Better prediction of protein contact number using a support vector regression analysis of amino acid sequence

Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

The NASCAR phenomenon: Auto racing sponsorships and shareholder wealth

This study presents the first analysis of the impact of NASCAR sponsorship announcements on the stock prices of sponsoring firms. The primary finding of the study-that NASCAR sponsorship announcements were accompanied by the largest increases in shareholder wealth ever recorded in the marketing literature in response to a voluntary marketing program-represents a striking and unambiguous stock market endorsement of the sponsorships. Indeed, the 24 sponsors analyzed in this study experienced mean increases in shareholder wealth of over $300 million dollars, net of all of the costs associated with the sponsorships. A multiple regression analysis of firm-specific stock price changes and select corporate and sponsorship attributes indicates that NASCAR sponsorships with more successful racing teams, corporate (as opposed to product or divisional) sponsorships, and sponsorships with direct ties to the consumer automotive industry are all positively correlated with perceived sponsorship success, while corporate cash flow per share (a well-known proxy for agency conflicts within the firm) is negatively related with shareholder approval.

Modifying insect population age structure to control vector-borne disease

Age is a critical determinant of the ability of most arthropod vectors to transmit a range of human pathogens. This is due to the fact that most pathogens require a period of extrinsic incubation in the arthropod host before pathogen transmission can occur. This developmental period for the pathogen often comprises a significant proportion of the expected lifespan of the vector. As such, only a small proportion of the population that is oldest contributes to pathogen transmission. Given this, strategies that target vector age would be expected to obtain the most significant reductions in the capacity of a vector population to transmit disease. The recent identification of biological agents that shorten vector lifespan, such as Wolbachia, entomopathogenic fungi and densoviruses, offer new tools for the control of vector-borne diseases. Evaluation of the efficacy of these strategies under field conditions will be possible due to recent advances in insect age-grading techniques. Implementation of all of these strategies will require extensive field evaluation and consideration of the selective pressures that reductions in vector longevity may induce on both vector and pathogen.

Evidence of a spotted fever-like rickettsia and a potential new vector from northeastern Australia

A spotted fever-like rickettsia was identified in a Hemaphysalis tick by polymerase chain reaction (PCR) amplification and sequencing of the 16S rDNA, ompA, and ompB genes. A comparison of these nucleotide sequences with those of other spotted fever group (SFG) rickettsiae revealed that the Hemaphysalis tick rickettsia was distinct from other previously reported strains. Phylogenetic analysis based on both ompA and ompB also indicates that the strain’s closest relatives are the agents of Thai tick typhus (Rickettsia honei strain TT-118) and Flinders Island spotted fever (R. honei). This study represents the first report of an R. honei-like agent from a Hemaphysalis tick in Australia and of a spotted fever group rickettsia from Cape York Peninsula, Queensland.

Field prevalence of Wolbachia in the mosquito vector Aedes albopictus

The endosymbiotic bacteria in the genus Wolbachia have been proposed as a potential candidate to deliver pathogen-blocking genes into natural populations of medically important insects. The successful application of Wolbachia in insect vector control depends on the ability of the agent to successfully invade and maintain itself at high frequency under field conditions. Here, we evaluated the prevalence of Wolbachia infections in a field population of the Wolbachia-superinfected mosquito Aedes albopictus. A field prevalence of 100% (n = 1,016) was found in a single population in eastern Thailand via polymerase chain reaction (PCR) testing of Wolbachia both from individual parent females and their corresponding F1 offspring. This is the first report of accurate Wolbachia prevalence in a field population of an insect disease vector. The prevalence of superinfection was estimated to be 99.41%. All single-infected individual mosquitoes (n = 6) were found to harbor group A Wolbachia. For this particular population, none was found to be single-infected with group B Wolbachia. Our results also show that PCR testing of field materials alone without checking F1 offspring overestimated the natural prevalence of single infection. Thus, the confirmation of infection status by means of F1 offspring was critical to the accurate estimates of Wolbachia prevalence under field conditions.

