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Ivanov JM, Tenchov R, Ralhan K, Iyer KA, Agarwal S, Zhou QA. In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery. J Chem Inf Model 2024. [PMID: 39289178 DOI: 10.1021/acs.jcim.4c00864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/19/2024]
Abstract
TBK1, or TANK-binding kinase 1, is an enzyme that functions as a serine/threonine protein kinase. It plays a crucial role in various cellular processes, including the innate immune response to viruses, cell proliferation, apoptosis, autophagy, and antitumor immunity. Dysregulation of TBK1 activity can lead to autoimmune diseases, neurodegenerative disorders, and cancer. Due to its central role in these critical pathways, TBK1 is a significant focus of research for therapeutic drug development. In this paper, we explore data from the CAS Content Collection regarding TBK1 and its implication in a large assortment of diseases and disorders. With the demand for developing efficient TBK1 inhibitors being outlined, we focus on utilizing a machine learning approach for developing predictive models for TBK1 inhibition, derived from the fragment-functional analysis descriptors. Using the extensive CAS Content Collection, we assembled a training set of TBK1 inhibitors with experimentally measured IC50 values. We explored several machine learning techniques combined with various molecular descriptors to derive and select the best TBK1 inhibitor QSAR models. Certain significant structural alerts that potentially contribute to inhibition of TBK1 are outlined and discussed. The merit of the article stems from identifying the most adequate TBK1 QSAR models and subsequent successful development of advanced positive training data to facilitate and enhance drug discovery for an important therapeutic target such as TBK1 inhibitors, based on an extensive, wide-ranging set of scientific information provided by the CAS Content Collection.
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Affiliation(s)
- Julian M Ivanov
- CAS, A Division of the American Chemical Society, Columbus, Ohio 43210, United States
| | - Rumiana Tenchov
- CAS, A Division of the American Chemical Society, Columbus, Ohio 43210, United States
| | | | - Kavita A Iyer
- ACS International India Pvt. Ltd., Pune 411044, India
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da Fonseca AM, Caluaco BJ, Madureira JMC, Cabongo SQ, Gaieta EM, Djata F, Colares RP, Neto MM, Fernandes CFC, Marinho GS, Dos Santos HS, Marinho ES. Screening of Potential Inhibitors Targeting the Main Protease Structure of SARS-CoV-2 via Molecular Docking, and Approach with Molecular Dynamics, RMSD, RMSF, H-Bond, SASA and MMGBSA. Mol Biotechnol 2024; 66:1919-1933. [PMID: 37490200 DOI: 10.1007/s12033-023-00831-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 07/17/2023] [Indexed: 07/26/2023]
Abstract
Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the Mpro protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H-Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (-6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (-9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (-9.8 kcal/mol/RMSD of 1.46 Å) and olysio (-9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the Mpro protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.
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Affiliation(s)
- Aluísio Marques da Fonseca
- Mestrado Acadêmico em Sociobiodiversidades e Tecnologias Sustentáveis - MASTS, Instituto de Engenharias e Desenvolvimento Sustentável, Universidade da Integração Internacional da Lusofonia Afro-Brasileira, Acarape, CE, Brazil
| | - Bernardino Joaquim Caluaco
- Instituto de Ciências Exatas e da Natureza, Universidade da Integração Internacional da Lusofonia Afro-Brasileira, Acarape, CE, Brazil
| | | | - Sadrack Queque Cabongo
- Instituto de Ciências Exatas e da Natureza, Universidade da Integração Internacional da Lusofonia Afro-Brasileira, Acarape, CE, Brazil
| | - Eduardo Menezes Gaieta
- Fundação Oswaldo Cruz - Fiocruz, R. São José, S/N - Precabura, Eusébio, Ceará, 61773-270, Brazil
| | - Faustino Djata
- Instituto de Ciências Exatas e da Natureza, Universidade da Integração Internacional da Lusofonia Afro-Brasileira, Acarape, CE, Brazil
| | - Regilany Paulo Colares
- Instituto de Ciências Exatas e da Natureza, Universidade da Integração Internacional da Lusofonia Afro-Brasileira, Acarape, CE, Brazil
| | - Moises Maia Neto
- Curso de Graduação Em Farmácia, Centro Universitário Fametro, Fortaleza, CE, Brazil
| | | | - Gabrielle Silva Marinho
- Faculdade de Filosofia, Dom Aureliano Matos - FAFIDAM, Universidade Estadual Do Ceará, Centro, Limoeiro Do Norte, CE, Brazil
| | | | - Emmanuel Silva Marinho
- Faculdade de Filosofia, Dom Aureliano Matos - FAFIDAM, Universidade Estadual Do Ceará, Centro, Limoeiro Do Norte, CE, Brazil
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3
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Lu W, Aihaiti A, Abudukeranmu P, Liu Y, Gao H. Arachidonic acid metabolism as a novel pathogenic factor in gastrointestinal cancers. Mol Cell Biochem 2024:10.1007/s11010-024-05057-2. [PMID: 38963615 DOI: 10.1007/s11010-024-05057-2] [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: 05/27/2024] [Accepted: 06/25/2024] [Indexed: 07/05/2024]
Abstract
Gastrointestinal (GI) cancers are a major global health burden, representing 20% of all cancer diagnoses and 22.5% of global cancer-related deaths. Their aggressive nature and resistance to treatment pose a significant challenge, with late-stage survival rates below 15% at five years. Therefore, there is an urgent need to delve deeper into the mechanisms of gastrointestinal cancer progression and optimize treatment strategies. Increasing evidence highlights the active involvement of abnormal arachidonic acid (AA) metabolism in various cancers. AA is a fatty acid mainly metabolized into diverse bioactive compounds by three enzymes: cyclooxygenase, lipoxygenase, and cytochrome P450 enzymes. Abnormal AA metabolism and altered levels of its metabolites may play a pivotal role in the development of GI cancers. However, the underlying mechanisms remain unclear. This review highlights a unique perspective by focusing on the abnormal metabolism of AA and its involvement in GI cancers. We summarize the latest advancements in understanding AA metabolism in GI cancers, outlining changes in AA levels and their potential role in liver, colorectal, pancreatic, esophageal, gastric, and gallbladder cancers. Moreover, we also explore the potential of targeting abnormal AA metabolism for future therapies, considering the current need to explore AA metabolism in GI cancers and outlining promising avenues for further research. Ultimately, such investigations aim to improve treatment options for patients with GI cancers and pave the way for better cancer management in this area.
