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PubMed2002

Rapid protein domain assignment from amino acid sequence using predicted secondary structure.

The elucidation of the domain content of a given protein sequence in the absence of determined structure or significant sequence homology to known domains is an important problem in structural biology. Here we address how successfully the delineation of continuous domains can be accomplished in the absence of sequence homology using simple baseline methods, an existing prediction algorithm (Domain Guess by Size), and a newly developed method (DomSSEA). The study was undertaken with a view to measuring the usefulness of these prediction methods in terms of their application to fully automatic domain assignment. Thus, the sensitivity of each domain assignment method was measured by calculating the number of correctly assigned top scoring predictions. We have implemented a new continuous domain identification method using the alignment of predicted secondary structures of target sequences against observed secondary structures of chains with known domain boundaries as assigned by Class Architecture Topology Homology (CATH). Taking top predictions only, the success rate of the method in correctly assigning domain number to the representative chain set is 73.3%. The top prediction for domain number and location of domain boundaries was correct for 24% of the multidomain set (+/-20 residues). These results have been put into context in relation to the results obtained from the other prediction methods assessed.

Amino Acid Sequence↗
PubMed2003

Weighted geometric docking: incorporating external information in the rotation-translation scan.

Weighted geometric docking is a prediction algorithm that matches weighted molecular surfaces. Each molecule is represented by a grid of complex numbers, storing information about the shape of the molecule in the real part and weight information in the imaginary part. The weights are based on experimental biochemical and biophysical data or on theoretical analyses of amino acid conservation or correlation patterns in multiple-sequence alignments of homologous proteins. Only a few surface residues on either one or both molecules are weighted. In contrast to methods that use postscan filtering based on biochemical information, our method incorporates the external data in the rotation-translation search, producing a different set of docking solutions biased toward solutions in which the up-weighted residues are at the interface. Similarly, interactions involving specified residues can be impeded. The weighted geometric algorithm was applied to five systems for which regular geometric docking of the unbound molecules gave poor results. We obtained much better ranking of the nearly correct prediction and higher statistical significance when weighted geometric docking was used. The method was successful even when the weighted portion of the surface corresponded only partially and approximately to the binding site.

Algorithms↗
PubMedDate not supplied

Data predictability for compression of digital fluorography images.

Images obtained by digital fluorography were checked for compressability. These images include images of coronary vessels and images of peripheral vessels. These images have a very low signal-to-noise ratio compared to the optical images usually used for developing compression methods. Configurational entropy was used to represent the information content of these images. Reversible prediction algorithms were extensively checked in a search for minimal residual information, enabling more efficient reversible compression. Optimal results were obtained for algorithms based on two or three neighboring pixels and a semiempirical rule, based on the noise level, was found which decides on the best approach. It was found that raw data images are more predictable than subtracted images although the latter are visually preferred.

Algorithms↗
PubMed2006

On-line adaptive algorithm with glucose prediction capacity for subcutaneous closed loop control of glucose: evaluation under fasting conditions in patients with Type 1 diabetes.

AIMS: To evaluate an algorithm with glucose prediction capacity and continuous adaptation of patient parameters-a model predictive control (MPC) algorithm-to control blood glucose concentration during fasting conditions in patients with Type 1 diabetes. In the subcutaneous (sc) route within a closed loop system. METHODS: Paired experiments were performed in six patients. Over 8 h the MPC algorithm was used to control glucose with s.c. insulin administration and two different glucose monitoring protocols: first, the algorithm was provided with intravenous (i.v.) glucose values for insulin dosage calculation directly (i.v.-s.c. route). Then, in the second experiment, i.v. glucose values were fed to the MPC with a delay of 30 min to simulate s.c. glucose measurements ('s.c.'-s.c. route). In both experiments plasma glucose, insulin dosage, and serum insulin levels were analysed. RESULTS: Glucose concentration was brought from hyper- to normoglycaemia and kept in the physiological range (6-7 mmol/l) with both routes in all subjects. Mean glucose concentration reached the threshold of 7 mmol/l approximately 2 (i.v.-s.c. route) and 3 ('s.c.'-s.c. route) hours after the start of glucose control with the MPC. During the last 2 h of automated glucose control, mean glucose concentration was 6.3 +/- 0.2 mmol/l and 6.6 +/- 0.3 mmol/l for i.v.-s.c. and 's.c.'-s.c. route, respectively. Glucose concentration, insulin doses, and serum insulin levels did not differ significantly between routes (P > 0.05). CONCLUSIONS: The MPC algorithm is suitable for glucose control during fasting within an extracorporeal artificial beta-cell in the subcutaneous route Type 1 diabetic patients.

