Probing the Druggability Limits for Enzymes of the NAD Biosynthetic Network in Glioma

Abstract

The biosynthesis of NAD constitutes an important metabolic module in the cell, since NAD is an essential cofactor involved in several metabolic reactions. NAD concentrations are known to be significantly increased in several cancers, particularly in glioma, consistent with the observation of up-regulation of several enzymes of the network. Modulating NAD biosynthesis in glioma is therefore an attractive therapeutic strategy. Here we report reconstruction of a biochemical network of NAD biosynthesis consisting of 22 proteins, 36 metabolites, and 86 parameters, tuned to mimic the conditions in glioma. Kinetic simulations of the network provide comprehensive insights about the role of individual enzymes. Further, quantitative changes in the same network between different states of health and disease enable identification of drug targets, based on specific alterations in the given disease. Through simulations of enzyme inhibition titrations, we identify NMPRTase as a potential drug target, while eliminating other possible candidates NMNAT, NAPRTase, and NRK. We have also simulated titrations of both binding affinities as well as inhibitor concentrations, which provide insights into the druggability limits of the target, a novel aspect that can provide useful guidelines for designing inhibitors with optimal affinities. Our simulations suggest that an inhibitor affinity of 10 nM used in a concentration range of 0.1 to 10 μM achieves a near maximal inhibition response for NMPRTase and that increasing the affinity any further is not likely to have a significant advantage. Thus, the quantitative appreciation defines a maximal extent of inhibition possible for a chosen enzyme in the context of its network. Knowledge of this type enables an upper affinity threshold to be defined as a goal in lead screening and refinement stages in drug discovery.

Identification of a co‐target for enhancing efficacy of sorafenib in HCC through a quantitative modeling approach

“…To capture a condition‐specific state of GSH net , transcriptome data of the condition was integrated into the model as described in Eqn , similar to that reported earlier . Briefly, we assumed that in a disease condition, there is no change in the catalytic activity of enzyme.…”

“…Mathematical modeling has proved to be an essential tool in understanding pathway dynamics in different patho/physiological scenarios . Modeling helps to capture the interplay between different players and facilitates the identification of key points of the pathway that can then be modulated as desired.…”

Optimización del ensayo de inhibición de la nicotinamida/ nicotinato mononucleótido adenililtransferasa de Leishmania braziliensis

“…El conocer los mecanismos mediante los cuales los seres vivos obtienen NAD es particularmente importante para comprender la relación entre su metabolismo y las alteraciones que conducen a enfermedades (Berger, et al, 2004). Las perturbaciones en la regulación de la síntesis del NAD derivan en deficiencias fatales para el organismo (Dolle, et al, 2013;Mao, et al, 2016;Padiadpu, et al, 2016;Sauve, 2008). Además, las particularidades de las rutas bioquímicas que involucran el NAD en organismos patógenos pueden considerarse como posibles blancos terapéuticos contra enfermedades infecciosas.…”