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Mousa SAS, El-Qaliei MIH, Atalla AA, Hussien AHH, Khodairy A, Abdou A, Drar AM, Gad MA. Synthesis, Insecticide Evaluation & Molecular Docking Studies of Some New Functionalized Pyrazole Derivatives Against the Cotton Leafworm, Spodoptera littoralis. Chem Biodivers 2024; 21:e202400831. [PMID: 39005105 DOI: 10.1002/cbdv.202400831] [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: 04/02/2024] [Revised: 07/14/2024] [Accepted: 07/15/2024] [Indexed: 07/16/2024]
Abstract
5-(Cyanomethyl)-3-((5,5-dimethyl-3-oxocyclohex-1-en-1-yl)amino)-1H-pyrazole-4-carbonitrile (3) is used as a key for the synthesis of arylidenes 5 a-fvia its reaction with some aldehydes 4 a-f. 5-[(5,5-Dimethyl-3-oxocyclohex-1-en-1-yl)amino]-3-(2-imino-2H-chromen-3-yl)-1H-pyrazole-4-carbonitrile (7) was synthesized via the reaction of compound (3) with 2-Hydroxybenzaldehyde in EtOH/piperidine. The target compounds were tested against cotton leafworm larvae in their second and fourth instar. The available data demonstrated that the LC50 values for commercial phenylpyrazole were 3.37 mg/L and 4.55 mg/L for the most affected synthesized compound, 5 b. The chemical structure of compound 5 bhas two cyano moieties, a pyrazole ring and a chlorophenyl, which may be increasing it efficiency. Evaluation of the latent effects of the examined synthesized compounds on various biological parameters, including adult longevity, pupal weight, proportion of normal, deformed pupae, adult emergency, fecundity, and egg hatchability, was done in an additional effort to slightly improve insecticidal compounds. Seven target synthesized compounds were subjected to a molecular docking analysis against glutamate-activated chloride channels. Twelve artificial compounds with the PDB ID of 4COF were subjected to a molecular docking study against the gamma-aminobutyric acid receptor (GABA).
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Affiliation(s)
- Sayed A S Mousa
- Department of Chemistry, Faculty of Science, Al-Azhar University at Assiut, 71524, Assiut, Egypt
| | - Mohamed I H El-Qaliei
- Department of Chemistry, Faculty of Science, Al-Azhar University at Assiut, 71524, Assiut, Egypt
| | - Ahmed A Atalla
- Department of Chemistry, Faculty of Science, Al-Azhar University at Assiut, 71524, Assiut, Egypt
| | - Ahmed H H Hussien
- Department of Chemistry, Faculty of Science, Al-Azhar University at Assiut, 71524, Assiut, Egypt
| | - Ahmed Khodairy
- Chemistry Department, Faculty of Science, Sohag University, 282524, Sohag, Egypt
| | - Aly Abdou
- Chemistry Department, Faculty of Science, Sohag University, 282524, Sohag, Egypt
| | - Ali M Drar
- Research Institute of Plant Protection, Agricultural Research Center, 12619, Giza, Doki, Egypt
| | - Mohamed A Gad
- Research Institute of Plant Protection, Agricultural Research Center, 12619, Giza, Doki, Egypt
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2
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Al‐kuraishy HM, Al‐Gareeb AI, Albuhadily AK, Elewa YHA, AL‐Farga A, Aqlan F, Zahran MH, Batiha GE. Sleep disorders cause Parkinson's disease or the reverse is true: Good GABA good night. CNS Neurosci Ther 2024; 30:e14521. [PMID: 38491789 PMCID: PMC10943276 DOI: 10.1111/cns.14521] [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: 07/13/2023] [Revised: 10/03/2023] [Accepted: 10/23/2023] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Parkinson's disease (PD) is a progressive neurodegenerative brain disease due to degeneration of dopaminergic neurons (DNs) presented with motor and non-motor symptoms. PD symptoms are developed in response to the disturbance of diverse neurotransmitters including γ-aminobutyric acid (GABA). GABA has a neuroprotective effect against PD neuropathology by protecting DNs in the substantia nigra pars compacta (SNpc). It has been shown that the degeneration of GABAergic neurons is linked with the degeneration of DNs and the progression of motor and non-motor PD symptoms. GABA neurotransmission is a necessary pathway for normal sleep patterns, thus deregulation of GABAergic neurotransmission in PD could be the potential cause of sleep disorders in PD. AIM Sleep disorders affect GABA neurotransmission leading to memory and cognitive dysfunction in PD. For example, insomnia and short sleep duration are associated with a reduction of brain GABA levels. Moreover, PD-related disorders including rigidity and nocturia influence sleep patterns leading to fragmented sleep which may also affect PD neuropathology. However, the mechanistic role of GABA in PD neuropathology regarding motor and non-motor symptoms is not fully elucidated. Therefore, this narrative review aims to clarify the mechanistic role of GABA in PD neuropathology mainly in sleep disorders, and how good GABA improves PD. In addition, this review of published articles tries to elucidate how sleep disorders such as insomnia and REM sleep behavior disorder (RBD) affect PD neuropathology and severity. The present review has many limitations including the paucity of prospective studies and most findings are taken from observational and preclinical studies. GABA involvement in the pathogenesis of PD has been recently discussed by recent studies. Therefore, future prospective studies regarding the use of GABA agonists in the management of PD are suggested to observe their distinct effects on motor and non-motor symptoms. CONCLUSION There is a bidirectional relationship between the pathogenesis of PD and sleep disorders which might be due to GABA deregulation.