Prospects for control of African trypanosomiasis by tsetse vector manipulation

The extensive antigenic variation phenomena African trypanosomes display in their mammalian host have hampered efforts to develop effective vaccines against trypanosomiasis. Human disease management aims largely to treat infected hosts by chemotherapy, whereas control of animal diseases relies on reducing tsetse populations as well as on drug therapy. The control strategies for animal diseases are carried out and financed by livestock owners, who have an obvious economic incentive. Sustaining largely insecticide-based control at a local level and relying on drugs for treatment of infected hosts for a disease for which there is no evidence of acquired immunity could prove extremely costly in the long run. It is more likely that a combination of several methods in an integrated, phased and area-wide approach would be more effective in controlling these diseases and subsequently improving agricultural output. New approaches that are environmentally acceptable, efficacious and affordable are clearly desirable for control of various medically and agriculturally important insects including tsetse. Here, Serap Aksoy and colleagues discuss molecular genetic approaches to modulate tsetse vector competence.

Semliki Forest virus as an expression vector in insect cell lines

Studies were undertaken to determine if replication-deficient Semliki Forest virus expression vectors could be successfully used to express foreign gene constructs in insect cell lines. Using green fluorescent protein (GFP) as a marker we recorded infection levels of nearly 100% in the Aedes albopictus cell lines C6/36 and Aa23T, as well as in the Ae. aegypti cell line MOS20. The virus was capable of infecting an Anopheles gambiae cell line MOS55. The amount of GFP protein produced in each cell line was quantified. Northern analysis of viral transcription revealed the presence of novel transcripts in Aa23T, C6/36, and MOS55 cell lines, but not in the BHK or MOS20. The initial characterization of these transcripts is described.

Control of vector-borne disease by genetic manipulation of insect populations: technological requirements and research priorities

The possibility of controlling vector-borne disease through the development and release of transgenic insect vectors has recently gained popular support and is being actively pursued by a number of research laboratories around the world. Several technical problems must be solved before such a strategy could be implemented: genes encoding refractory traits (traits that render the insect unable to transmit the pathogen) must be identified, a transformation system for important vector species has to be developed, and a strategy to spread the refractory trait into natural vector populations must be designed. Recent advances in this field of research make it seem likely that this technology will be available in the near future. In this paper we review recent progress in this area as well as argue that care should be taken in selecting the most appropriate disease system with which to first attempt this form of intervention. Much attention is currently being given to the application of this technology to the control of malaria, transmitted by Anopheles gambiae in Africa. While malaria is undoubtedly the most important vector-borne disease in the world and its control should remain an important goal, we maintain that the complex epidemiology of malaria together with the intense transmission rates in Africa may make it unsuitable for the first application of this technology. Diseases such as African trypanosomiasis, transmitted by the tsetse fly, or unstable malaria in India may provide more appropriate initial targets to evaluate the potential of this form of intervention.

Modification of arthropod vector competence via symbiotic bacteria

Some of the world's most devastating diseases are transmitted by arthropod vectors. Attempts to control these arthropods are currently being challenged by the widespread appearance of insecticide resistance. It is therefore desirable to develop alternative strategies to complement existing methods of vector control. In this review, Charles Beard, Scott O'Neill, Robert Tesh, Frank Richards and Serap Aksoy present an approach for introducing foreign genes into insects in order to confer refractoriness to vector populations, ie. the inability to transmit disease-causing agents. This approach aims to express foreign anti-parasitic or anti-viral gene products in symbiotic bacteria harbored by insects. The potential use of naturally occurring symbiont-based mechanisms in the spread of such refractory phenotypes is also discussed.

Predicting sprint running times from isokinetic and squat lift tests: A regression analysis

This study examined the relationship between isokinetic hip extensor/hip flexor strength, 1-RM squat strength, and sprint running performance for both a sprint-trained and non-sprint-trained group. Eleven male sprinters and 8 male controls volunteered for the study. On the same day subjects ran 20-m sprints from both a stationary start and with a 50-m acceleration distance, completed isokinetic hip extension/flexion exercises at 1.05, 4.74, and 8.42 rad.s(-1), and had their squat strength estimated. Stepwise multiple regression analysis showed that equations for predicting both 20-m maximum velocity nm time and 20-m acceleration time may be calculated with an error of less than 0.05 sec using only isokinetic and squat strength data. However, a single regression equation for predicting both 20-m acceleration and maximum velocity run times from isokinetic or squat tests was not found. The regression analysis indicated that hip flexor strength at all test velocities was a better predictor of sprint running performance than hip extensor strength.

