1
|
Nayarisseri A, Abdalla M, Joshi I, Yadav M, Bhrdwaj A, Chopra I, Khan A, Saxena A, Sharma K, Panicker A, Panwar U, Mendonça Junior FJB, Singh SK. Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer. Sci Rep 2024; 14:13251. [PMID: 38858458 PMCID: PMC11164920 DOI: 10.1038/s41598-024-63762-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 05/31/2024] [Indexed: 06/12/2024] Open
Abstract
Cervical cancer stands as a prevalent gynaecologic malignancy affecting women globally, often linked to persistent human papillomavirus infection. Biomarkers associated with cervical cancer, including VEGF-A, VEGF-B, VEGF-C, VEGF-D, and VEGF-E, show upregulation and are linked to angiogenesis and lymphangiogenesis. This research aims to employ in-silico methods to target tyrosine kinase receptor proteins-VEGFR-1, VEGFR-2, and VEGFR-3, and identify novel inhibitors for Vascular Endothelial Growth Factors receptors (VEGFRs). A comprehensive literary study was conducted which identified 26 established inhibitors for VEGFR-1, VEGFR-2, and VEGFR-3 receptor proteins. Compounds with high-affinity scores, including PubChem ID-25102847, 369976, and 208908 were chosen from pre-existing compounds for creating Deep Learning-based models. RD-Kit, a Deep learning algorithm, was used to generate 43 million compounds for VEGFR-1, VEGFR-2, and VEGFR-3 targets. Molecular docking studies were conducted on the top 10 molecules for each target to validate the receptor-ligand binding affinity. The results of Molecular Docking indicated that PubChem IDs-71465,645 and 11152946 exhibited strong affinity, designating them as the most efficient molecules. To further investigate their potential, a Molecular Dynamics Simulation was performed to assess conformational stability, and a pharmacophore analysis was also conducted for indoctrinating interactions.
Collapse
Affiliation(s)
- Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India.
- Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India.
| | - Mohnad Abdalla
- Key Laboratory of Chemical Biology (Ministry of Education), Department of Pharmaceutics, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, 44 Cultural West Road, Jinan, 250012, Shandong Province, People's Republic of China
| | - Isha Joshi
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
| | - Manasi Yadav
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
| | - Anushka Bhrdwaj
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India
| | - Ishita Chopra
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
- School of Medicine and Health Sciences, The George Washington University, Ross Hall, 2300 Eye Street, Washington, D.C., NW, 20037, USA
| | - Arshiya Khan
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India
| | - Arshiya Saxena
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
| | - Khushboo Sharma
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India
| | - Aravind Panicker
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
| | - Umesh Panwar
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India
| | | | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India.
| |
Collapse
|
2
|
Panwar U, Murali A, Khan MA, Selvaraj C, Singh SK. Virtual Screening Process: A Guide in Modern Drug Designing. Methods Mol Biol 2024; 2714:21-31. [PMID: 37676591 DOI: 10.1007/978-1-0716-3441-7_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Due to its capacity to drastically cut the cost and time necessary for experimental screening of compounds, virtual screening (VS) has grown to be a crucial component of drug discovery and development. VS is a computational method used in drug design to identify potential drugs from enormous libraries of chemicals. This approach makes use of molecular modeling and docking simulations to assess the small molecule's ability to bind to the desired protein. Virtual screening has a bright future, as high computational power and modern techniques are likely to further enhance the accuracy and speed of the process.
Collapse
Affiliation(s)
- Umesh Panwar
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Aarthy Murali
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Mohammad Aqueel Khan
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Chandrabose Selvaraj
- Center for Transdisciplinary Research, Department of Pharmacology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
- Department of Data Sciences, Centre of Biomedical Research, SGPGIMS Campus, Lucknow, Uttar Pradesh, India
| |
Collapse
|
3
|
Murali A, Panwar U, Singh SK. Exploring the Role of Chemoinformatics in Accelerating Drug Discovery: A Computational Approach. Methods Mol Biol 2024; 2714:203-213. [PMID: 37676601 DOI: 10.1007/978-1-0716-3441-7_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Cheminformatics and its role in drug discovery is expected to be the privileged approach in handling large number of chemical datasets. This approach contributes toward the pharmaceutical development and assessment of chemical compounds at a faster rate efficiently. Additionally, as technological advancement impacts research, cheminformatics is being used more and more in the field of health science. This chapter describes the concepts of cheminformatics along with its involvement in drug discovery with a case study.
Collapse
Affiliation(s)
- Aarthy Murali
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Umesh Panwar
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
- Department of Data Sciences, Centre of Biomedical Research, SGPGIMS Campus, Lucknow, Uttar Pradesh, India
| |
Collapse
|
4
|
Roy S, Roy S, Mahata B, Pramanik J, Hennrich ML, Gavin AC, Teichmann SA. CLICK-chemoproteomics and molecular dynamics simulation reveals pregnenolone targets and their binding conformations in Th2 cells. Front Immunol 2023; 14:1229703. [PMID: 38022565 PMCID: PMC10644475 DOI: 10.3389/fimmu.2023.1229703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 10/05/2023] [Indexed: 12/01/2023] Open
Abstract
Pregnenolone (P5) is synthesized as the first bioactive steroid in the mitochondria from cholesterol. Clusters of differentiation 4 (CD4+) and Clusters of differentiation 8 (CD8+) immune cells synthesize P5 de novo; P5, in turn, play important role in immune homeostasis and regulation. However, P5's biochemical mode of action in immune cells is still emerging. We envisage that revealing the complete spectrum of P5 target proteins in immune cells would have multifold applications, not only in basic understanding of steroids biochemistry in immune cells but also in developing new therapeutic applications. We employed a CLICK-enabled probe to capture P5-binding proteins in live T helper cell type 2 (Th2) cells. Subsequently, using high-throughput quantitative proteomics, we identified the P5 interactome in CD4+ Th2 cells. Our study revealed P5's mode of action in CD4+ immune cells. We identified novel proteins from mitochondrial and endoplasmic reticulum membranes to be the primary mediators of P5's biochemistry in CD4+ and to concur with our earlier finding in CD8+ immune cells. Applying advanced computational algorithms and molecular simulations, we were able to generate near-native maps of P5-protein key molecular interactions. We showed bonds and interactions between key amino acids and P5, which revealed the importance of ionic bond, hydrophobic interactions, and water channels. We point out that our results can lead to designing of novel molecular therapeutics strategies.
