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Development and Application of Computational Approaches in Drug Discovery Desenvolvimento e Aplicacao de Metodos Computacionais na Descoberta de Farmacos
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Development and Application of Computational Approaches in Drug Discovery = Desenvolvimento e Aplicacao de Metodos Computacionais na Descoberta de Farmacos. |
| 개인저자 | Zanette, Camila. |
| 단체저자명 | University of California, Irvine. Pharmacological Sciences - Ph.D.. |
| 발행사항 | [S.l.]: University of California, Irvine., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 153 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-03B. Dissertation Abstract International |
| ISBN | 9781085647892 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, Irvine, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-03, Section: B.
Advisor: Mobley, David L. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | The early stages of drug discovery is a long and costly process. A way to reduce the time, resources, and financial investment spent is to apply computational tools. With the tremendous progress and achievements in computational chemistry, the application of computational tools in the drug lead discovery and design has increased. Today, computational chemistry is considered a highly valuable and well established tool in drug discovery. A variety of computational chemistry methods are used for guiding molecular design and finding new potential drugs and targets. Some examples of these methods are molecular dynamics simulations, free energy calculations, virtual screening, structure-activity relationship analysis, and so on. Despite the fact that computational chemistry technics are widely used in industry and academic environment, there is still room for improvement. Here, I present several studies in which I developed and applied computational chemistry tools in drug discovery problems. The first study is the development of a tool as part of the Open Force Field consortium to learn chemical perception of force fields typing rules. Secondly, I describe my work on using a new hybrid method to calculate free energies of small molecules. Thirdly, I present a binding mode prediction study to help the understanding of structure-activity relationship in lissoclimides. Lastly, I present a study applying molecular dynamic simulation to guide the redesigning of a macrocyclic peptide. |
| 일반주제명 | Computational chemistry. Pharmaceutical sciences. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
