Development and Validation of Molecular Overlays Derived from Three-Dimensional Hydrophobic Similarity with PharmScreen

Abstract

Molecular alignment is a standard procedure for three-dimensional (3D) similarity measurements and pharmacophore elucidation. This process is influenced by several factors, such as the physicochemical descriptors utilized to account for the molecular determinants of biological activity and the reference templates. Relying on the hypothesis that the maximal achievable binding affinity for a drug-like molecule is largely due to desolvation, we explore a novel strategy for 3D molecular overlays that exploits the partitioning of molecular hydrophobicity into atomic contributions in conjunction with information about the distribution of hydrogen-bond (HB) donor/acceptor groups. A brief description of the method, as implemented in the software package PharmScreen, including the derivation of the fractional hydrophobic contributions within the quantum mechanical version of the Miertus-Scrocco-Tomasi (MST) continuum model, and the procedure utilized for the optimal superposition between molecules, is presented. The computational procedure is calibrated by using a data set of 402 molecules pertaining to 14 distinct targets taken from the literature and validated against the AstraZeneca test, which comprises 121 experimentally derived sets of molecular overlays. The results point out the suitability of the MST-based hydrophobic parameters for generating molecular overlays, as correct predictions were obtained for 94%, 79%, and 54% of the molecules classified into easy, moderate, and hard sets, respectively. Moreover, the results point out that this accuracy is attained at a much lower degree of identity between the templates used by hydrophobic/HB fields and electrostatic/steric ones. These findings support the usefulness of the hydrophobic/HB descriptors to generate complementary overlays that may be valuable to rationalize structure-activity relationships and for virtual screening campaigns.

Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches

“…Accordingly, the relationships between compounds in a given library and one or more known actives are examined by similarity measurements using suitable molecular descriptors. These measurements can be performed based on 1D and 2D descriptors, generally encoding information about the chemical nature of compounds and their topological features [ 25 , 26 , 27 ], and 3D descriptors associated to molecular fields [ 28 , 29 , 30 , 31 ], shape and volume [ 32 , 33 ], and pharmacophores [ 28 , 34 ].…”

RM1 Semiempirical Model: Chemistry, Pharmaceutical Research, Molecular Biology and Materials Science

“…Choice of this level of theory was motivated by its low computational cost compared to ab initio methods". 64 The authors compared the performances of MST/RM1 and MST/B3LYP to evaluate the effects of the method to calculate the hydrophobic contributions, having obtained similar results. In conclusion, the authors mentioned: "Therefore, these findings support the suitability of the semiempirical RM1 Hamiltonian, which offers a much better balance between overlay accuracy and computational expensiveness".…”

“…The RM1 UME for all lanthanides, now range from a minimum of 0.04 Å for Dy III , 39 Ho III39 and Er III39 to 0.08 Å for Ce III , 39 Yb III37 and Lu III trivalent ions. 37 Recently, Vázquez et al 64 reported a strategy for "3D molecular overlays that exploits the partitioning of molecular hydrophobicity into atomic contributions in conjunction with information about the distribution of hydrogen-bond (HB)". This method was implemented in the PharmScreen software, and the authors added the derivation of the fractional hydrophobic contributions that included a quantum mechanical version of the MST continuum model.…”

“…This method was implemented in the PharmScreen software, and the authors added the derivation of the fractional hydrophobic contributions that included a quantum mechanical version of the MST continuum model. 64 The authors commented that the choice of implementing their strategy in RM1 was due to this model's low computational demand: "The hydrophobic descriptors were obtained by using the MST solvation model parameterized for the semiempirical Hamiltonian RM1. Choice of this level of theory was motivated by its low computational cost compared to ab initio methods".…”

“…In conclusion, the authors mentioned: "Therefore, these findings support the suitability of the semiempirical RM1 Hamiltonian, which offers a much better balance between overlay accuracy and computational expensiveness". 64…”