Alignment independent 3D-QSAR studies and molecular dynamics simulations for the identification of potent and...

Sphingosine 1-phosphate type 1 (S1P₁) receptors are expressed on lymphocytes and regulate immune cells trafficking. Sphingosine 1-phosphate and its analogues cause internalization and degradation of S1P₁ receptors, preventing the auto reactivity of immune cells in the target tissues. It has been shown that S1P₁ receptor agonists such as fingolimod can be suitable candidates for treatment of autoimmune diseases. The current study aimed to generate GRIND-based 3D-QSAR predictive models for agonistic activities of 2-imino-thiazolidin-4-one derivatives on S1P₁ to be used in virtual screening of chemical libraries. The developed model for the S1P₁ receptor agonists showed appropriate power of predictivity in internal (r²_acc 0.93 and SDEC 0.18) and external (r² 0.75 and MAE (95% data), 0.28) validations. The generated model revealed the importance of variables DRY-N1 and DRY-O in the potency and selectivity of these compounds towards S1P₁ receptor. To propose potential chemical entities with S1P₁ agonistic activity, PubChem chemicals database was searched and the selected compounds were virtually tested for S1P₁ receptor agonistic activity using the generated models, which resulted in four potential compounds with high potency and selectivity towards S1P₁ receptor. Moreover, the affinities of the identified compounds towards S1P₁ receptor were evaluated using molecular dynamics simulations. The results indicated that the binding energies of the compounds were in the range of -39.31 to -46.18 and -3.20 to -9.75 kcal mol^-1, calculated by MM-GBSA and MM-PBSA algorithms, respectively. The findings in the current work may be useful for the identification of potent and selective S1P₁ receptor agonists with potential use in diseases such as multiple sclerosis.