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Structure-based drug design
Published on December 29, 2016 34 min
A selection of talks on Pharmaceutical Sciences
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Overview of nonclinical safety assessment
- Dr. Claudette L. Fuller
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Drug-induced liver injury: risk factors and drug development in DILI
- Prof. James H. Lewis
- Georgetown University Medical Center, USA
Drugging conformational states of GPCRs
- Prof. Dr. Peter Kolb
- Philipps-Universität Marburg, Germany
Hello, I'm Nathan Brown from the Institute of Cancer Research in London. And I'm going to talk to you today about structure-based drug design and the computational methods we apply in developing medicinal chemistry strategies.
So structure-based drug design, what is it we're trying to achieve? We're using computational methods to design, select, and prioritize synthetic chemistry targets that will then contribute positively to the medicinal chemistry project.
And how we achieve this is to work around this design, make test iterative cycle where we identify new molecules to make, we enumerate those molecules in the computer. We calculate predictions, prioritize compounds, and synthesize and test them, by far the most time-consuming part of the cycle, and then extensive data analysis that allows us to distill down the learning from the synthesis and testing to make even better decisions in the next cycle.
So in this talk I'm going to cover a few different types of the main methods that we apply in drug discovery with computational methods. First, we're going to cover bioisosteric replacements and scaffold hopping which is a subset of bioisosteric replacement. We're then going to cover analogue-by-catalogue searching. It starts when we've got a hit compound of interest, how to identify other compounds that are analogs of that to validate that chemotype of that scaffold. Then I'm going to move on to virtual library design where we can enumerate virtual libraries and make predictions about those libraries that can then be tested using structure-based methods. We'll touch briefly on homology modeling. This is where we predict the protein structure, given the sequence of that protein and also the protein structure of a similar protein targets of interest. Then we'll cover the elucidation of pharmacophores and what the pharmacophore is in context and how we use pharmacophores to search large libraries of compounds by taking into account the three dimensional structure of the molecules under investigation. And lastly, we'll move into virtual ligand docking, that's how we can simulate the docking of ligands into proteins and protein binding sites to understand potential interactions that can be exploited in optimizing potency in the drug program.