Administration, Cutaneous↗
PubMed1999

Comparison of clinical staging algorithms and 111indium-capromab pendetide immunoscintigraphy in the prediction of lymph node involvement in high risk prostate carcinoma patients.

BACKGROUND: The pretherapy prediction of occult lymph node involvement and the avoidance of otherwise futile and potentially morbid definitive local therapy is paramount in men with newly diagnosed prostate carcinoma. To identify patients with prostate carcinoma who likely have lymph node involvement and would benefit from staging lymphadenectomy prior to definitive local therapy, the authors compared the ability of several predictive staging algorithms and a radiolabeled monoclonal antibody scan to predict lymphatic metastases prior to treatment. METHODS: Between August 1991 and June 1994, 198 men with clinical T2 or T3 classified (TNM) prostate carcinoma (bone scan negative) who were at high risk of lymph node involvement underwent a 111In-capromab pendetide scan prior to staging lymphadenectomy. Several predictive models based on preoperative prostate specific antigen level, biopsy Gleason score, and clinical stage were selected to predict those men having a > or =20% probability of lymph node involvement. The ability to predict pathologic stage using several clinical algorithms and the monoclonal antibody scan was compared with pathologic examination of the lymph nodes. RESULTS: Overall, 39% of the pelvic lymph node specimens were positive for metastatic disease by pathologic analysis. Published algorithms predicting lymph node metastases had a positive predictive value (PPV) ranging from 40.5% to 46.6% and an area under the receiver operating characteristic curve (AUC) ranging from 0.52 to 0.61. The monoclonal antibody scan had a PPV of 66.7% and an AUC of 0.71. The differences between the PPV and the AUC for the individual clinical algorithms when compared with immunoscintigraphy were statistically significant. Combining the radiolabeled monoclonal antibody scan with clinical predictive models, a PPV of up to 72.1% could be obtained. CONCLUSIONS: These data suggest that the PPVs for the clinical predictive algorithms are similar and that the PPV of the radiolabeled monoclonal antibody scan alone or in combination with the algorithms has additional value in predicting lymph node involvement in prostate carcinoma patients at high risk of regional disease spread. These algorithms and the 111In-capromab pendetide scan may be used for the appropriate selection of candidates for definitive local therapy in men with clinically localized prostate carcinoma and significant risk of lymph node involvement.

Aged↗
PubMed1997

Predicting protein secondary structure with probabilistic schemata of evolutionarily derived information.

We demonstrate the applicability of our previously developed Bayesian probabilistic approach for predicting residue solvent accessibility to the problem of predicting secondary structure. Using only single-sequence data, this method achieves a three-state accuracy of 67% over a database of 473 non-homologous proteins. This approach is more amenable to inspection and less likely to overlearn specifics of a dataset than "black box" methods such as neural networks. It is also conceptually simpler and less computationally costly. We also introduce a novel method for representing and incorporating multiple-sequence alignment information within the prediction algorithm, achieving 72% accuracy over a dataset of 304 non-homologous proteins. This is accomplished by creating a statistical model of the evolutionarily derived correlations between patterns of amino acid substitution and local protein structure. This model consists of parameter vectors, termed "substitution schemata," which probabilistically encode the structure-based heterogeneity in the distributions of amino acid substitutions found in alignments of homologous proteins. The model is optimized for structure prediction by maximizing the mutual information between the set of schemata and the database of secondary structures. Unlike "expert heuristic" methods, this approach has been demonstrated to work well over large datasets. Unlike the opaque neural network algorithms, this approach is physicochemically intelligible. Moreover, the model optimization procedure, the formalism for predicting one-dimensional structural features and our previously developed method for tertiary structure recognition all share a common Bayesian probabilistic basis. This consistency starkly contrasts with the hybrid and ad hoc nature of methods that have dominated this field in recent years.

Algorithms↗
PubMed1995

Evolutionary conservation of both the hydrophilic and hydrophobic nature of transmembrane residues.

An algorithm (HRG), developed to allow the pairwise comparisons of the aligned residues of several members of large gene families of polytopic integral membrane proteins is described. Using hydrophobicity scales, application of this algorithm allows the number and size of the membrane-spanning domains of bacteriorhodopsin, a polytopic protein whose structure has been partially determined, to be predicted with a high degree of accuracy (sensitivity 94%, specificity 82% for predicting the membrane embedded or extramembranous location of residues). As opposed to previously reported structure-prediction algorithms, delineation of putative transmembrane segments from connecting loops is also more clearly evident with the application of the HRG algorithm, even with proteins from widely divergent species. This indicates strong evolutionary pressure for the conservation of both the hydrophobic and hydrophilic character of residues in membrane-embedded regions of polytopic proteins, such as those of the G-protein-coupled receptor superfamily. These and other structural and functional implications evident from the application of the HRG algorithm are considered.