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Affiliation(s)
- Hayder M. Al‐kuraishy
- Department of Clinical Pharmacology and Medicine, College of MedicineAl‐Mustansiriya UniversityBaghdadIraq
| | - Ali I. Al‐Gareeb
- Department of Clinical Pharmacology and Medicine, College of MedicineAl‐Mustansiriya UniversityBaghdadIraq
| | - Ali K. Albuhadily
- Department of Clinical Pharmacology and Medicine, College of MedicineAl‐Mustansiriya UniversityBaghdadIraq
| | - Yaser Hosny Ali Elewa
- Department of Histology and Cytology, Faculty of Veterinary MedicineZagazig UniversityZagazigEgypt
- Faculty of Veterinary MedicineHokkaido UniversitySapporoJapan
| | - Ammar AL‐Farga
- Biochemistry Department, College of SciencesUniversity of JeddahJeddahSaudia Arbia
| | - Faisal Aqlan
- Department of Chemistry, College of SciencesIbb UniversityIbb GovernorateYemen
| | | | - Gaber El‐Saber Batiha
- Department of Pharmacology and Therapeutics, Faculty of Veterinary MedicineDamanhur UniversityDamanhurEgypt
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3
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Chen H, Siu SWI, Wong CTT, Qiu J, Cheung AKK, Lee SMY. Anti-epileptic Kunitz-like peptides discovered in the branching coral Acropora digitifera through transcriptomic analysis. Arch Toxicol 2022; 96:2589-2608. [PMID: 35604417 DOI: 10.1007/s00204-022-03311-4] [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: 02/24/2022] [Accepted: 04/27/2022] [Indexed: 11/29/2022]
Abstract
Approximately 50 million people are suffering from epilepsy worldwide. Corals have been used for treating epilepsy in traditional Chinese medicine, but the mechanism of this treatment is unknown. In this study, we analyzed the transcriptome of the branching coral Acropora digitifera and obtained its Kyoto Encyclopedia of Genes and Genomes (KEGG), EuKaryotic Orthologous Groups (KOG) and Gene Ontology (GO) annotation. Combined with multiple sequence alignment and phylogenetic analysis, we discovered three polypeptides, we named them AdKuz1, AdKuz2 and AdKuz3, from A. digitifera that showed a close relationship to Kunitz-type peptides. Molecular docking and molecular dynamics simulation indicated that AdKuz1 to 3 could interact with GABAA receptor but AdKuz2-GABAA remained more stable than others. The biological experiments showed that AdKuz1 and AdKuz2 exhibited an anti-inflammatory effect by decreasing the aberrant level of nitric oxide (NO), IL-6, TNF-α and IL-1β induced by LPS in BV-2 cells. In addition, the pentylenetetrazol (PTZ)-induced epileptic effect on zebrafish was remarkably suppressed by AdKuz1 and AdKuz2. AdKuz2 particularly showed superior anti-epileptic effects compared to the other two peptides. Furthermore, AdKuz2 significantly decreased the expression of c-fos and npas4a, which were up-regulated by PTZ treatment. In addition, AdKuz2 reduced the synthesis of glutamate and enhanced the biosynthesis of gamma-aminobutyric acid (GABA). In conclusion, the results indicated that AdKuz2 may affect the synthesis of glutamate and GABA and enhance the activity of the GABAA receptor to inhibit the symptoms of epilepsy. We believe, AdKuz2 could be a promising anti-epileptic agent and its mechanism of action should be further investigated.