Collapse
Affiliation(s)
- Sougata Roy
- Department of Biology, Ashoka University, Rajiv Gandhi Education City, Sonipat, Haryana, India
| | - Sudeep Roy
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czechia
| | - Bidesh Mahata
- Division of Immunology, Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Jhuma Pramanik
- Division of Immunology, Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Marco L. Hennrich
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, EMBL, Heidelberg, Germany
- Cellzome, a GlaxoSmithKline (GSK) company, Genomic Sciences, Pharma R&D, Heidelberg, Germany
| | - Anne-Claude Gavin
- Department for Cell Physiology and Metabolism, Centre Medical Universitaire, University of Geneva, Geneva, Switzerland
- Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Sarah A. Teichmann
- Cellular Genetics, Wellcome Sanger Institute, Cambridge, United Kingdom
- Theory of Condensed Matter, Cavendish Laboratory, Cambridge, United Kingdom
| |
Collapse
|
5
|
Structural insights into the RNA interaction with Yam bean Mosaic virus (coat protein) from Pachyrhizus erosus using bioinformatics approach. PLoS One 2022; 17:e0270534. [PMID: 35867657 PMCID: PMC9307209 DOI: 10.1371/journal.pone.0270534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 06/11/2022] [Indexed: 11/19/2022] Open
Abstract
Plants are constantly threatened by a virus infection, i.e., Potyviruses, the second largest genus of plant viruses which results in several million-dollar losses in various essential crops globally. Yam bean (Pachyrhizus erosus) is considered to be one of the essential tuberous legume crops holding a great potential source of starch. Yam Bean Mosaic Virus (YBMV) of Potyvirus group belonging to the family potyviridae affects Yam bean and several angiosperms both in the tropical and sub-tropical regions causing large economical losses in crops. In this study, we attempted to understand the sequence-structure relationship and mode of RNA binding mechanism in YBMV CP using in silico integrative modeling and all-atoms molecular dynamics (MD) simulations. The assembly of coat protein (CP) subunits from YBMV and the plausible mode of RNA binding were compared with the experimental structure of CP from Watermelon mosaic virus potyvirus (5ODV). The transmembrane helix region is present in the YBMV CP sequence ranging from 76 to 91 amino acids. Like the close structural-homolog, 24 CPs monomeric sub-units formed YBMV a conserved fold. Our computational study showed that ARG124, ARG155, and TYR151 orient towards the inner side of the virion, while, THR122, GLN125, SER92, ASP94 reside towards the outer side of the virion. Despite sharing very low sequence similarity with CPs from other plant viruses, the strongly conserved residues Ser, Arg, and Asp within the RNA binding pocket of YBMV CP indicate the presence of a highly conserved RNA binding site in CPs from different families. Using several bioinformatics tools and comprehensive analysis from MD simulation, our study has provided novel insights into the RNA binding mechanism in YBMV CP. Thus, we anticipate that our findings from this study will be useful for the development of new therapeutic agents against the pathogen, paving the way for researchers to better control this destructive plant virus.
Collapse
|
6
|
Sharma A, Choi HK, Kim YK, Lee HJ. Delphinidin and Its Glycosides' War on Cancer: Preclinical Perspectives. Int J Mol Sci 2021; 22:11500. [PMID: 34768930 PMCID: PMC8583959 DOI: 10.3390/ijms222111500] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 10/19/2021] [Accepted: 10/21/2021] [Indexed: 12/24/2022] Open
Abstract
Until now, several studies have looked at the issue of anthocyanin and cancer, namely the preventive and inhibitory effects of anthocyanins, as well as the underlying molecular processes. However, no targeted review is available regarding the anticarcinogenic effects of delphinidin and its glycosides on various cancers and their plausible molecular mechanisms. Considerable evidence shows significant anticancer properties of delphinidin-rich preparations and delphinidin alone both in vitro and in vivo. This review covers the in vitro and preclinical implications of delphinidin-mediated cell protection and cancer prevention; thus, we strongly recommend that delphinidin-rich preparations be further investigated as potential functional food, dietary antioxidant supplements, and natural health products targeting specific chronic diseases, including cancer. In addition to in vitro investigations, future research should focus on more animal and human studies to determine the true potential of delphinidin.
Collapse
Affiliation(s)
- Anshul Sharma
- Department of Food and Nutrition, College of Bionanotechnology, Gachon University, Seongnam-si 13120, Gyeonggi-do, Korea;
| | - Hyo-Kyoung Choi
- Korea Food Research Institute, Wanju-gun 55365, Jeollabuk-do, Korea;
| | - Yeon-Kye Kim
- Food Safety and Processing Research Division, National Institute of Fisheries Science, Gijang-eup, Busan 46083, Korea;
| | - Hae-Jeung Lee
- Department of Food and Nutrition, College of Bionanotechnology, Gachon University, Seongnam-si 13120, Gyeonggi-do, Korea;
- Institute for Aging and Clinical Nutrition Research, Gachon University, Seongnam-si 13120, Gyeonggi-do, Korea
| |
Collapse
|
7
|
Selvaraj C, Chandra I, Singh SK. Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries. Mol Divers 2021; 26:1893-1913. [PMID: 34686947 PMCID: PMC8536481 DOI: 10.1007/s11030-021-10326-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 09/24/2021] [Indexed: 12/27/2022]
Abstract
The global spread of COVID-19 has raised the importance of pharmaceutical drug development as intractable and hot research. Developing new drug molecules to overcome any disease is a costly and lengthy process, but the process continues uninterrupted. The critical point to consider the drug design is to use the available data resources and to find new and novel leads. Once the drug target is identified, several interdisciplinary areas work together with artificial intelligence (AI) and machine learning (ML) methods to get enriched drugs. These AI and ML methods are applied in every step of the computer-aided drug design, and integrating these AI and ML methods results in a high success rate of hit compounds. In addition, this AI and ML integration with high-dimension data and its powerful capacity have taken a step forward. Clinical trials output prediction through the AI/ML integrated models could further decrease the clinical trials cost by also improving the success rate. Through this review, we discuss the backend of AI and ML methods in supporting the computer-aided drug design, along with its challenge and opportunity for the pharmaceutical industry. From the available information or data, the AI and ML based prediction for the high throughput virtual screening. After this integration of AI and ML, the success rate of hit identification has gained a momentum with huge success by providing novel drugs.
Collapse
Affiliation(s)
- Chandrabose Selvaraj
- CADD and Molecular Modelling Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India.
| | - Ishwar Chandra
- CADD and Molecular Modelling Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India
| | - Sanjeev Kumar Singh
- CADD and Molecular Modelling Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India.
| |
Collapse
|
8
|
Nayak C, Singh SK. In silico identification of natural product inhibitors against Octamer-binding transcription factor 4 (Oct4) to impede the mechanism of glioma stem cells. PLoS One 2021; 16:e0255803. [PMID: 34613998 PMCID: PMC8494328 DOI: 10.1371/journal.pone.0255803] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 07/23/2021] [Indexed: 02/07/2023] Open
Abstract
Octamer-binding transcription factor 4 (Oct4) is a core regulator in the retention of stemness, invasive, and self-renewal properties in glioma initiating cells (GSCs) and its overexpression inhibits the differentiation of glioma cells promoting tumor cell proliferation. The Pit-Oct-Unc (POU) domain comprising POU-specific domain (POUS) and POU-type homeodomain (POUHD) subdomains is the most critical part of the Oct4 for the generation of induced pluripotent stem cells from somatic cells that lead to tumor initiation, invasion, posttreatment relapse, and therapeutic resistance. Therefore, the present investigation hunts for natural product inhibitors (NPIs) against the POUHD domain of Oct4 by employing receptor-based virtual screening (RBVS) followed by binding free energy calculation and molecular dynamics simulation (MDS). RBVS provided 13 compounds with acceptable ranges of pharmacokinetic properties and good docking scores having key interactions with the POUHD domain. More Specifically, conformational and interaction stability analysis of 13 compounds through MDS unveiled two compounds ZINC02145000 and ZINC32124203 which stabilized the backbone of protein even in the presence of linker and POUS domain. Additionally, ZINC02145000 and ZINC32124203 exhibited stable and strong interactions with key residues W277, R242, and R234 of the POUHD domain even in dynamic conditions. Interestingly, ZINC02145000 and ZINC32124203 established communication not only with the POUHD domain but also with the POUS domain indicating their incredible potency toward thwarting the function of Oct4. ZINC02145000 and ZINC32124203 also reduced the flexibility and escalated the correlations between the amino acid residues of Oct4 evidenced by PCA and DCCM analysis. Finally, our examination proposed two NPIs that can impede the Oct4 function and may help to improve overall survival, diminish tumor relapse, and achieve a cure not only in deadly disease GBM but also in other cancers with minimal side effects.
