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Shrivastava A, Magani SKJ, Lokhande KB, Chintakhindi M, Singh A. Exploring the role of TLK2 mutation in tropical calcific pancreatitis: an in silico and molecular dynamics simulation study. J Biomol Struct Dyn 2024:1-20. [PMID: 38500246 DOI: 10.1080/07391102.2024.2329797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 03/06/2024] [Indexed: 03/20/2024]
Abstract
Tropical calcific pancreatitis (TCP) is a juvenile form of non-alcoholic chronic pancreatitis seen exclusively in tropical countries. The disease poses a high risk of complications, including pancreatic diabetes and cancer, leading to significant mortality due to poor diagnosis and ineffective treatments. This study employed whole exome sequencing (WES) of 5 TCP patient samples to identify genetic variants associated with TCP. Advanced computational techniques were used to gain atomic-level insights into disease progression, including microsecond-scale long MD simulations and essential dynamics. In silico virtual screening was performed to identify potential therapeutic compounds targeting the mutant protein using the Asinex and DrugBank compound library. WES analysis predicted several single nucleotide variants (SNVs) associated with TCP, including a novel missense variant (c.T1802A or p.V601E) in the TLK2 gene. Computational analysis revealed that the p.V601E mutation significantly affected the structure of the TLK2 kinase domain and its conformational dynamics, altering the interaction profile between ATP and the binding pocket. These changes could impact TLK2's kinase activity and functions, potentially correlating with TCP progression. Promising lead compounds that selectively bind to the TLK2 mutant protein were identified, offering potential for therapeutic interventions in TCP. These findings hold great potential for future research.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Ashish Shrivastava
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
| | - Sri Krishna Jayadev Magani
- Cancer Biology Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
| | - Kiran Bharat Lokhande
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
| | | | - Ashutosh Singh
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
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Chadaeva IV, Filonov SV, Zolotareva KA, Khandaev BM, Ershov NI, Podkolodnyy NL, Kozhemyakina RV, Rasskazov DA, Bogomolov AG, Kondratyuk EY, Klimova NV, Shikhevich SG, Ryazanova MA, Fedoseeva LA, Redina ОЕ, Kozhevnikova OS, Stefanova NA, Kolosova NG, Markel AL, Ponomarenko MP, Oshchepkov DY. RatDEGdb: a knowledge base of differentially expressed genes in the rat as a model object in biomedical research. Vavilovskii Zhurnal Genet Selektsii 2023; 27:794-806. [PMID: 38213701 PMCID: PMC10777291 DOI: 10.18699/vjgb-23-92] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 09/11/2023] [Accepted: 09/15/2023] [Indexed: 01/13/2024] Open
Abstract
The animal models used in biomedical research cover virtually every human disease. RatDEGdb, a knowledge base of the differentially expressed genes (DEGs) of the rat as a model object in biomedical research is a collection of published data on gene expression in rat strains simulating arterial hypertension, age-related diseases, psychopathological conditions and other human afflictions. The current release contains information on 25,101 DEGs representing 14,320 unique rat genes that change transcription levels in 21 tissues of 10 genetic rat strains used as models of 11 human diseases based on 45 original scientific papers. RatDEGdb is novel in that, unlike any other biomedical database, it offers the manually curated annotations of DEGs in model rats with the use of independent clinical data on equal changes in the expression of homologous genes revealed in people with pathologies. The rat DEGs put in RatDEGdb were annotated with equal changes in the expression of their human homologs in affected people. In its current release, RatDEGdb contains 94,873 such annotations for 321 human genes in 836 diseases based on 959 original scientific papers found in the current PubMed. RatDEGdb may be interesting first of all to human geneticists, molecular biologists, clinical physicians, genetic advisors as well as experts in biopharmaceutics, bioinformatics and personalized genomics. RatDEGdb is publicly available at https://www.sysbio.ru/RatDEGdb.