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Affiliation(s)
- Weiqin Lu
- General Surgery, Cancer Center, Department of Vascular Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | | | | | - Yajun Liu
- Aksu First People's Hospital, Xinjiang, China
| | - Huihui Gao
- Cancer Center, Department of Hospital Infection Management and Preventive Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China.
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Paulus J, Sewald N. Small molecule- and peptide-drug conjugates addressing integrins: A story of targeted cancer treatment. J Pept Sci 2024; 30:e3561. [PMID: 38382900 DOI: 10.1002/psc.3561] [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: 09/20/2023] [Revised: 11/15/2023] [Accepted: 11/16/2023] [Indexed: 02/23/2024]
Abstract
Targeted cancer treatment should avoid side effects and damage to healthy cells commonly encountered during traditional chemotherapy. By combining small molecule or peptidic ligands as homing devices with cytotoxic drugs connected by a cleavable or non-cleavable linker in peptide-drug conjugates (PDCs) or small molecule-drug conjugates (SMDCs), cancer cells and tumours can be selectively targeted. The development of highly affine, selective peptides and small molecules in recent years has allowed PDCs and SMDCs to increasingly compete with antibody-drug conjugates (ADCs). Integrins represent an excellent target for conjugates because they are overexpressed by most cancer cells and because of the broad knowledge about native binding partners as well as the multitude of small-molecule and peptidic ligands that have been developed over the last 30 years. In particular, integrin αVβ3 has been addressed using a variety of different PDCs and SMDCs over the last two decades, following various strategies. This review summarises and describes integrin-addressing PDCs and SMDCs while highlighting points of great interest.
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Affiliation(s)
- Jannik Paulus
- Organic and Bioorganic Chemistry, Faculty of Chemistry, Bielefeld University, Bielefeld, Germany
| | - Norbert Sewald
- Organic and Bioorganic Chemistry, Faculty of Chemistry, Bielefeld University, Bielefeld, Germany
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Ahlawat V, Sura K, Singh B, Dangi M, Chhillar AK. Bioinformatics Approaches in the Development of Antifungal Therapeutics and Vaccines. Curr Genomics 2024; 25:323-333. [PMID: 39323620 PMCID: PMC11420568 DOI: 10.2174/0113892029281602240422052210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 12/31/2023] [Accepted: 03/11/2024] [Indexed: 09/27/2024] Open
Abstract
Fungal infections are considered a great threat to human life and are associated with high mortality and morbidity, especially in immunocompromised individuals. Fungal pathogens employ various defense mechanisms to evade the host immune system, which causes severe infections. The available repertoire of drugs for the treatment of fungal infections includes azoles, allylamines, polyenes, echinocandins, and antimetabolites. However, the development of multidrug and pandrug resistance to available antimycotic drugs increases the need to develop better treatment approaches. In this new era of -omics, bioinformatics has expanded options for treating fungal infections. This review emphasizes how bioinformatics complements the emerging strategies, including advancements in drug delivery systems, combination therapies, drug repurposing, epitope-based vaccine design, RNA-based therapeutics, and the role of gut-microbiome interactions to combat anti-fungal resistance. In particular, we focused on computational methods that can be useful to obtain potent hits, and that too in a short period.
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Affiliation(s)
- Vaishali Ahlawat
- Centre for Biotechnology, M.D. University, Rohtak, Haryana, India
- Centre for Bioinformatics, M.D. University, Rohtak, Haryana, India
| | - Kiran Sura
- Centre for Bioinformatics, M.D. University, Rohtak, Haryana, India
| | - Bharat Singh
- Department of Biotechnology and Central Research Cell, MMEC, Maharishi Markandeshwar (Deemed to be University), Mullana-Ambala, Haryana-133207, India
| | - Mehak Dangi
- Centre for Bioinformatics, M.D. University, Rohtak, Haryana, India
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Ikram M, Shah I, Hussain H, Mughal EU, Naeem N, Sadiq A, Nazir Y, Ali Shah SW, Zahoor M, Ullah R, Ali EA, Umar MN. Synthesis, molecular docking evaluation for LOX and COX-2 inhibition and determination of in-vivo analgesic potentials of aurone derivatives. Heliyon 2024; 10:e29658. [PMID: 38694111 PMCID: PMC11058299 DOI: 10.1016/j.heliyon.2024.e29658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 04/11/2024] [Accepted: 04/11/2024] [Indexed: 05/03/2024] Open
Abstract
In the current study, seven (7) aurone derivatives (ADs) were synthesized and employed to in-vitro LOX and COX-2 assays, in-vivo models of acetic acid-induced mice writhing, formalin-induced mice paw licking and tail immersion test to evaluate their analgesic potential at the doses of 10 mg and 20 mg/kg body weight. Molecular docking was performed to know the active binding site at both LOX and COX-2 as compared to standard drugs. Among the ADs, 2-(3,4-dimethoxybenzylidene)benzofuran-3(2H)-one (WE-4)possessed optimal LOX and COX-2 inhibitory strength (IC50=0.30 μM and 0.22 μM) as compared to standard (ZileutonIC50 = 0.08 μM, CelecoxibIC50 = 0.05 μM). Similarly in various pain models compound WE-4 showed significantly (p < 0.05) highest percent analgesic potency as compared to control at a dose of 20 mg/kg i.e. 77.60 % analgesic effect in acetic acid model, 49.97 % (in Phase-1) and 70.93 % (inPhase-2) analgesic effect in formalin pain model and 74.71 % analgesic response in tail immersion model. By the administration of Naloxone, the tail flicking latencies were reversed (antagonized) in all treatments. The WE-4 (at 10 mg/kg and 20 mg/kg) was antagonized after 90 min from 11.23 ± 0.93 and 13.41 ± 1.21 to 5.30 ± 0.48 and 4.80 ± 0.61 respectively as compared to standard Tramadol (from 17.74 ± 1.33 to 3.70 ± 0.48), showing the opiodergic receptor involvement. The molecular docking study of ADs revealed that WE-4 had a higher affinity for LOX and COX-2 with docking scores of -4.324 and -5.843 respectively. As a whole, among the tested ADs, compound WE-4 demonstrated excellent analgesic effects that may have been caused by inhibiting the LOX and COX-2 pathways.
