Alignment independent 3D-QSAR studies and molecular dynamics simulations for the identification of potent and selective S1P1 receptor agonists

Abstract

a b s t r a c tSphingosine 1-phosphate type 1 (S1P 1 ) receptors are expressed on lymphocytes and regulate immune cells trafficking. Sphingosine 1-phosphate and its analogues cause internalization and degradation of S1P 1 receptors, preventing the auto reactivity of immune cells in the target tissues. It has been shown that S1P 1 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 S1P 1 to be used in virtual screening of chemical libraries. The developed model for the S1P 1 receptor agonists showed appropriate power of predictivity in internal (r 2 acc 0.93 and SDEC 0.18) and external (r 2 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 S1P 1 receptor. To propose potential chemical entities with S1P 1 agonistic activity, PubChem chemicals database was searched and the selected compounds were virtually tested for S1P 1 receptor agonistic activity using the generated models, which resulted in four potential compounds with high potency and selectivity towards S1P 1 receptor. Moreover, the affinities of the identified compounds towards S1P 1 receptor were evaluated using molecular dynamics simulations. The results indicated that the binding energies of the compounds were in the range of À39.31 to À46.18 and À3.20 to À9.75 kcal mol À1 , 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 S1P 1 receptor agonists with potential use in diseases such as multiple sclerosis.

Identification of Novel Mutations in Arabidopsis thaliana DOF 4.2 Coding Gene

“…Translation of the obtained sequence showed that the mutation at position 19is silent while the two others have resulted in missense mutation at the positions 18 (S18G) and nonsense mutation of tryptophan at position 39to stop codon ( Figure 1). Previous studies have shown the variation of amino acid sequence of DOF 4.2-ZF MD simulations have been extensively used to virtually investigate proteinprotein/DNA and protein-small molecules interactions [27][28][29] . Different studies have used MD simulation based algorithms to report the interaction of DOF family proteins with DNA 26,30,31 .…”

“…MD simulations have been extensively used to virtually investigate protein-protein/DNA and protein-small molecules interactions. 27 - 29 Different studies have used MD simulation based algorithms to report the interaction of DOF family proteins with DNA. 26 , 30 , 31 Pandey et al explored the DNA binding ability of DOF domain from wheat showing that single K29R mutation could adversely affect its binding capability.…”

Drug Repurposing for Identification of S1P1 agonists with Potential Application in Multiple Sclerosis Using in Silico Drug Design Approaches

“…Using GOLD program, these 21 S1P 1 agonists were docked into S1P 1 according to the procedure explained in our previous work. 19 The binding site for docking was determined based on the coordinates of an inhibitor (namely ML056) co-crystallized with the S1P 1 (PDB ID:3V2Y). ChemPLP scoring function was used for carrying out docking process.…”

Three-Dimensional Quantitative Structure and Activity Relationship of Flavones on Their Hypochlorite Scavenging Capacity

“…The method developed by Roy et al in DTC Lab 39,40 (https:// dtclab.webs.com/software-tools) was applied for the calculation of applicability domain.…”