of FTIR spectra from proteins with known structure from X-ray crystallography have been suggested. These prediction methods, often referred to as pattern recognition based approaches, demonstrated good prediction accuracy using some error measure, e.g., the standard error of prediction (SEP). However, to avoid possible adverse effects from differences in recording, the analysis has been mostly based on reference sets of FTIR spectra from proteins recorded in one laboratory only. As a result, these studies were based on reference sets of FTIR spectra from a limited number of proteins. Pattern recognition based approaches, however, rely on reference sets of FTIR spectra from as many proteins as possible representing all possible band shape variation to be related to the diversity of protein structural classes. Hence, if we want to build reliable pattern recognition based systems to support proteomics research, which are capable of making good predictions from spectral data of any unknown protein, one common goal should be to build a comprehensive protein infrared spectra databank (PISD) containing FTIR spectra of proteins of known structure. We have started the process of developing a comprehensive PISD composed of spectra recorded in different laboratories. As part of this work, here we investigate possible effects on prediction accuracy achieved by a neural network analysis when using reference sets composed of FTIR spectra from different laboratories. Surprisingly low magnitude of difference in SEPs throughout all our experiments suggests that FTIR spectra recorded in different laboratories may be safely combined into one reference set with only minor deterioration of prediction accuracy in the worst case.

Algorithms↗

PubMed2004

Conformational changes in alamethicin associated with substitution of its alpha-methylalanines with leucines: a FTIR spectroscopic analysis and correlation with channel kinetics.

Alamethicin, a 20 residue-long peptaibol remains a favorite high voltage-dependent channel-forming peptide. However, the structural significance of its abundant noncoded residues (alpha-methylalanine or Aib) for its ion channel activity remains unknown, although a previous study showed that replacement of all Aib residues with leucines preserved the essential channel behavior except for much faster single-channel events. To correlate these functional properties with structural data, here we compare the secondary structures of an alamethicin derivative where all the eight Aibs were replaced by leucines and the native alamethicin. Fourier transform infrared (FTIR) spectra of these peptides were recorded in methanol and in aqueous phospholipid membranes. Results obtained show a significant conformational change in alamethicin upon substitution of its Aib residues with Leu. The amide I band occurs at a lower frequency for the Leu-derivative indicating that its alpha-helices are involved in stronger hydrogen-bonding. In addition, the structure of the Leu-derivative is quite sensitive to membrane fluidity changes. The amide I band shifts to higher frequencies when the lipids are in the fluid phase. This indicates either a decreased solvation due to a more complete peptide insertion or a peptide stretching to match the full thickness of the bilayer. These results contribute to explain the fast single-channel kinetics displayed by the Leu-derivative.

Alamethicin↗

PubMed2004

Beyond average protein secondary structure content prediction using FTIR spectroscopy.

This paper demonstrates that secondary structure information beyond purely protein secondary structure content can be predicted from FTIR (Fourier transform infrared spectroscopy) spectra of proteins with a high degree of accuracy. Both neural networks and adaptive neuro-fuzzy inference systems (ANFISs) were employed to predict helix/sheet segment information. The best results were achieved using ANFISs with fuzzy subtractive clustering based on normalised, compressed amide I data with an average SEP (standard error of prediction, root mean of squared errors) of 1.51. Predictions for average helix/sheet length based merely on the amide I band maximum position in combination with the full-width at half-height resulted in a comparable average SEP of 1.62. This suggests the importance of information on the position and width of the amide I band maximum for the prediction of helix/sheet segment information. Finally, the most promising pattern recognition approaches found in this study were applied to a protein with an as yet unknown x-ray structure: native a1-antichymotrypsin (a1-ACT).

Algorithms↗

PubMed2003

Fourier transform infrared spectroscopy suggests unfolding of loop structures precedes complete unfolding of pig citrate synthase.

Pig citrate synthase (PCS) can be used as a model enzyme to gain some insight into the structural basis of protein thermostability. The thermal unfolding characteristics of the specific secondary structure elements within PCS were monitored in detail by following changes in its amide I band components. The result of our study indicates that PCS undergoes irreversible thermal denaturation. Detailed analysis reveals that the different secondary structures display a multistep transition with a major and a minor transition at different temperatures and a very small initial transition at the same temperature (30 degrees C). A plot of temperature-induced changes in (1)H-(2)H exchange, the decrease in the absorbance of the alpha-helical structures, and the increase in the absorbance of aggregated structures all have in common a multistep transition, the minor one centered at 45 degrees C and the major one around 59 degrees C. In contrast, a band that is tentatively assigned to loop structures displays these same minor and major transitions but at lower temperatures (39 and 52 degrees C, respectively). The transition, which occurs at 39-45 degrees C, is not associated with the appearance of aggregated structures. This transition may reflect a change in the tertiary structure of the protein. However, the final transition, which occurs at a higher temperature (52-59 degrees C), reflects unfolding and aggregation of the polypeptide chains. The Fourier transform infrared (FTIR) analysis suggests that PCS has a thermolabile region that unfolds first, some 7 degrees C below the main unfolding of the protein. We propose that this reflects the unfolding of the highly flexible loop segments, which in turn triggers the unfolding of the predominantly helical core structure of PCS.