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Affiliation(s)
- Muhammad Ikram
- Department of Pharmacy, Abdul Wali Khan University Mardan (AWKUM), Mardan, 23390, Pakistan
| | - Ismail Shah
- Department of Pharmacy, Abdul Wali Khan University Mardan (AWKUM), Mardan, 23390, Pakistan
| | - Haya Hussain
- Department of Pharmacy, Shaheed Benazir Bhutto University Sheringal, Dir (Upper) 18000, Khyber Pakhtunkhwa, Pakistan
| | | | - Nafeesa Naeem
- Department of Chemistry, University of Gujrat, Gujrat, 50700, Pakistan
| | - Amina Sadiq
- Department of Chemistry, Govt. College Women University, Sialkot, 51300, Pakistan
| | - Yasir Nazir
- Department of Chemistry, University of Sialkot, Sialkot, 51300, Pakistan
| | - Syed Wadood Ali Shah
- Department of Pharmacy, University of Malakand, Chakdara, Chakdara 18800, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Zahoor
- Department of Biochemistry, University of Malakand, Chakdara, Dir Lower, KPK, 18800, Pakistan
| | - Riaz Ullah
- Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Essam A. Ali
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
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Ahmad B, Saeed A, Al-Amery A, Celik I, Ahmed I, Yaseen M, Khan IA, Al-Fahad D, Bhat MA. Investigating Potential Cancer Therapeutics: Insight into Histone Deacetylases (HDACs) Inhibitions. Pharmaceuticals (Basel) 2024; 17:444. [PMID: 38675404 PMCID: PMC11054547 DOI: 10.3390/ph17040444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 03/21/2024] [Accepted: 03/22/2024] [Indexed: 04/28/2024] Open
Abstract
Histone deacetylases (HDACs) are enzymes that remove acetyl groups from ɛ-amino of histone, and their involvement in the development and progression of cancer disorders makes them an interesting therapeutic target. This study seeks to discover new inhibitors that selectively inhibit HDAC enzymes which are linked to deadly disorders like T-cell lymphoma, childhood neuroblastoma, and colon cancer. MOE was used to dock libraries of ZINC database molecules within the catalytic active pocket of target HDACs. The top three hits were submitted to MD simulations ranked on binding affinities and well-occupied interaction mechanisms determined from molecular docking studies. Inside the catalytic active site of HDACs, the two stable inhibitors LIG1 and LIG2 affect the protein flexibility, as evidenced by RMSD, RMSF, Rg, and PCA. MD simulations of HDACs complexes revealed an alteration from extended to bent motional changes within loop regions. The structural deviation following superimposition shows flexibility via a visual inspection of movable loops at different timeframes. According to PCA, the activity of HDACs inhibitors induces structural dynamics that might potentially be utilized to define the nature of protein inhibition. The findings suggest that this study offers solid proof to investigate LIG1 and LIG2 as potential HDAC inhibitors.
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Affiliation(s)
- Basharat Ahmad
- School of Life Science and Technology, Center for Informational Biology, University of Electronics Science and Technology of China, Chengdu 610056, China
| | - Aamir Saeed
- Department of Bioinformatics, Hazara University Mansehra, Mansehra 21120, Pakistan
| | - Ahmed Al-Amery
- Department of Physiology and Medical Physics, College of Medicine, University of Thi-Qar, Nasiriyah 64001, Iraq
| | - Ismail Celik
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Erciyes University, 38280 Kayseri, Turkey;
| | - Iraj Ahmed
- Atta-Ur-Rehman School of Applied Biosciences (ASAB), National University of Science and Technology (NUST), Islamabad 44000, Pakistan;
| | - Muhammad Yaseen
- Institute of Chemical Sciences, University of Swat, Charbagh 19130, Pakistan;
| | - Imran Ahmad Khan
- Department of Chemistry, Government College University Faisalabad, Faisalabad 38000, Pakistan;
| | - Dhurgham Al-Fahad
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Thi-Qar, Nasiriyah 64001, Iraq;
| | - Mashooq Ahmad Bhat
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh 11421, Saudi Arabia
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8
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Banat R, Daoud S, Taha MO. Ligand-based pharmacophore modeling and machine learning for the discovery of potent aurora A kinase inhibitory leads of novel chemotypes. Mol Divers 2024:10.1007/s11030-024-10814-y. [PMID: 38446372 DOI: 10.1007/s11030-024-10814-y] [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: 10/02/2023] [Accepted: 01/19/2024] [Indexed: 03/07/2024]
Abstract
Aurora-A (AURKA) is serine/threonine protein kinase involved in the regulation of numerous processes of cell division. Numerous studies have demonstrated strong association between AURKA and cancer. AURKA is overexpressed in many cancers, such as colon, breast and prostate cancers. Consequently, AURKA has emerged as promising target for therapeutic intervention in cancer management. Herein, we describe a computational workflow for the discovery of novel anti-AURKA inhibitory leads starting with ligand-based assessment of the pharmacophoric space of six diverse sets of inhibitors. Subsequently, machine learning/QSAR modeling was coupled with genetic function algorithm to search for the best possible combination of machine learner, ligand-based pharmacophore(s) and molecular descriptors capable of explaining variation in anti-AURKA bioactivities within a collected list of inhibitors. Two learners succeeded in achieving acceptable structure/activity correlations, namely, random forests and extreme gradient boosting (XGBoost). Three pharmacophores emerged in the successful ML models. These were then used as 3D search queries to mine the National Cancer Institute database for novel anti-AURKA leads. Top-ranking 38 hits were assessed in vitro for their anti-AURKA bioactivities. Among them, three compounds exhibited promising dose-response curves, demonstrating experimental IC50 values ranging from sub-micromolar to low micromolar values. Remarkably, two of these compounds are of novel chemotypes.