Algorithms↗
PubMed1991

Molecular design and modeling of protein-heparin interactions.

The methods and approaches taken to investigate heparin-apoE peptide interactions have involved a series of steps, including (1) identification of the heparin-binding domains of apoE, (2) determination of the minimal amino acid sequence regions involved in heparin binding, heparin-induced conformational changes, and stability of apoE peptide structures in solution, (3) modeling of these peptide and oligosaccharide structures, and (4) examination of their behavior during molecular dynamics calculations to determine if the modeled complexes simulate the results of the solution study. The heparin-binding regions of apoE were determined by fragmentation of the protein and identification of the heparin-binding fragments by ligand-blotting procedures using 125I-labeled heparin. Studies with synthetic peptide fragments of various lengths and dot-blot procedures with 125I-labeled heparin identified the minimal residues critical for heparin-binding and CD studies established the prominent secondary structures of these domains. These studies also showed that heparin binds to the apoE(211-243) and apoE(129-169) regions to induce and stabilize beta-strand and alpha-helical peptide conformations. Secondary structure algorithms were used to identify the specific residues with the highest probabilities of forming alpha-helix and beta-strand structures. Based on the predictive algorithms, the apoE(211-234) and apoE(129-159) structures were built using the Insight program and their molecular interactions with various heparin oligosaccharide models were investigated by molecular dynamics. In agreement with the solution studies in the presence of salt, the molecular dynamics studies showed that the oligosaccharides stabilized the beta-strand and alpha-helical peptide configurations against simulated thermal denaturations. Further modeling studies are in progress to examine the mechanism of the heparin-induced increase in ordered structure of these peptides.

Algorithms↗
PubMed2003

CD4(+) T cells from healthy subjects and colon cancer patients recognize a carcinoembryonic antigen-specific immunodominant epitope.

The carcinoembryonic antigen (CEA) is an attractive target for immunotherapeutic purposes because of its expression profile, its role in tumor progression, and its immunogenicity. However, CEA belongs to the CD66 immunoglobulin super-gene family that comprises highly homologous molecules expressed on leukocytes, making CEA a potential autoantigen expressed on hematopoietic cells. We used a MHC class II epitope prediction algorithm (TEPITOPE) to select 11 sequence segments of CEA that could form promiscuous CD4(+) T-cell epitopes and used synthetic peptides corresponding to the predicted sequences to propagate in vitro CD4(+) T cells from healthy donors and colon cancer patients. CD4(+) T cells from all subjects strongly recognized the sequence segment (LWWVNNQSLPVSP), repeated at residues 177-189 and 355-367. Importantly, we demonstrated that this highly immunodominant region contains a naturally processed epitope(s). Cross-recognition experiments with peptide analogues present on the CD66 homologous proteins showed that CEA(177-189/355-367)-specific CD4(+) T cells did not recognize the analogues, demonstrating that recognition of the immunodominant epitope is CEA specific. These data suggest that the repertoire of CEA(177-189/355-367)-specific CD4(+) T cells might have been shaped by a selective process to exclude CD4(+) T cells specific for CD66 homologues expressed on leukocyte, while preserving the CEA-specific repertoire. The features of strong immunogenicity and immunodominance in the absence of potential induction of autoimmunity make the identified CEA epitope of particular interest for the development of antitumor vaccines.

Alleles↗
PubMed2001

An algorithm for modifying neurotransmitter release probability based on pre- and postsynaptic spike timing.

The precise times of occurrence of individual pre- and postsynaptic action potentials are known to play a key role in the modification of synaptic efficacy. Based on stimulation protocols of two synaptically connected neurons, we infer an algorithm that reproduces the experimental data by modifying the probability of vesicle discharge as a function of the relative timing of spikes in the pre- and postsynaptic neurons. The primary feature of this algorithm is an asymmetry with respect to the direction of synaptic modification depending on whether the presynaptic spikes precede or follow the postsynaptic spike. Specifically, if the presynaptic spike occurs up to 50 ms before the postsynaptic spike, the probability of vesicle discharge is upregulated, while the probability of vesicle discharge is downregulated if the presynaptic spike occurs up to 50 ms after the postsynaptic spike. When neurons fire irregularly with Poisson spike trains at constant mean firing rates, the probability of vesicle discharge converges toward a characteristic value determined by the pre- and postsynaptic firing rates. On the other hand, if the mean rates of the Poisson spike trains slowly change with time, our algorithm predicts modifications in the probability of release that generalize Hebbian and Bienenstock-Cooper-Munro rules. We conclude that the proposed spike-based synaptic learning algorithm provides a general framework for regulating neurotransmitter release probability.

