Improving the accuracy of ultrafast ligand-based screening: incorporating lipophilicity into ElectroShape as an extra dimension.

In a previous paper, we presented the ElectroShape method, which we used to achieve successful ligand-based virtual screening. It extended classical shape-based methods by applying them to the four-dimensional shape of the molecule where partial charge was used as the fourth dimension to capture electrostatic information. This paper extends the approach by using atomic lipophilicity (alogP) as an additional molecular property and validates it using the improved release 2 of the Directory of Useful Decoys (DUD). When alogP replaced partial charge, the enrichment results were slightly below those of ElectroShape, though still far better than purely shape-based methods. However, when alogP was added as a complement to partial charge, the resulting five-dimensional enrichments shows a clear improvement in performance. This demonstrates the utility of extending the ElectroShape virtual screening method by adding other atom-based descriptors.

ElectroShape: fast molecular similarity calculations incorporating shape, chirality and electrostatics.

We present ElectroShape, a novel ligand-based virtual screening method, that combines shape and electrostatic information into a single, unified framework. Building on the ultra-fast shape recognition (USR) approach for fast non-superpositional shape-based virtual screening, it extends the method by representing partial charge information as a fourth dimension. It also incorporates the chiral shape recognition (CSR) method, which distinguishes enantiomers. It has been validated using release 2 of the Directory of useful decoys (DUD), and shows a near doubling in enrichment ratio at 1% over USR and CSR, and improvements as measured by Receiver Operating Characteristic curves. These improvements persisted even after taking into account the chemotype redundancy in the sets of active ligands in DUD. During the course of its development, ElectroShape revealed a difference in the charge allocation of the DUD ligand and decoy sets, leading to several new versions of DUD being generated as a result. ElectroShape provides a significant addition to the family of ultra-fast ligand-based virtual screening methods, and its higher-dimensional shape recognition approach has great potential for extension and generalisation.

Molecular similarity including chirality.

This paper presents CSR, or Chiral Shape Recognition, a novel method to compute molecular similarity that builds on the Ultra-fast Shape Recognition (USR) method, but distinguishes enantiomers. It has great potential for generalisation, and was tested on the DUD dataset, where it was found a significant improvement in enrichment over USR having screened and ranked the top 0.25 %, 0.5 % and 1% of the database.