Collapse
Affiliation(s)
- Chirasmita Nayak
- Computer-Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Computer-Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi Tamil Nadu, India
| |
Collapse
|
9
|
Aarthy M, Singh SK. Interpretations on the Interaction between Protein Tyrosine Phosphatase and E7 Oncoproteins of High and Low-Risk HPV: A Computational Perception. ACS OMEGA 2021; 6:16472-16487. [PMID: 34235319 PMCID: PMC8246469 DOI: 10.1021/acsomega.1c01619] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 06/08/2021] [Indexed: 05/17/2023]
Abstract
The most prevalent and common sexually transmitted infection is caused by human papillomavirus (HPV) among sexually active women. Numerous genotypes of HPV are available, among which the major oncoproteins E6 and E7 lead to the progression of cervical cancer. The E7 oncoprotein interacts with cytoplasmic tumor suppressor protein PTPN14, which is the key regulator of cellular growth control pathways effecting the reduction of steady-state level. Disrupting the interaction between the tumor suppressor and the oncoprotein is vital to cease the development of cancer. Hence, the mechanism of interaction between E7 and tumor suppressor is explored through protein-protein and protein-ligand binding along with the conformational stability studies. The obtained results state that the LXCXE domain of HPV E7 of high and low risks binds with the tumor suppressor protein. Also, the small molecules bind in the interface of E7-PTPN14 that disrupts the interaction between the tumor suppressor and oncoprotein. These results were further supported by the dynamics simulation stating the stability over the bounded complex and the energy maintained during postdocking as well as postdynamics calculations. These observations possess an avenue in the drug discovery that leads to further validation and also proposes a potent drug candidate to treat cervical cancer caused by HPV.
Collapse
|
10
|
Nayarisseri A. Most Promising Compounds for Treating COVID-19 and Recent Trends in Antimicrobial & Antifungal Agents. Curr Top Med Chem 2020; 20:2119-2125. [PMID: 33153418 DOI: 10.2174/156802662023201001094634] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Multidrug resistance in microbes poses a major health crisis and demands for the discovery of novel antimicrobial agents. The recent pandemic of SARS-CoV-2 has raised a public health emergency in almost all the countries of the world. Unlike viruses, a bacterium plays a significant role in various environmental issues such as bioremediation. Furthermore, biosurfactants produced by various bacterial species have an edge over traditionally produced chemical surfactants for its biodegradability, low toxicity and better interfacial activity with various applications in agriculture and industry. This special issue focuses on the global perspective of drug discovery for various antimicrobial, antiviral, and antifungal agents for infectious diseases. The issue also emphasizes the ongoing developments and the role of microbes in environmental remediation. We wish the articles published in this issue will enhance the current understanding in microbiology among the readers, and serve as the "seed of an idea" for drug development for ongoing COVID-19 pandemic.
Collapse
Affiliation(s)
- Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Indore-452 010, Madhya Pradesh, India,Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd, Indore-452010, Madhya Pradesh,
India
| |
Collapse
|
11
|
Nayarisseri A, Khandelwal R, Madhavi M, Selvaraj C, Panwar U, Sharma K, Hussain T, Singh SK. Shape-based Machine Learning Models for the Potential Novel COVID-19 Protease Inhibitors Assisted by Molecular Dynamics Simulation. Curr Top Med Chem 2020; 20:2146-2167. [PMID: 32621718 DOI: 10.2174/1568026620666200704135327] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 03/20/2020] [Accepted: 04/25/2020] [Indexed: 12/17/2022]
Abstract
BACKGROUND The vast geographical expansion of novel coronavirus and an increasing number of COVID-19 affected cases have overwhelmed health and public health services. Artificial Intelligence (AI) and Machine Learning (ML) algorithms have extended their major role in tracking disease patterns, and in identifying possible treatments. OBJECTIVE This study aims to identify potential COVID-19 protease inhibitors through shape-based Machine Learning assisted by Molecular Docking and Molecular Dynamics simulations. METHODS 31 Repurposed compounds have been selected targeting the main coronavirus protease (6LU7) and a machine learning approach was employed to generate shape-based molecules starting from the 3D shape to the pharmacophoric features of their seed compound. Ligand-Receptor Docking was performed with Optimized Potential for Liquid Simulations (OPLS) algorithms to identify highaffinity compounds from the list of selected candidates for 6LU7, which were subjected to Molecular Dynamic Simulations followed by ADMET studies and other analyses. RESULTS Shape-based Machine learning reported remdesivir, valrubicin, aprepitant, and fulvestrant as the best therapeutic agents with the highest affinity for the target protein. Among the best shape-based compounds, a novel compound identified was not indexed in any chemical databases (PubChem, Zinc, or ChEMBL). Hence, the novel compound was named 'nCorv-EMBS'. Further, toxicity analysis showed nCorv-EMBS to be suitable for further consideration as the main protease inhibitor in COVID-19. CONCLUSION Effective ACE-II, GAK, AAK1, and protease 3C blockers can serve as a novel therapeutic approach to block the binding and attachment of the main COVID-19 protease (PDB ID: 6LU7) to the host cell and thus inhibit the infection at AT2 receptors in the lung. The novel compound nCorv- EMBS herein proposed stands as a promising inhibitor to be evaluated further for COVID-19 treatment.
Collapse
Affiliation(s)
- Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore-452010, Madhya Pradesh, India,Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd., Mahalakshmi Nagar, Indore-452010, Madhya
Pradesh, India,Research Chair for Biomedical Applications of Nanomaterials, Biochemistry Department, College of Science, King
Saud University, Riyadh, Saudi Arabia,Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| | - Ravina Khandelwal
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore-452010, Madhya Pradesh, India
| | - Maddala Madhavi
- Department of Zoology, Nizam College, Osmania University, Hyderabad-500001, Telangana State, India
| | - Chandrabose Selvaraj
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| | - Umesh Panwar
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| | - Khushboo Sharma
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore-452010, Madhya Pradesh, India
| | - Tajamul Hussain
- Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia,Research Chair for Biomedical Applications of Nanomaterials, Biochemistry Department, College of Science, King
Saud University, Riyadh, Saudi Arabia
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| |
Collapse
|
12
|
Aher A, Udhwani T, Khandelwal R, Limaye A, Hussain T, Nayarisseri A, Singh SK. In silico Insights on IL-6: A Potential Target for Multicentric Castleman Disease. Curr Comput Aided Drug Des 2020; 16:641-653. [DOI: 10.2174/1573409915666190902142524] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 06/01/2019] [Accepted: 07/11/2019] [Indexed: 12/29/2022]
Abstract
Background:
Multicentric Castleman Disease (MCD) is a confrontational lymphoproliferative
disorder described by symptoms such as lymph node proliferation, unwarranted secretion of
inflammatory cytokines, hyperactive immune system, and in severe cases, multiple organ dysfunction.
Interleukin-6 (IL-6) is a pleiotropic cytokine which is involved in a large range of physiological
processes in our body such as pro-inflammation, anti-inflammation, differentiation of T-cells
and is reported to be a key pathological factor in MCD. In the case of MCD, it was observed that
IL-6 is overproduced from T-cells and macrophages which disturb Hepcidin, a vital regulator of
iron trafficking in macrophage. The present study endeavour to expound the inhibitor which binds
to IL-6 protein receptor with high affinity.