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Affiliation(s)
- Hanbin Chen
- State Key Laboratory of Quality Research in Chinese Medicine and Institute of Chinese Medical Sciences, University of Macau, Macao, China.,Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Shirley Weng In Siu
- Institute of Science and Environment, University of Saint Joseph, Macao, China
| | - Clarence Tsun Ting Wong
- Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, China
| | - Jianwen Qiu
- Department of Biology and Hong Kong Branch of the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Hong Kong Baptist University, Hong Kong, China.,Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China
| | - Alex Kwok-Kuen Cheung
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
| | - Simon Ming Yuen Lee
- State Key Laboratory of Quality Research in Chinese Medicine and Institute of Chinese Medical Sciences, University of Macau, Macao, China. .,Department of Pharmaceutical Sciences, Faculty of Health Sciences, University of Macau, Macao, China.
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4
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Yadav M, Abdalla M, Madhavi M, Chopra I, Bhrdwaj A, Soni L, Shaheen U, Prajapati L, Sharma M, Sikarwar MS, Albogami S, Hussain T, Nayarisseri A, Singh SK. Structure-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation and Pharmacokinetic modelling of Cyclooxygenase-2 (COX-2) inhibitor for the clinical treatment of Colorectal Cancer. MOLECULAR SIMULATION 2022. [DOI: 10.1080/08927022.2022.2068799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Manasi Yadav
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India
| | - Mohnad Abdalla
- Key Laboratory of Chemical Biology (Ministry of Education), Department of Pharmaceutics, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, PR People’s Republic of China
| | - Maddala Madhavi
- Department of Zoology, Osmania University, Hyderabad, Telangana State, India
| | - Ishita Chopra
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India
- Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd, Indore, Madhya Pradesh, India
| | - Anushka Bhrdwaj
- 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
| | - Lovely Soni
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India
| | - Uzma Shaheen
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India
| | - Leena Prajapati
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India
| | - Megha Sharma
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India
| | | | - Sarah Albogami
- Department of Biotechnology, College of Science, Taif University, Taif, Saudi Arabia
| | - Tajamul Hussain
- Research Chair for Biomedical Applications of Nanomaterials, Biochemistry Department, College of Science, King Saud University, Riyadh, Saudi Arabia
- Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India
- Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd, Indore, 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, Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, India
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5
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Mukherjee S, Abdalla M, Yadav M, Madhavi M, Bhrdwaj A, Khandelwal R, Prajapati L, Panicker A, Chaudhary A, Albrakati A, Hussain T, Nayarisseri A, Singh SK. Structure-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation of VEGF inhibitors for the clinical treatment of Ovarian Cancer. J Mol Model 2022; 28:100. [PMID: 35325303 DOI: 10.1007/s00894-022-05081-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 03/08/2022] [Indexed: 11/28/2022]
Abstract
Vascular endothelial growth factor (VEGF) and its receptor play an important role both in physiologic and pathologic angiogenesis, which is identified in ovarian cancer progression and metastasis development. The aim of the present investigation is to identify a potential vascular endothelial growth factor inhibitor which is playing a crucial role in stimulating the immunosuppressive microenvironment in tumor cells of the ovary and to examine the effectiveness of the identified inhibitor for the treatment of ovarian cancer using various in silico approaches. Twelve established VEGF inhibitors were collected from various literatures. The compound AEE788 displays great affinity towards the target protein as a result of docking study. AEE788 was further used for structure-based virtual screening in order to obtain a more structurally similar compound with high affinity. Among the 80 virtual screened compounds, CID 88265020 explicates much better affinity than the established compound AEE788. Based on molecular dynamics simulation, pharmacophore and comparative toxicity analysis of both the best established compound and the best virtual screened compound displayed a trivial variation in associated properties. The virtual screened compound CID 88265020 has a high affinity with the lowest re-rank score and holds a huge potential to inhibit the VGFR and can be implemented for prospective future investigations in ovarian cancer.
