Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Department of Biotechnology

PTEN is a tumour suppressor gene known for regulating apoptosis, cell growth, and many other pathways. It is one of the most frequently mutated genes comprising the phosphatase domain (PD) and C terminal domain (C2). Direct therapeutic methods are not applicable for targeting PTEN because once gets mutated, it needs restoration. For mutant detection and restoration using PTEN mRNA there is a need to explore various mutations taking place in PTEN, identify their particular domains, and study their interactions within the cellular system. Here, we have tried to highlight a few such regions in the mutated PTEN of breast cancer patients. In this study, we have selected the top-most-occurring PTEN mutation in breast cancer and compared them to determine the specific properties of each mutation and its effect on functionality. Molecular dynamic simulation for 50 ns was performed on five structures to compare the structural behaviour of mutated PTEN in the system. Our finding suggests that frameshift mutations are more damaging and affect the c2 domain. Frameshift mutant fs_ACTT is the highest occurring as well as the most damaging mutation in all the compared structures. Docking study shows that substitution mutations D92H and R130Q causes loss of binding ability towards PIP2 in normal PTEN, interfering the dephosphorylation process. Overall, the C2 domain is more frequently mutated, and the amino acid residues in the C2 domain show more fluctuations compared to the other regions. Our study can provide the basis for selecting frequently mutated C2 domain as a potential therapeutic marker. Communicated by Ramaswamy H. Sarma. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

World University root node

School of Bio Sciences and Technology

Vellore Campus

Journal of Biomolecular Structure and Dynamics

Molecular dynamic study on PTEN frameshift mutations in breast cancer provide c2 domain as a potential biomarker

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder and is characterized by degeneration and axon loss from the upper motor neuron, that descends from the lower motor neuron in the brain. Over the period, assorted outcomes from medical findings, molecular pathogenesis, and structural and biophysical studies have abetted in providing thoughtful insights underlying the importance of disease-causing genes in ALS. Consequently, numerous mechanisms were proposed for the pathogenesis of ALS, considering protein mutations, aggregation, and misfolding. Besides, the answers to the majority of ALS cases that happen to be sporadic still remain obscure. The application in discovering susceptibility factors in ALS contemplating the genetic factors is to be further dissevered in the future years with innovation in research studies. Hence, this review targets in revisiting the breakthroughs on the disease-causing genes related with ALS. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Journal of Molecular Neuroscience

A Systematic and Comprehensive Review on Disease-Causing Genes in Amyotrophic Lateral Sclerosis

Antimicrobial peptides (AMPs) like tritrpticins, exhibit non-specific membrane lysis of gram-negative bacteria and can replace antibiotics, combating multi-drug resistance observed in UTI patients. Tritrpticins designated–NT, T1, T2, T3, T5, T7 and T8, were computationally investigated by interaction with Escherichia coli membrane model, mammalian cell toxicity and structural stability to identify a potential drug scaffold for UTI. Initially T3 was eliminated due to low interaction with Escherichia coli membrane model, based on its computed solvation energy. Further, negative support vector machine (SVM) scores revealed non-toxicity of T1, T2, T5, T7 and T8. Finally, at 310 K and varying pH 4.5–9.0, T5 exhibited highest structural stability based on its highest consistency of hydrogen bonds (H-bonds), root mean square deviation (RMSD) and secondary structure profiles along with its lowest conformational free energy. Overall, T5 could be considered a promising peptide drug scaffold to combat UTI. ABBREVIATIONSAMP antimicrobial peptidePBEQ Poisson Boltzmann equationH-bonds hydrogen bondsMIC minimum inhibitory concentrationLD50 lethal dose, 50%RMSD root mean square deviationSVM support vector machineUTI urinary tract infection Communicated by Ramaswamy H. Sarma. © 2019 Informa UK Limited, trading as Taylor & Francis Group.

Identification of therapeutic peptide scaffold from tritrpticin family for urinary tract infections using in silico techniques

Whole exome sequencing is an adept method to reveal novel and disease-related SNPs and INDELs as it screen the actionable areas of the genome. We evaluated the exome sequenced datasets of patients with Parkinson's disease (PD) in South African ethnic origin. The primary focus of this study was to discover the SNPs and INDELs patterns responsible for PD. The variant discovery was performed with genome analysis tool kit best practices variant detection pipelines. The SNPs were linked to the genes and categorized based on the filter-based annotation from ANNOVAR. We identified a total of 7955 SNPs and 9952 INDELs in all seven datasets together. A total of 130 missense nsSNPs were prioritized based on its damaging effect predicted from SIFT and Polyphen2 annotation. We noticed a novel nsSNP rs111655870 in gene LRRK2 that shows the mutation of a Leucine to Phenylalanine at position 208 which can alter the protein function. The study also filtered seven nsSNPs in genes NAGA, SULT4A1, MYH8, FLNA, TPM3, ATP13A1, CLN8 that have potentially deleterious effects predicted by various computational tools. This analysis suggested that the above filtered nsSNPs and INDELs have a functional impact and provide the footing for genetic studies related to PD. Further screening of these variations provides deeper insight for molecular mechanism of disease progression. © 2020