Methods:
MolegroVirtual Docker software was employed to find the best-established drug from
the list of selected inhibitors of IL-6. This compound was subjected to virtual screening against
PubChem database to get inhibitors with a very similar structure. These inhibitors were docked to
obtain a compound binding with high affinity to the target protein. The established compound and
the virtual screened compound were subjected to relative analysis of interactivity energy variables
and ADMET profile studies.
Results:
Among all the selected inhibitors, the virtual screened compound PubChem CID:
101119084 is seen to possess the highest affinity with the target protein. Comparative studies and
ADMET analysis further implicate this compound as a better inhibitor of the IL-6 protein.
Conclusion:
Hence, this compound recognized in the study possesses high potential as an IL-6 inhibitor
which might assist in the treatment of Multicentric Castleman Disease and should be examined
for its efficiency by in vivo studies.
Collapse
Affiliation(s)
- Abhishek Aher
- In Silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Trishang Udhwani
- In Silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Ravina Khandelwal
- In Silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Akanksha Limaye
- In Silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Tajamul Hussain
- Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Anuraj Nayarisseri
- In Silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| |
Collapse
|
13
|
Prajapati L, Khandelwal R, Yogalakshmi KN, Munshi A, Nayarisseri A. Computer-Aided Structure Prediction of Bluetongue Virus Coat Protein VP2 Assisted by Optimized Potential for Liquid Simulations (OPLS). Curr Top Med Chem 2020; 20:1720-1732. [DOI: 10.2174/1568026620666200516153753] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 12/13/2019] [Accepted: 12/17/2019] [Indexed: 12/13/2022]
Abstract
Background:
The capsid coated protein of Bluetongue virus (BTV) VP2 is responsible for
BTV transmission by the Culicoides vector to vertebrate hosts. Besides, VP2 is responsible for BTV
entry into permissive cells and hence plays a major role in disease progression. However, its mechanism
of action is still unknown.
Objective:
The present investigation aimed to predict the 3D structure of Viral Protein 2 of the bluetongue
virus assisted by Optimized Potential for Liquid Simulations (OPLS), structure validation, and an
active site prediction.
Methods:
The 3D structure of the VP2 protein was built using a Python-based Computational algorithm.
The templates were identified using Smith waterman’s Local alignment. The VP2 protein structure validated
using PROCHECK. Molecular Dynamics Simulation (MDS) studies were performed using an
academic software Desmond, Schrodinger dynamics, for determining the stability of a model protein.
The Ligand-Binding site was predicted by structure comparison using homology search and proteinprotein
network analysis to reveal their stability and inhibition mechanism, followed by the active site
identification.
Results:
The secondary structure of the VP2 reveals that the protein contains 220 alpha helix atoms,
40 310 helix, 151 beta sheets, 134 coils and 424 turns, whereas the 3D structure of Viral Protein 2 of
BTV has been found to have 15774 total atoms in the structure. However, 961 amino acids were found
in the final model. The dynamical cross-correlation matrix (DCCM) analysis tool identifies putative protein
domains and also confirms the stability of the predicted model and their dynamical behavior difference
with the correlative fluctuations in motion.
Conclusion:
The biological interpretation of the Viral Protein 2 was carried out. DCCM maps were calculated,
using a different coordinate reference frame, through which, protein domain boundaries and
protein domain residue constituents were identified. The obtained model shows good reliability. Moreover,
we anticipated that this research should play a promising role in the identification of novel candidates
with the target protein to inhibit their functional significance.
Collapse
Affiliation(s)
- Leena Prajapati
- Department of Environmental Science and Technology, Central University of Punjab, Bathinda-151001, Punjab, India
| | - Ravina Khandelwal
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
| | | | - Anjana Munshi
- Department of Human Genetics and Molecular Medicine, Central University of Punjab, Bathinda - 151001 Punjab, India
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
| |
Collapse
|
14
|
Pandey B, Aarthy M, Sharma M, Singh SK, Kumar V. Computational analysis identifies druggable mutations in human rBAT mediated Cystinuria. J Biomol Struct Dyn 2020; 39:5058-5067. [PMID: 32602810 DOI: 10.1080/07391102.2020.1784792] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Culex quinquefasciatus Cqm1 protein acts as the receptor for Lysinibacillus sphaericus mosquito-larvicidal binary (BinAB) toxin that is used worldwide for mosquito control. We found amino acid transporter protein, rBAT, as phylogenetically closest Cqm1 homolog in humans. The present study reveals large evolutionary distance between Cqm1 and rBAT, and rBAT ectodomain lacks the sequence motif which serves as binding-site for the BinAB toxin. Thus, BinAB toxin can be expected to remain safe for humans. rBAT (heavy subunit; SLC3A1) and catalytic b0,+AT (light subunit; SLC7A9), linked by single disulfide bond, mediate renal reabsorption of cystine and dibasic amino acids in Na+ independent manner. Mutations in rBAT cause type I Cystinuria disease which shows global prevalence, and rBAT can be thought as an important pharmacological target. However, 3D structures of rBAT and b0,+AT, the two components of b0,+ heteromeric amino acid transporter systems, are not available. We constructed a reliable homology model of rBAT using Cqm1 coordinates and that of transmembrane b0,+AT subunit using LAT1 coordinates. Mapping of pathogenic mutations onto rBAT ectodomain revealed their scattered distribution throughout the rBAT protein. Further, our computational simulations-based scoring of several known deleterious mutations of rBAT revealed that mutations those do not compromise the protein fold and stability, are localized on the same face of the molecule. These residues are expected to interact with the b0,+AT transporter. The present study thus identifies druggable sites on rBAT that could be targeted for the treatment of type I Cystinuria.Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- Bharati Pandey
- Radiation Biology & Health Sciences Division, Bhabha Atomic Research Centre, Mumbai, India
| | - Murali Aarthy
- Computer-aided drug design Lab, Department of Bioinformatics, Alagappa University, Karaikudi, India
| | - Mahima Sharma
- Radiation Biology & Health Sciences Division, Bhabha Atomic Research Centre, Mumbai, India
| | - Sanjeev Kumar Singh
- Computer-aided drug design Lab, Department of Bioinformatics, Alagappa University, Karaikudi, India
| | - Vinay Kumar
- Homi Bhabha National Institute, Mumbai, India
| |
Collapse
|
15
|
Selvaraj C, Dinesh DC, Panwar U, Abhirami R, Boura E, Singh SK. Structure-based virtual screening and molecular dynamics simulation of SARS-CoV-2 Guanine-N7 methyltransferase (nsp14) for identifying antiviral inhibitors against COVID-19. J Biomol Struct Dyn 2020; 39:4582-4593. [PMID: 32567979 PMCID: PMC7332868 DOI: 10.1080/07391102.2020.1778535] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The recent pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) calls the whole world into a medical emergency. For tackling Coronavirus Disease 2019 (COVID-19), researchers from around the world are swiftly working on designing and identifying inhibitors against all possible viral key protein targets. One of the attractive drug targets is guanine-N7 methyltransferase which plays the main role in capping the 5′-ends of viral genomic RNA and sub genomic RNAs, to escape the host’s innate immunity. We performed homology modeling and molecular dynamic (MD) simulation, in order to understand the molecular architecture of Guanosine-P3-Adenosine-5’,5’-Triphosphate (G3A) binding with C-terminal N7-MTase domain of nsp14 from SARS-CoV-2. The residue Asn388 is highly conserved in present both in N7-MTase from SARS-CoV and SARS-CoV-2 and displays a unique function in G3A binding. For an in-depth understanding of these substrate specificities, we tried to screen and identify inhibitors from the Traditional Chinese Medicine (TCM) database. The combination of several computational approaches, including screening, MM/GBSA, MD simulations, and PCA calculations, provides the screened compounds that readily interact with the G3A binding site of homology modeled N7-MTase domain. Compounds from this screening will have strong potency towards inhibiting the substrate-binding and efficiently hinder the viral 5’-end RNA capping mechanism. We strongly believe the final compounds can become COVID-19 therapeutics, with huge international support. Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- Chandrabose Selvaraj
