An alignment‐independent 3D‐QSAR study on series of hydroxamic acid‐based tumor necrosis factor‐α converting enzyme inhibitors

Alizadeh, Ali; Hamzeh‐Mivehroud, Maryam; Sokouti, Babak; Dastmalchi, Siavoush

doi:10.1002/cem.2817

Cited by 5 publications

(1 citation statement)

References 46 publications

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“…Alignment-independent methods like GRIND overcome the problem with alignment and this method is widely used in SAR research. [26][27][28][29] Important positions around molecules (hot spots) are extracted from MIFs using AMANDA discretization algorithm. [30] Encoding of the filtered MIFs into GRIND variables was performed by the maximal auto-and cross-correlation (MACC2) algorithm.…”

Section: Molecular Similaritymentioning

confidence: 99%

Design, synthesis and biological evaluation of novel aryldiketo acids with enhanced antibacterial activity against multidrug resistant bacterial strains

Cvijetić

Verbić

Resende

et al. 2018

European Journal of Medicinal Chemistry

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Antimicrobial resistance (AMR) is a major health problem worldwide, because of ability of bacteria, fungi and viruses to evade known therapeutic agents used in treatment of infections. Aryldiketo acids (ADK) have shown antimicrobial activity against several resistant strains including Gram-positive Staphylococcus aureus bacteria. Our previous studies revealed that ADK analogues having bulky alkyl group in ortho position on a phenyl ring have up to ten times better activity than norfloxacin against the same strains. Rational modifications of analogues by introduction of hydrophobic substituents on the aromatic ring has led to more than tenfold increase in antibacterial activity against multidrug resistant Gram positive strains. To elucidate a potential mechanism of action for this potentially novel class of antimicrobials, several bacterial enzymes were identified as putative targets according to literature data and pharmacophoric similarity searches for potent ADK analogues. Among the seven bacterial targets chosen, the strongest favorable binding interactions were observed between most active analogue and S. aureus dehydrosqualene synthase and DNA gyrase. Furthermore, the docking results in combination with literature data suggest that these novel molecules could also target several other bacterial enzymes, including prenyl-transferases and methionine aminopeptidase. These results and our statistically significant 3D QSAR model could be used to guide the further design of more potent derivatives as well as in virtual screening for novel antibacterial agents.

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Section: Molecular Similaritymentioning

confidence: 99%

Design, synthesis and biological evaluation of novel aryldiketo acids with enhanced antibacterial activity against multidrug resistant bacterial strains

Cvijetić

Verbić

Resende

et al. 2018

European Journal of Medicinal Chemistry

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Computational explorations to gain insight into the structural features of TNF-α receptor I inhibitors

et al. 2018

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

Alizadeh

Jafari

Dastmalchi

2020

Journal of Molecular Graphics and Modelling

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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.

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An alignment‐independent 3D‐QSAR study on series of hydroxamic acid‐based tumor necrosis factor‐α converting enzyme inhibitors

Cited by 5 publications

References 46 publications

Design, synthesis and biological evaluation of novel aryldiketo acids with enhanced antibacterial activity against multidrug resistant bacterial strains

Design, synthesis and biological evaluation of novel aryldiketo acids with enhanced antibacterial activity against multidrug resistant bacterial strains

Computational explorations to gain insight into the structural features of TNF-α receptor I inhibitors

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

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