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Affiliation(s)
- Sourav Mukherjee
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore, 452010, Madhya Pradesh, 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, Shandong Province, 250012, People's Republic of China
| | - Manasi Yadav
- 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, India
| | - Anushka Bhrdwaj
- 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
| | - Leena Prajapati
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore, 452010, Madhya Pradesh, India
| | - Aravind Panicker
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore, 452010, Madhya Pradesh, India
| | - Aashish Chaudhary
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore, 452010, Madhya Pradesh, India
| | - Ashraf Albrakati
- Department of Human Anatomy, College of Medicine, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia
| | - 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
| | - Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, 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.
- Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd, 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.
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6
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Nayarisseri A. Experimental and Computational Approaches to Improve Binding Affinity in Chemical Biology and Drug Discovery. Curr Top Med Chem 2021; 20:1651-1660. [PMID: 32614747 DOI: 10.2174/156802662019200701164759] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Drug discovery is one of the most complicated processes and establishment of a single drug may require multidisciplinary attempts to design efficient and commercially viable drugs. The main purpose of drug design is to identify a chemical compound or inhibitor that can bind to an active site of a specific cavity on a target protein. The traditional drug design methods involved various experimental based approaches including random screening of chemicals found in nature or can be synthesized directly in chemical laboratories. Except for the long cycle design and time, high cost is also the major issue of concern. Modernized computer-based algorithm including structure-based drug design has accelerated the drug design and discovery process adequately. Surprisingly from the past decade remarkable progress has been made concerned with all area of drug design and discovery. CADD (Computer Aided Drug Designing) based tools shorten the conventional cycle size and also generate chemically more stable and worthy compounds and hence reduce the drug discovery cost. This special edition of editorial comprises the combination of seven research and review articles set emphasis especially on the computational approaches along with the experimental approaches using a chemical synthesizing for the binding affinity in chemical biology and discovery as a salient used in de-novo drug designing. This set of articles exfoliates the role that systems biology and the evaluation of ligand affinity in drug design and discovery for the future.
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Affiliation(s)
- Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
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7
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Qureshi S, Khandelwal R, Madhavi M, Khurana N, Gupta N, Choudhary SK, Suresh RA, Hazarika L, Srija CD, Sharma K, Hindala MR, Hussain T, Nayarisseri A, Singh SK. A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma. Curr Top Med Chem 2021; 21:790-818. [PMID: 33463471 DOI: 10.2174/1568026621666210119112336] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 12/18/2020] [Accepted: 12/24/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Mantle cell lymphoma (MCL) is a type of non-Hodgkin lymphoma characterized by the mutation and overexpression of the cyclin D1 protein by the reciprocal chromosomal translocation t(11;14)(q13:q32). AIM The present study aims to identify potential inhibition of MMP9, Proteasome, BTK, and TAK1 and determine the most suitable and effective protein target for the MCL. METHODOLOGY Nine known inhibitors for MMP9, 24 for proteasome, 15 for BTK and 14 for TAK1 were screened. SB-3CT (PubChem ID: 9883002), oprozomib (PubChem ID: 25067547), zanubrutinib (PubChem ID: 135565884) and TAK1 inhibitor (PubChem ID: 66760355) were recognized as drugs with high binding capacity with their respective protein receptors. 41, 72, 102 and 3 virtual screened compounds were obtained after the similarity search with compound (PubChem ID:102173753), PubChem compound SCHEMBL15569297 (PubChem ID:72374403), PubChem compound SCHEMBL17075298 (PubChem ID:136970120) and compound CID: 71814473 with best virtual screened compounds. RESULT MMP9 inhibitors show commendable affinity and good interaction profile of compound holding PubChem ID:102173753 over the most effective established inhibitor SB-3CT. The pharmacophore study of the best virtual screened compound reveals its high efficacy based on various interactions. The virtual screened compound's better affinity with the target MMP9 protein was deduced using toxicity and integration profile studies. CONCLUSION Based on the ADMET profile, the compound (PubChem ID: 102173753) could be a potent drug for MCL treatment. Similar to the established SB-3CT, the compound was non-toxic with LD50 values for both the compounds lying in the same range.