- Computer Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, India
| | - Dhurvas Chandrasekaran Dinesh
- Section of Molecular Biology and Biochemistry, Institute of Organic Chemistry and Biochemistry AS CR, v.v.i, Prague 6, Czech Republic
| | - Umesh Panwar
- Computer Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, India
| | - Rajaram Abhirami
- Computer Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, India
| | - Evzen Boura
- Section of Molecular Biology and Biochemistry, Institute of Organic Chemistry and Biochemistry AS CR, v.v.i, Prague 6, Czech Republic
| | - Sanjeev Kumar Singh
- Computer Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, India
| |
Collapse
|
16
|
Limaye A, Sweta J, Madhavi M, Mudgal U, Mukherjee S, Sharma S, Hussain T, Nayarisseri A, Singh SK. In Silico Insights on GD2 : A Potential Target for Pediatric Neuroblastoma. Curr Top Med Chem 2020; 19:2766-2781. [DOI: 10.2174/1568026619666191112115333] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 09/02/2019] [Accepted: 09/25/2019] [Indexed: 02/07/2023]
Abstract
Background:Originating from the abnormal growth of neuroblasts, pediatric neuroblastoma affects the age group below 15 years. It is an aggressive heterogenous cancer with a high morbidity rate. Biological marker GD2 synthesised by the GD2 gene acts as a powerful predictor of neuroblastoma cells. GD2 gangliosides are sialic acid-containing glycosphingolipids. Differential expression during brain development governs the function of the GD2. The present study explains the interaction of the GD2 with its established inhibitors and discovers the compound having a high binding affinity against the target protein. Technically, during the development of new compounds through docking studies, the best drug among all pre-exist inhibitors was filtered. Hence in reference to the best docked compound, the study proceeded further.Methodology:The In silico approach provides a platform to determine and establish potential inhibitor against GD2 in Pediatric neuroblastoma. The 3D structure of GD2 protein was modelled by homology base fold methods using Smith-Watermans’ Local alignment. A total of 18 established potent compounds were subjected to molecular docking and Etoposide (CID: 36462) manifested the highest affinity. The similarity search presented 336 compounds similar to Etoposide.Results:Through virtual screening, the compound having PubChem ID 10254934 showed a better affinity towards GD2 than the established inhibitor. The comparative profiling of the two compounds based on various interactions such as H-bond interaction, aromatic interactions, electrostatic interactions and ADMET profiling and toxicity studies were performed using various computational tools.Conclusion:The docking separated the virtual screened drug (PubChemID: 10254934) from the established inhibitor with a better re-rank score of -136.33. The toxicity profile of the virtual screened drug was also lesser (less lethal) than the established drug. The virtual screened drug was observed to be bioavailable as it does not cross the blood-brain barrier. Conclusively, the virtual screened compound obtained in the present investigation is better than the established inhibitor and can be further augmented by In vitro analysis, pharmacodynamics and pharmacokinetic studies.
Collapse
Affiliation(s)
- Akanksha Limaye
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Jajoriya Sweta
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Maddala Madhavi
- Department of Zoology, Nizam College, Osmania University, Hyderabad - 500001, Telangana State, India
| | - Urvy Mudgal
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Sourav Mukherjee
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Shreshtha Sharma
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Tajamul Hussain
- Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| |
Collapse
|
17
|
Chen Z, Zhang R, Shi W, Li L, Liu H, Liu Z, Wu L. The Multifunctional Benefits of Naturally Occurring Delphinidin and Its Glycosides. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2019; 67:11288-11306. [PMID: 31557009 DOI: 10.1021/acs.jafc.9b05079] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Delphinidin (Del) and its glycosides are water-soluble pigments, belonging to a subgroup of flavonoids. They are health-promoting candidates for pharmaceutical and nutraceutical uses, as indicated by exhibiting antioxidation, anti-inflammation, antimicroorganism, antidiabetes, antiobesity, cardiovascular protection, neuroprotection, and anticancer properties. Glycosylation modification of Del is associated with increased stability and reduced biological activity. Del and its glycosides can be the alternative inhibitors of CBRs, ERα/β, EGFR, BCRP, and SGLT-1, and virtual docking indicates that the sugar moiety may not effectively interact with the active sites of the targets. Structure-based characteristics confer the multifunctional properties of Del and its glycosides. Because of their health-promoting effects, Del and its glycosides are promising and have been developed as potential pharmaceuticals. However, more investigation on the underlying mechanisms of Del and its glycosides in mediating cellular processes with high specificity are still needed. The research progression of Del and its glycosides over the last 10 years is comprehensively reviewed in this article.
Collapse
Affiliation(s)
- Zhixi Chen
- College of Pharmacy , Gannan Medical University , Ganzhou 341000 , China
| | - Rui Zhang
- College of Pharmacy , Gannan Medical University , Ganzhou 341000 , China
| | - Weimei Shi
- College of Pharmacy , Gannan Medical University , Ganzhou 341000 , China
| | - Linfu Li
- College of Pharmacy , Gannan Medical University , Ganzhou 341000 , China
| | - Hai Liu
- College of Pharmacy , Gannan Medical University , Ganzhou 341000 , China
| | - Zhiping Liu
- School of Basic Medicine , Gannan Medical University , Ganzhou 341000 , China
| | - Longhuo Wu
- College of Pharmacy , Gannan Medical University , Ganzhou 341000 , China
| |
Collapse
|
18
|
Nayarisseri A. Prospects of Utilizing Computational Techniques for the Treatment of Human Diseases. Curr Top Med Chem 2019; 19:1071-1074. [PMID: 31490742 DOI: 10.2174/156802661913190827102426] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Anuraj Nayarisseri
- In silico Research Laboratory Eminent Biosciences Mahalakshmi Nagar, Indore - 452010 Madhya Pradesh, India.,Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd., Indore - 452010 Madhya Pradesh, India
| |
Collapse
|
19
|
Yadav M, Khandelwal R, Mudgal U, Srinitha S, Khandekar N, Nayarisseri A, Vuree S, Singh SK. Identification of Potent VEGF Inhibitors for the Clinical Treatment of Glioblastoma, A Virtual Screening Approach. Asian Pac J Cancer Prev 2019; 20:2681-2692. [PMID: 31554364 PMCID: PMC6976853 DOI: 10.31557/apjcp.2019.20.9.2681] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 09/02/2019] [Indexed: 02/04/2023] Open
Abstract
Vascular endothelial growth factor (VEGF) expression could be found in all glioblastomas. VEGF takes part in numerous changes including the endothelial cell proliferation, the vasculature of solid tumor: its survival invasion, and migration, chemotaxis of bone marrow-derived progenitor cells, vasodilation and vascular permeability. VEGF inhibition can be a smart therapeutic strategy because it is extremely specific and less toxic than cytotoxic therapy. To establish better inhibition of VEGF than the current inhibitors, present study approach is by molecular docking, virtual screening to illustrate the inhibitor with superior affinity against VEGF to have a cautious pharma profile. To retrieve the best established and high-affinity high affinity molecule, Molegro Virtual Docker software was executed. The high-affinity scoring compounds were subjected to further similarity search to retrieve the drugs with similar properties from pubchem database. The completion of virtual screening reveals that PubChem compound SCHEMBL1250485 (PubChem CID: 66965667) has the highest affinity. The study of the drug-likeness was verified using OSIRIS Property Explorer software which supported the virtual screened result. Further ADMET study and drug comparative study strongly prove the superiority of the new established inhibitor with lesser rerank score and toxicity. Overall, the new inhibitor has higher potential to stop the expression of VEGF in glioblastoma and positively can be further analysed through In vitro studies.