Optimising fed-batch production of recombinant proteins using the baculovirus expression vector system

Fed-batch culture can offer significant improvement in recombinant protein production compared to batch culture in the baculovirus expression vector system (BEVS), as shown by Nguyen et al. (1993) and Bedard et al. (1994) among others. However, a thorough analysis of fed-batch culture to determine its limits in improving recombinant protein production over batch culture has yet to be performed. In this work, this issue is addressed by the optimisation of single-addition fed-batch culture. This type of fed-batch culture involves the manual addition of a multi-component nutrient feed to batch culture before infection with the baculovirus. The nutrient feed consists of yeastolate ultrafiltrate, lipids, amino acids, vitamins, trace elements, and glucose, which were added to batch cultures of Spodoptera frugiperda (Sf9) cells before infection with a recombinant Autographa californica nuclear polyhedrosis virus (Ac-NPV) expressing beta-galactosidase (beta-Gal). The fed-batch production of beta-Gal was optimised using response surface methods (RSM). The optimisation was performed in two stages, starting with a screening procedure to determine the most important variables and ending with a central-composite experiment to obtain a response surface model of volumetric beta-Gal production. The predicted optimum volumetric yield of beta-Gal in fed-batch culture was 2.4-fold that of the best yields in batch culture. This result was confirmed by a statistical analysis of the best fed-batch and batch data (with average beta-Gal yields of 1.2 and 0.5 g/L, respectively) obtained from this laboratory. The response surface model generated can be used to design a more economical fed-batch operation, in which nutrient feed volumes are minimised while maintaining acceptable improvements in beta-Gal yield. (C) 1998 John Wiley & Sons, Inc.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

Gene transfer and expression of a non-viral polycation-based vector in CD4(+) cells

CD4-selective targeting of an antibody-polycation-DNA complex was investigated The complex was synthesized with the anti-CD4 monoclonal antibody B-F5, polylysine(268) (pLL) and either the pGL3 control vector containing the luciferase reporter gene or the pGeneGrip vector containing the green fluorescent protein (GFP) gene. B-F5-pLL-DNA complexes inhibited the binding of I-125-B-F5 to CD4(+) Jurkat cells, while complexes synthesised either without B-F5 or using a non-specific mouse IgG1 antibody had little or no effect Expression of the luciferase reporter gene was achieved in Jurkat cells using the B-F5-pLL-pGL3 complex and was enhanced in the presence of PMA. Negligible luciferase activity was defected with the non-specific antibody complex in Jurkat cells or with the B-F5-pLL-pGL3 complex in the CD4(-) K-562 cells. Using complexes synthesised with the pGeneGrip vector, the transfection efficiency in Jurkat and K-562 cells was examined using confocal microscopy. More than 95% of Jurkat cells expressed GFP and the level of this expression was markedly enhanced by PMA. Negligible GFP expression was seen in K-562 cells or when B-F5 was replaced by a nonspecific antibody. Using flow cytometry, fluorescein-labelled complex showed specific targeting to CD4(+) cells in a mixed cell population from human peripheral blood. These studies demonstrate the selective transfection of CD4(+) T-lymphoid cells using a polycation-based gene delivery system. The complex may provide a means of delivering anti-HIV gene therapies to CD4(+) cells in vivo.

Computational chemistry on Fujitsu vector-parallel processors: Development and performance of applications software

In this and a preceding paper, we provide an introduction to the Fujitsu VPP range of vector-parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the implementation and performance of seven popular chemistry application packages. The codes discussed range from classical molecular dynamics to semiempirical and ab initio quantum chemistry. All have evolved from sequential codes, and have typically been parallelised using a replicated data approach. As such they are well suited to the large-memory/fast-processor architecture of the VPP. For one code, CASTEP, a distributed-memory data-driven parallelisation scheme is presented. (C) 2000 Published by Elsevier Science B.V. All rights reserved.