Abstract
We propose a numerical framework that permits an effective atlas-like representation of chemico-biological space based on a series of Cartesian planes mapping the ligands with the corresponding targets connected by an affinity parameter (K(i) or related). The numerical framework is derived from the concept of ligand efficiency indices, which provide a natural coordinate system combining the potency toward the target (biological space) with the physicochemical properties of the ligand (chemical space). This framework facilitates navigation in the multidimensional drug discovery space using map-like representations based on pairs of combined variables related to the efficiency of the ligands per Dalton (molecular weight or number of non-hydrogen atoms) and per unit of polar surface area (or number of polar atoms).
Highlights
Successful drug discovery requires the optimization of a large number of variables in two different domains: chemical and biological
We briefly summarize the earlier concepts used to navigate chemical space and present an algebraic framework based on ligand efficiency indices (LEIs) that permits an intuitive, graphical, representation of the combined Chemico-Biological Space (CBS)
We propose that an effective use of the concept of LEIs in the future should require the use of multiple non-redundant variables, within a numerical formulation that uses similar numerical scales
Summary
Successful drug discovery requires the optimization of a large number of variables in two different domains: chemical and biological. An example of the distribution of target:ligand pairs in the 2007 version of PDBBind using variables NSEI-NBEI is shown in the supplementary material (section I, Fig. S1b).
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