Alignment-independent technique for 3D QSAR analysis

Abstract

Molecular biochemistry is controlled by 3D phenomena but structure–activity models based on 3D descriptors are infrequently used for large data sets because of the computational overhead for determining molecular conformations. A diverse dataset of 146 androgen receptor binders was used to investigate how different methods for defining molecular conformations affect the performance of 3D-quantitative spectral data activity relationship models. Molecular conformations tested: (1) global minimum of molecules’ potential energy surface; (2) alignment-to-templates using equal electronic and steric force field contributions; (3) alignment using contributions “Best-for-Each” template; (4) non-energy optimized, non-aligned (2D > 3D). Aggregate predictions from models were compared. Highest average coefficients of determination ranged from RTest2 = 0.56 to 0.61. The best model using 2D > 3D (imported directly from ChemSpider) produced RTest2 = 0.61. It was superior to energy-minimized and conformation-aligned models and was achieved in only 3–7 % of the time required using the other conformation strategies. Predictions averaged from models built on different conformations achieved a consensus RTest2 = 0.65. The best 2D > 3D model was analyzed for underlying structure–activity relationships. For the compound strongest binding to the androgen receptor, 10 substructural features contributing to binding were flagged. Utility of 2D > 3D was compared for two other activity endpoints, each modeling a medium sized data set. Results suggested that large scale, accurate predictions using 2D > 3D SDAR descriptors may be produced for interactions involving endocrine system nuclear receptors and other data sets in which strongest activities are produced by fairly inflexible substrates.Electronic supplementary materialThe online version of this article (doi:10.1007/s10822-016-9909-0) contains supplementary material, which is available to authorized users.

Combined 3D-QSAR and Molecular Docking Analysis of Thienopyrimidine Derivatives as Staphylococcus aureus Inhibitors

“…Molecular alignment of compound is a capital step in the construction of 3D-QSAR models. 36 In the present study ligand-based alignment technique has been chosen in which a template molecule is first isolated over which remaining molecules are aligned, the compound1 was selected as a template and all other molecules were aligned based on the common structure.…”

An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors

“… 23 The highly expensive and time-consuming procedure of drug development requires the utilization of complementary in silico methods to cut-down the cost and time and increase the success rate. 11 In the current study we have used in silico QSAR approach based on alignment independent method to generate a 3D model for activity prediction of a set of FGFR2 inhibitors. One of the important issues in alignment independent 3D-QSAR calculations is the use of active conformation of the studied compounds.…”

“…In alignment-dependent analysis the studied compounds are required to be aligned with each other whereas in alignment free method there is no need for superpositioning of molecules prior to development of 3D models, which can be considered as an advantage. GRid-Independent Descriptors (GRIND) is one of the alignment-independent methods 10 , 11 in which molecular interaction fields (MIF) are used to describe the interaction energy between ligands and different types of probes. 12 Then data mining are performed on the pool of calculated descriptors according to their impact on the biological activity followed by calculating favorable and unfavorable interactions.…”

Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks

“…When these shifts for atom pairs in a molecule were combined with corresponding interatomic distances, the abstract pattern became 3 dimensional and in that way reflects that molecule's Cartesian 3D nature. Distances were calculated from 3D mol files using an in house program written in R and facilitated with R studio (Wilkes et al, 2016). NMR chemical shifts for atoms of interest for 13 C and 15 N were obtained in the Spectrus software package (ACD/Labs package, Toronto, Canada) and used as the electrostatic component of the SDAR molecular descriptors.…”