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Daniel Hoffmann

Publications and source records attributed to Daniel Hoffmann.

17 recordsLinked to original sources
PubMed2006

SearchXLinks. A program for the identification of disulfide bonds in proteins from mass spectra.

We present the computer program SearchXLinks that analyzes mass spectra with the aim of identifying disulfide bonds and other modifications in proteins of known amino acid sequence. Disulfide bonds can be intra- or intermolecular. To decrease the number of false positives, the analysis of in-source decay and tandem mass spectra are coupled into the program. The steps taken during a SearchXLinks run are outlined, and the computational costs are discussed. The application of the program is illustrated by the analysis of data from recent studies on bovine ribonuclease A and bovine serum albumin. The software can be used free of charge on the Internet at http://www.searchxlinks.de.

Amino Acid Sequence↗
PubMed2006

The enzyme-binding region of human GM2-activator protein.

The GM2-activator protein (GM2AP) is an essential cofactor for the lysosomal degradation of ganglioside GM2 by beta-hexosaminidase A (HexA). It mediates the interaction between the water-soluble exohydrolase and its membrane-embedded glycolipid substrate at the lipid-water interface. Functional deficiencies in this protein result in a fatal neurological storage disorder, the AB variant of GM2 gangliosidosis. In order to elucidate this cofactor's mode of action and identify the surface region of GM2AP responsible for binding to HexA, we designed several variant forms of this protein and evaluated the consequences of these mutations for lipid- and enzyme-binding properties using a variety of biophysical and functional studies. The point mutants D113K, M117V and E123K showed a drastically decreased capacity to stimulate HexA-catalysed GM2 degradation. However, surface plasmon resonance (SPR) spectroscopy showed that the binding of these variants to immobilized lipid bilayers and their ability to solubilize lipids from anionic vesicles were the same as for the wild-type protein. In addition, a fluorescence resonance energy transfer (FRET)-based assay system showed that these variants had the same capacity as wild-type GM2AP for intervesicular lipid transfer from donor to acceptor liposomes. The concentration-dependent effect of these variants on hydrolysis of the synthetic substrate 4-methylumbelliferyl-2-acetamido-2-deoxy-6-sulfo-beta-D-glucopyranoside (MUGS) indicated a weakened association with the enzyme's alpha subunit. This identifies the protein region affected by these mutations, the single short alpha helix of GM2AP, as the major determinant for the interaction with the enzyme. These results further confirm that the function of GM2AP is not restricted to a biological detergent that simply disrupts the membrane structure or lifts the substrate out of the lipid plane. In contrast, our data argue in favour of the critical importance of distinct activator-hexosaminidase interactions for GM2 degradation, and corroborate the view that the activator/lipid complex represents the true substrate for the degrading enzyme.

Animals↗
PubMed2005

Evolution of HIV resistance during treatment interruption in experienced patients and after restarting a new therapy.

BACKGROUND: To analyse the evolution of resistance patterns in patients undergoing treatment interruption (TI) and re-initiating highly active anti-retroviral therapy (HAART). METHODS: HIV-RT and -PR gene-sequences were analysed in 14 patients (>5 failing prior drugs) before and during TI and under a new HAART. Genotypes were interpreted using two bioinformatics systems. Additionally, virus load (VL) and CD4(+)-T-cell counts were measured. RESULTS: Six patients (42%) achieved sustained undetectable VL up to one year after TI (responders), while 8 (57%) maintained VL of more than 2,000 copies/mL (non-responders). Different patterns of resistance-mutations evolution were detected. During TI loss of all mutations was observed in three patients, a reduction of mutations was detected in seven patients, and no alteration was seen in four patients. In the responders, 87.5% of protease inhibitor (PI)-resistance mutations waned during TI and remained undetectable under the new treatment. In contrast, in the non-responder group most PI-resistance mutations continued noticeable under the new therapy. Loss of primary PI-resistance mutations and the presence of one fully active PI in the new regimen significantly correlated with success of subsequent treatment (p=0.028). In two patients new reverse transcriptase associated mutations were detected during TI, G190A (NNRTI mutation) and K70R (NRTI mutation). Appearance of K70R could be explained by a reverse direction of a previously described pathway of thymidin analogues mutation resistance development, while G190A could be due to prolonged subinhibitory drug levels after cessation of NNRTIs. CONCLUSION: In the evolution of HAART-resistance, different patterns were observed in responders and non-responders during but not before TI. Absence of PI-resistance associated mutations during and after TI and administration of a predicted fully active PI for the new therapy correlated with success. Newly detected mutations during TI may indicate reversibility of previously described mutational pathways.

