Virtual screening against Mycobacterium tuberculosis dihydrofolate reductase: Suggested workflow for compound prioritization using structure interaction fingerprints

Abstract

In this study, we suggest a new workflow for the identification and prioritization of potential compounds targeted against Mycobacterium tuberculosis dihydrofolate reductase, an important folate cycle enzyme and a validated target for the development of anti-tubercular agents. First, we have performed an integrated pharmacophore and structure-based virtual screening using Maybridge small molecule database, subsequently interaction patterns from known actives to the receptor were applied for scoring and ranking the virtual screening hits using structure interaction fingerprint (SIFt)-based similarity approach. In addition, agglomerative hierarchical clustering of the structure interaction fingerprints permits the easy separation of active from inactive binding modes. Using this approach we screened 59275 Maybridge compounds and 20 compounds were prioritized as promising virtual screening hits. Though using a receptor interaction scoring approach, the results were not biased toward the chemical classes of the known actives and the proposed compounds were structurally diverse with low molecular weights and structural complexities. Our results suggest that structure-based virtual screening coupled with the SIFt should be a valuable tool for prioritization of virtual screening hits.