Genomics

Next generation sequencing exome data analysis aids in the discovery of SNP and INDEL patterns in Parkinson's disease

Aim: The rapid emergence of β-lactam resistance in gram-negative bacteria is a major problem in the treatment of infections caused by pathogenic bacterial strains, in particular Klebsiella pneumoniae. In our study, we are presenting a systems biology approach to understand the role of SHV-11 gene in drug resistance mechanism patterns in K. pneumoniae strain. Results: From the results, we have observed that the SHV-11 gene has a role in drug resistance mechanism along with its functional partner genes gyrA, parC, glsA, osmE, yjhA, yhdT, rimL, pepB, KPN_00437, and KPN_01875. We have also observed that of 51 genes, 27 genes were enriched in various Gene Ontology terms such as DNA metabolic process, DNA repair, and response to stress. The genes gyrA, parC, gyrB, parE, recA, dnaA, polB, dnaK, mutS, and dnaN constitute &gt;41% of the total interactions; thus, these genes can be considered as hub nodes in the network, and they can be used as the potential drug targets. Conclusions: Drug exposure leads to the DNA damage in bacterial spp. We observed that the SHV11 gene along with the functional partners help in maintaining the genomic integrity by withstanding the environmental stress by inducing DNA damage repair mechanism. Our results provide a detailed understanding on the role of SHV-11 gene in drug resistance mechanisms in K. pneumoniae, and we are of the opinion that our results will be useful for researchers exploring the antibiotic resistance mechanisms in pathogenic bacteria. © 2020, Mary Ann Liebert, Inc., publishers.

Department of Bio-Sciences

Microbial Drug Resistance

Role of SHV-11, a Class A β-Lactamase, Gene in Multidrug Resistance among Klebsiella pneumoniae Strains and Understanding Its Mechanism by Gene Network Analysis

Background: The increasing cases of non-small cell lung cancer pose a relentless threat to human health. Therefore, using fragment-based drug discovery as the modus operandi, the present study aimed to design small molecule inhibitors for Anaplastic Lymphoma Kinase (ALK) positive Non-Small Cell Lung Cancer (NSCLC) and for its secondary mutation (F1174L). Materials and methods: A total of 12 ALK inhibitors (both FDA and clinical) reported in the literature was utilised in the present study to design the novel and potent ALK inhibitors. Fragment script and BREED of Schrödinger suite was used to generate novel structural combinations. GLIDE algorithm was employed to identify the fragments with high binding affinity to the native and mutant forms of ALK. Screened out fragments were subjected to ADMET analysis. Additionally, the impact of F1174L mutation in the stability of ALK protein was assessed using SDM and I-Mutant tools. RING algorithm was employed to compare the pattern of intramolecular interaction between the native and F1174L ALK protein. Results: A novel hybrid molecule LF16 was identified with better binding, superior CNS activity, higher drug score and low toxicity. Annihilation of intramolecular interactions with Ile 1179, Ile 1170 and Phe1098 were found to be the cause of the destabilizing effect of the mutant protein. Of note, these residues were found to play important roles in the formation of F-core as well as in stabilizing αC-helix, which is important for maintaining the inactive form of ALK. Moreover, Conclusion: We believe that these results could foster the designing and development of novel ALK inhibitors towards the management of crizotinib resistance in the near future. © 2020, Association of Pharmaceutical Teachers of India. All rights reserved.

VIT Unitversity

Fulltext

Indian Journal of Pharmaceutical Education and Research

Design of ALK Inhibitors for Non-Small Cell Lung Cancer – A Fragment Based Approach

Background and aims: Ovarian cancer (OC) is the seventh most commonly detected cancer among women. This study aimed to map the hub and core genes and potential pathways that might be involved in the molecular pathogenesis of OC. Methods: In the present work, we analyzed a microarray dataset (GSE126519) from the Gene Expression Omnibus (GEO) database and used the GEO2R tool to screen OC cells and ovarian SINE-resistant cancer cells for differentially expressed genes (DEGs). For the functional annotation of the DEGs, we conducted Gene Ontology (GO) and pathway enrichment analyses (KEGG) using the DAVID v6.8 online server and GenoGo Metacore™, Cortellis Solution software. Protein–protein interaction (PPI) networks were constructed using the STRING database, and Cytoscape software was used for visualization. The survival analysis was performed using the online platform GEPIA2 to determine the prognostic value of the expression of hub genes in cell lines from OC patients. Results: We identified a total of 809 upregulated and 700 downregulated DEGs. GO analysis revealed that the genes with statistically significant differences in expression were mainly associated with biological processes involved in the cell cycle, the mitotic cell cycle, mitotic nuclear division, organ morphogenesis, cell development, and cell morphogenesis. By using the Analyze Networks (AN) algorithm in GeneGo, we identified the most relevant biological networks involving DEGs that were mainly enriched in the cell cycle (in metaphase checkpoints) and revealed the role of APC in cell cycle regulation pathways. We found 10 hub genes and four core genes (FZD6, FZD8, CDK2, and RBBP8) that are strongly linked to OC. Conclusion: This study sheds light on the molecular pathogenesis of OC and is expected to provide potential molecular biomarkers that are beneficial for the treatment and clinical molecular diagnosis of OC. © 2019 Kumar, Kumar, Siva, Doss and Zayed.

