Druggability Assessment of Allosteric Proteins by Dynamics Simulations in the Presence of Probe Molecules

Druggability assessment of a target protein has emerged
in recent
years as an important concept in hit-to-lead optimization. A reliable
and physically relevant measure of druggability would allow informed
decisions on the risk of investing in a particular target. Here, we
define “druggability” as a quantitative estimate of
binding sites and affinities for a potential drug acting on a specific
protein target. In the present study, we describe a new methodology
that successfully predicts the druggability and maximal binding affinity
for a series of challenging targets, including those that function
through allosteric mechanisms. Two distinguishing features of the
methodology are (i) simulation of the binding dynamics of a diversity
of probe molecules selected on the basis of an analysis of approved
drugs and (ii) identification of druggable sites and estimation of
corresponding binding affinities on the basis of an evaluation of
the geometry and energetics of bound probe clusters. The use of the
methodology for a variety of targets such as murine double mutant-2,
protein tyrosine phosphatase 1B (PTP1B), lymphocyte function-associated
antigen 1, vertebrate kinesin-5 (Eg5), and p38 mitogen-activated protein
kinase provides examples for which the method correctly captures the
location and binding affinities of known drugs. It also provides insights
into novel druggable sites and the target’s structural changes
that would accommodate, if not promote and stabilize, drug binding.
Notably, the ability to identify high affinity spots even in challenging
cases such as PTP1B or Eg5 shows promise as a rational tool for assessing
the druggability of protein targets and identifying allosteric or
novel sites for drug binding.