Browsing by Author "Yadav, Archana"

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KIXBASE: A comprehensive web resource for identification and exploration of KIX domains
(Nature Publishing Group, 2017) Yadav, Archana; Thakur, Jitendra K.; Yadav, Gitanjali
The KIX domain has emerged in the last two decades as a critical site of interaction for transcriptional assembly, regulation and gene expression. Discovered in 1994, this conserved, triple helical globular domain has been characterised in various coactivator proteins of yeast, mammals and plants, including the p300/CBP (a histone acetyl transferase), MED15 (a subunit of the mediator complex of RNA polymerase II), and RECQL5 helicases. In this work, we describe the first rigorous meta analysis of KIX domains across all forms of life, leading to the development of KIXBASE, a predictive web server and global repository for detection and analysis of KIX domains. To our knowledge, KIXBASE comprises the largest online collection of KIX sequences, enabling assessments at the level of both sequence and structure, incorporating PSIPRED and MUSTER at the backend for further annotation and quality assessment. In addition, KIXBASE provides useful information about critical aspects of KIX domains such as their intrinsic disorder, hydrophobicity profiles, functional classification and annotation based on domain architectures. KIXBASE represents a significant enrichment of the currently annotated KIX dataset, especially in the plant kingdom, thus highlighting potential targets for biochemical characterization. The KIX webserver and database are both freely available to the scientific community, at http://www.nipgr.res.in/kixbase/home.php
Molecular recognition by the KIX domain and its role in gene regulation
(Oxford University Press, 2014) Thakur, Jitendra K.; Yadav, Archana; Yadav, Gitanjali
The kinase-inducible domain interacting (KIX) domain is a highly conserved independently folding three-helix bundle that serves as a docking site for transcription factors, whereupon promoter activation and target specificity are achieved during gene regulation. This docking event is a harbinger of an intricate multi-protein assembly at the transcriptional apparatus and is regulated in a highly precise manner in view of the critical role it plays in multiple cellular processes. KIX domains have been characterized in transcriptional coactivators such as p300/CREB-binding protein and mediator of RNA polymerase II transcription subunit 15, and even recQ protein-like 5 helicases in various organisms. Their targets are often intrinsically disordered regions within the transactivation domains of transcription factors that attain stable secondary structure only upon complexation with KIX. In this article, we review the KIX domain in terms of its sequence and structure and present the various implications of its ability to act as a transcriptional switch, the mechanistic basis of molecular recognition by KIX, its binding specificity, target promiscuity, combinatorial potential and unique mode of regulation via allostery. We also discuss the possible roles of KIX domains in plants and hope that this review will accelerate scientific interest in KIX and pave the way for novel avenues of research on this critical domain.
Terzyme: a tool for identification and analysis of the plant terpenome
(BioMed Central Ltd, 2018) Priya, Piyush; Yadav, Archana; Chand, Jyoti; Yadav, Gitanjali
BACKGROUND: Terpenoid hydrocarbons represent the largest and most ancient group of phytochemicals, such that the entire chemical library of a plant is often referred to as its 'terpenome'. Besides having numerous pharmacological properties, terpenes contribute to the scent of the rose, the flavors of cinnamon and the yellow of sunflowers. Rapidly increasing -omics datasets provide an unprecedented opportunity for terpenome detection, paving the way for automated web resources dedicated to phytochemical predictions in genomic data. RESULTS: We have developed Terzyme, a predictive algorithm for identification, classification and assignment of broad substrate unit to terpene synthase (TPS) and prenyl transferase (PT) enzymes, known to generate the enormous structural and functional diversity of terpenoid compounds across the plant kingdom. Terzyme uses sequence information, plant taxonomy and machine learning methods for predicting TPSs and PTs in genome and proteome datasets. We demonstrate a significant enrichment of the currently identified terpenome by running Terzyme on more than 40 plants. CONCLUSIONS: Terzyme is the result of a rigorous analysis of evolutionary relationships between hundreds of characterized sequences of TPSs and PTs with known specificities, followed by analysis of genome-wide gene distribution patterns, ontology based clustering and optimization of various parameters for building accurate profile Hidden Markov Models. The predictive webserver and database is freely available at http://nipgr.res.in/terzyme.html and would serve as a useful tool for deciphering the species-specific phytochemical potential of plant genomes.