was going to send you a DM as I prefer not to discuss politics in public but found out your profile does not allow DMs.

IsoMIF for the detection of binding-site similarities with applications in drug repurposing, and to corroborate screening/docking results for molecules with known targets. Lastly, if you obtain a Modeller license, it allows you to perform mutations within PyMOL. Check it out.

NRGTEN to generate conformational ensembles, to predict the effect of mutations on protein flexibility and stability, to generate dynamical signatures for mutants (say you want to increase stability without affecting binding-site flexibility);

FlexAID for docking simulations and to refine approximate poses obtained with NRGRank; Surfaces to analyse protein-ligand and protein-protein interfaces with accuracy equivalent to MD-based FEP calculations in predicting DDG of mutations;

The tools are: GetCleft for the definition and refinement of cavities; NRGRank for ultra-massive virtual screening (50K molecules/h in a laptop), pre-loaded molecule datasets (all FDA approved drugs, all ligands in PDB, all tetra peptides);

Their combination in this plugin makes it possible to perform complex and innovative workflows in understanding protein function, drug development and protein engineering. (2/N)

I don'y like mate but I like this paper, what a monumental achievement, from genome to structure/function. Wow.

let alone that any health intervention may take upwards of 15 years alone to be approved...

It is happening to our preprint too, It is a new outreach program to expand the visibility of research - people interested in our research get to hear about someone else's upon reading what was supposed to be our abstract... and someone else is reading our abstracts elsewhere too.

Thanks Nathanael - we need to catch up - I am aware I let the ball drop on that email you sent me long ago. Can we do a zoom in the new year?

(5/5) We characterize the patterns of glycosylation and its role in mediating Ab binding and conformational stability. This study was performed entirely with experimental structures, 1560 in total and without the incredible efforts of the structural community it would not have been possible.

(4/N) Enthalpic trade-off mutations in the RBM favour immune escape at the expense of ACE2 binding, whereas entropic trade-off mutations do not affect RBM but favour the closed state, thus entropically decreasing ACE2 binding.

(3/N) We perform a longitudinal analysis of the effect of mutations, we show the changing epistatic effect of mutations, define two evolutionary trade-off hypotheses for viral evolution: Enthalpic and Entropic.

(2/N) We use a combination of Surfaces' energies and geometry to define 14 epitope classes that go beyond Barnes' classes