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Affiliation(s)
- Rajaa Banat
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan
| | - Safa Daoud
- Department of Pharmaceutical Chemistry and Pharmacognosy, Faculty of Pharmacy, Applied Sciences Private University, Amman, Jordan
| | - Mutasem Omar Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, Jordan.
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Rezaei H, Zarezade V, Khodadadi I, Tavilani H, Tanzadehpanah H, Karimi J. Unveiling Arformoterol as a potent LSD1 inhibitor for breast cancer treatment: A comprehensive study integrating 3D-QSAR pharmacophore modeling, molecular docking, molecular dynamics simulations and in vitro assays. Int J Biol Macromol 2024; 258:129048. [PMID: 38159701 DOI: 10.1016/j.ijbiomac.2023.129048] [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: 09/03/2023] [Revised: 12/09/2023] [Accepted: 12/23/2023] [Indexed: 01/03/2024]
Abstract
Lysine Specific Demethylase 1 (LSD1) has been identified as a chromatin-modifying enzyme implicated in various cancer pathogeneses, highlighting the potential for novel epigenetic cancer treatments through the development of effective inhibitors. We employed 3D-QSAR pharmacophore modeling, molecular docking, and molecular dynamics simulations to identify a promising drug candidate for LSD1 inhibition. RMSD, RMSF, H-bond, and DSSP analysis demonstrated that ZINC02599970 (Arformoterol) and ZINC13453966 exhibited the highest LSD1 inhibitory potential. Experimental validation using MCF-7 and MDA-MB-231 cell lines revealed that Arformoterol displayed potent antiproliferative activity with IC50 values of 12.30 ± 1.48 μM and 19.69 ± 1.15 μM respectively. In contrast, the IC50 values obtained for the control (tranylcypromine) in exposure to MCF-7 and MDA-MB-231 cells were 104.6 ± 1.69 μM and 77 ± 0.67 μM, respectively. Arformoterol demonstrated greater LSD1 inhibitory potency in MCF-7 cells compared to MDA-MB-231 cells. Also, the expression of genes involved in chromatin rearrangement (LSD1), angiogenesis (VEGF1), cell migration (RORα), signal transduction (S100A8), apoptosis, and cell cycle (p53) were investigated. Arformoterol enhanced apoptosis and induced cell cycle arrest at the G2/M phase, both in MCF-7 and MDA-MB-231 cancer cells. Based on our findings, we propose that Arformoterol represents a promising candidate for breast cancer treatment, owing to its potent LSD1 inhibitory activity.
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Affiliation(s)
- Hamzeh Rezaei
- Department of Clinical Biochemistry, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
| | | | - Iraj Khodadadi
- Department of Clinical Biochemistry, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Heidar Tavilani
- Department of Clinical Biochemistry, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Hamid Tanzadehpanah
- Antimicrobial Resistance Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Jamshid Karimi
- Department of Clinical Biochemistry, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran.
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Temre MK, Devi B, Singh VK, Goel Y, Yadav S, Pandey SK, Kumar R, Kumar A, Singh SM. Molecular characterization of glutor-GLUT interaction and prediction of glutor's drug-likeness: implications for its utility as an antineoplastic agent. J Biomol Struct Dyn 2023; 41:11262-11273. [PMID: 36571488 DOI: 10.1080/07391102.2022.2161010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 12/15/2022] [Indexed: 12/27/2022]
Abstract
Recent experimental evidence from our and other laboratories has strongly indicated that glutor, a piperazine-2-one derivative, which is a pan-GLUT inhibitor, displays a promising antineoplastic action by hampering glucose uptake owing to its ability to inhibit GLUT1 and GLUT3, which are overexpressed in neoplastic cells. However, the molecular mechanism(s) of the inhibiting action of glutor has remained elusive. Thus, for optimal utilization of the antineoplastic potential of glutor, it is essential to decipher the precise mechanism(s) of its interaction with GLUTs. Therefore, the present investigation was carried out to understand the molecular mechanism(s) of the binding of glutor to GLUT1 and GLUT3 in silico. This study suggests that glutor can effectively bind to GLUTs at the reported binding site. Moreover, the docking of glutor to GLUT was stabilised by several contacts between these two partners as shown by the 200 ns long molecular dynamic simulation carried out using Gromacs, indicating the formation of a stable complex. Moreover, glutor was found to possess all characteristics conducive to its drug-likeness. Hence, these observations suggest that glutor has the potential to be used in antineoplastic therapeutic applications.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mithlesh Kumar Temre
- School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Bharti Devi
- Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi, India
| | - Vinay Kumar Singh
- Centre for Bioinformatics, School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Yugal Goel
- School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Saveg Yadav
- School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Shrish Kumar Pandey
- School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Rajnish Kumar
- Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi, India
| | - Ajay Kumar
- Department of Zoology, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Sukh Mahendra Singh
- School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, India
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Daoud S, Alabed SJ, Bardaweel SK, Taha MO. Discovery of potent maternal embryonic leucine zipper kinase (MELK) inhibitors of novel chemotypes using structure-based pharmacophores. Med Chem Res 2023; 32:2574-2586. [DOI: 10.1007/s00044-023-03160-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 10/05/2023] [Indexed: 07/10/2024]
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12
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Sarmah P, Konwar P, Saikia J, Borah T, Verma JS, Banik D. Screening of potent inhibitor from Aquilaria malaccensis Lam. against arachidonic inflammatory enzymes: an insight from molecular docking, ADMET, molecular dynamics simulation and MM-PBSA approaches. J Biomol Struct Dyn 2023:1-15. [PMID: 37885259 DOI: 10.1080/07391102.2023.2271977] [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: 05/02/2023] [Accepted: 08/29/2023] [Indexed: 10/28/2023]
Abstract