Anti-Retroviral Agents↗
PubMed2005

Computational methods for the design of effective therapies against drug resistant HIV strains.

The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure exerted by the human immune system and by combination drug therapy. We have developed several computational methods whose combined use can support the design of optimal antiretroviral therapies based on viral genomic data.

Database Management Systems↗
PubMed2005

Estimating HIV evolutionary pathways and the genetic barrier to drug resistance.

BACKGROUND: The evolution of drug-resistant viruses challenges the management of human immunodeficiency virus (HIV) infections. Understanding this evolutionary process is important for the design of effective therapeutic strategies. METHODS: We used mutagenetic trees, a family of probabilistic graphical models, to describe the accumulation of resistance-associated mutations in the viral genome. On the basis of these models, we defined the genetic barrier, a quantity that summarizes the difficulty for the virus to escape from the selective pressure of the drug by developing escape mutations. RESULTS: From HIV reverse-transcriptase sequences that had been obtained from treated patients, we derived evolutionary models for zidovudine, zidovudine plus lamivudine, and zidovudine plus didanosine. The genetic barriers to resistance to zidovudine, stavudine, lamivudine, and didanosine, for the above 3 regimens, were computed and analyzed. We found both the mode and the rate of development of resistance to be heterogeneous. The genetic barrier to zidovudine resistance was increased if lamivudine was added to zidovudine but was decreased for didanosine. The barrier to lamivudine resistance was maintained with zidovudine plus didanosine, whereas the barrier to didanosine resistance was reduced most with zidovudine plus lamivudine. CONCLUSION: Mutagenetic trees provide a quantitative picture of the evolution of drug resistance. The genetic barrier is a useful tool for design of effective treatment strategies.

Anti-HIV Agents↗
PubMed2005

Mtreemix: a software package for learning and using mixture models of mutagenetic trees.

SUMMARY: Mixture models of mutagenetic trees constitute a class of probabilistic models for describing evolutionary processes that are characterized by the accumulation of permanent genetic changes. They have been applied to model the accumulation of chromosomal gains and losses in tumor development and the development of drug resistance-associated mutations in the HIV genome.Mtreemix is a software package for estimating mutagenetic trees mixture models from observed cross-sectional data and for using these models for predictions. We provide programs for model fitting, model selection, simulation, likelihood computation and waiting time estimation. AVAILABILITY: Mtreemix, including source code, documentation, sample data files and precompiled Solaris and Linux binaries, is freely available for non-commercial users at http://mtreemix.bioinf.mpi-sb.mpg.de/

Algorithms↗
PubMed2004

Photoaffinity labelling of the human GM2-activator protein. Mechanistic insight into ganglioside GM2 degradation.