Department of Integrative Biology

Frontiers in Bioengineering and Biotechnology

Integrative Bioinformatics Approaches to Map Potential Novel Genes and Pathways Involved in Ovarian Cancer

Abstract: The main objective of this study (ABST and MIC) is used to recognize the possible drug resistance in microorganisms like Escherichia coli, Staphylococcus aureus and to assure susceptibility to drug of choice for particular infections. Here we use various medicinal plant extracts like Basil leaves (Ocimum tenuiflorum), Aloe vera (Aloe barbadensis miller), karpuravalli (Plectranthus amboinicus), kuppaimani (Acalypha indica) to determine an antimicrobial activity. By using different concentrations of these extracts, we evaluate whether the bacteria are susceptible to these compounds or not. We use Gram positive and Gram-negative microorganisms for the evaluation of pharmacological examinations and furthermore we have used immobilization technique for long term preservation. This technique will be useful to keep the medicinal plant extracts in an active form for a longer period of time.

INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH

evaluation of culinary plants by using ABST and MIC for pharmacological studies

Cancer is a disease that is characterized by uncontrolled cell growth with the ability to penetrate or develop to the other parts of the body. Various studies have shown the significance of identifying drug targets for cancer, although this process continues challenging in the field of anti-cancer drug designing. The primary purpose of this study is to design a novel approach to identify target genes for cancer. The sub-network of colorectal, pancreatic, and prostate cancers were constructed from human protein–protein interaction network. The potential genes were analyzed using hubs and centrality measures. For the identification of target genes, we retrieve those genes that had the highest score in both mutation rates and graph centrality. Moreover, gene deletion analysis revealed that MYC, TP53, and EGFR genes remained potential targets in colorectal, pancreatic, and prostate cancer respectively. Results suggest that combining network measures with mutation frequencies in cancer genes might assist in recognizing several potential drug targets. Future enhancement of this current approach is to combine these network properties with the biological insights from gene expression data, and their functions will provide a reliable method for rational drug designing.

Network Modeling Analysis in Health Informatics and Bioinformatics

Identification of target genes in cancer diseases using protein–protein interaction networks

Breast cancer (BC) is the most commonly diagnosed cancer among females worldwide, and among the BC-associated mutations in various proteins, mutations in the RAC-alpha serine/threonine-protein kinase (AKT1) remain the most dominant. We thus attempted to understand the potential molecular pathogenicity profile of the mutations in AKT1 using a comprehensive computational protocol involving analyses of biochemistry-disruption and destabilizing properties and conservation. Our predictions revealed that E17K, R67W, V164G, E319G, R391G, D32Y, L52H, L52R, and W80R were the most pathogenic mutations. In addition, the change of glutamate to lysine at position 17 of AKT1 (E17K) was found to be highly predominant. An extensive two-step molecular dynamics (simple and complex) simulation (MDS) using GROMACS (GROningen MAchine for Chemical Simulations) was then initiated to analyze and understand the structural impact of the E17K mutation on the function of AKT1. The simple MDS analysis revealed that the E17K mutation decreases the compactness and intramolecular hydrogen bonds of the protein. We also performed a virtual screening analysis with 19 AKT inhibitors obtained from the Selleck Chemicals website those satisfied the Lipinski rule of 5. Among these 19 compounds, Akti-1/2 exhibited the best binding affinity with both native AKT1 and the E17K mutant. The molecular interaction study also revealed that the co-crystallized AKT1 inhibitor N-(4-(5-(3-acetamidophenyl)-2-(2-aminopyridin-3-yl)-3H-imidazo [4,5-b]pyridin-3-yl)benzyl)-3-fluorobenzamide (12j) exhibited a better interaction with native AKT1 compared with the E17K mutant AKT1 protein, whereas, Akti-1/2 exhibited the opposite effects, i.e., a better interaction with the E17K mutant AKT1 than the native AKT1. These findings from the interaction analysis were further supported by the complex MDS, which measured the compactness and intermolecular hydrogen bonds of the proteins. The results obtained in this study suggest that Akti-1/2 might be a better inhibitor for the treatment of BC caused by the E17K mutation in AKT1. © 2019 Elsevier Ltd

Computers in Biology and Medicine

A computational approach for investigating the mutational landscape of RAC-alpha serine/threonine-protein kinase (AKT1) and screening inhibitors against the oncogenic E17K mutation causing breast cancer