The three primary enzymes COX (cyclooxygenase), LOX (lipoxygenase) and CYT-P450 (cytochrome P450), which are part of the arachidonic inflammatory pathway, play crucial role in the development of asthma, rheumatoid arthritis and cardiovascular diseases. Ethnomedicinally, plant-derived chemicals have a major role in the treatment of fatal illnesses. Aquilaria malaccensis Lam. widely known as agarwood is prized for its fragrance and therapeutic properties. The phytochemicals and extracts of this plant have significant healing properties in the treatment of serious illnesses. In the current work, an in-silico approach including molecular docking, ADMET (absorption, distribution, metabolism, excretion and toxicity), molecular dynamics (MD) simulation and molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) was performed to screen 33 bioactive compounds from this plant against COX-2 and 5-LOX in order to find the most effective inhibitor. 2-(2-Phenylethyl)chromone was found to inhibit both 5-LOX and COX-2, showing the highest binding affinities (-9.1 kcal/mol and -9.0 kcal/mol, respectively) than standard Ibuprofen and nordihydroguaiaretic acid (NDGA). 2-(2-Phenylethyl)chromone showed the highest drug-likeness score and low risk of toxicity compared to other phytochemicals. MD modeling and MM-PBSA calculations showed that 2-(2-Phenylethyl)chromone had a strong persistent binding interaction with 5-LOX than COX-2, and this interaction is comparable to the bounded standards Ibuprofen and NDGA. From this study, we may infer that the 2-(2-Phenylethyl)chromone can serve as a potent inhibitor and has scope to be employed in the treatment of inflammatory ailments.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Prasanna Sarmah
- Agrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Parthapratim Konwar
- Agrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Jadumoni Saikia
- Agrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Twinkle Borah
- Agrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Jitendra Singh Verma
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
- Engineering Sciences and Technology Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
| | - Dipanwita Banik
- Agrotechnology and Rural Development Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
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13
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Kaur R, Rani S, Singh P. Structure and ligand based design for identification of highly potent molecules against 5-LOX. Bioorg Med Chem Lett 2023; 94:129448. [PMID: 37591315 DOI: 10.1016/j.bmcl.2023.129448] [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: 05/01/2023] [Revised: 08/10/2023] [Accepted: 08/14/2023] [Indexed: 08/19/2023]
Abstract
We report here small molecules consisting of dichlorophenyl substituted oxindole that is further tagged with pyrrole/indole moieties. These molecules were designed on the basis of the analysis of binding mode of 5-LOX with arachidonic acid and zileuton. The molecules traverse the active site pocket of the enzyme that otherwise hosts AA and zileuton. Moreover, with a provision of derivatization at pyrrole/indole-N, the physico-chemical properties of the molecules can be adjusted. Appreciable 5-LOX inhibitory activities of the compounds in sub-micromolar range were observed and their aqueous solubility, binding with human serum albumin and stability in blood plasma and liver microsomes were checked. The Michaelis-Menten constants obtained during the binding of the compounds with 5-LOX indicated competitive binding of the compounds with the enzyme. Overall, the combination of molecular modelling and experimental studies identified promising molecules against inflammatory diseases.
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Affiliation(s)
- Rajbir Kaur
- Department of Chemistry, UGC Sponsored Centre for Advanced Studies, Guru Nanak Dev University, Amritsar 143005, India
| | - Sudesh Rani
- Department of Chemistry, UGC Sponsored Centre for Advanced Studies, Guru Nanak Dev University, Amritsar 143005, India
| | - Palwinder Singh
- Department of Chemistry, UGC Sponsored Centre for Advanced Studies, Guru Nanak Dev University, Amritsar 143005, India.
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14
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Yao X, Liu Y, Jiao H, Ma W, Chen M. Association of LOX gene G473A polymorphism with the occurrence of allergic rhinitis and efficacy of montelukast sodium in children. Cell Cycle 2023; 22:2280-2287. [PMID: 38009683 PMCID: PMC10730226 DOI: 10.1080/15384101.2023.2286802] [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: 07/17/2023] [Accepted: 10/26/2023] [Indexed: 11/29/2023] Open
Abstract
Allergic rhinitis (AR) is very common in adolescents, and current treatment options are complex and unsatisfactory. The objective of this study was to analyze the association of lysyl oxidase (LOX) gene G473A polymorphism with susceptibility to AR in children. In addition, we analyzed the therapeutic effect of montelukast sodium on AR. Forty-five children with AR (research group, 8.16±2.88 years old) and 51 healthy children (control group, 8.22±3.87 years old) during the same period were selected. The LOX gene G473A polymorphism was detected with polymerase chain reaction (PCR)-restriction fragment length polymorphism method. The effect of G473A polymorphism in the occurrence of AR was assessed by logistic regression analysis. In addition, the levels of C-reactive protein (CRP), Interleukin (IL-6), and IL-8 were measured to observe the relationship between G473A polymorphism and inflammatory factors. Finally, montelukast sodium was given to children with AR to investigate the effect of G473A polymorphism on clinical outcomes. The number of G473A polymorphisms in the research group was not significantly different from the control group for GA-type (P = 0.521). However, the number of GG-type polymorphisms was less while the number of type AA was more than the control group (P = 0.044 and 0.046). Children carrying the AA gene had an approximately 4-fold increased risk of AR, while those carrying the GG gene had a decreased risk (P < 0.001). Moreover, children carrying the GG gene had lower levels of CRP, IL-6, and IL-8 and better clinical outcomes, while those carrying the AA gene had higher levels of inflammatory factors and worse outcomes (P<0.05). LOX gene G473A polymorphism is closely associated with AR pathogenesis and may have an important research value in antagonizing the therapeutic effect of montelukast sodium.
