Bilgisayar ortamında ve deneysel olarak IL1-β reseptör inhibitörü peptitlerin belirlenmesi

Therapeutic peptides have become promising due to their high affinity and specificity to the target, deep tissue penetration, low toxicity, convenience for structural modifications, and cost effectiveness. For a lead molecule to reach the market, approximately a 15-year period and an investment of around 2.6 billion dollars are necessary. One of the most important parameters to evaluate the lead compounds in the process of Drug Discovery and Development is binding affinity, which is the strength of the non-covalent interactions between the ligand and the target molecules. This thesis study focuses on in silico design of peptides to block IL1β – Receptor instead of therapeutically used recombinant protein, Anakinra, which has the same structure as the human native IL1 – Receptor antagonist molecule. In order to verify the validity of the computationally designed peptides, surface plasmon resonance methods were used to measure the binding affinity of them. 9 different peptide sequences were designed from the three-dimensional structure of IL1-Receptor Antagonist protein by considering the type and number of non-covalent interactions that form with the receptor. In order to evaluate the binding affinities of these peptides, molecular docking simulations were performed for 100 runs by fixing the bonds. Peptide C, which is Arg – Ile – Trp – Asp – Val – Asn – Gln, showed the highest binding affinity with KD of 7.91x10-8 M. The docking studies were repeated to confirm the binding affinity of Peptide C without fixing the bonds for 999 runs. Since Peptide C is consistent in terms of its binding affinity to the receptor, N- terminus and C- terminus modifications were applied to increase the conformational stability of the peptide. N- terminus modification resulted as Phe insertion to the amino group of Peptide C, while C- terminus modification requires Lys insertion. The modifications increased the number of hydrophobic interactions while also keeping hydrogen bonds between the peptide and the receptor that both N- and C- termini modified peptide has KD of 0.24x10-9 M. To understand unbinding pathway and binding affinities of our designed peptides in a more accurate and realistic environment, SMD simulations were performed for unmodified sequence which is Peptide C, N- terminus modified 8- amino acid peptide, and both N- and C- termini modified 9- amino acid peptide. The binding affinity values for the three of the peptides from SMD simulations are consistent with the average values obtained from the docking. Since water molecules are present in SMD simulations, they interfere between the peptide and the receptor molecules that the distance between the interactions increase thereby, causing the loss of some of the hydrogen bonds and most of the hydrophobic interactions. Due to this fact and realistic aspect of SMD, three of the peptides show binding affinities to the receptor at the average values of the docking results. In Chapter 3, three of the peptides obtained as a result of the computational studies were synthesized using Fmoc Solid Phase Peptide Synthesis methods. High Performance Liquid Chromatography was used to analyze the synthesis. Even though, we showed that our first synthesis which is for the unmodified peptide was successful, due to a problem occurrence either in the column or in the instrument, after a while, we even could not obtain the chromatograms of the standard samples of the peptides. The chromatograms of the standard samples were obtained using a different instrument. However, due to TFA fragmentation of the peptides, our synthesis products might have corrupted that further studies continued with the custom synthesis peptides. Finally, to validate the binding affinity of the peptides experimentally, Surface Plasmon Resonance (SPR) method was used. In Biacore T200 instrument, CM5 sensor chip surface was immobilized with IL1-Receptor using amine coupling chemistry. To verify the accuracy of the instrument, binding affinity of IL1-β to IL1-Receptor was measured performing kinetics analysis. Concentration dependency was obtained and KD was found out as 2.8 nM which is a consistent result with the literature value, 2.7 nM. Although concentration dependency was also obtained for the peptides, binding affinity values could not be obtained yet due to the bulk effect of DMSO. The kinetics analysis to measure binding affinity of the peptides will be repeated by performing solvent correction prior to the analysis to prevent bulk effect of DMSO.