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

Abstract

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.

Antiproliferative Agents That Interfere with the Cell Cycle at the G1→S Transition: Further Development and Characterization of a Small Library of Stilbene‐Derived Compounds

“…GALAHAD aligns molecules and generates pharmacophore hypotheses in the form of hypermolecules incorporating the structural information of the dataset. [32,33] The core computational methodology of GALAHAD is a genetic algorithm that operates on a set of individual models in which each model is defined by a set of torsions for each molecule in the dataset. The pharmacophore is obtained through a procedure whereby the program first identifies corresponding features in ligands paired on the basis of structural similarity, then aligns the conformations in Cartesian space and merges the ligands into a single hypermolecule.…”

Subunit-Selective Mutational Analysis and Tissue Culture Evaluations of the Interactions of the E138K and M184I Mutations in HIV-1 Reverse Transcriptase

“…For ETR, 20 mutations, including V90I, A98G, L100I, K101E/H/P, V106I, E138A/G/K/Q, V179D/ F/T, Y181C/I/V, G190S/A, and M230L, have been identified as resistance-associated mutations (RAMs) (43), while 15 mutations, including K101E/P, E138A/G/K/Q/R, V179L, Y181C/I/V, H221Y, F227C, and M230I/L, have been recognized as RAMs for RPV (26). However, the degree of resistance conferred by each of these mutations can be variable, and studies on recombinant HIV-1 RT enzymes and HIV-1 infectious clones have demonstrated, for example, that the G190A mutation does not affect susceptibility to ETR (53).…”

Molecular Characterization of CYP2B6 Substrates

“…Our attempts to update the Catalyst models with new data and utilize excluded volumes have been unsuccessful to this point and this could be due to data variability or the inclusion of stereoisomers. We also attempted to use additional 3D-QSAR methods including GALAHAD [47] and a 4D-QSAR method [48] but were also unable to generate a significant model with these software tools, which further indicated the complexity perhaps inherent in this dataset (stereoselectivity and multiple pharmacophores). Our attempts with the pharmacophore software, Phase was partially successful, producing a pharmacophore with 2 hydrogen bonds and 2 hydrophobic areas, using 14 of the 21 training molecules (Fig 3C).…”