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Affiliation(s)
- Xikun Yao
- Department of Otolaryngology, Sunshine Union Hospital, Weifang, Shandong, China
| | - Yan Liu
- Department of Pediatrics, Sunshine Union Hospital, Weifang, Shandong, China
| | - Hong Jiao
- Department of Otolaryngology, Sunshine Union Hospital, Weifang, Shandong, China
| | - Wenjie Ma
- Department of Otolaryngology, Sunshine Union Hospital, Weifang, Shandong, China
| | - Minliang Chen
- Department of Otolaryngology, Sunshine Union Hospital, Weifang, Shandong, China
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15
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Bhowmik R, Kant R, Manaithiya A, Saluja D, Vyas B, Nath R, Qureshi KA, Parkkila S, Aspatwar A. Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study. Front Pharmacol 2023; 14:1265573. [PMID: 37705534 PMCID: PMC10495588 DOI: 10.3389/fphar.2023.1265573] [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: 07/23/2023] [Accepted: 08/10/2023] [Indexed: 09/15/2023] Open
Abstract
Mycobacterium tuberculosis is the bacterial strain that causes tuberculosis (TB). However, multidrug-resistant and extensively drug-resistant tuberculosis are significant obstacles to effective treatment. As a result, novel therapies against various strains of M. tuberculosis have been developed. Drug development is a lengthy procedure that includes identifying target protein and isolation, preclinical testing of the drug, and various phases of a clinical trial, etc., can take decades for a molecule to reach the market. Computational approaches such as QSAR, molecular docking techniques, and pharmacophore modeling have aided drug development. In this review article, we have discussed the various techniques in tuberculosis drug discovery by briefly introducing them and their importance. Also, the different databases, methods, approaches, and software used in conducting QSAR, pharmacophore modeling, and molecular docking have been discussed. The other targets targeted by these techniques in tuberculosis drug discovery have also been discussed, with important molecules discovered using these computational approaches. This review article also presents the list of drugs in a clinical trial for tuberculosis found drugs. Finally, we concluded with the challenges and future perspectives of these techniques in drug discovery.
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Affiliation(s)
- Ratul Bhowmik
- Medicinal Chemistry and Molecular Modelling Lab, Department of Pharmaceutical Chemistry, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, India
| | - Ravi Kant
- Medical Biotechnology Laboratory, Dr. B. R. Ambedkar Center for Biomedical Research, Delhi School of Public Health, IoE, University of Delhi, Delhi, India
| | - Ajay Manaithiya
- Medicinal Chemistry and Molecular Modelling Lab, Department of Pharmaceutical Chemistry, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, India
| | - Daman Saluja
- Medical Biotechnology Laboratory, Dr. B. R. Ambedkar Center for Biomedical Research, Delhi School of Public Health, IoE, University of Delhi, Delhi, India
| | - Bharti Vyas
- Department of Bioinformatics, School of Interdisciplinary Studies, Jamia Hamdard, New Delhi, India
| | - Ranajit Nath
- Department of Pharmaceutics, School of Pharmaceutical Sciences, Siksha ‘O’ Anusandhan University, Bhubaneswar, Odisha, India
| | - Kamal A. Qureshi
- Department of Pharmaceutics, Unaizah College of Pharmacy, Qassim University, Unaizah, Al-Qassim, Saudi Arabia
| | - Seppo Parkkila
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Ltd., Tampere University Hospital, Tampere, Finland
| | - Ashok Aspatwar
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
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16
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Azad I, Khan T, Ahmad N, Khan AR, Akhter Y. Updates on drug designing approach through computational strategies: a review. Future Sci OA 2023; 9:FSO862. [PMID: 37180609 PMCID: PMC10167725 DOI: 10.2144/fsoa-2022-0085] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 04/12/2023] [Indexed: 05/16/2023] Open
Abstract
The drug discovery and development (DDD) process in pursuit of novel drug candidates is a challenging procedure requiring lots of time and resources. Therefore, computer-aided drug design (CADD) methodologies are used extensively to promote proficiency in drug development in a systematic and time-effective manner. The point in reference is SARS-CoV-2 which has emerged as a global pandemic. In the absence of any confirmed drug moiety to treat the infection, the science fraternity adopted hit and trial methods to come up with a lead drug compound. This article is an overview of the virtual methodologies, which assist in finding novel hits and help in the progression of drug development in a short period with a specific medicinal solution.
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Affiliation(s)
- Iqbal Azad
- Department of Chemistry, Integral University, Dasauli, P.O. Bas-ha, Kursi Road, Lucknow, 226026, UP, India
| | - Tahmeena Khan
- Department of Chemistry, Integral University, Dasauli, P.O. Bas-ha, Kursi Road, Lucknow, 226026, UP, India
| | - Naseem Ahmad
- Department of Chemistry, Integral University, Dasauli, P.O. Bas-ha, Kursi Road, Lucknow, 226026, UP, India
| | - Abdul Rahman Khan
- Department of Chemistry, Integral University, Dasauli, P.O. Bas-ha, Kursi Road, Lucknow, 226026, UP, India
| | - Yusuf Akhter
- Department of Biotechnology, Babasaheb Bhimrao Ambedkar University, Vidya Vihar, Raebareli Road, Lucknow, UP, 2260025, India
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17
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Stanger L, Holinstat M. Bioactive lipid regulation of platelet function, hemostasis, and thrombosis. Pharmacol Ther 2023; 246:108420. [PMID: 37100208 PMCID: PMC11143998 DOI: 10.1016/j.pharmthera.2023.108420] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 04/15/2023] [Accepted: 04/17/2023] [Indexed: 04/28/2023]
Abstract
Platelets are small, anucleate cells in the blood that play a crucial role in the hemostatic response but are also implicated in the pathophysiology of cardiovascular disease. It is widely appreciated that polyunsaturated fatty acids (PUFAs) play an integral role in the function and regulation of platelets. PUFAs are substrates for oxygenase enzymes cyclooxygenase-1 (COX-1), 5-lipoxygenase (5-LOX), 12-lipoxygenase (12-LOX) and 15-lipoxygenase (15-LOX). These enzymes generate oxidized lipids (oxylipins) that exhibit either pro- or anti-thrombotic effects. Although the effects of certain oxylipins, such as thromboxanes and prostaglandins, have been studied for decades, only one oxylipin has been therapeutically targeted to treat cardiovascular disease. In addition to the well-known oxylipins, newer oxylipins that demonstrate activity in the platelet have been discovered, further highlighting the expansive list of bioactive lipids that can be used to develop novel therapeutics. This review outlines the known oxylipins, their activity in the platelet, and current therapeutics that target oxylipin signaling.
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Affiliation(s)
- Livia Stanger
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI, United States of America
| | - Michael Holinstat
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI, United States of America; Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan Medical School, Ann Arbor, MI, United States of America.
