A leishmaniasis study: Structure-based screening and molecular dynamics mechanistic analysis for discovering potent inhibitors of spermidine synthase

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• 作者：Abhinav Grover ; Shashank Prakash Katiyar ; Sanjeev Kumar Singh ; Vikash Kumar Dubey ; Durai Sundar
• 关键词：Ld ; Leishmania donovani ; SS ; Spermidine synthase ; LSS ; Spermidine synthase of Leishmania donovani ; TSS ; Spermidine synthase of Trypanosoma cruzi ; HSS ; Spermidine synthase of human ; DFMO ; d ; l-¦Á-difluoromethylornithine ; ODC ; Ornithine decarboxylase ; MD ; M
• 刊名：Biochimica et Biophysica Acta - Proteins and Proteomics
• 出版年：2012
• 出版时间：December, 2012
• 年：2012
• 卷：1824
• 期：12
• 页码：1476-1483
• 全文大小：1040 K

文摘

Protozoa Leishmania donovani (Ld) is the main cause of the endemic disease leishmaniasis. Spermidine synthase (SS), an important enzyme in the synthetic pathway of polyamines in Ld, is an essential element for the survival of this protozoan. Targeting SS may provide an important aid for the development of drugs against Ld. However, absence of tertiary structure of spermidine synthase of Leishmania donovani (LSS) limits the possibilities of structure based drug designing. Presence of the same enzyme in the host itself further challenges the drug development process. We modeled the tertiary structure of LSS using homology modeling approach making use of homologous X-ray crystallographic structure of spermidine synthase of Trypanosoma cruzi (TSS) (2.5 ? resolution). The modeled structure was stabilized using Molecular Dynamics simulations. Based on active site structural differences between LSS and human spermidine synthase (HSS), we screened a large dataset of compounds against modeled protein using Glide virtual screen docking and selected two best inhibitors based on their docking scores (? 10.04 and ? 13.11 respectively) with LSS and having least/no binding with the human enzyme. Finally Molecular Dynamics simulations were used to assess the dynamic stability of the ligand bound structures and to elaborate on the binding modes. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.