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Affiliation(s)
- I V Chadaeva
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - S V Filonov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Novosibirsk State University, Novosibirsk, Russia
| | - K A Zolotareva
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - B M Khandaev
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - N I Ershov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - N L Podkolodnyy
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Novosibirsk State University, Novosibirsk, Russia
| | - R V Kozhemyakina
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - D A Rasskazov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A G Bogomolov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - E Yu Kondratyuk
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Siberian Federal Scientific Centre of Agro-BioTechnologies of the Russian Academy of Sciences, Krasnoobsk, Novosibirsk region, Russia
| | - N V Klimova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - S G Shikhevich
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - M A Ryazanova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - L A Fedoseeva
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - О Е Redina
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - O S Kozhevnikova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - N A Stefanova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - N G Kolosova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A L Markel
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Novosibirsk State University, Novosibirsk, Russia
| | - M P Ponomarenko
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - D Yu Oshchepkov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
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Shrivastava A, Mathur K, Verma RK, Jayadev Magani SK, Vyas DK, Singh A. Molecular dynamics study of tropical calcific pancreatitis (TCP) associated calcium-sensing receptor single nucleotide variation. Front Mol Biosci 2022; 9:982831. [PMID: 36275616 PMCID: PMC9581290 DOI: 10.3389/fmolb.2022.982831] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 09/16/2022] [Indexed: 12/01/2022] Open
Abstract
Tropical Calcific Pancreatitis (TCP) is a chronic non-alcoholic pancreatitis characterised by extensive calcification. The disease usually appears at a younger age and is more common in tropical regions. This disease’s progression can lead to pancreatic diabetes, which can subsequently lead to pancreatic cancer. The CASR gene encodes a calcium-sensing receptor (CaSR), which is a GPCR protein of class C. It is expressed in the islets of Langerhans, the parathyroid gland, and other tissues. It primarily detects small gradients in circulating calcium concentrations and couples this information to intracellular signalling, which helps to regulate PTH (parathyroid hormone) secretion and mineral ion homeostasis. From co-leading insulin release, CaSR modulates ductal HCO3− secretion, Ca2+ concentration, cell-cell communication, β-cell proliferation, and intracellular Ca2+ release. In pancreatic cancer, the CaSR limits cell proliferation. TCP-related four novel missense mutations P163R, I427S, D433H and V477A, found in CaSR extracellular domain (ECD) protein, which were reported in the mutTCPdb Database (https://lms.snu.edu.in/mutTCPDB/index.php). P163R mutation occurs in ligand-binding domain 1 (LBD-1) of the CaSR ECD. To investigate the influence of these variations on protein function and structural activity multiple in-silico prediction techniques such as SIFT, PolyPhen, CADD scores, and other methods have been utilized. A 500 ns molecular dynamic simulation was performed on the CaSR ECD crystal structure and the corresponding mutated models. Furthermore, Principal Component Analysis (PCA) and Essential Dynamics analysis were used to forecast collective motions, thermodynamic stabilities, and the critical subspace crucial to CaSR functions. The results of molecular dynamic simulations showed that the mutations P163R, I427S, D433H, and V477A caused conformational changes and decreased the stability of protein structures. This study also demonstrates the significance of TCP associated mutations. As a result of our findings, we hypothesised that the investigated mutations may have an effect on the protein’s structure and ability to interact with other molecules, which may be related to the protein’s functional impairment.
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Affiliation(s)
- Ashish Shrivastava
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
| | - Kartavya Mathur
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
| | - Rohit Kumar Verma
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
| | - Sri Krishna Jayadev Magani
- Cancer Biology Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
- *Correspondence: Sri Krishna Jayadev Magani, ; Ashutosh Singh,
| | - Deepak Krishna Vyas
- Department of Biotechnology, Lachoo Memorial College of Science and Technology, Jodhpur, RJ, India
| | - Ashutosh Singh
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
- *Correspondence: Sri Krishna Jayadev Magani, ; Ashutosh Singh,
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Bordin DS, Kucheryavyy YA, Kiryukova MA. The revised pancreatitis etiology-based classification system TIGAR-O, version 2: adaptation for the Russian clinical practice. ALMANAC OF CLINICAL MEDICINE 2020; 48:349-363. [DOI: 10.18786/2072-0505-2020-48-062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
Abstract
The discoveries in molecular genetics and breakthrough visualization techniques in the last 20 years have changed our understanding of the pancreatitis causes and biomarkers, expanded our knowledge on the pathophysiology of the disease, and promoted the development of new additional conservative treatments. From the practical perspective, the physician's comprehension of the etiology is of particular importance. It is for this reason that the activities to elaborate an etiology-based classification of pancreatitis have been already started since long ago. The first internationally acknowledged system was TIGAR-O checklist, introduced in 2001. Being innovative at the time, it structured our understanding of the etiology of chronic pancreatitis. The revised version (version 2) was published in 2019 and is less known to the Russian medical community, although from the authors' point of view, it has been substantially extended and structured to be maximally convenient and useful for physicians in routine medical practice. The review presents key provisions of the TIGAR-O, version 2 and recommendations for its adaption to the Russian clinical setting.
