Identification of potential inhibitors against nuclear Dam1 complex subunit Ask1 of Candida albicans using virtual screening and MD simulations. (February 2018)

• Record Type: Journal Article
• Authors: Tripathi, Himanshu; Khan, Feroz
• Is Part Of: Computational biology and chemistry. Volume 72(2018)
• Page Start: 33
• Page End: 44
• Publication Date: 2018-02
• Subjects: Protein modeling -- MM-PBSA -- virtual screening -- Dam1 complex -- molecular docking -- Antifungal -- Drug; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2017.12.013
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Identified potential inhibitors of Dam1 complex subunit Ask1 of C. albicans by using clustering, virtual screening, docking & MD simulations. Developed ab-initio 3D model of C. albicans target protein Dam1 complex subunit Ask1. Identified D4 domain binding site of Ask1 model and its native conformation through 300 ns MD simulation & FEL analysis. Identified Sclerotiamide (CID:10647785), (+)-Stephacidin A (CID:16127922), (+)-Notoamide B (CID:16127923), Notoamide R (CID:46919488), and Avrainvillamide (CID:11719255) as potential inhibitors of C. albicans Ask1 subunit of Dam1 complex. Hypothesized cell division inhibition mechanism of hit compounds by interfering with chromosomal segregation. Abstract: Identification of hit compounds against specific target form the starting point for a drug discovery program. A consistent decline of new chemical entities (NCEs) in recent years prompted a challenge to explore newer approaches to discover potential hit compounds that in turn can be converted into leads, and ultimately drug with desired therapeutic efficacy. The vast amount of omics and activity data available in public databases offers an opportunity to identify novel targets and their potential inhibitors. State of the art in silico methods viz ., clustering of compounds, virtual screening, molecular docking, MD simulations and MMPBSA calculations were employed in a pipeline to identify potential 'hits' against those targets as well whose structures, as of now, could only predict through threading approaches. In the present work, we have started from scratch, amino acid sequence of target and compounds retrieved from PubChem compound database, modeled it in such a way that led to the identification of possible inhibitors of Dam1 complex subunit Ask1 of Candida albicans . We also propose a ligand based binding site determination approach. We have identified potential inhibitors of Ask1 subunit of a Dam1 complex of C. albicans, which is required to prevent precocious spindle elongation in pre-mitotic phases. The proposed scheme may aid to find virtually potential inhibitors of other unique targets against candida.