Action Potentials↗
PubMed2026

Tackling non-canonical splicing in arrhythmogenic cardiomyopathy to reduce the uncertain significance variants burden.

BACKGROUND: Splice-altering variants (SAVs), particularly those outside canonical splice sites, are an underappreciated contributor to inherited cardiovascular diseases. In arrhythmogenic cardiomyopathy (ACM), these variants frequently remain classified as of uncertain significance (VUS) due to limited predictive power and lack of transcript-level evidence, constraining genetic yield and clinical management. Our study aimed to determine the functional impact of SAVs in ACM genes and refine their classification using ACMG/AMP and ClinGen SVI criteria. METHODS: SAVs identified in 200 ACM probands underwent SpliceAI prediction, GTEx cardiac exon-usage annotation, and functional assessment using pSPL3-based minigene assays. Aberrant transcripts were quantified using Percent Splicing Alteration (PSA). Segregation data and ACMG/AMP criteria refined by ClinGen SVI were applied to integrate functional and clinical evidence for classification. RESULTS: Aberrant splicing was confirmed in 9/20 variants (45%), including synonymous, missense, and non-canonical intronic changes. SpliceAI scores correlated strongly with PSA values (R²=0.86). Case-control burden testing revealed significant enrichment of splice-altering variants in DSP, DSG2, DSC2 and FLNC. Integrating predictive algorithms with experimental validation and segregation analysis markedly enhances reclassification of 16/20 variants (80%). CONCLUSION: Splicing defects beyond canonical sites significantly shape ACM genetic landscape. Integrating predictive models with experimental validation clarifies uncertain variants bridging the gap between genomic uncertainty and clinical decision-making.

Humans↗
PubMedDate not supplied

Semiautomatic algorithm to remove resonance artifacts from the direct radial artery pressure.

Resonance artifacts introduced by the catheter-manometer system are removed from the direct radial artery pressure using a three-step algorithm. First, the fast-flush method is used to identify the natural frequency and damping coefficient of the monitoring system by digitizing and analyzing the pressure transient created by the flush. Second, resistor, capacitor, and inductor values are found for an RLC second-order model of the catheter-manometer system in use. Third, the algorithm predicts the undistorted radial artery pressure, removing the resonance artifacts by inverse-filtering the digitized monitored pressure waveform using the RLC circuit derived previously. The algorithm was implemented using a personal computer, but it could also be used without the computer by incorporating an analog-to-digital convertor and a microprocessor in the hemodynamic monitor.

Algorithms↗
PubMed2001

Usefulness of the Framingham risk score and body mass index to predict early coronary artery calcium in young adults (Muscatine Study).

The value of a coronary artery disease prediction algorithm, the Framingham risk score (score), for detecting coronary artery calcium (CAC) was examined in 385 men and 472 women, aged 29 to 43 years. Scores were compared in subjects with and without CAC and were also used to predict presence of CAC. Receiver-operating characteristic curves were computed to compare different prediction models. The score model was compared with age only, natural logarithm of body mass index (lnBMI) only, and score plus lnBMI models. CAC was detected in 30% of men and 16% of women. The mean score was significantly higher in men and women with CAC. For every 2-point increase in the score, the odds of CAC increased by 30% in women and 20% in men. Significant associations between CAC status and risk factors were observed for age in women, and high- density lipoprotein cholesterol and blood pressure in men and women. The area under the receiver-operating characteristic curve for the score was 0.67 and 0.57 for women and men, respectively. When lnBMI was added to the score model, the area increased to 0.76 in women (lnBMI p <0.0001, score p <0.005). For men, the area increased from 0.57 to 0.67, and the score was no longer significant (p >0.60) in the model with lnBMI (p <0.0001). Score predicts CAC in asymptomatic young adults. Inclusion of lnBMI in the score model adds significantly to the prediction of CAC in women and men. The lnBMI model has a greater predictive value than the score in this young population.

Adult↗
PubMed1987

Studies of frequently recurring substructures in human alpha-like globin mRNA precursors.

