Difference between revisions of "CHECKSPMUTATE"
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CHECKSPMUTATE uses the CHECKSPODATA routine, which reoptimises the minima/transition states of a database. CHECKSPMUTATE extends this by allowing for user-selected sections of the coordinates of the stationary points comprising the database to be mutated before the reoptimisation takes place. Thus a database can be transformed so that it describes the behaviour of a mutated protein as opposed to the Wild Type. Though this new database will need to be tidied up through the use of, eg, [[SHORTCUT]], [[SHORTCUT 2 BARRIER]] and [[UNTRAP]], this process should be far quicker than starting a whole new database from scratch. In the example below, I shall show how a pathway describing the approach of the cofactor, NADH, towards another cofactor, haem, within the pocket of HemS (a pathway which took months to find and fully connect) could be quickly replicated in a system where the wt HemS has been replaced by a mutated form (or even by another protein entirely). |
CHECKSPMUTATE uses the CHECKSPODATA routine, which reoptimises the minima/transition states of a database. CHECKSPMUTATE extends this by allowing for user-selected sections of the coordinates of the stationary points comprising the database to be mutated before the reoptimisation takes place. Thus a database can be transformed so that it describes the behaviour of a mutated protein as opposed to the Wild Type. Though this new database will need to be tidied up through the use of, eg, [[SHORTCUT]], [[SHORTCUT 2 BARRIER]] and [[UNTRAP]], this process should be far quicker than starting a whole new database from scratch. In the example below, I shall show how a pathway describing the approach of the cofactor, NADH, towards another cofactor, haem, within the pocket of HemS (a pathway which took months to find and fully connect) could be quickly replicated in a system where the wt HemS has been replaced by a mutated form (or even by another protein entirely). |
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| + | == Preparation == |
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| + | To use CHECKSPMUTATE, we first need a database of interest, or a subset of it. In my example, I had extracted the minima and transition states comprising the pathway I was interested in using [[DIJKSTRA]] and moved the new min.data, points.min, points.ts and ts.data files to a new directory. Therefore, each of the stationary points in my database described a stage along this pathway. I wanted to see how this pathway, describing the approach of NADH to haem within the wt HemS pocket, changed when certain mutations were made to the HemS structure. One such residue of interest was a phe-gate (which appeared to regulate the approach of NADH) and so a mutation from phenylalanine to alanine (F104A) was made. |
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Revision as of 11:08, 2 June 2020
Purpose
It can take an awfully long time to create a large database or to fully optimise a specific feature of it such as afully connected pathway showing complex protein folding. This is particularly acute when considering large proteins/protein+ligand systems.
What if we are interested in examining how a Wild Type protein behaves with respect to some carefully selected mutants? Or in comparing one protein against a close homologue? It would seem like a colossal waste of time to create large databases for each of these similar cases, completely independently from each other. This is where CHECKSPMUTATE comes in.
CHECKSPMUTATE uses the CHECKSPODATA routine, which reoptimises the minima/transition states of a database. CHECKSPMUTATE extends this by allowing for user-selected sections of the coordinates of the stationary points comprising the database to be mutated before the reoptimisation takes place. Thus a database can be transformed so that it describes the behaviour of a mutated protein as opposed to the Wild Type. Though this new database will need to be tidied up through the use of, eg, SHORTCUT, SHORTCUT 2 BARRIER and UNTRAP, this process should be far quicker than starting a whole new database from scratch. In the example below, I shall show how a pathway describing the approach of the cofactor, NADH, towards another cofactor, haem, within the pocket of HemS (a pathway which took months to find and fully connect) could be quickly replicated in a system where the wt HemS has been replaced by a mutated form (or even by another protein entirely).
Preparation
To use CHECKSPMUTATE, we first need a database of interest, or a subset of it. In my example, I had extracted the minima and transition states comprising the pathway I was interested in using DIJKSTRA and moved the new min.data, points.min, points.ts and ts.data files to a new directory. Therefore, each of the stationary points in my database described a stage along this pathway. I wanted to see how this pathway, describing the approach of NADH to haem within the wt HemS pocket, changed when certain mutations were made to the HemS structure. One such residue of interest was a phe-gate (which appeared to regulate the approach of NADH) and so a mutation from phenylalanine to alanine (F104A) was made.