Validity of ligand efficiency metrics.

A recent viewpoint article (Improving the plausibility of success with inefficient metrics. ACS Med. Chem. Lett. 2014, 5, 2-5) argued that the standard definition of ligand efficiency (LE) is mathematically invalid. In this viewpoint, we address this criticism and show categorically that the definition of LE is mathematically valid. LE and other metrics such as lipophilic ligand efficiency (LLE) can be useful during the multiparameter optimization challenge faced by medicinal chemists.

Lead optimization using matched molecular pairs: inclusion of contextual information for enhanced prediction of HERG inhibition, solubility, and lipophilicity.

Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the effect of a substructural transformation on a molecular property is independent of the context (i.e., the local structural environment in which that transformation occurs). Experiments with large sets of hERG, solubility, and lipophilicity data demonstrate that the inclusion of contextual information can enhance the predictive power of MMP analyses, with significant trends (both positive and negative) being identified that are not apparent when using conventional, context-independent approaches.

GALAHAD: 1. pharmacophore identification by hypermolecular alignment of ligands in 3D.

Alignment of multiple ligands based on shared pharmacophoric and pharmacosteric features is a long-recognized challenge in drug discovery and development. This is particularly true when the spatial overlap between structures is incomplete, in which case no good template molecule is likely to exist. Pair-wise rigid ligand alignment based on linear assignment (the LAMDA algorithm) has the potential to address this problem (Richmond et al. in J Mol Graph Model 23:199-209, 2004). Here we present the version of LAMDA embodied in the GALAHAD program, which carries out multi-way alignments by iterative construction of hypermolecules that retain the aggregate as well as the individual attributes of the ligands. We have also generalized the cost function from being purely atom-based to being one that operates on ionic, hydrogen bonding, hydrophobic and steric features. Finally, we have added the ability to generate useful partial-match 3D search queries from the hypermolecules obtained. By running frozen conformations through the GALAHAD program, one can utilize the extended version of LAMDA to generate pharmacophores and pharmacosteres that agree well with crystal structure alignments for a range of literature datasets, with minor adjustments of the default parameters generating even better models. Allowing for inclusion of partial match constraints in the queries yields pharmacophores that are consistently a superset of full-match pharmacophores identified in previous analyses, with the additional features representing points of potentially beneficial interaction with the target.

Unsupervised 3D ring template searching as an ideas generator for scaffold hopping: use of the LAMDA, RigFit, and field-based similarity search (FBSS) methods.

Crystal structures taken from the Cambridge Structural Database were used to build a ring scaffold database containing 19 050 3D structures, with each such scaffold then being used to generate a centroid connecting path (CCP) representation. The CCP is a novel object that connects ring centroids, ring linker atoms, and other important points on the connection path between ring centroids. Unsupervised searching in the scaffold and CCP data sets was carried out using the atom-based LAMDA and RigFit search methods and the field-based similarity search method. The performance of these methods was tested with three different ring scaffold queries. These searches demonstrated that unsupervised 3D scaffold searching methods can find not only the types of ring systems that might be retrieved in carefully defined pharmacophore searches (supervised approach) but also additional, structurally diverse ring systems that could form the starting point for lead discovery programs or other scaffold-hopping applications. Not only are the methods effective but some are sufficiently rapid to permit scaffold searching in large chemical databases on a routine basis.

Alignment of three-dimensional molecules using an image recognition algorithm.

This paper describes a novel approach, based on image recognition in two dimensions, for the atom-based alignment of two rigid molecules in three dimensions. The atoms are characterised by their partial charges and their positions relative to the remaining atoms in the molecule. Based on this information, a cost of matching a pair of atoms, one from each molecule, is assigned to all possible pairs. A preliminary set of intermolecular atom equivalences that minimises the total atom matching cost is then determined using an algorithm for solving the linear assignment problem. Several geometric heuristics are described that aim to reduce the number of atom equivalences that are inconsistent with the 3D structures. Those that remain are used to calculate an alignment transformation that achieves an optimal superposition of atoms that have a similar local geometry and partial charge. This alignment is then refined by calculating a new set of equivalences consisting of atom pairs that are approximately overlaid, irrespective of partial charge. A range of examples is provided to demonstrate the efficiency and effectiveness of the method.