Browsing by Subject "In silico"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Open Access DNA codon recognition by a cubane wire: In silico approach(DergiPark, 2021) Mirzaei, M.; Hadipour, N.; Gülseren, OğuzDNA codons, consisting of triplet nucleotides (NTs), could play important roles for RNA transcription and protein translation in living systems. Therefore, their recognition could be seen important for diagnosis and therapy purposes. Based on triplet sequence formations of Adenine (A), Guanine (G), Cytosine (C) and Thymine (T) NTs, 64 codons were investigated in this work regarding their complexation with a molecular cubane (CUB) wire. To achieve this aim, each of singular 64 codons and CUB were optimized to be prepared for docking processes of complex formations. Hence, 64 complexes of codon-CUB were docked to see the recognition potency of CUB wire versus each of DNA codons. Interestingly, the obtained docking scores indicated that the CUB could work specifically versus the DNA codons, in which G-rich and A-rich triples were seen to be more favorable for complexation with CUB in comparison with other C-rich and T-rich triplet codons. Moreover, the results indicated that not pure G triplet but GAG codon was the most favorable one to be recognized by the CUB wire. However, pure T triplet was the worst one for such complex formations. The results of this work remarkably indicated that the CUB wire could work for recognition process of DNA codons from each other and such recognition could be very much specified for each of G-rich and A-rich codons, in which GAG codon was the best one among all the 64 investigated codons.Item Open Access The impacts of 13 novel mutations of SARS-CoV-2 on protein dynamics: In silico analysis from Turkey(Elsevier, 2022-09) Unlu, Sezina; Uskudar-Guclu, Aylina; Cela, IsliSARS-CoV-2 inherits a high rate of mutations making it better suited to the host since its fundamental role in evolution is to provide diversity into the genome. This research aims to identify variations in Turkish isolates and predict their impacts on proteins. To identify novel variations and predict their impacts on protein dynamics, in silico methodology was used. The 411 sequences from Turkey were analysed. Secondary structure prediction by Garnier-Osguthorpe-Robson (GOR) was used. To find the effects of identified Spike mutations on protein dynamics, the SARS-CoV-2 structures (PDB:6VYB, 6M0J) were uploaded and predicted by Cutoff Scanning Matrix (mCSM), DynaMut and MutaBind2. To understand the effects of these mutations on Spike protein molecular dynamics (MD) simulation was employed. Turkish sequences were aligned with sequences worldwide by MUSCLE, and phylogenetic analysis was performed via MegaX. The 13 novel mutations were identified, and six of them belong to spike glycoprotein. Ten of these variations revealed alteration in the secondary structure of the protein. Differences of free energy between the reference sequence and six mutants were found below zero for each of six isolates, demonstrating these variations have stabilizing effects on protein structure. Differences in vibrational entropy calculation revealed that three variants have rigidification, while the other three have a flexibility effect. MD simulation revealed that point mutations in spike glycoprotein and RBD:ACE-2 complex cause changes in protein dynamics compared to the wild-type, suggesting possible alterations in binding affinity. The phylogenetic analysis showed Turkish sequences distributed throughout the tree, revealing multiple entrances to Turkey. © 2022 Elsevier B.V.Item Open Access RNA based biomarkers for prediction of the endometrial window of implantation(Bilkent University, 2020-12) Dedeoğlu, EgeEarly reproductive failure is the most common issue related to successful pregnancies, as around 30% of all conceptions reach live birth. The path to a successful pregnancy is reliant on the successful implantation of the embryo to the endometrium. This event requires three major components; a viable embryo ready for implantation, a receptive endometrium in which the implantation will occur, and healthy crosstalk between the embryo and receptive endometrium. It is estimated that two out of all three implantation failures are related to endometrial origin. This has led many researchers to attempt to elucidate the mechanism behind endometrial receptivity and generate a prediction of successful implantation of endometrial origin. Although there have been plenty of articles on this subject, there is still no consensus regarding standard endometrial receptivity biomarkers. Additionally, most of these articles’ findings cannot find their way into clinics. This is highlighted by the fact that the success rate of embryo implantation in ART applied in clinics is only around 10%. This study aimed to identify novel methods and biomarkers to predict the endometrium's receptivity, which could be applied in clinics easier and faster than the current kits in the market. We took several different approaches to achieve this aim. The first was to identify and validate particular miRNAs that showed a change in expression levels of the different days of the endometrial cycle in a healthy women’s serum. Our bioinformatical analysis has yielded ten miRNAs that show statistical differences in the human endometrium and being expressed in the serum. Downstream RNA-Seq and qPCR experiments have validated specific miRNAs previously predicted and identified novel miRNAs used for this purpose. The second was using in silico methods, identifying novel genes present in the endometrium that can predict the optimal point of receptivity. If considered and validated in vitro, this novel gene-list will be a cheaper but still as powerful alternative to the current endometrial test kit used in clinics today. Further validation RNA-Seq experiments on healthy and infertile females will elucidate our novel biomarkers' strength, designed to be used in ART clinics worldwide. Furthermore, upon building on these findings, it is possible to uncover previously overlooked mechanisms leading to women's implantation success.