Literature DB >> 24080467

Bioisosteric approach in designing new monastrol derivatives: an investigation on their ADMET prediction using in silico derived parameters.

Syed Fahad Hassan1, Umer Rashid, Farzana Latif Ansari, Zaheer Ul-Haq.   

Abstract

Medicinal chemists are facing an increasing challenge to deliver safer and more effective medicines. An appropriate balance between drug-like properties such as solubility, permeability, metabolic stability, efficacy and toxicity is one of the most challenging problems during lead optimization of a potential drug candidate. Insoluble and impermeable compounds can result in erroneous biological data and unreliable SAR in enzyme and cell-based assays. The weak inhibitory activity and non-drug-like properties of monastrol, the first small mitotic kinesin Eg5 inhibitor, has hampered its further development. In this investigation, a bioisosteric approach was applied that resulted in the replacement of C-5 carbonyl of monastrol with thio-carbonyl. Further lead optimization of drug-like properties was evaluated through in silico predictions by using ADMET predictor software. This minor structural modification resulted in upgraded human effective jejunal permeability (Peff) and improved permeability in Madin-Darby canine kidney (MDCK) cells. Furthermore, C-5 thiocarbonyl analogue of monastrol (named as Special-2) was found safe to administer orally with no phospholipidosis toxicity, no raised levels of serum glutamate oxaloacetate transaminase (SGOT) and no potential towards cardiotoxicity. Molecular docking study was also carried out to understand the binding modes of these compounds. The docking study showed high binding affinity of the designed compounds against KSP. Hence a combination of in silico ADMET studies and molecular docking can help to improve prediction success and these compounds might be act as potential candidate for KSP inhibition.
Copyright © 2013 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ADMET; Antimitotic; Bioisosterism; Kinesin spindle protein; Monastrol

Mesh:

Substances:

Year:  2013        PMID: 24080467     DOI: 10.1016/j.jmgm.2013.09.002

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


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