How nice would it be to be able to draw a molecule in your favourite 2D sketcher, and see in real time how its 3D electrostatic potential looks like, what interactions it makes in the active site, how its shape and electrostatics compare to a known active? This is why we decided to build from ground up a new molecular design platform around this engaging idea. As we started fleshing out the details of the algorithm, a number of obvious and more subtle gotchas emerged. While a ligand is being sketched on a 2D canvas, its 3D counterpart which is growing inside the protein active site should automatically adjust its torsion angles to pick up the most favourable contacts and avoid steric clashes. Where no crystal structures are available, there might be reference ligands with known affinity for the target to compare to. In either case, when an aromatic ring is decorated with an ortho or meta substituent, the algorithm should put it on the right side of the 3D structure, in order to best fit the pocket or to mimic the reference ligand. Where relevant, the same paradigm should apply to the cis/trans geometry of double bonds and to the stereochemistry of tetrahedral centres, if unspecified. All these actions should take place with as little intervention from the user as possible. A single 2D change such as switching a bond from wedged to dashed or converting a carbonyl group into a sulfoxide in the middle of a molecule may have a dramatic leverage on its 3D pose, requiring a complete reassessment. Adding or removing a single bond may break a molecule into two separate fragments, or suddenly attach a large, previously disconnected moiety. Similar disruptive actions include the cyclization of a linear chain, the breakage of a ring, or changes in hybridization. While drawing a molecule in 2D, we often go through a number of chemically invalid states: e.g., to draw a sulfonyl group, we may start from a gem-diol, turn it into a gem-dicarbonyl monster, and finally convert the carbon atom into a sulfur. Likewise, we most often draw a tetravalent nitrogen before adding a positive formal charge. The algorithm must cope with such invalid intermediates. In this talk we will illustrate how we addressed the challenge of providing immediate 3D poses from 2D sketches in our Grow3D algorithm. We will also give an overview of the integration of Grow3D in the context of our molecular design platform, showing its effectiveness in bridging the gap between 2D and 3D methods.

Design in 2D, model in 3D: Live 3D pose generation from 2D sketches

2019 Fall National Meeting

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