Dr Reetu Sharma

Dr Reetu Sharma
Indian Institute of Chemical Technology | IICT · Biology Division (IICT)

PhD
Principal Investigator (DBT)

About

35
Publications
2,920
Reads
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127
Citations
Citations since 2017
9 Research Items
86 Citations
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201720182019202020212022202305101520
Introduction
Our interest is to advance the understanding for lifestyle diseases using data science, machine learning/AI approaches in a collaborative environment for a better health and future

Publications

Publications (35)
Article
Full-text available
The utilization of approved medication is a requisite to combat certain diseases for health; however, the undesirable adverse effects (AEs) due to medication are generally unavoidable. Hypertension is one of such AEs resulting from approved medication in which blood pressure in the arteries gets elevated and is a risk factor for several diseases in...
Article
Full-text available
Elucidating the relation between the medicines: targets, targets: diseases and diseases: diseases are of fundamental significance as-is for societal benefit. Hypertension is one of the dangerous health conditions prevalent in society, is a risk factor for several other diseases if left untreated and anti-hypertensives (AHs) are the approved drugs t...
Preprint
Full-text available
Millions of people have been forfeiting their lives due to SARS-CoV-2 infection. Most of them are patients suffering from comorbid complications. However, what makes these patients susceptible to mortality is unknown. For this, we employed a novel network-based approach to Covid-19 associated human target coding genes (TC-genes) overlapping with hi...
Article
Full-text available
Clustering brings molecules having similar patterns together and is governed mainly by the structural features (SFs). The challenge is to cluster in such a way that the minimum number of groups with significant molecules having similar prevalent patterns comes together with minimal human intervention. Determining an automatic and reliable approach...
Article
An oligomer usually refers to a macromolecular complex formed by non-covalent interactions of monomers. Several thermophilic proteins are oligomers. The significance of oligomerization of individual proteins for stability at higher temperature is of prime importance for understanding evolution and increasing industrial productivity. The functional...
Article
An oligomer usually refers to a macromolecular complex formed by non-covalent interactions of monomers. Several thermophilic proteins are oligomers. The significance of oligomerization of individual proteins for stability at higher temperature is of prime importance for understanding evolution and increasing industrial productivity. The functional...
Article
Full-text available
Molecular Property Diagnostic Suite (MPDS TB ) is a web tool (http://mpds.osdd.net) designed to assist the in silico drug discovery attempts towards Mycobacterium tuberculosis (Mtb). MPDS TB tool has nine modules which are classified into data library (1–3), data processing (4–5) and data analysis (6–9). Module 1 is a repository of literature and r...
Article
Thermus thermophilius isopropylmalate dehydrogenase catalyzes oxidative decarboxylation and dehydrogenation of isopropylmalate. Substitution of leucine to alanine at position 172 enhances the thermal stability among the known point mutants. Exploring the dynamic properties of non-covalent interactions such as saltbridges, hydrogen bonds and hydroph...
Data
Unique salt bridges and their percentage of existence in wt and mut at 300 K and 337 K. Drnona and Arnona represents donor and acceptor residue number followed by its abbreviation (3 Letter), respectively. D and A indicates interacting donor and acceptor atom, respectively. The color formatting indicates the percentage of time the interaction (prec...
Data
Unique HBs between SS of wt and mut at 300 K and 337 K. The color formatting indicates the percentage of time interaction existed is as in S1 Table. (PDF)
Data
Percentage existence of HBs between PP of wt and mut at 300 K and 337 K. The color formatting indicates the percentage of time interaction existed is as in S1 Table. (PDF)
Data
Unique IP HBs between donor and acceptor atom of wt and mut at 300 K and 337 K. The color formatting indicates the percentage of time interaction existed as in S1 Table. (PDF)
Data
Percentage of existence of unique HBs between CC of wt and mut at 300 K and 337 K. The color formatting indicates the percentage of time interaction existed is as in S1 Table. (PDF)
Data
Unique intra hydrophobic contacts and the percentage of their existence in wt and mut at 300 K and 337 K. The color formatting indicates the percentage of time interaction existed is as in S1 Table. (PDF)
Data
Difference in HBs between A) MM, B) MS, C) SS D) CC, E) HH (y-axis) based on percentage of time the interaction existed (x-axis) at 337 K and 300 K in mut (blue) and wt (red). (TIFF)
Data
Tertiary structures of A) wt (PDB id: 1IPD) [20] and B) mut (PDB id: 1OSJ) [19]. Subunit 1 and 2 are represented in green and blue, respectively. (TIFF)
Data
Percentage of time HBs existed between MM of the wt and mut at 300 K and 337 K. The color formatting pattern is as followed in S1 Table. (PDF)
Data