In general, the results obtained from secondary structure prediction algorithms are often inconsistent with those obtained experimentally. The reason for this disagreement is that the experimentally determined structures have higher free energies (as judged by the currently used "energy rules") than the predicted ones. To overcome this limitation we have developed a new approach which incorporates the frequencies of occurrence of substructures in the growing mRNA chain. This has been accomplished by simulating the folding process of pre-mRNAs. Using this approach we have significantly improved current helical structural prediction for 142 analyzed tRNAs and 16 S rRNA. We have next applied this method to the human alpha-like globins. Comparison of the structures obtained by running the currently used algorithms with those computed by the new method indicates that the final most stable secondary structure contains some infrequently occurring substructures. In addition, some of the frequently recurring substructures are not included in the final structure. Comparison of the simulated folding processes of the human alpha-like globin pre-mRNAs reveals some conserved helices and hairpin loop structures in those frequently recurring substructures. Among these several compensating base changes (transitions and transversions) have been identified.

Algorithms↗
PubMed2005

Membrane topology of human ABC proteins.

In this review, we summarize the currently available information on the membrane topology of some key members of the human ABC protein subfamilies, and present the predicted domain arrangements. In the lack of high-resolution structures for eukaryotic ABC transporters this topology is based only on prediction algorithms and biochemical data for the location of various segments of the polypeptide chain, relative to the membrane. We suggest that topology models generated by the available prediction methods should only be used as guidelines to provide a basis of experimental strategies for the elucidation of the membrane topology.

ATP-Binding Cassette Transporters↗
PubMed1995

Interspike interval embedding of chaotic signals.

According to a theorem of Takens [Lecture Notes in Mathematics (Springer-Verlag, Berlin, 1981), Vol. 898], dynamical state information can be reproduced from a time series of amplitude measurements. In this paper we investigate whether the same information can be reproduced from interspike interval (ISI) measurements. Assuming an integrate-and-fire model coupling the dynamical system to the spike train, there is a one-to-one correspondence between the system states and interspike interval vectors of sufficiently large dimension. The correspondence implies in particular that a data series of interspike intervals, formed in this manner, can be forecast from past history. This capability is demonstrated using a nonlinear prediction algorithm, and is found to be robust to noise. A set of interspike intervals measured from a simple neuronal circuit is studied for deterministic structure using a prediction error statistic. (c) 1995 American Institute of Physics.

Journal Article↗
PubMed2005

Monte Carlo simulations of a nozzle for the treatment of ocular tumours with high-energy proton beams.

By the end of 2002, 33 398 patients worldwide had been treated with proton radiotherapy, 10 829 for eye diseases. The dose prediction algorithms used today for ocular proton therapy treatment planning rely on parameterizations of measured proton dose distributions, i.e., broad-beam and pencil-beam techniques, whose predictive capabilities are inherently limited by severe approximations and simplifications in modelling the radiation transport physics. In contrast, the Monte Carlo radiation transport technique can, in principle, provide accurate predictions of the proton treatment beams by taking into account all the physical processes involved, including coulombic energy loss, energy straggling, multiple Coulomb scattering, elastic and nonelastic nuclear interactions, and the transport of secondary particles. It has not been shown, however, whether it is possible to commission a proton treatment planning system by using data exclusively from Monte Carlo simulations of the treatment apparatus and a phantom. In this work, we made benchmark comparisons between Monte Carlo predictions and measurements of an ocular proton treatment beamline. The maximum differences between absorbed dose profiles from simulations and measurements were 6% and 0.6 mm, while typical differences were less than 2% and 0.2 mm. The computation time for the entire virtual commissioning process is less than one day. The study revealed that, after a significant development effort, a Monte Carlo model of a proton therapy apparatus is sufficiently accurate and fast for commissioning a treatment planning system.

Computer Simulation↗
PubMed2000

Estimating the significance of sequence order in protein secondary structure and prediction.

MOTIVATION: How critical is the sequence order information in predicting protein secondary structure segments? We tried to get a rough insight on it from a theoretical approach using both a prediction algorithm and structural fragments from Protein Databank (PDB). RESULTS: Using reverse protein sequences and PDB structural fragments, we theoretically estimated the significance of the order for protein secondary structure and prediction. On average: (1) 79% of protein sequence segments resulted in the same prediction in both normal and reverse directions, which indicated a relatively high conservation of secondary structure propensity in the reverse direction; (2) the reversed sequence prediction alone performed less accurately than the normal forward sequence prediction, but comparably high (2% difference); (3) the commonly predicted regions showed a slightly higher prediction accuracy (4%) than the normal sequences prediction; and (4) structural fragments which have counterparts in reverse direction in the same protein showed a comparable degree of secondary structure conservation (73% identity with reversed structures on average for pentamers). CONTACT: jong@biosophy.org; dietmann@ebi.ac.uk; heger@ebi.ac.uk; holm@ebi.ac.uk

Algorithms↗