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Affiliation(s)
- D. S. Bordin
- The Loginov Moscow Clinical Scientific Center; A.I. Yevdokimov Moscow State University of Medicine and Dentistry; Tver State Medical University
| | - Yu. A. Kucheryavyy
- A.I. Yevdokimov Moscow State University of Medicine and Dentistry; Il'inskaya Hospital
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Abstract
The Toxic-metabolic, Idiopathic, Genetic, Autoimmune, Recurrent and severe acute pancreatitis and Obstructive (TIGAR-O) Pancreatitis Risk/Etiology Checklist (TIGAR-O_V1) is a broad classification system that lists the major risk factors and etiologies of recurrent acute pancreatitis, chronic pancreatitis, and overlapping pancreatic disorders with or without genetic, immunologic, metabolic, nutritional, neurologic, metaplastic, or other features. New discoveries and progressive concepts since the 2001 TIGAR-O list relevant to understanding and managing complex pancreatic disorders require an update to TIGAR-O_V2 with both a short (S) and long (L) form. The revised system is designed as a hierarchical checklist for health care workers to quickly document and track specific factors that, alone or in combinations, may contribute to progressive pancreatic disease in individual patients or groups of patients and to assist in treatment selection. The rationale and key clinical considerations are summarized for each updated classification item. Familiarity with the structured format speeds up the completion process and supports thoroughness and consideration of complex or alternative diagnoses during evaluation and serves as a framework for communication. The structured approach also facilitates the new health information technologies that required high-quality data for accurate precision medicine. A use primer accompanies the TIGAR-O_V2 checklist with rationale and comments for health care workers and industries caring for patients with pancreatic diseases.
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Singh G, Jayadev Magani SK, Sharma R, Bhat B, Shrivastava A, Chinthakindi M, Singh A. Structural, functional and molecular dynamics analysis of cathepsin B gene SNPs associated with tropical calcific pancreatitis, a rare disease of tropics. PeerJ 2019; 7:e7425. [PMID: 31592339 PMCID: PMC6778667 DOI: 10.7717/peerj.7425] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Accepted: 07/07/2019] [Indexed: 01/13/2023] Open
Abstract
Tropical Calcific Pancreatitis (TCP) is a neglected juvenile form of chronic non-alcoholic pancreatitis. Cathepsin B (CTSB), a lysosomal protease involved in the cellular degradation process, has recently been studied as a potential candidate gene in the pathogenesis of TCP. According to the Cathepsin B hypothesis, mutated CTSB can lead to premature intracellular activation of trypsinogen, a key regulatory mechanism in pancreatitis. So far, CTSB mutations have been studied in pancreatitis and neurodegenerative disorders, but little is known about the structural and functional effect of variants in CTSB. In this study, we investigated the effect of single nucleotide variants (SNVs) specifically associated with TCP, using molecular dynamics and simulation algorithms. There were two non-synonymous variants (L26V and S53G) of CTSB, located in the propeptide region. We tried to predict the effect of these variants on structure and function using multiple algorithms: SIFT, Polyphen2, PANTHER, SDM sever, i-Mutant2.0 suite, mCSM algorithm, and Vadar. Further, using databases like miRdbSNP, PolymiRTS, and miRNASNP, two SNPs in the 3′UTR region were predicted to affect the miRNA binding sites. Structural mutated models of nsSNP mutants (L26V and S53G) were prepared by MODELLER v9.15 and evaluated using TM-Align, Verify 3D, ProSA and Ramachandran plot. The 3D mutated structures were simulated using GROMACS 5.0 to predict the impact of these SNPs on protein stability. The results from in silico analysis and molecular dynamics simulations suggested that these variants in the propeptide region of Cathepsin B could lead to structural and functional changes in the protein and thus could be pathogenic. Hence, the structural and functional analysis results have given interim conclusions that these variants can have a deleterious effect in TCP pathogenesis, either uniquely or in combination with other mutations. Thus, it could be extrapolated that Cathepsin B gene can be screened in samples from all TCP patients in future, to decipher the distribution of variants in patients.
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Affiliation(s)
- Garima Singh
- Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Greater Noida, Uttar Pradesh, India
| | - Sri Krishna Jayadev Magani
- Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Greater Noida, Uttar Pradesh, India
| | - Rinku Sharma
- Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Greater Noida, Uttar Pradesh, India
| | - Basharat Bhat
- Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Greater Noida, Uttar Pradesh, India
| | - Ashish Shrivastava
- Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Greater Noida, Uttar Pradesh, India
| | | | - Ashutosh Singh
- Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Greater Noida, Uttar Pradesh, India
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