| dc.identifier.uri | http://hdl.handle.net/11401/76956 | |
| dc.description.sponsorship | This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. | en_US |
| dc.format | Monograph | |
| dc.format.medium | Electronic Resource | en_US |
| dc.language.iso | en_US | |
| dc.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dc.type | Dissertation | |
| dcterms.abstract | Abstract of the Dissertation <bold>Targeted Design of Dual Kinase Inhibitors for Breast Cancer</bold> by <bold>Yulin Huang</bold> <bold>Doctor of Philosophy</bold> in <bold>Biochemistry and Structural Biology</bold> Stony Brook University <bold>2013</bold> In this dissertation, several projects for kinase drug design are presented. These projects employ computational techniques to study binding specificity and resistance of kinase inhibitors with breast cancer target proteins through structural and energetic analysis. In Chapter 1, an introduction to molecular targeted therapeutics for breast cancer and computational techniques for structure-based drug discovery is described. ErbB family members and IGFIR are important targets for breast cancer. In Chapter 2, we have characterized the determinants which drive binding affinity for the FDA-approved small molecule drug lapatinib specificity with the goal of uncovering the origins of the specificity across different ErbB family members. Results have incorporated homology modeling, molecular dynamic simulations, free energy calculations, binding analysis, and hydration analysis. A key finding of our work was identification of a physically unique water-mediated H-bond network which compellingly explains why lapatinib has high affinity for EGFR and HER2 but not the highly homologous ErbB4. Our model also helps to explain drug resistance which can arise due to disruption of the water-mediated network. In Chapter 3, we have employed MM-GBSA method with the same protocol used in Chapter 2 to quantify the binding free energies of lapatinb two lapatinib conformations (conf1 and conf2) with EGFR, HER2 and ErbB4. To further explore the energy and the probability of two conformations, umbrella sampling with potential mean force (PMF) calculation was performed. Both MM-GBSA and PMF results show that conf1 always yield more favorable binding energy with all three proteins than conf2, indicating that conf1 with ErbB4, as seen in crystal structure 3BBT, is only a local minimum and conf1 is the global minimum. The two conformations may co-exist in an equilibrium with ErbB4, which may also help explain why lapatinib binds to ErbB4 less tightly than to EGFR and HER2. In Chapter 4, thermodynamic integration (TI) method was used to examine the structure activity relationship (SAR) for a series of ligands with an imidazopyrazine scaffold interacting with the intermediate form of IGF-IR. Twelve different Δ Δ Gbind relationships were studied as well as several " null" transformations to validate the simulation protocols. From a series of 19 simulation windows (2ns of simulation per window), we obtained a relative binding free energy of close to zero with negligible standard error of the mean for five null transformations, indicating the model construction and simulation are robust. Overall, the results of the study were mixed. While single perturbations involving aliphatic changes (i.e. N, Me, Et) yielded excellent results compared to experiment more complicated perturbations involving bulky groups (Ph) or polar groups (OH, NH2) yielded large errors. Studies to explore the sources of these errors are ongoing. In Chapter 5, we have presented preliminary virtual screening results targeting intermediate and active forms of IGF-IR using DOCK 6.6 to identify new drug leads. Compounds from the ZINC/ChemDiv catalog of purchasable compounds (1.2M) were flexibly docked and the single lowest-energy pose for each compound was retained. The top 100,000 molecules were then clustered based on MACCS fingerprints and the top 250 cluster heads and all families members were selected based on the four different scoring methods: (1) standard DOCK score (2) van der Waals footprint similarity score (3) electrostatic footprint similarity score and (4) the combined footprint sum. The top 20 compounds for each category will be advanced to experimental testing after visual inspection and additional analysis. In particular, compounds will be minimized and assessed in the binding pocket of EGFR, HER2 and IGF-IR to identify possible combinations for use as dual inhibitors. In Chapter 6, we conclude with a description of ongoing projects and ideas for future directions. | |
| dcterms.available | 2017-09-20T16:51:32Z | |
| dcterms.contributor | London, Erwin | en_US |
| dcterms.contributor | Rizzo, Robert C | en_US |
| dcterms.contributor | Green, David F | en_US |
| dcterms.contributor | Deng, Yuefan. | en_US |
| dcterms.creator | Huang, Yulin | |
| dcterms.dateAccepted | 2017-09-20T16:51:32Z | |
| dcterms.dateSubmitted | 2017-09-20T16:51:32Z | |
| dcterms.description | Department of Biochemistry and Structural Biology. | en_US |
| dcterms.extent | 150 pg. | en_US |
| dcterms.format | Monograph | |
| dcterms.format | Application/PDF | en_US |
| dcterms.identifier | http://hdl.handle.net/11401/76956 | |
| dcterms.issued | 2013-12-01 | |
| dcterms.language | en_US | |
| dcterms.provenance | Made available in DSpace on 2017-09-20T16:51:32Z (GMT). No. of bitstreams: 1
Huang_grad.sunysb_0771E_11391.pdf: 5003634 bytes, checksum: 2a6a92486d9baae753920473a8418341 (MD5)
Previous issue date: 1 | en |
| dcterms.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dcterms.subject | DOCK, EGFR, ErbB4, HER2, MD, TI | |
| dcterms.subject | Biochemistry | |
| dcterms.title | Targeted Design of Dual Kinase Inhibitors for Breast Cancer | |
| dcterms.type | Dissertation | |