The GM2-activator protein (GM2AP) is an essential cofactor for the degradation of ganglioside GM2 by lysosomal beta-hexosaminidase A. It mediates the interaction between the water-soluble exohydrolase and its membrane-bound substrate at the lipid-water interphase. Inherited defects in the gene encoding this glycoprotein result in a fatal neurological storage disorder, the AB variant of GM2-gangliosidosis. To elucidate the mode of action of this glycoprotein cofactor, we synthesized the two photoaffinity labels [14C]C3-TPD-GM2 and [14C]C7-TPD-GM2. Incubation of GM2AP with these substrate analogues and subsequent irradiation led to covalent labelling of the protein. After separation of tryptic peptides by reverse-phase HPLC, the labelled peptide fractions were analysed by MALDI-TOF and sequenced by ESI-Q-TOF mass spectrometry. Both labels were found to be specifically photoincorporated into a part of the surface loop comprising residues V153-L163, a stretch of amino acids that was previously identified as the most flexible region in the crystal structure of the activator. Our results provide strong evidence that this loop constitutes the part of the activator protein that directly interacts with the ganglioside substrate, suggesting that the hydrophobicity and the great structural mobility of this element are crucial for the extraction of the membrane-embedded glycolipid, its stabilization inside the spacious cavity and its guidance to the enzyme's active site. This study demonstrates that the approach of photoaffinity labelling in conjunction with accurate mass measurements can provide insight into substrate binding interactions that complements structural information.

Amino Acid Sequence↗
PubMed2003

Geno2pheno: Estimating phenotypic drug resistance from HIV-1 genotypes.

Therapeutic success of anti-HIV therapies is limited by the development of drug resistant viruses. These genetic variants display complex mutational patterns in their pol gene, which codes for protease and reverse transcriptase, the molecular targets of current antiretroviral therapy. Genotypic resistance testing depends on the ability to interpret such sequence data, whereas phenotypic resistance testing directly measures relative in vitro susceptibility to a drug. From a set of 650 matched genotype-phenotype pairs we construct regression models for the prediction of phenotypic drug resistance from genotypes. Since the range of resistance factors varies considerably between different drugs, two scoring functions are derived from different sets of predicted phenotypes. Firstly, we compare predicted values to those of samples derived from 178 treatment-naive patients and report the relative deviance. Secondly, estimation of the probability density of 2000 predicted phenotypes gives rise to an intrinsic definition of a susceptible and a resistant subpopulation. Thus, for a predicted phenotype, we calculate the probability of membership in the resistant subpopulation. Both scores provide standardized measures of resistance that can be calculated from the genotype and are comparable between drugs. The geno2pheno system makes these genotype interpretations available via the Internet (http://www.genafor.org/).

Anti-HIV Agents↗
PubMed2003

Structural modeling of ataxin-3 reveals distant homology to adaptins.

Spinocerebellar ataxia type 3 (SCA3) is a polyglutamine disorder caused by a CAG repeat expansion in the coding region of a gene encoding ataxin-3, a protein of yet unknown function. Based on a comprehensive computational analysis, we propose a structural model and structure-based functions for ataxin-3. Our predictive strategy comprises the compilation of multiple sequence and structure alignments of carefully selected proteins related to ataxin-3. These alignments are consistent with additional information on sequence motifs, secondary structure, and domain architectures. The application of complementary methods revealed the homology of ataxin-3 to ENTH and VHS domain proteins involved in membrane trafficking and regulatory adaptor functions. We modeled the structure of ataxin-3 using the adaptin AP180 as a template and assessed the reliability of the model by comparison with known sequence and structural features. We could further infer potential functions of ataxin-3 in agreement with known experimental data. Our database searches also identified an as yet uncharacterized family of proteins, which we named josephins because of their pronounced homology to the Josephin domain of ataxin-3.

Adaptor Protein Complex gamma Subunits↗
PubMed2003

Methods for optimizing antiviral combination therapies.

