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MOTIVATION: The genome projects produce a wealth of protein sequences. Theoretical methods to predict possible structures and functions are needed for screening purposes, large-scale comparisons and in-depth analysis to identify worthwhile targets for further experimental research. Sequence-structure alignment is a basic tool for the identification of model folds for protein sequences and the construction of crude structural models. Empirical contact potentials (potentials of mean force) are used to optimize and evaluate such alignments. RESULTS: We propose new scoring schemes based on a contact definition derived from Voronoi decompositions of the three-dimensional coordinates of protein structures. We demonstrate that Voronoi potentials are superior to pure distance-based contact potentials with respect to recognition rate and significance for native folds. Moreover, the scoring scheme has the potential to provide a reasonable balance of detail and ion such that it is also useful for the recognition of distantly related (both homologous and non-homologous) proteins. This is demonstrated here on a set of structural alignments showing much better correspondence of native and model scores for the Voronoi potentials as compared to conventional distance-based potentials.
Survival of patients with pediatric acute lymphoblastic leukemia (ALL) after allogeneic hematopoietic stem cell transplantation (allo-SCT) is mainly compromised by leukemia relapse, carrying dismal prognosis. As novel individualized therapeutic approaches are urgently needed, we performed whole-exome sequencing of leukemic blasts of 10 children with post–allo-SCT relapses with the aim of thoroughly characterizing the mutational landscape and identifying druggable mutations. We found that post–allo-SCT ALL relapses display highly diverse and mostly patient-individual genetic lesions. Moreover, mutational cluster analysis showed substantial clonal dynamics during leukemia progression from initial diagnosis to relapse after allo-SCT. Only very few alterations stayed constant over time. This dynamic clonality was exemplified by the detection of thiopurine resistance-mediating mutations in the nucleotidase NT5C2 in 3 patients’ first relapses, which disappeared in the post–allo-SCT relapses on relief of selective pressure of maintenance chemotherapy. Moreover, we identified TP53 mutations in 4 of 10 patients after allo-SCT, reflecting acquired chemoresistance associated with selective pressure of prior antineoplastic treatment. Finally, in 9 of 10 children’s post–allo-SCT relapse, we found alterations in genes for which targeted therapies with novel agents are readily available. We could show efficient targeting of leukemic blasts by APR-246 in 2 patients carrying TP53 mutations. Our findings shed light on the genetic basis of post–allo-SCT relapse and may pave the way for unraveling novel therapeutic strategies in this challenging situation.
We propose a new alignment procedure that is capable of aligning protein sequences and structures in a unified manner. Recursive dynamic programming (RDP) is a hierarchical method which, on each level of the hierarchy, identifies locally optimal solutions and assembles them into partial alignments of sequences and/or structures. In contrast to classical dynamic programming, RDP can also handle alignment problems that use objective functions not obeying the principle of prefix optimality, e.g.\ scoring schemes derived from energy potentials of mean force. For such alignment problems, RDP aims at computing solutions that are near-optimal with respect to the involved cost function and biologically meaningful at the same time. Towards this goal, RDP maintains a dynamic balance between different factors governing alignment fitness such as evolutionary relationships and structural preferences. As in the RDP method gaps are not scored explicitly, the problematic assignment of gap cost parameters is circumvented. In order to evaluate the RDP approach we analyse whether known and accepted multiple alignments based on structural information can be reproduced with the RDP method. For this purpose, we consider the family of ferredoxins as our prime example. Our experiments show that, if properly tuned, the RDP method can outperform methods based on classical sequence alignment algorithms as well as methods that take purely structural information into account.