Collapse
Affiliation(s)
- Mohini Yadav
- In silico Research Laboratory, Eminent Biosciences, Indore - 452 010, Madhya Pradesh, India. ,
| | - Ravina Khandelwal
- In silico Research Laboratory, Eminent Biosciences, Indore - 452 010, Madhya Pradesh, India. ,
| | - Urvy Mudgal
- In silico Research Laboratory, Eminent Biosciences, Indore - 452 010, Madhya Pradesh, India. ,
| | - Sivaraj Srinitha
- In silico Research Laboratory, Eminent Biosciences, Indore - 452 010, Madhya Pradesh, India. ,
| | - Natasha Khandekar
- In silico Research Laboratory, Eminent Biosciences, Indore - 452 010, Madhya Pradesh, India. ,
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Indore - 452 010, Madhya Pradesh, India. ,
- Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd., Indore-452010, Madhya Pradesh, India
| | - Sugunakar Vuree
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Division of Research and Development, Lovely Professional University, Phagwara, Punjab-144411, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| |
Collapse
|
20
|
Ali MA, Vuree S, Goud H, Hussain T, Nayarisseri A, Singh SK. Identification of High-affinity Small Molecules Targeting Gamma Secretase for the Treatment of Alzheimer’s Disease. Curr Top Med Chem 2019; 19:1173-1187. [DOI: 10.2174/1568026619666190617155326] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2018] [Revised: 01/12/2019] [Accepted: 04/10/2019] [Indexed: 02/07/2023]
Abstract
Background:
Alzheimers Disease (AD) is a neurodegenerative disease which is characterized by
the deposition of amyloid plaques in the brain- a concept supported by most of the researchers worldwide. The
main component of the plaques being amyloid-beta (Aβ42) results from the sequential cleavage of Amyloid
precursor protein (APP) by beta and gamma secretase. This present study intends to inhibit the formation of
amyloid plaques by blocking the action of gamma secretase protein with Inhibitors (GSI).
Methods:
A number of Gamma Secretase Inhibitors (GSI) were targeted to the protein by molecular docking.
The inhibitor having the best affinity was used as a subject for further virtual screening methods to obtain
similar compounds. The generated compounds were docked again at the same docking site on the protein to
find a compound with higher affinity to inhibit the protein. The highlights of virtually screened compound
consisted of Pharmacophore Mapping of the docking site. These steps were followed by comparative assessments
for both the compounds, obtained from the two aforesaid docking studies, which included interaction
energy descriptors, ADMET profiling and PreADMET evaluations.
Results:
111 GSI classified as azepines, sulfonamides and peptide isosteres were used in the study. By molecular
docking an amorpholino-amide, compound (22), was identified to be the high affinity compound GSI
along with its better interaction profiles.The virtually screened pubchem compound AKOS001083915
(CID:24462213) shows the best affinity with gamma secretase. Collective Pharmacophore mapping (H bonds,
electrostatic profile, binding pattern and solvent accesibility) shows a stable interaction. The resulting ADMETand
Descriptor values were nearly equivalent.
Conclusion:
These compounds identified herein hold a potential as Gamma Secretase inhibitors.According to
PreADMET values the compound AKOS001083915 is effective and specific to the target protein. Its
BOILED-egg plot analysis infers the compound permeable to blood brain barrier.Comparative study for both
the compounds resulted in having nearly equivalent properties. These compounds have the capacity to inhibit
the protein which is indirectly responsible for the formation of amyloid plaques and can be further put to in
vitro pharmacokinetic and dynamic studies.
Collapse
Affiliation(s)
- Meer Asif Ali
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Sugunakar Vuree
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Division of Research and Development, Lovely Professional University, Phagwara, Punjab, India
| | - Himshikha Goud
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Tajamul Hussain
- Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| |
Collapse
|
21
|
Sharda S, Khandelwal R, Adhikary R, Sharma D, Majhi M, Hussain T, Nayarisseri A, Singh SK. A Computer - Aided Drug Designing for Pharmacological Inhibition of Mutant ALK for the Treatment of Non-small Cell Lung Cancer. Curr Top Med Chem 2019; 19:1129-1144. [DOI: 10.2174/1568026619666190521084941] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 04/12/2019] [Accepted: 04/15/2019] [Indexed: 12/13/2022]
Abstract
Background:
Lung cancer is the most common among all the types of cancer worldwide with
1.8 million people diagnosed every year, leading to 1.6 million deaths every year according to the American
cancer society. The involvement of mutated Anaplasic Lymphoma Kinase (ALK) positive fusion
protein in the progression of NSCLC has made a propitious target to inhibit and treat NSCLC. In the
present study, the main motif is to screen the most effective inhibitor against ALK protein with the potential
pharmacological profile. The ligands selected were docked with Molegro Virtual Docker (MVD) and
CEP-37440 (PubChem CID- 71721648) was the best docked pre-established compound with a permissible
pharmacological profile.
Methods:
The selected ligands were docked with Molegro Virtual Docker (MVD). With reference to the
obtained compound with the lowest re-rank score, PubChem database was virtually screened to retrieve a
large set of similar compounds which were docked to find the compound with higher affinity. Further
comparative studies and in silico prediction included pharmacophore studies, proximity energy parameters,
ADMET and BOILED-egg plot analysis.
Results:
CEP-37440 (PubChem CID- 71721648) was the best docked pre-established compound with
preferable pharmacological profile and PubChem compound CID-123449015 came out as the most efficient
virtually screened inhibitor. Interestingly, the contours of the virtual screened compound PubChem
CID- 123449015 fall within our desired high volume cavity of protein having admirable property to control
the ALK regulation to prevent carcinogenesis in NSCLC. BOILED-Egg plot analysis depicts that
both the compounds have analogous characteristics in the divergent aspects. Moreover, in the evaluations
of Blood Brain Barrier, Human Intestinal Absorption, AMES toxicity, and LD50, the virtually screened
compound (PubChem CID-123449015) was found within high optimization.
Conclusion:
These investigations denote that the virtually screened compound (PubChem CID-
123449015) is more efficient to be a better prospective candidate for NSCLC treatment having good
pharmacological profile than the pre-established compound CEP-37440 (PubChem CID- 71721648) with
low re-rank score. The identified virtually screened compound has high potential to act as an ALK inhibitor
and can show promising results in the research of non-small cell lung cancer (NSCLC).
