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Iram Khan Iqbal

Researcher at Council of Scientific and Industrial Research

Publications -  5
Citations -  114

Iram Khan Iqbal is an academic researcher from Council of Scientific and Industrial Research. The author has contributed to research in topics: NAD+ kinase & Acetylation. The author has an hindex of 3, co-authored 4 publications receiving 67 citations.

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Journal ArticleDOI

Bioenergetics of Mycobacterium: An Emerging Landscape for Drug Discovery

TL;DR: Inhibitors of oxidative phosphorylation can synergize with frontline TB drugs to shorten the course of treatment and play a critical role in the survival of persisters.
Journal ArticleDOI

Imaging the NADH:NAD+ Homeostasis for Understanding the Metabolic Response of Mycobacterium to Physiologically Relevant Stresses.

TL;DR: Reported strains capable of measuring the metabolic state of Mtb cells in vitro and in vivo with spatio-temporal resolution are generated and it is believed that this tool will facilitate further studies on mycobacterial physiology and will create new avenues of research for anti-tuberculosis drug discovery.
Journal ArticleDOI

Hydrogen sulfide-induced GAPDH sulfhydration disrupts the CCAR2-SIRT1 interaction to initiate autophagy

TL;DR: In this paper, hydrogen sulfide (H2S) sulfhydrates the active site cysteine of the glycolytic enzyme GAPDH (glyceraldehyde-3-phosphate dehydrogenase).
Book ChapterDOI

Quantification of the Metabolic Heterogeneity in Mycobacterial Cells Through the Measurement of the NADH/NAD+ Ratio Using a Genetically Encoded Sensor

TL;DR: This chapter describes the details of a method used in the generation of reporter strains for the measurement of the NADH/NAD+ ratio in mycobacteria, and believes that such reporter stains can be used in novel screens for small molecules that could alter the metabolism of bacterial cells and thus aid in the development of new class of therapeutic agents.
Journal ArticleDOI

Orally Bioavailable CBP and p300 Selective Degraders for the Treatment of AR- and ER-dependent Cancers

TL;DR: In this article , a ternary complex modeling algorithm, ALMOND (ALgorithm for MOdeling Neo substrate Degraders) was used to identify structurally unique highly selective CBP/p300 degraders, which were further optimized for potency, selectivity and ADME properties.