@article{ShityakovBencurovaFoersteretal.2020,
  author    = {Shityakov, Sergey and Bencurova, Elena and F{\"o}rster, Carola and Dandekar, Thomas},
  title     = {Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches},
  series = {BMC Bioinformatics},
  volume    = {2020},
  journal   = {BMC Bioinformatics},
  doi       = {10.1186/s12859-020-3461-6},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229169},
  year      = {2020},
  abstract  = {Background Processing and analysis of DNA sequences obtained from next-generation sequencing (NGS) face some difficulties in terms of the correct prediction of DNA sequencing outcomes without the implementation of bioinformatics approaches. However, algorithms based on NGS perform inefficiently due to the generation of long DNA fragments, the difficulty of assembling them and the complexity of the used genomes. On the other hand, the Sanger DNA sequencing method is still considered to be the most reliable; it is a reliable choice for virtual modeling to build all possible consensus sequences from smaller DNA fragments. Results In silico and in vitro experiments were conducted: (1) to implement and test our novel sequencing algorithm, using the standard cloning vectors of different length and (2) to validate experimentally virtual shotgun sequencing using the PCR technique with the number of cycles from 1 to 9 for each reaction. Conclusions We applied a novel algorithm based on Sanger methodology to correctly predict and emphasize the performance of DNA sequencing techniques as well as in de novo DNA sequencing and its further application in synthetic biology. We demonstrate the statistical significance of our results.},
  language  = {en}
}
@article{SarukhanyanShityakovDandekar2020,
  author    = {Sarukhanyan, Edita and Shityakov, Sergey and Dandekar, Thomas},
  title     = {Rational drug design of Axl tyrosine kinase type I inhibitors as promising candidates against cancer},
  series = {Frontiers in Chemistry},
  volume    = {7},
  journal   = {Frontiers in Chemistry},
  number    = {920},
  issn      = {2296-2646},
  doi       = {10.3389/fchem.2019.00920},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-199505},
  year      = {2020},
  abstract  = {The high level of Axl tyrosine kinase expression in various cancer cell lines makes it an attractive target for the development of anti-cancer drugs. In this study, we carried out several sets of in silico screening for the ATP-competitive Axl kinase inhibitors based on different molecular docking protocols. The best drug-like candidates were identified, after parental structure modifications, by their highest affinity to the target protein. We found that our newly designed compound R5, a derivative of the R428 patented analog, is the most promising inhibitor of the Axl kinase according to the three molecular docking algorithms applied in the study. The molecular docking results are in agreement with the molecular dynamics simulations using the MM-PBSA/GBSA implicit solvation models, which confirm the high affinity of R5 toward the protein receptor. Additionally, the selectivity test against other kinases also reveals a high affinity of R5 toward ABL1 and Tyro3 kinases, emphasizing its promising potential for the treatment of malignant tumors.},
  language  = {en}
}