Collapse
Affiliation(s)
- Saphy Sharda
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Ravina Khandelwal
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Ritu Adhikary
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Diksha Sharma
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Manisha Majhi
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Tajamul Hussain
- Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| |
Collapse
|
22
|
Sweta J, Khandelwal R, Srinitha S, Pancholi R, Adhikary R, Ali MA, Nayarisseri A, Vuree S, Singh SK. Identification of High-Affinity Small Molecule Targeting IDH2 for the Clinical Treatment of Acute Myeloid Leukemia. Asian Pac J Cancer Prev 2019; 20:2287-2297. [PMID: 31450897 PMCID: PMC6852809 DOI: 10.31557/apjcp.2019.20.8.2287] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2018] [Accepted: 08/22/2019] [Indexed: 02/06/2023] Open
Abstract
Acute myeloid leukemia (AML) is symbolized by an increase in the number of myeloid cells in the bone marrow and an arrest in their maturation, frequently resulting in hematopoietic insufficiency (granulocytopenia, thrombocytopenia, or anemia) with or without leukocytosis either by a predominance of immature forms or a loss of normal hematopoiesis. IDH2 gene encodes for isocitrate dehydrogenase enzyme which is involved in the TCA cycle domino effect and converts isocitrate to alpha-ketoglutarate. In the U.S, the annual incidence of AML progressively increases with age to a peak of 12.6 per 100,000 adults of 65 years or older. Mutations in isocitrate dehydrogenase 2 (arginine 132) have been demonstrated to be recurrent gene alterations in acute myeloid leukemia (AML) by forming 2-Hydroxy alpha ketoglutarate which, instead of participating in TCA cycle, accumulates to form AML. The current study approaches by molecular docking and virtual screening to elucidate inhibitor with superior affinity against IDH2 and achieve a pharmacological profile. To obtain the best established drug Molegro Virtual Docker algorithm was executed. The compound AG-221 (Pub CID 71299339) having the high affinity score was subjected to similarity search to retrieve the drugs with similar properties. The virtual screened compound SCHEMBL16391748 (PubChem CID-117816179) shows high affinity for the protein. Comparative study and ADMET study for both the above compounds resulted in equivalent chemical properties. Virtual screened compound SCHEMBL16391748 (PubChem CID-117816179) shows the lowest re-rank score. These drugs are identified as high potential IDH2 inhibitors and can halt AML when validated through further In vitro screening.
Collapse
Affiliation(s)
- Jajoriya Sweta
- In silico Research Laboratory, Eminent Biosciences, Vijaynagar, Indore- 452010, Madhya Pradesh, India
| | - Ravina Khandelwal
- In silico Research Laboratory, Eminent Biosciences, Vijaynagar, Indore- 452010, Madhya Pradesh, India
| | - Sivaraj Srinitha
- In silico Research Laboratory, Eminent Biosciences, Vijaynagar, Indore- 452010, Madhya Pradesh, India
| | - Rashi Pancholi
- In silico Research Laboratory, Eminent Biosciences, Vijaynagar, Indore- 452010, Madhya Pradesh, India
| | - Ritu Adhikary
- In silico Research Laboratory, Eminent Biosciences, Vijaynagar, Indore- 452010, Madhya Pradesh, India
| | - Meer Asif Ali
- In silico Research Laboratory, Eminent Biosciences, Vijaynagar, Indore- 452010, Madhya Pradesh, India
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Vijaynagar, Indore- 452010, Madhya Pradesh, India
- Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd, Mahalakshmi Nagar, Indore-452010, Madhya Pradesh, India
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India. ,
| | - Sugunakar Vuree
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Division of Research and Development, Lovely Professional University, Phagwara, Punjab, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India. ,
| |
Collapse
|
23
|
Patidar K, Panwar U, Vuree S, Sweta J, Sandhu MK, Nayarisseri A, Singh SK. An In silico Approach to Identify High Affinity Small Molecule
Targeting m-TOR Inhibitors for the Clinical Treatment of
Breast Cancer. Asian Pac J Cancer Prev 2019; 20:1229-1241. [PMID: 31030499 PMCID: PMC6948900 DOI: 10.31557/apjcp.2019.20.4.1229] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Breast cancer is the most frequent malignancy among women. It is a heterogeneous disease with different subtypes defined by its hormone receptor. A hormone receptor is mainly concerned with the progression of the PI3K/AKT/mTOR pathway which is often dysregulated in breast cancer. This is a major signaling pathway that controls the activities such as cell growth, cell division, and cell proliferation. The present study aims to suppress mTOR protein by its various inhibitors and to select one with the highest binding affinity to the receptor protein. Out of 40 inhibitors of mTOR against breast cancer, SF1126 was identified to have the best docking score of -8.705, using Schrodinger Suite which was further subjected for high throughput screening to obtain best similar compound using Lipinski’s filters. The compound obtained after virtual screening, ID: ZINC85569445 is seen to have the highest affinity with the target protein mTOR. The same result based on the binding free energy analysis using MM-GBSA showed that the compound ZINC85569445 to have the the highest binding free energy. The next study of interaction between the ligand and receptor protein with the pharmacophore mapping showed the best conjugates, and the ZINC85569445 can be further studied for future benefits of treatment of breast cancer.
Collapse
Affiliation(s)
- Khushboo Patidar
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India. ,
| | - Umesh Panwar
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi,Tamil Nadu, India
| | - Sugunakar Vuree
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Division of Research and Development, Lovely Professional University, Phagwara, Punjab, India
| | - Jajoriya Sweta
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India. ,
| | - Manpreet Kaur Sandhu
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India. ,
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India. , ,Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi,Tamil Nadu, India.,Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd., Indore, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi,Tamil Nadu, India
| |
Collapse
|
24
|
Nayarisseri A, Singh SK. Functional Inhibition of VEGF and EGFR Suppressors in Cancer Treatment. Curr Top Med Chem 2019; 19:178-179. [DOI: 10.2174/156802661903190328155731] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Anuraj Nayarisseri
- Principal Scientist In silico Research Laboratory Eminent Biosciences 91, Sector-A, Mahalakshmi Nagar Indore - 452010, Madhya Pradesh, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Design and Molecular Modelling Lab. Department of Bioinformatics, Alagappa University Karaikudi -630003,Tamil Nadu, India
| |
Collapse
|
25
|
Udhwani T, Mukherjee S, Sharma K, Sweta J, Khandekar N, Nayarisseri A, Singh SK. Design of PD-L1 inhibitors for lung cancer. Bioinformation 2019; 15:139-150. [PMID: 31435160 PMCID: PMC6677907 DOI: 10.6026/97320630015139] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 02/10/2019] [Accepted: 02/19/2019] [Indexed: 12/31/2022] Open
Abstract
The progression of lung cancer is associated with inactivation of programmed cell death protein 1, abbreviated as PD- 1 which regulates the suppression of the body's immune system by suppressing T- cell inflammatory activity and is responsible for preventing cancer cell growth. It is of interest to identify inhibitors for PD-L1 dimeric structure through molecular docking and virtual screening. The virtual screened compound XGIQBUNWFCCMAS-UHFFFAOYSA-N (PubChem CID: 127263272) displays a high affinity with the target protein. ADMET analysis and cytotoxicity studies further add weight to this compound as a potential inhibitor of PD-L1. The established compound BMS-202 still shows the high re-rank score, but the virtual screened drug possesses a better ADMET profile with a higher intestinal absorption value and lower toxicity.