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18
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Vemula D, Jayasurya P, Sushmitha V, Kumar YN, Bhandari V. CADD, AI and ML in drug discovery: A comprehensive review. Eur J Pharm Sci 2023; 181:106324. [PMID: 36347444 DOI: 10.1016/j.ejps.2022.106324] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/26/2022] [Accepted: 11/03/2022] [Indexed: 11/06/2022]
Abstract
Computer-aided drug design (CADD) is an emerging field that has drawn a lot of interest because of its potential to expedite and lower the cost of the drug development process. Drug discovery research is expensive and time-consuming, and it frequently took 10-15 years for a drug to be commercially available. CADD has significantly impacted this area of research. Further, the combination of CADD with Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) technologies to handle enormous amounts of biological data has reduced the time and cost associated with the drug development process. This review will discuss how CADD, AI, ML, and DL approaches help identify drug candidates and various other steps of the drug discovery process. It will also provide a detailed overview of the different in silico tools used and how these approaches interact.
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Affiliation(s)
- Divya Vemula
- National Institute of Pharmaceutical Education and Research- Hyderabad, India
| | - Perka Jayasurya
- National Institute of Pharmaceutical Education and Research- Hyderabad, India
| | - Varthiya Sushmitha
- National Institute of Pharmaceutical Education and Research- Hyderabad, India
| | | | - Vasundhra Bhandari
- National Institute of Pharmaceutical Education and Research- Hyderabad, India.
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19
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Nayak SS, Sundararajan V. Robust anti-inflammatory activity of genistein against neutrophil elastase: a microsecond molecular dynamics simulation study. J Biomol Struct Dyn 2023; 41:11612-11628. [PMID: 36705087 DOI: 10.1080/07391102.2023.2170919] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 12/26/2022] [Indexed: 01/28/2023]
Abstract
Human Neutrophil Elastase (HNE) is one of the major causes of tissue destruction in numerous chronic and inflammatory disorders and has been reported as a therapeutic target for inflammatory diseases. Overexpression of this enzyme plays a critical role in the pathogenesis of rheumatoid arthritis (RA). The focus of this study is to identify potent natural inhibitors that could target the active site of the HNE through the use of computational methods. The molecular structure of small molecules was retrieved from several natural compound databases. This was followed by structure-based virtual screening, molecular docking, ADMET property predictions and molecular dynamic simulation studies to screen potential HNE inhibitors. In total, 1881 natural compounds were extracted and subjected to molecular docking studies, and 10 compounds were found to have good interactions, exhibiting the best docking scores. Genistein showed higher binding efficacy (-10.28 Kcal/mol) to HNE in comparison to other natural compounds. The conformational stability of the docked complex of the ELANE gene (HNE) with genistein was assessed using 1-microsecond molecular dynamic simulation (MDs), which reliably revealed the unique stereochemical alteration of the complex, indicating its conformational stability and flexibility. Alterations in the enzyme structure upon complex formation were further characterized through clustering analysis and linear interaction energy (LIE) calculation. The outcomes of this research propose novel potential candidates against target HNE.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Smruti Sudha Nayak
- Department of Bio-Sciences, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, India
| | - Vino Sundararajan
- Department of Bio-Sciences, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, India
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20
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Kasoju N, Remya NS, Sasi R, Sujesh S, Soman B, Kesavadas C, Muraleedharan CV, Varma PRH, Behari S. Digital health: trends, opportunities and challenges in medical devices, pharma and bio-technology. CSI TRANSACTIONS ON ICT 2023; 11:11-30. [PMCID: PMC10089382 DOI: 10.1007/s40012-023-00380-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 03/27/2023] [Indexed: 04/12/2024]
Abstract
Digital health interventions refer to the use of digital technology and connected devices to improve health outcomes and healthcare delivery. This includes telemedicine, electronic health records, wearable devices, mobile health applications, and other forms of digital health technology. To this end, several research and developmental activities in various fields are gaining momentum. For instance, in the medical devices sector, several smart biomedical materials and medical devices that are digitally enabled are rapidly being developed and introduced into clinical settings. In the pharma and allied sectors, digital health-focused technologies are widely being used through various stages of drug development, viz. computer-aided drug design, computational modeling for predictive toxicology, and big data analytics for clinical trial management. In the biotechnology and bioengineering fields, investigations are rapidly growing focus on digital health, such as omics biology, synthetic biology, systems biology, big data and personalized medicine. Though digital health-focused innovations are expanding the horizons of health in diverse ways, here the development in the fields of medical devices, pharmaceutical technologies and biotech sectors, with emphasis on trends, opportunities and challenges are reviewed. A perspective on the use of digital health in the Indian context is also included.
