@AlexandervanTe1 account on how changes in Martini have affected the modelling of short peptide self assembly in water is out now in Acc. Chem. Res. excellent input from an undergrad project students who is also an author… @scotch_research@StrathChem https://t.co/BLNYCrdEKQ
.@ChrisStephens as my MP, please oppose the #PolicingBill
It will give police more powers to shut down protest, stop and search without suspicion, and criminalise Gypsy and Traveller communities.
#PoliceCrackdownBill
https://t.co/cr1tCOlq92
Hot off the press... being able to search for peptides longer than 3 amino acids has always been a goal - our new ML approach now makes that possible! https://t.co/FPGJMtzimx @AlexandervanTe1#MachineLearning#CoarseGraining#MLCG
@sudarshanb259 Yes. We restrict the dataset (ie. remove all peptides with log P > 0) then run the algorithm in order to find the interesting cases of peptides that do aggregate but at least less due to the hydrophobic effect.
3. This is the interesting part, that it does aggregate despite being soluble (at least as far as log P < 0 = soluble) means the molecules are interacting in an attractive fashion in the way we would expect for a self-assembling nanomaterial.
@AlexandervanTe1@scotch_research 3. A basic question. When you write "a soluble hexapeptide that aggregates in water" in Figure 2, is it soluble in water? If so, how can it still form aggregates?
Ahh sorry i misunderstood. During the CGMD simulation there are 300 peptides in the simulation box. The datasets are 8000 (20^3) for tripeptides, up to 64,000,000 (20^6) for hexapeptides.
2. sum(SP2) is the total number of SP2 carbon atoms, max ASA and Bulkiness are described in the references listed, twitter character limit ties my hands a bit here. Briefly, maxASA is the highest ASA for an amino acid in the tripeptide Gly-X-Gly in all biophysical conformations.
@AlexandervanTe1@scotch_research 2. In the Judred parameters, what does sum(SP2) means? Is it the total number of SP2 hybridized atoms? What is Max SASA and how do you define bulkiness?
@AlexandervanTe1@scotch_research Interesting work. I want some clarifications to understand the work better.
1. How many peptides, in total, have you considered for 50ns CGMD run?
My poster submission for #ScotCHEM2020, Beyond tripeptides - how machine learning can help to reduce computational search spaces, particularly in the field of peptide self-assembly.
PDF version with clickable links: https://t.co/JcKXEJfwDR
@scotch_research