Collapse
Affiliation(s)
- Trishang Udhwani
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore 452010,Madhya Pradesh,India
| | - Sourav Mukherjee
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore 452010,Madhya Pradesh,India
| | - Khushboo Sharma
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore 452010,Madhya Pradesh,India
| | - Jajoriya Sweta
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore 452010,Madhya Pradesh,India
| | - Natasha Khandekar
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore 452010,Madhya Pradesh,India
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore 452010,Madhya Pradesh,India
- Bioinformatics Research Laboratory,LeGene Biosciences Pvt Ltd., Mahalakshmi Nagar,Indore 452010,Madhya Pradesh,India
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi 630 003, Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi 630 003, Tamil Nadu, India
| |
Collapse
|
26
|
Gokhale P, Chauhan APS, Arora A, Khandekar N, Nayarisseri A, Singh SK. FLT3 inhibitor design using molecular docking based virtual screening for acute myeloid leukemia. Bioinformation 2019; 15:104-115. [PMID: 31435156 PMCID: PMC6677903 DOI: 10.6026/97320630015104] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 02/10/2019] [Accepted: 02/19/2019] [Indexed: 02/08/2023] Open
Abstract
Acute Myeloid Leukaemia (AML) is a blood cancer, which affects the red blood cells in the bone marrow. Of the possible proteins that are affected in AML, fms-like tyrosine kinase 3 (FLT3) has long been recognized as a potential therapeutic target as it affects the other signaling pathways and leads to a cascade of events. First-generation inhibitors sorafenib and midostaurin, as well as secondgeneration agents such as quizartinib and crenolanib are known. It is of interest to identify new compounds against FLT3 with improved activity using molecular docking and virtual screening. Molecular docking of existing inhibitors selected a top scoring bestestablished candidate Quizartinib having PubChem CID: 24889392. Similarity searching resulted in compound XGIQBUNWFCCMASUHFFFAOYSA-NPubChemCID: 44598530 which shows higher affinity scores. A comparative study of both the compounds using a drug-drug comparison, ADMET studies, boiled egg plot and pharmacophore parameters and properties confirmed the result and predicted the ligand to be an efficient inhibitor of FLT3.
Collapse
Affiliation(s)
- Padmini Gokhale
- In silico Research Laboratory,Eminent Biosciences,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
| | | | - Anushka Arora
- In silico Research Laboratory,Eminent Biosciences,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
| | - Natasha Khandekar
- In silico Research Laboratory,Eminent Biosciences,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
| | - Anuraj Nayarisseri
- In silico Research Laboratory,Eminent Biosciences,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
- Bioinformatics Research Laboratory,LeGene Biosciences Pvt Ltd.,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
- Computer Aided Drug Designing and Molecular Modeling Lab,Department of Bioinformatics,Alagappa University,Karaikudi-630 003,Tamil Nadu,India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab,Department of Bioinformatics,Alagappa University,Karaikudi-630 003,Tamil Nadu,India
| |
Collapse
|
27
|
Jain D, Udhwani T, Sharma S, Gandhe A, Reddy PB, Nayarisseri A, Singh SK. Design of novel JAK3 Inhibitors towards Rheumatoid Arthritis using molecular docking analysis. Bioinformation 2019; 15:68-78. [PMID: 31435152 PMCID: PMC6677909 DOI: 10.6026/97320630015068] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 02/10/2019] [Accepted: 02/19/2019] [Indexed: 01/06/2023] Open
Abstract
Multiple cytokines play a pivotal role in the pathogenesis of Rheumatoid Arthritis by inducing intracellular signaling and it is known that the members of the Janus kinase (JAK) family are essential for such signal transduction. Janus kinase 3 is a tyrosine kinase that belongs to the Janus family of kinases. Drugs targeting JAK3 in the treatment of Rheumatoid arthritis is relevant. Therefore, it is of interest to design suitable inhibitors for JAK3 dimer using molecular docking with Molegro Virtual Docker. The compound possessing the highest affinity score is subjected to virtual screening to retrieve inhibitors. The compound SCHEMBL19100243 (PubChem CID- 76749591) displays a high affinity with the target protein. The affinity scores of this compound are more than known drugs. ADMET analysis and BOILED Egg plot provide insights into this compound as a potent inhibitor of JAK3.
Collapse
Affiliation(s)
- Divya Jain
- In silico Research Laboratory,Eminent Biosciences,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
- Department of Biotechnology and Microbiology,Government PG Arts and Science College, Ratlam-457001, Madhya Pradesh,India
| | - Trishang Udhwani
- In silico Research Laboratory,Eminent Biosciences,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
| | - Shreshtha Sharma
- In silico Research Laboratory,Eminent Biosciences,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
| | - Aishwarya Gandhe
- In silico Research Laboratory,Eminent Biosciences,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
| | - Palugulla Bhaskar Reddy
- Department of Biotechnology and Microbiology,Government PG Arts and Science College, Ratlam-457001, Madhya Pradesh,India
| | - Anuraj Nayarisseri
- In silico Research Laboratory,Eminent Biosciences,Mahalakshmi Nagar,Indore-452010,Madhya Pradesh,India
- Bioinformatics Research Laboratory,LeGene Biosciences Pvt Ltd., Mahalakshmi Nagar,Indore-452010, Madhya Pradesh,India
- Computer Aided Drug Designing and Molecular Modeling Lab,Department of Bioinformatics, Alagappa University,Karaikudi-630 003,Tamil Nadu,India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab,Department of Bioinformatics, Alagappa University,Karaikudi-630 003,Tamil Nadu,India
| |
Collapse
|
28
|
Shukla P, Khandelwal R, Sharma D, Dhar A, Nayarisseri A, Singh SK. Virtual Screening of IL-6 Inhibitors for Idiopathic Arthritis. Bioinformation 2019; 15:121-130. [PMID: 31435158 PMCID: PMC6677908 DOI: 10.6026/97320630015121] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 02/10/2019] [Accepted: 02/19/2019] [Indexed: 12/16/2022] Open
Abstract
Juvenile idiopathic arthritis (JIA) is a heterogeneous disease characterized by the arthritis of unknown origin and IL6 is a known target for JIA. 20 known inhibitors towards IL-6 were screened and Methotrexate (MTX) having PubChem ID: 126941 showed high binding capacity with the receptor IL-6. The similarity searching with this compound gave 269 virtual screened compounds. The said screening presented 269 possible drugs having structural similarity to Methotrexate. The docking studies of the screened drugs separated the compound having PubChem CID: 122677576 (re-rank value of -140.262). Toxicity and interaction profile validated this compound for having a better affinity with the target protein. Conclusively, this study shows that according to ADMET profile and BOILED-Egg plot, the compound (PubChem CID: 122677576) obtained from Virtual Screen could be the best drug in future during the prevention of juvenile idiopathic arthritis. In the current study, the drug CID: 122677576 is a potent candidate for treating JIA. The pharmacophore study revealed that the drug CID: 122677576 is a non-inhibitor of CYP450 microsomal enzymes and was found to be non-toxic, similar to the established drug Methotrexate (CID: 126941). It has a lower LD50 value of 2.6698mol/kg as compared to the established compound having LD50 value as 23.4955mol/kg. Moreover, the compound was found to be non-carcinogenic.
Collapse
Affiliation(s)
- Palak Shukla
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore – 452010,Madhya Pradesh, India
| | - Ravina Khandelwal
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore – 452010,Madhya Pradesh, India
| | - Diksha Sharma
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore – 452010,Madhya Pradesh, India
| | - Anindya Dhar
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore – 452010,Madhya Pradesh, India
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar,Indore – 452010,Madhya Pradesh, India
- Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd.,Mahalakshmi Nagar,Indore - 452010,Madhya Pradesh,India
- Computer Aided Drug Designing and Molecular Modelling Lab,Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modelling Lab,Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
| |
Collapse
|