Applications of molecular dynamics in drug discovery and technology transfer via a web-based platform
In this thesis we apply molecular dynamics (MD) simulations and other in silico techniques in drug discovery. Specifically, (a) we developed an algorithm to detect cryptic pockets based on MD simulations of the protein solvated in a mixture of water and benzene, (b) we performed the first 150-fragme...
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| Formato: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | España |
| Recursos: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/665077 |
| Acesso em linha: | http://hdl.handle.net/10803/665077 |
| Access Level: | acceso abierto |
| Palavra-chave: | Molecular dynamics Simulation Drug discovery Web application Fragment Dinàmica molecular Simulació Fàrmacs Aplicació web 615 |
| Resumo: | In this thesis we apply molecular dynamics (MD) simulations and other in silico techniques in drug discovery. Specifically, (a) we developed an algorithm to detect cryptic pockets based on MD simulations of the protein solvated in a mixture of water and benzene, (b) we performed the first 150-fragment screening against the chemokine CXCL12 using a MD-driven protocol and (c) we studied the conformational plasticity of the μ-opioid receptor (MOR) bound to two different drugs to study the molecular basis of selective modulation. Additionally, we created a web platform entitled PlayMolecule, where we have published several applications including: (a) ProteinPrepare, a protein preparation wizard for MD simulations, (b) CryptoScout, an application to unravel cryptic binding sites using mixed-solvent simulations, (c) DeepSite, a binding site detector using convolutional neural networks (CNN) and (d) OPM built database, a database of all the eukaryotic OPM membrane proteins built in a membrane and water system ready for simulation. |
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