MOTIVATION: Despite some progress with antiretroviral combination therapies, therapeutic success in the management of HIV-infected patients is limited. The evolution of drug-resistant genetic variants in response to therapy plays a key role in treatment failure and finding a new potent drug combination after therapy failure is considered challenging. RESULTS: To estimate the activity of a drug combination against a particular viral strain, we develop a scoring function whose independent variables describe a set of antiviral agents and viral DNA sequences coding for the molecular targets of the respective drugs. The construction of this activity score involves (1) predicting phenotypic drug resistance from genotypes for each drug individually, (2) probabilistic modeling of predicted resistance values and integration into a score for drug combinations, and (3) searching through the mutational neighborhood of the considered strain in order to estimate activity on nearby mutants. For a clinical data set, we determine the optimal search depth and show that the scoring scheme is predictive of therapeutic outcome. Properties of the activity score and applications are discussed.

Algorithms↗
PubMed2003

Tenofovir resistance and resensitization.

Human immunodeficiency viruses in 321 samples from tenofovir-naïve patients were retrospectively evaluated for resistance to this nucleotide analogue. All virus strains with insertions between amino acids 67 and 70 of the reverse transcriptase (n = 6) were highly resistant. Virus strains with the Q151M mutation were divided into susceptible (n = 12) and highly resistant (n = 8) viruses. This difference was due to the absence or presence of the K65R mutation, which was confirmed by site-directed mutagenesis. Viral clones with various combinations of the mutations M41L, K70R, L210W, and T215F or T215Y were analyzed for cross-resistance induced by thymidine analogue mutations (TAMs). The levels of increased resistance induced by single, double, and triple mutations at the indicated positions could be ranked as follows: for mutants with single mutations, mutations at positions 41 > 215 > 70; for mutants with double mutations, mutations at positions 41 and 215 > 70 and 215 = 210 and 215 > 41 and 70; for mutants with triple mutations, mutations at positions 41, 210, and 215 > 41, 70, and 215. Viral clones with M184V or M184I exhibited slightly increased susceptibilities to tenofovir (0.7-fold). Almost all clones with TAM-induced resistance were resensitized when M184V was present (P < 0.001). Among the viruses in the clinical samples, the rate of tenofovir resistance significantly increased with the number of TAMs both in the samples with 184M and in those with 184V (P = 0.005 and P = 0.003, respectively). A resensitizing effect of M184V was confirmed for all samples exhibiting at least one TAM (P = 0.03). However, accumulation of at least two TAMs resulted in more than 2.0-fold reduced susceptibility to tenofovir, irrespective of the presence of M184V. Decision tree building, a classical machine learning technique, was used to generate models for the interpretation of mutations with respect to tenofovir resistance. The application of previously proposed cutoffs for a reduced response to therapy and treatment failure demonstrated the central roles of positions 215 and 65 for 1.5- and 4.0-fold reduced susceptibilities, respectively. Thus, clinically relevant resistance may be conferred by the accumulation of TAMs, and the resensitizing effect of M184V should be considered only minor.

Adenine↗
PubMed2002

Screening for disulfide bonds in proteins by MALDI in-source decay and LIFT-TOF/TOF-MS.

An automated screening method is presented that uses MALDI in-source decay (MALDI-ISD) of disulfide bonds for identification of disulfide-linked peptides in MALDI mass spectra. Peptides released by ISD of a disulfide bond can be detected at an m/z ratio that corresponds to the singly protonated peptide with a reduced cysteine residue. Therefore, screening of peak lists for signal patterns that fulfill the equation, m/z (peak A) + m/z (peak B) - m/z (H2 + H+) = m/z (peak C), facilitated identification of putative ISD fragments of disulfide-linked peptides (peaks A and B) and their precursors (peak C). Signals (peak C) from putatively disulfide-linked peptides were subjected to LIFT-TOF/TOF-MS to confirm the existence of a disulfide bond. Using this method, we identified all 4 disulfide bonds in RNAseA and 8 two-disulfide clusters comprising 16 out of the 17 disulfide bonds in BSA. The presented screening method accelerated the identification of disulfide bonds in RNAseA and BSA, because the number of MS/MS spectra to be acquired was reduced by 1 order of magnitude. Less than 5% of the signals selected for LIFT-TOF/TOF-MS did not correspond to disulfide-linked peptides. Furthermore, the number of possible assignments for disulfide-linked peptides was reduced by 2-3 orders of magnitude, because knowledge of the mechanism of disulfide bond fragmentation by ISD permitted use of stricter rules for the interpretation of mass spectra. Therefore, interpretation of MS/ MS spectra of disulfide-linked peptides was considerably simplified in comparison to conventional approaches.