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Affiliation(s)
- Shahrukh Qureshi
- 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
| | - Maddala Madhavi
- Department of Zoology, Nizam College, Osmania University, Hyderabad - 500001, Telangana State, India
| | - Naveesha Khurana
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
| | - Neha Gupta
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
| | - Saurav K Choudhary
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
| | - Revathy A Suresh
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
| | - Lima Hazarika
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
| | - Chillamcherla D Srija
- 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
| | - Mali R Hindala
- 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 K Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India
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8
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Nayarisseri A, Khandelwal R, Tanwar P, Madhavi M, Sharma D, Thakur G, Speck-Planche A, Singh SK. Artificial Intelligence, Big Data and Machine Learning Approaches in Precision Medicine & Drug Discovery. Curr Drug Targets 2021; 22:631-655. [PMID: 33397265 DOI: 10.2174/1389450122999210104205732] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 08/21/2020] [Accepted: 09/14/2020] [Indexed: 11/22/2022]
Abstract
Artificial Intelligence revolutionizes the drug development process that can quickly identify potential biologically active compounds from millions of candidate within a short period. The present review is an overview based on some applications of Machine Learning based tools, such as GOLD, Deep PVP, LIB SVM, etc. and the algorithms involved such as support vector machine (SVM), random forest (RF), decision tree and Artificial Neural Network (ANN), etc. at various stages of drug designing and development. These techniques can be employed in SNP discoveries, drug repurposing, ligand-based drug design (LBDD), Ligand-based Virtual Screening (LBVS) and Structure- based Virtual Screening (SBVS), Lead identification, quantitative structure-activity relationship (QSAR) modeling, and ADMET analysis. It is demonstrated that SVM exhibited better performance in indicating that the classification model will have great applications on human intestinal absorption (HIA) predictions. Successful cases have been reported which demonstrate the efficiency of SVM and RF models in identifying JFD00950 as a novel compound targeting against a colon cancer cell line, DLD-1, by inhibition of FEN1 cytotoxic and cleavage activity. Furthermore, a QSAR model was also used to predict flavonoid inhibitory effects on AR activity as a potent treatment for diabetes mellitus (DM), using ANN. Hence, in the era of big data, ML approaches have been evolved as a powerful and efficient way to deal with the huge amounts of generated data from modern drug discovery to model small-molecule drugs, gene biomarkers and identifying the novel drug targets for various diseases.
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Affiliation(s)
- Anuraj Nayarisseri
- 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
| | - Poonam Tanwar
- 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
| | - Diksha Sharma
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
| | - Garima Thakur
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore - 452010, Madhya Pradesh, India
| | - Alejandro Speck-Planche
- Programa Institucional de Fomento a la Investigacion, Desarrollo e Innovacion, Universidad Tecnologica Metropolitana, Ignacio Valdivieso 2409, P.O. 8940577, San Joaquin, Santiago, Chile
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630003, Tamil Nadu, India
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9
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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.
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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
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10
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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.
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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
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11
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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.
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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
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12
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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.
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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
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13
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Ali W, Shar NA. Molecular docking analysis of timepidium with Acetylcholine and lumacaftor with GABA(A) activator. Bioinformation 2019; 15:832-837. [PMID: 31902984 PMCID: PMC6936661 DOI: 10.6026/97320630015832] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 12/10/2019] [Accepted: 12/11/2019] [Indexed: 12/12/2022] Open
Abstract
Epilepsy is a chronic disorder characterized by disturbed tissue related molecular activity within the brain irrespective of age. The cause is very difficult to understand towards a suitable treatment. However, its symptoms like seizures are treated and suppressed by known medications. Moreover, the condition is linked with neuro-transmitters such as GABA (gamma amino butyric acid) and acetylcholine. Therefore, it is of interest to design and develop inhibitors for these targets. Hence, we describe the molecular binding features of timepidium with acetylcholine and lumacaftor with GABA(A) activator using molecular docking based geometric optimization and screening analysis for further consideration.
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Affiliation(s)
- Warda Ali
- Department of Biomedical Engineering, NED University of Engineering and Technology Karachi, Pakistan
| | - Nisar A Shar
- Department of Biomedical Engineering, NED University of Engineering and Technology Karachi, Pakistan
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14
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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
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15
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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.
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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
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16
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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.
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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
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17
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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).
