Typically, the more a drug molecule changes shape upon binding to its target, the weaker its interaction will be, and the weaker its functional biological (disease-modifying) effect. Hits and early-stage molecules in a drug discovery pipeline therefore often have many shapes in solution, only one or a few of which are the right shape to bind to the target. ‘Conformational design’ aims to make rational, precision changes to molecules so that they are the right shape for binding with the target (the bioactive conformation) for as much time as possible. C4XD are world-leaders in conformational design for drug discovery.
The ability to measure drug dynamic 3D-shapes using the Conformetrix proprietary technology greatly enables conformational design. When the desired bioactive conformation is known from protein X-ray crystallography data, simple comparison between the set of free drug dynamic shapes and the bioactive conformation immediately highlights and prioritises areas for redesign of the molecule (see upper figure). This is usefully done by displaying the measured conformetrics for a single rotatable bond with a circular histogram. Bonds where conformational adjustment is required to improve the binding affinity by training the free ligand’s conformational envelope towards the bioactive conformation are immediately obvious and provide clear rationales for medicinal chemistry decision making. These graphs further help distinguish different kinds of conformational design (modal, torsional or librational selection) and even indicate where molecules are too rigid and need to be made more flexible.
In some cases, the bioactive conformation is not known from protein X-ray crystallography data. In these cases, comparison of the local bond conformetrics of ligands from the same series with different affinities immediately identifies the conformational-affinity trend to follow. When two or more ligands with different scaffolds but overlapping pharmacophores are known, comparison of their global shapes allows the bioactive conformation to be rapidly and reliably determined, even without any protein 3D-shape data (see our article in J. Med. Chem). Many natural ligands (e.g. peptides) have high affinity and in these cases, they tend to have a small number of 3D-shapes, and this means they can be used to predict the binding pharmacophore with surprising accuracy. In this 3D-context, scaffold-hopping between series, and even from peptide to drug, becomes a relatively trivial exercise.
Off-target effects can also be specifically and rationally removed from a series using conformational design. In our orexin-1 programme, we were able to precisely measure the shapes required for binding to Ox-1 over the very similar Ox-2 target and thereby design highly selective (1000x fold) Ox-1 antagonists, even in the absence of protein 3D-data. Breakthroughs like this lead to safer drug molecules with much lower side-effect risk profiles, providing better and cleaner molecules for later drug development.
Free drug 3D-shape also has an impact on a range of other areas in drug discovery and development, including ADME, solid-state polymorphism and catalyst development. For example, polar surface area as a predictor for permeability is well known to be very dependent on the quality of conformational data used.
If you would like to know more about the importance of solution state free ligand 3D structures and how they can be used to transform the medicinal chemistry workflow please read our article 'Measurement, Interpretation and Use of Free Ligand Solution Conformations in Drug Discovery' in Progress in Medicinal Chemistry