Algorithms↗
PubMed2002

Diversity and complexity of HIV-1 drug resistance: a bioinformatics approach to predicting phenotype from genotype.

Drug resistance testing has been shown to be beneficial for clinical management of HIV type 1 infected patients. Whereas phenotypic assays directly measure drug resistance, the commonly used genotypic assays provide only indirect evidence of drug resistance, the major challenge being the interpretation of the sequence information. We analyzed the significance of sequence variations in the protease and reverse transcriptase genes for drug resistance and derived models that predict phenotypic resistance from genotypes. For 14 antiretroviral drugs, both genotypic and phenotypic resistance data from 471 clinical isolates were analyzed with a machine learning approach. Information profiles were obtained that quantify the statistical significance of each sequence position for drug resistance. For the different drugs, patterns of varying complexity were observed, including between one and nine sequence positions with substantial information content. Based on these information profiles, decision tree classifiers were generated to identify genotypic patterns characteristic of resistance or susceptibility to the different drugs. We obtained concise and easily interpretable models to predict drug resistance from sequence information. The prediction quality of the models was assessed in leave-one-out experiments in terms of the prediction error. We found prediction errors of 9.6-15.5% for all drugs except for zalcitabine, didanosine, and stavudine, with prediction errors between 25.4% and 32.0%. A prediction service is freely available at http://cartan.gmd.de/geno2pheno.html.

Computational Biology↗
PubMed2002

Partial reduction and two-step modification of proteins for identification of disulfide bonds.

An experimental protocol was established to combine partial reduction, cyanylation, and a second modification step for the assignment of disulfide bonds in proteins that are resistant to proteolysis under native conditions. After proteolysis, disulfide bonds were assigned via MALDI mass spectrometry with subsequent semiautomatic interpretation using the program SearchXLinks, which enumerates all possible combinations of proteolytic fragments for all observed monoisotopic masses. The putative assignment of disulfide bonds was confirmed by ISD and PSD fragmentation of the corresponding protonated molecules.

Algorithms↗
PubMedDate not supplied

Learning multiple evolutionary pathways from cross-sectional data.

We introduce a mixture model of trees to describe evolutionary processes that are characterized by the ordered accumulation of permanent genetic changes. The basic building block of the model is a directed weighted tree that generates a probability distribution on the set of all patterns of genetic events. We present an EM-like algorithm for learning a mixture model of K trees and show how to determine K with a maximum likelihood approach. As a case study, we consider the accumulation of mutations in the HIV-1 reverse transcriptase that are associated with drug resistance. The fitted model is statistically validated as a density estimator, and the stability of the model topology is analyzed. We obtain a generative probabilistic model for the development of drug resistance in HIV that agrees with biological knowledge. Further applications and extensions of the model are discussed.

Algorithms↗
PubMedDate not supplied

A multiobjective evolutionary method for the design of peptidic mimotopes.

Peptides that mimic protein epitopes are interesting drug candidates. However, the design of effective peptidic drugs is difficult for several reasons, such as the fast degradation of peptides, their high flexibility, and thus high entropy loss on binding to the target. We therefore propose an in silico method for the automated design of peptides that are optimal with respect to several objectives. We present a Pareto-based multiobjective evolutionary algorithm for in silico peptide design. Using a simple molecular model, we apply the method to the design of peptides that (a) mimic antibody epitopes of the proteins thrombin and blood coagulation factor VIII, respectively, that (b) are short, and (c) are conformationally stable.

Algorithms↗