Animals↗

PubMed2003

Neuro-fuzzy structural classification of proteins for improved protein secondary structure prediction.

Fourier transform infrared (FTIR) spectroscopy is a very flexible technique for characterization of protein secondary structure. Measurements can be carried out rapidly in a number of different environments based on only small quantities of proteins. For this technique to become more widely used for protein secondary structure characterization, however, further developments in methods to accurately quantify protein secondary structure are necessary. Here we propose a structural classification of proteins (SCOP) class specialized neural networks architecture combining an adaptive neuro-fuzzy inference system (ANFIS) with SCOP class specialized backpropagation neural networks for improved protein secondary structure prediction. Our study shows that proteins can be accurately classified into two main classes "all alpha proteins" and "all beta proteins" merely based on the amide I band maximum position of their FTIR spectra. ANFIS is employed to perform the classification task to demonstrate the potential of this architecture with moderately complex problems. Based on studies using a reference set of 17 proteins and an evaluation set of 4 proteins, improved predictions were achieved compared to a conventional neural network approach, where structure specialized neural networks are trained based on protein spectra of both "all alpha" and "all beta" proteins. The standard errors of prediction (SEPs) in % structure were improved by 4.05% for helix structure, by 5.91% for sheet structure, by 2.68% for turn structure, and by 2.15% for bend structure. For other structure, an increase of SEP by 2.43% was observed. Those results were confirmed by a "leave-one-out" run with the combined set of 21 FTIR spectra of proteins.

Fuzzy Logic↗

PubMed2002

Copper-induced conformational change in a marsupial prion protein repeat peptide probed using FTIR spectroscopy.

We report the first Fourier transform infrared analysis of prion protein (PrP) repeats and the first study of PrP repeats of marsupial origin. Large changes in the secondary structure and an increase in hydrogen bonding within the peptide groups were evident from a red shift of the amide I band by >7 cm(-1) and an approximately five-fold reduction in amide hydrogen-deuterium exchange for peptide interacting with Cu(2+) ions. Changes in the tertiary structure upon copper binding were also evident from the appearance of a new band at 1564 cm(-1), which arises from the ring vibration of histidine. The copper-induced conformational change is pH dependent, and occurs at pH >7.

Animals↗

PubMed2002

Automatic amide I frequency selection for rapid quantification of protein secondary structure from Fourier transform infrared spectra of proteins.

Here we report the development of a new neural network based approach for rapid quantification of protein secondary structure from Fourier transform infrared (FTIR) spectra of proteins. A technique for efficiently reducing the amount of spectral data by almost 90% is suggested to facilitate faster neural network analysis. Additionally, an automatic procedure is introduced for selecting only those regions within the amide I band of protein FTIR spectra, which can be best related to secondary structure contents by subsequent neural network analysis. Based on a given reference set of FTIR spectra from proteins with known secondary structure, a subset of merely 29 out of 101 amide I absorbance values could be identified, which lead to an improved prediction accuracy. The average prediction accuracy achieved for helix, sheet, turn, bend, and other is 4.96% which is better than that achieved by alternative methods that have been previously reported indicating the significant potential of this approach. Our suggested automatic amide I frequency selection procedure may be easily extended to identify promising regions from spectral data recorded by other spectroscopic techniques, like for example circular dichroism spectroscopy.

Algorithms↗

PubMed2002

Three-dimensional structure of the S4-S5 segment of the Shaker potassium channel.

The propagation of action potentials during neuronal signal transduction in phospholipid membranes is mediated by ion channels, a diverse group of membrane proteins. The S4-S5 linker peptide (S4-S5), that connects the S4 and S5 transmembrane segments of voltage-gated potassium channels is an important region of the Shaker ion-channel protein. Despite its importance, very little is known about its structure. Here we provide evidence for an amphipathic alpha-helical conformation of a synthetic S4-S5 peptide of the voltage-gated Drosophila melanogaster Shaker potassium channel in water/trifluoroethanol and in aqueous phospholipid micelles. The three-dimensional solution structures of the S4-S5 peptide were obtained by high-resolution nuclear magnetic resonance spectroscopy and distance-geometry/simulated-annealing calculations. The detailed structural features are discussed with respect to model studies and available mutagenesis data on the mechanism and selectivity of the potassium channel.

Amino Acid Sequence↗