Probing the binding mechanism of substituted pyridine derivatives as effective and selective lysine-specific demethylase 1 inhibitors using 3D-QSAR, molecular docking and molecular dynamics simulations

<p>Lysine-specific demethylase 1 (LSD1) was regarded as a promising anticancer target for the novel drug discovery. In this work, we carried out a molecular modeling study on the substituted pyridine derivatives as LSD1 inhibitors using three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations. Molecular docking studies predicted the probable binding mode of ligands, and suggested Lys661 and Asp555 might be key residues. Our 3D-QSAR models exhibited satisfactory internal and external predicted capacity. For the comparative molecular field analysis (CoMFA) model, its training set had of 0.595 and of 0.959, while test set had of 0.512 and of 0.846. For the best comparative molecular similarity indices analysis (CoMSIA) model, its training set had of 0.733 and of 0.982, while test set had of 0.695 and of 0.922. MD simulations result revealed the detailed binding process and found an important conserved water-bridge motif between ligands and protein. The binding free energies calculation using Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) approach coincided well with the experimental bioactivity and demonstrated that the electrostatic interaction was the major driving force for binding. The energy decomposition pointed out some significant residues (Asp555, Lys661, Trp695, Tyr761 and FAD) for the LSD1 potency increase. Based on these results, five new inhibitors were designed, and their activities were predicted using our 3D-QSAR models.</p> <p>Communicated by Ramaswamy H. Sarma</p> <p>Abbreviations3D-QSAR</p><p>three-dimensional quantitative structure-activity relationship</p>AD<p>applicability domain</p>AML<p>acute myeloid leukemia</p>CoMFA<p>Comparative molecular field analysis</p>CoMSIA<p>Comparative molecular similarity indices analysis</p>DNMTs<p>DNA methyltransferases</p>E2F1<p>E2F transcription factor 1</p>ESP<p>Electrostatic potentials</p>FAD<p>Flavin adenine dinucleotide</p>GAFF<p>General Amber force field</p>H3K4<p>Histone 3 lysine 4</p>H3K9<p>Histone 3 lysine 9</p>LOO<p>Leave-one-out</p>LSD1<p>Lysine-specific demethylase 1</p>MAO-A<p>Monoamine oxidase A</p>MAO-B<p>Monoamine oxidase B</p>MAE<p>Mean absolute error</p>MD<p>Molecular dynamics</p>MLL<p>mixed lineage leukemia</p>MM-PBSA<p>Molecular Mechanics Poisson–Boltzmann Surface Area</p>PLS<p>Partial least square</p>PME<p>Particle Mesh Ewald</p>RMSD<p>Root-mean square deviation</p>RMSE<p>Root-mean square error</p>RMSF<p>Root-mean-square fluctuations</p>SASA<p>Solvent accessible surface area</p>SEE<p>Standard error of estimate</p>TCP<p>Tranylcypromine</p><p></p> <p>three-dimensional quantitative structure-activity relationship</p> <p>applicability domain</p> <p>acute myeloid leukemia</p> <p>Comparative molecular field analysis</p> <p>Comparative molecular similarity indices analysis</p> <p>DNA methyltransferases</p> <p>E2F transcription factor 1</p> <p>Electrostatic potentials</p> <p>Flavin adenine dinucleotide</p> <p>General Amber force field</p> <p>Histone 3 lysine 4</p> <p>Histone 3 lysine 9</p> <p>Leave-one-out</p> <p>Lysine-specific demethylase 1</p> <p>Monoamine oxidase A</p> <p>Monoamine oxidase B</p> <p>Mean absolute error</p> <p>Molecular dynamics</p> <p>mixed lineage leukemia</p> <p>Molecular Mechanics Poisson–Boltzmann Surface Area</p> <p>Partial least square</p> <p>Particle Mesh Ewald</p> <p>Root-mean square deviation</p> <p>Root-mean square error</p> <p>Root-mean-square fluctuations</p> <p>Solvent accessible surface area</p> <p>Standard error of estimate</p> <p>Tranylcypromine</p>