<i>In Silico</i> Exploration for Identifying Structure–Activity Relationship of MEK Inhibition and Oral Bioavailability for Isothiazole Derivatives

Melagraki, Georgia; Afantitis, Antreas; Sarimveis, Haralambos; Igglessi‐Markopoulou, Olga; Koutentis, P. A.; Kollias, George

doi:10.1111/j.1747-0285.2010.01029.x

Cited by 59 publications

(35 citation statements)

References 42 publications

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“…Details on the domain of applicability calculation are given in the literature. [52–57] To implement the domain of applicability calculation, we used the Enalos Domain–Similarity node.…”

Section: Methodsmentioning

confidence: 99%

Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL)

Melagraki¹,

Ntougkos²,

Rinotas³

et al. 2017

PLoS Comput Biol

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We present an in silico drug discovery pipeline developed and applied for the identification and virtual screening of small-molecule Protein-Protein Interaction (PPI) compounds that act as dual inhibitors of TNF and RANKL through the trimerization interface. The cheminformatics part of the pipeline was developed by combining structure–based with ligand–based modeling using the largest available set of known TNF inhibitors in the literature (2481 small molecules). To facilitate virtual screening, the consensus predictive model was made freely available at: http://enalos.insilicotox.com/TNFPubChem/. We thus generated a priority list of nine small molecules as candidates for direct TNF function inhibition. In vitro evaluation of these compounds led to the selection of two small molecules that act as potent direct inhibitors of TNF function, with IC50 values comparable to those of a previously-described direct inhibitor (SPD304), but with significantly reduced toxicity. These molecules were also identified as RANKL inhibitors and validated in vitro with respect to this second functionality. Direct binding of the two compounds was confirmed both for TNF and RANKL, as well as their ability to inhibit the biologically-active trimer forms. Molecular dynamics calculations were also carried out for the two small molecules in each protein to offer additional insight into the interactions that govern TNF and RANKL complex formation. To our knowledge, these compounds, namely T8 and T23, constitute the second and third published examples of dual small-molecule direct function inhibitors of TNF and RANKL, and could serve as lead compounds for the development of novel treatments for inflammatory and autoimmune diseases.

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Section: Methodsmentioning

confidence: 99%

Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL)

Melagraki¹,

Ntougkos²,

Rinotas³

et al. 2017

PLoS Comput Biol

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“…59 QSPR models were developed for modeling and predicting both MEK inhibitory activity and oral bioavailability of novel isothiazole-4-carboxamidines. 60 …”

Section: Discussionmentioning

confidence: 99%

Advances in computationally modeling human oral bioavailability

Wang

Hou

2015

Advanced Drug Delivery Reviews

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Although significant progress has been made in experimental high throughput screening (HTS) of ADME (absorption, distribution, metabolism, excretion) and pharmacokinetic properties, the ADME and Toxicity (ADME-Tox) in silico modeling is still indispensable in drug discovery as it can guide us to wisely select drug candidates prior to expensive ADME screenings and clinical trials. Compared to other ADME-Tox properties, human oral bioavailability (HOBA) is particularly important but extremely difficult to predict. In this paper, the advances in human oral bioavailability modeling will be reviewed. Moreover, our deep insight on how to construct more accurate and reliable HOBA QSAR and classification models will also discussed.

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“…Many approaches were proposed to estimate AD, for instance based on descriptor ranges, Euclidean distance or probability density, each having their pros and cons. In this study, we implemented the Euclidean distance approach using the KNIME [73] node APD [74, 75] to evaluate if the test sets are within the AD of the training set.…”

Section: Methodsmentioning

confidence: 99%

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

Jain

Grandits

Richter

et al. 2017

J Comput Aided Mol Des

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The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein–ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein–ligand interactions.Electronic supplementary materialThe online version of this article (doi:10.1007/s10822-017-0021-x) contains supplementary material, which is available to authorized users.

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In Silico Exploration for Identifying Structure–Activity Relationship of MEK Inhibition and Oral Bioavailability for Isothiazole Derivatives

Cited by 59 publications

References 42 publications

Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL)

Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL)

Advances in computationally modeling human oral bioavailability

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

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