TY - JOUR A1 - Isaacs, Darren A1 - Mikasi, Sello Given A1 - Obasa, Adetayo Emmanuel A1 - Ikomey, George Mondinde A1 - Shityakov, Sergey A1 - Cloete, Ruben A1 - Jacobs, Graeme Brendon T1 - Structural comparison of diverse HIV-1 subtypes using molecular modelling and docking analyses of integrase inhibitors JF - Viruses N2 - The process of viral integration into the host genome is an essential step of the HIV-1 life cycle. The viral integrase (IN) enzyme catalyzes integration. IN is an ideal therapeutic enzyme targeted by several drugs; raltegravir (RAL), elvitegravir (EVG), dolutegravir (DTG), and bictegravir (BIC) having been approved by the USA Food and Drug Administration (FDA). Due to high HIV-1 diversity, it is not well understood how specific naturally occurring polymorphisms (NOPs) in IN may affect the structure/function and binding affinity of integrase strand transfer inhibitors (INSTIs). We applied computational methods of molecular modelling and docking to analyze the effect of NOPs on the full-length IN structure and INSTI binding. We identified 13 NOPs within the Cameroonian-derived CRF02_AG IN sequences and further identified 17 NOPs within HIV-1C South African sequences. The NOPs in the IN structures did not show any differences in INSTI binding affinity. However, linear regression analysis revealed a positive correlation between the Ki and EC50 values for DTG and BIC as strong inhibitors of HIV-1 IN subtypes. All INSTIs are clinically effective against diverse HIV-1 strains from INSTI treatment-naïve populations. This study supports the use of second-generation INSTIs such as DTG and BIC as part of first-line combination antiretroviral therapy (cART) regimens, due to a stronger genetic barrier to the emergence of drug resistance. KW - integrase KW - naturally occurring polymorphisms KW - HIV-1 KW - molecular modelling KW - molecular docking KW - diversity Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-211170 SN - 1999-4915 VL - 12 IS - 9 ER - TY - JOUR A1 - Shityakov, Sergey A1 - Bencurova, Elena A1 - Förster, Carola A1 - Dandekar, Thomas T1 - Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches JF - BMC Bioinformatics N2 - 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. KW - Shotgun method KW - Sanger sequencing KW - Virtual sequencing KW - Polymerase chain reaction KW - Gene expression vectors KW - Synthetic biology Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-229169 VL - 2020 ER - TY - JOUR A1 - Sarukhanyan, Edita A1 - Shityakov, Sergey A1 - Dandekar, Thomas T1 - Rational drug design of Axl tyrosine kinase type I inhibitors as promising candidates against cancer JF - Frontiers in Chemistry N2 - 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. KW - Axl tyrosine kinase KW - anti-cancer drug-like molecules KW - rational drug design KW - molecular docking KW - molecular dynamics Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-199505 SN - 2296-2646 VL - 7 IS - 920 ER -