Virtual screening and prediction of the molecular mechanism of bioactive compounds in silico
Bashir Akhlaq Akhoon, Krishna Pal Singh, Madhumita Karmakar, Suchi Smita, Rakesh Pandey, Shailendra K. Gupta · 2015
This chapter focuses on the virtual screening techniques for the prediction of bioactive compounds using various in silico methods. Administration of docking, pharmacophore, and QSAR-based virtual screening methods would be a cost-effective strategy to envisage novel therapeutic bioactive molecules. The principal success of virtual screening lies in its potential to remove the bulk of inactive compounds, rather than to select bioactive molecules for a specified target. However, the development of advanced virtual screening programs leading to higher prediction accuracy and greater reliability has shown the potential to predict compounds that exhibit the intended biological activity. In this chapter, we have reported various available docking-based programs that are helpful in selecting or screening of biologically active compounds using different commonly available databases. We have also shown how QSAR can be used as a virtual screening tool to predict and rank the bioactivity of the molecules. Moreover, we also included some pharmacophore-based case studies accomplished in our own lab to reflect how such a strategy can be applied to predict the bioactivity of the chosen molecule toward the specified process. Since there are several pitfalls in the scoring functions, the consensus approach that will combine all the available three methods would be more beneficial to get the actual leads.