Pathway-based Screening Strategy for Multitarget Inhibitors of Diverse Proteins in Metabolic Pathways

Abstract

Many virtual screening methods have been developed for identifying single-target inhibitors based on the strategy of “one–disease, one–target, one–drug”. The hit rates of these methods are often low because they cannot capture the features that play key roles in the biological functions of the target protein. Furthermore, single-target inhibitors are often susceptible to drug resistance and are ineffective for complex diseases such as cancers. Therefore, a new strategy is required for enriching the hit rate and identifying multitarget inhibitors. To address these issues, we propose the pathway-based screening strategy (called PathSiMMap) to derive binding mechanisms for increasing the hit rate and discovering multitarget inhibitors using site-moiety maps. This strategy simultaneously screens multiple target proteins in the same pathway; these proteins bind intermediates with common substructures. These proteins possess similar conserved binding environments (pathway anchors) when the product of one protein is the substrate of the next protein in the pathway despite their low sequence identity and structure similarity. We successfully discovered two multitarget inhibitors with IC50 of <10 µM for shikimate dehydrogenase and shikimate kinase in the shikimate pathway of Helicobacter pylori. Furthermore, we found two selective inhibitors (IC50 of <10 µM) for shikimate dehydrogenase using the specific anchors derived by our method. Our experimental results reveal that this strategy can enhance the hit rates and the pathway anchors are highly conserved and important for biological functions. We believe that our strategy provides a great value for elucidating protein binding mechanisms and discovering multitarget inhibitors.

Alternative splicing in human cancer cells is modulated by the amiloride derivative 3,5‐diamino‐6‐chloro‐N‐(N‐(2,6‐dichlorobenzoyl)carbamimidoyl)pyrazine‐2‐carboxide

“…After identifying these potential target proteins, we integrated molecular docking (GEMDOCK, Yang and Chen, ) and statistically analyzed thousands of docked poses for site‐moiety maps (SiMMaps, Chen et al ., ) to further investigate and evaluate their binding environments. Our previous studies have shown that GEMDOCK has a similar performance to other docking methods (Ewing et al ., ; Kramer et al ., ) and was successfully used to identify novel inhibitors and binding sites (Chin et al ., ; Hsu et al ., , ; Yang et al ., ). An anchor of a SiMMap possesses three properties: a binding subpocket with interacting residues, the moiety composition of screening compounds, and the pocket–moiety interaction type (electrostatic, hydrogen‐bonding, or vdW).…”

Identification of Novel Polyphenolic Inhibitors of Shikimate Dehydrogenase (AroE)

“…2 While a number of studies have sought to identify inhibitors of other enzymes in the pathway, [3][4][5][6][7][8][9] a relatively small number of compounds have been identified that block the pathway's fourth reaction, the NADPH-dependent conversion of 3-dehydroshikimate to shikimate. [10][11][12] This reaction is catalyzed by shikimate dehydrogenase (AroE). 1 Here, we have designed an in vitro screen to evaluate the ability of compounds from a combined library of more than 5500 small molecules to inhibit the AroE enzyme from the bacterium, Pseudomonas putida (PpAroE).…”

Pharmacophore anchor models of flaviviral NS3 proteases lead to drug repurposing for DENV infection

“…To demonstrate the use of PA/CPA models in drug discovery, we proposed an integrated anchor-based virtual screening method which employed pharmacophore anchors from the models in virtual screening to discover true inhibitor hits (Methods: Integrated anchor-based screening approach). Our previous studies showed the applicability of anchors to identify true hit compounds [ 33 , 34 ]. Here, we employed this strategy against DENV NS3 protease for screening of FDA drug dataset (Methods: Proteins-compound datasets).…”