Back

Impact of Inert Crowders on Host-Guest Recognition Process

Majumdar, B. B.; Mondal, J.

2022-03-04 biophysics
10.1101/2022.03.03.482924 bioRxiv
Show abstract

Biological environments typically contain high concentrations (300-400 mg/mL) of different macromolecules at volume fractions as large as 30%-40%. Biomolecular processes, especially ubiquitous recognition phenomena, occurring in such crowded heterogeneous media would differ significantly compared to the dilute buffer solutions. Here we quantify the impact of inert crowders on prototypical host-guest recognition process by explicit-solvent molecular dynamics (MD) simulations in atomic resolution. We demonstrate that the crowders, especially when smaller in size, would facilitate the binding process of guest molecule by decreasing the free energy barrier for binding via excluded volume effect and desolvation of the host receptor. However, the extent of crowder-induced stabilization of host-guest complex is found to be significantly higher when the guest molecule is sterically constricted to approach the host along a centrosymmetric direction, contrary to its unrestricted, freely diffusive movement. A kinetic analysis of the recognition process reveals that the origin of relatively stronger crowder impact, during constricted movement of guest molecule, lies in significantly enhanced residence time of the guest inside the host by crowders, compared to freely diffusive ligand movement. Together our results suggest that the extent of im-pact of crowding on recognition processes would be contingent upon presence or absence of constriction on ligand movement. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/482924v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@130e57dorg.highwire.dtl.DTLVardef@12aa364org.highwire.dtl.DTLVardef@4d23ddorg.highwire.dtl.DTLVardef@6da639_HPS_FORMAT_FIGEXP M_FIG TOC graphic C_FIG

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.