A Collective Variable for the Rapid Exploration of Protein Druggability

Abstract

An efficient molecular simulation methodology has been developed for the evaluation of the druggability (ligandability) of a protein. Previously proposed techniques were designed to assess the druggability of crystallographic structures and cannot be tightly coupled to molecular dynamics (MD) simulations. By contrast, the present approach, JEDI (Just Exploring Druggability at protein Interfaces), features a druggability potential made of a combination of empirical descriptors that can be collected "on-the-fly" during MD simulations. Extensive validation studies indicate that JEDI analyses discriminate druggable and nondruggable protein binding site conformations with accuracy similar to alternative methodologies, and at a fraction of the computational cost. Since the JEDI function is continuous and differentiable, the druggability potential can be used as collective variable to rapidly detect cryptic druggable binding sites in proteins with a variety of MD free energy methods. Protocols for applications to flexible docking problems are outlined.

Exploring Cryptic Pockets Formation in Targets of Pharmaceutical Interest with SWISH

“…Thus hPNMT has been used to test other algorithms for cryptic pockets such as JEDI. 34 From 1HNN to 2G8N, the pocket volume increases when the protein is in complex with a selective inhibitor (3-Hydroxymethyl-1,2,3,4-tetrahydroisoquinoline or F83), which requires the displacement of the K57 side chain, and a small movement of the α3 helix (see Fig. 1 d left).…”

“…their hydrophobicity) such as JEDI are being actively developed, but they still require prior knowledge of the cavity location. 34 At the other end of the spectrum are machine learning approaches such as Cryptosite, a hidden sites identification tool. They show promise, but are limited by the scarce availability of experimentally-determined cryptic pockets and lack the atomic-level insight that MD-based approaches can provide.…”

Intrinsically Disordered Proteins as Drug Targets

“…10,34,71,72 These methods analyze the cavities over static structures coming from experiments or simulations such as DrugPred, 73 Cavity 74 or fpocket, 75 or coupled to MD simulations and calculate the druggability "on-the -fly", such as the recently developed JEDI. 76 Zhang and coworkers 44 have studied the ligand-binding cavities of diverse IDPs comparing some of their properties with those of ordered proteins. They concluded that IDPs are predicted to possess more binding cavities than ordered proteins of a similar length, showing different geometries.…”

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“…To that extent, usual CAAD techniques can be useful to estimate the druggability and the effects of small molecules on IDP interactions [10,34,71,72]. These methods analyze the cavities over static structures coming from experiments or simulations such as DrugPred [73], Cavity [74] or fpocket [75], or coupled to MD simulations and calculate the druggability "on-the -fly", such as the recently developed JEDI [76].…”