Unique HBs between MS of wt and mut at 300 K and 337 K. The color formatting indicates the percentage of time interaction existed is as in S1 Table. (PDF)
Data
Difference of unique NCI in mut and wt at 337 K and 300 K after removing the interactions having percentage of existence less than or equal to 10%. (PDF)
Chapter
Modeling chemical reactivity and biological activity are two topics of outstanding importance in chemistry and biology. There is little doubt that computational approaches have emerged as tools of outstanding utilities and played vital role. While the development of computational biology and chemistry have contrasting styles, with former focusing...
Article
Full-text available
Modeling chemical reactivity and biological activity are two topics of outstanding importance in chemistry and biology. There is little doubt that computational approaches have emerged as tools of outstanding utilities and played vital role. While the development of computational biology and chemistry have contrasting styles, with former focusing o...
Article
Full-text available
The catalytic activity of L-aspartate α-decarboxylase (ADC) is essential for the growth of several micro-organisms, including Mycobacterium tuberculosis (Mtb), and has triggered efforts for the development of pharmaceutically active compounds against tuberculosis. The present study is a continuation of our recent chemoinformatics-based design appro...
Article
Full-text available
L-aspartate α-decarboxylase (ADC) belongs to a class of pyruvoyl dependent enzymes and catalyzes the conversion of aspartate to β-alanine in the pantothenate pathway, which is critical for the growth of several micro-organisms, including Mycobacterium tuberculosis (Mtb). Its presence only in micro-organisms, fungi and plants and its absence in anim...
Data
Binding poses of known inhibitors/ligands. The known inhibitors or ligands are shown as thick ball and stick. Atoms are colored as: H: white, C: green, N: blue, O: red and S: yellow. The interacting MtbADC residues are drawn as thin wireframe with the same color scheme and are labeled. Hydrogen bond interactions are shown as dotted yellow lines, al...
Data
Pantothenate and CoA biosynthesis pathway. L-Aspartate α-decarboxylase (ADC) catalyzes the decarboxylation of L-aspartate to β-alanine. (TIFF)
Data
The 28 ligand hits from the Maybridge, NCI and FDA databases which interact with at least one of the conserved functional residues of MtbADC residues involved in substrate binding and their glide score (kcal/mol). The ligands are ranked according to their glide scores in their respective databases. The ligands that interact with Pyr25 are in bold....
Data
The structures of known and reported inhibitors against ADC. (TIFF)
Data
Fumarate binding in ADC. (a) The superimposed view of the TthADC:fumarate crystal structure (red) and MtbADC:fumarate docking model (blue) is shown. The processed model for MtbADC was generated from the crystal structure of unprocessed protein and docking of fumarate was achieved using the Glide Extra Precision mode. The interacting conserved resid...
Data
Ligands docked to monomeric MtbADC. The structures of the top three hits, obtained by docking the Maybridge, NCI and FDA databases with the processed monomeric MtbADC structure. These molecules are big and cannot be genuine inhibitors as the actual active site is formed in the cleft of a dimer with relatively smaller volume and only molecules of sm...
Data
The ADMET properties of the 28 ligands. The ligands that interact with Pyr25 are in bold. The entries of Table 2 are underlined. The definitions of the properties are as in Table 2. (DOCX)
Data
Interactions of selected known inhibitors/ligands with MtbADC as verified by Glide XP. (DOCX)
Article
Full-text available
Cytokinesis in many eukaryotes involves the function of an actomyosin-based contractile ring. In fission yeast, actomyosin ring maturation and stability require a conserved signaling pathway termed the SIN (septation initiation network). The SIN consists of a GTPase (Spg1p) and three protein kinases, all of which localize to the mitotic spindle pol...

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Projects

Projects (2)
Project
Goals: 1) Deciphering the Dynamics of Non-Covalent Interactions Affecting Thermal Stability of a Protein 2)Elucidating the Preference of Protein Oligomerization for Thermal Stability
Project
1. Employed data science-driven approaches to identify the patterns associated with the structural and functional aspect of certain marketed medicines and diseases. 2. Decision rules to predict drug-induced adverse effect in advance are suggested comparing machine learning algorithms. 3. Improvised k-means, an unsupervised machine learning approach and employed it to cluster the marketed anti-hypertensives to identify the biomarkers (pattern) within a group. 4. Implemented novel network medicine based approaches reveal disease-disease relationships. Recently, she has identified how hypertension is related to selective diseases, highlighting the interplay among market available anti-hypertensives target coding genes. 5. Our work suggests that hypertension is deeply connected to certain diseases through common genes. 6. Deciphered how Covid-19 led to high mortality of comorbid patients from clinical trial datasets through a network of common genes.