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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
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18
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Design, synthesis, in silico ADMET profile and GABA‐A docking of novel phthalazines as potent anticonvulsants. Arch Pharm (Weinheim) 2019; 352:e1800387. [DOI: 10.1002/ardp.201800387] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Revised: 03/03/2019] [Accepted: 03/17/2019] [Indexed: 11/07/2022]
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19
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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.
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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
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20
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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.
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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
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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.
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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
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22
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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.
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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
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23
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Tahir RA, Wu H, Javed N, Khalique A, Khan SAF, Mir A, Ahmed MS, Barreto GE, Qing H, Ashraf GM, Sehgal SA. Pharmacoinformatics and molecular docking reveal potential drug candidates against Schizophrenia to target TAAR6. J Cell Physiol 2018; 234:13263-13276. [PMID: 30569503 DOI: 10.1002/jcp.27999] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 11/30/2018] [Indexed: 11/10/2022]
Abstract
Schizophrenia (SZ) is a complex disabling disorder that leads to the mental disability and afflicts 1% of the world's total population and placed in top ten medical disorders. In current work, bioinformatics analyses were carried out on Trace amine (TA)-associated receptor 6 (TAAR6) to recognize the potential drugs and compounds against SZ. Comparative modeling and threading-based approaches were utilized for the structure prediction of TAAR6. Fifty-nine predicted structures were evaluated by various model assessment techniques and final model having only eight amino acids in the outlier region and 98.5% overall quality factor was chosen for further pharmacoinformatics and molecular docking analyses. From an extensive literature review, 11 Food and Drug Administration (FDA) approved drugs were analyzed by computational techniques and Aripiprazole was found as the most effective drug against SZ by targeting TAAR6. Here, we report five novel molecules which exhibited the highest binding affinity, effective drug properties, and interestingly, observed better results than the approved selected drugs against SZ by targeting TAAR6. The docking analyses revealed that Arg-92, Trp-98, Gln-191, Thr-192, Ala-290, Cys-291, Tyr-293, and Glu-294 residues were observed as critical interacting residues in receptor-ligand interactions. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, Lipinski rule of five, highest binding affinity coupled with virtual screening (VS), and pharmacophore modeling approach illustrated that aripiprazole (-8.6 kcal/mol) and TAAR6_0094 (-9.3 kcal/mol) are potential inhibitors for targeting TAAR6. It is suggested that schizophrenic patients have to use Aripiprazole for the medication of SZ by targeting TAAR6 and develop effective therapies by utilizing scrutinized novel compound.
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Affiliation(s)
- Rana Adnan Tahir
- Key Laboratory of Molecular Medicine and Biotherapy in the Ministry of Industry and Information Technology, Department of Biology, School of Life Sciences, Beijing Institute of Technology, Beijing, China.,Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus, Islamabad, Pakistan
| | - Hao Wu
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Naima Javed
- Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus, Islamabad, Pakistan
| | - Anila Khalique
- State Key Laboratory of Medicinal Chemical Biology, Key Laboratory of Bioactive Materials of Ministry of Education, College of Life Sciences, Nankai University, Tianjin, China
| | | | - Asif Mir
- Department of Bioinformatics and Biotechnology, International Islamic University Islamabad, Islamabad, Pakistan
| | - Muhammad Saad Ahmed
- Department of Biological Engineering/Institute of Biotransformation and Synthetic Biosystem, School of Life Sciences, Beijing Institute of Technology, Beijing, China
| | - George E Barreto
- Departamento de Nutrición y Bioquímica, Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Hong Qing
- Key Laboratory of Molecular Medicine and Biotherapy in the Ministry of Industry and Information Technology, Department of Biology, School of Life Sciences, Beijing Institute of Technology, Beijing, China
| | - Ghulam Md Ashraf
- King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Sheikh Arslan Sehgal
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus, Islamabad, Pakistan.,University of Chinese Academy of Sciences, Beijing, China
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Patidar K, Deshmukh A, Bandaru S, Lakkaraju C, Girdhar A, Gutlapalli VR, Banerjee T, Nayarisseri A, Singh SK. Virtual Screening Approaches in Identification of Bioactive Compounds Akin to Delphinidin as Potential HER2 Inhibitors for the Treatment of Breast Cancer. Asian Pac J Cancer Prev 2016; 17:2291-5. [DOI: 10.7314/apjcp.2016.17.4.2291] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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