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Affiliation(s)
- Naresh Kasoju
- Sree Chitra Tirunal Institute for Medical Science and Technology, Thiruvananthapuram, 695011 Kerala India
| | - N. S. Remya
- Sree Chitra Tirunal Institute for Medical Science and Technology, Thiruvananthapuram, 695011 Kerala India
| | - Renjith Sasi
- Sree Chitra Tirunal Institute for Medical Science and Technology, Thiruvananthapuram, 695011 Kerala India
| | - S. Sujesh
- Sree Chitra Tirunal Institute for Medical Science and Technology, Thiruvananthapuram, 695011 Kerala India
| | - Biju Soman
- Sree Chitra Tirunal Institute for Medical Science and Technology, Thiruvananthapuram, 695011 Kerala India
| | - C. Kesavadas
- Sree Chitra Tirunal Institute for Medical Science and Technology, Thiruvananthapuram, 695011 Kerala India
| | - C. V. Muraleedharan
- Sree Chitra Tirunal Institute for Medical Science and Technology, Thiruvananthapuram, 695011 Kerala India
| | - P. R. Harikrishna Varma
- Sree Chitra Tirunal Institute for Medical Science and Technology, Thiruvananthapuram, 695011 Kerala India
| | - Sanjay Behari
- Sree Chitra Tirunal Institute for Medical Science and Technology, Thiruvananthapuram, 695011 Kerala India
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21
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Grasso G, Di Gregorio A, Mavkov B, Piga D, Labate GFD, Danani A, Deriu MA. Fragmented blind docking: a novel protein-ligand binding prediction protocol. J Biomol Struct Dyn 2022; 40:13472-13481. [PMID: 34641761 DOI: 10.1080/07391102.2021.1988709] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
In the present paper we propose a novel blind docking protocol based on Autodock-Vina. The developed docking protocol can provide binding site identification and binding pose prediction at the same time, by a systematical exploration of the protein volume performed with several preliminary docking calculations. In our opinion, this protocol can be successfully applied during the first steps of the virtual screening pipeline, because it provides binding site identification and binding pose prediction at the same time without visual evaluation of the binding site. After the binding pose prediction, MM/GBSA re-scoring rescoring procedures has been applied to improve the accuracy of the protein-ligand bound state. The FRAD protocol has been tested on 116 protein-ligand complexes of the Heat Shock Protein 90 - alpha, on 176 of Human Immunodeficiency virus protease 1, and on more than 100 protein-ligand system taken from the PDBbind dataset. Overall, the FRAD approach combined to MM/GBSA re-scoring can be considered as a powerful tool to increase the accuracy and efficiency with respect to other standard docking approaches when the ligand-binding site is unknown.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Gianvito Grasso
- Dalle Molle Institute for Artificial Intelligence, IDSIA - USI/SUPSI, Lugano-Viganello, Switzerland
| | - Arianna Di Gregorio
- Dalle Molle Institute for Artificial Intelligence, IDSIA - USI/SUPSI, Lugano-Viganello, Switzerland.,PolitoBIOMedLab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Italy
| | - Bojan Mavkov
- Dalle Molle Institute for Artificial Intelligence, IDSIA - USI/SUPSI, Lugano-Viganello, Switzerland
| | - Dario Piga
- Dalle Molle Institute for Artificial Intelligence, IDSIA - USI/SUPSI, Lugano-Viganello, Switzerland
| | | | - Andrea Danani
- Dalle Molle Institute for Artificial Intelligence, IDSIA - USI/SUPSI, Lugano-Viganello, Switzerland
| | - Marco A Deriu
- PolitoBIOMedLab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Italy
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22
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Alabed SJ, Zihlif M, Taha M. Discovery of new potent lysine specific histone demythelase-1 inhibitors (LSD-1) using structure based and ligand based molecular modelling and machine learning. RSC Adv 2022; 12:35873-35895. [PMID: 36545090 PMCID: PMC9751883 DOI: 10.1039/d2ra05102h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
Lysine-specific histone demethylase 1 (LSD-1) is an epigenetic enzyme that oxidatively cleaves methyl groups from monomethyl and dimethyl Lys4 of histone H3 and is highly overexpressed in different types of cancer. Therefore, it has been widely recognized as a promising therapeutic target for cancer therapy. Towards this end, we employed various Computer Aided Drug Design (CADD) approaches including pharmacophore modelling and machine learning. Pharmacophores generated by structure-based (SB) (either crystallographic-based or docking-based) and ligand-based (LB) (either supervised or unsupervised) modelling methods were allowed to compete within the context of genetic algorithm/machine learning and were assessed by Shapley additive explanation values (SHAP) to end up with three successful pharmacophores that were used to screen the National Cancer Institute (NCI) database. Seventy-five NCI hits were tested for their LSD-1 inhibitory properties against neuroblastoma SH-SY5Y cells, pancreatic carcinoma Panc-1 cells, glioblastoma U-87 MG cells and in vitro enzymatic assay, culminating in 3 nanomolar LSD-1 inhibitors of novel chemotypes.
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Affiliation(s)
- Shada J Alabed
- Department of Pharmacy, Faculty of Pharmacy, Al-Zaytoonah University of Jordan Amman Jordan
| | - Malek Zihlif
- Department of Pharmacology, Faculty of Medicine, University of Jordan Amman Jordan
| | - Mutasem Taha
- Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan Amman Jordan
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23
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Bashir B, Riaz N, Ejaz SA, Saleem M, Iqbal A, Mahmood HMK, Ejaz S, Ashraf M, Aziz-ur-Rehman, Bhattarai K. Parsing p-Tolyloxy-1,3,4-oxadiazolepropanamides as 15-Lipoxygenase Inhibitors Prop up by In Vitro and In Silico Profiling Including Structure Determination. J Mol Struct 2022. [DOI: 10.1016/j.molstruc.2022.134664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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24
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Novel 5,6-diphenyl-1,2,4-triazine-3-thiol derivatives as dual COX-2/5-LOX inhibitors devoid of cardiotoxicity. Bioorg Chem 2022; 129:106147. [PMID: 36126607 DOI: 10.1016/j.bioorg.2022.106147] [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: 05/24/2022] [Revised: 08/26/2022] [Accepted: 09/08/2022] [Indexed: 11/23/2022]
Abstract
A novel series of 5,6-diphenyl-1,2,4-triazine-3-thiol derivatives were designed, synthesized, and screened for their inhibitory potential against COX-2 and 5-LOX enzymes. The compounds from the series have shown moderate to excellent inhibitory potential against both targets. Compound 6k showed the inhibitions against COX-2 (IC50 = 0.33 ± 0.02 μM) and 5-LOX inhibition (IC50 = 4.90 ± 0.22 μM) which was better than the standard celecoxib (IC50 = 1.81 ± 0.13 μM) for COX-2 and zileuton (IC50 = 15.04 ± 0.18 μM) for 5-LOX respectively. Further investigation on the selected derivative 6k in rat paw edema models revealed significant anti-inflammatory efficacy. Compound 6k has also shown negligible ulcerogenic liability as compared to indomethacin. Moreover, in vivo biochemical analysis also established the compound's antioxidant properties. Compounds 6c and 6k were also observed to be devoid of cardiotoxicity post-myocardial infarction in rats. The molecular docking and dynamics simulation studies of the most active derivative 6k affirmed their consentient binding interactions with COX-2 specific ravine and cleft of 5-LOX.
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Wang R, Xu J, Yan R, Liu H, Zhao J, Xie Y, Deng W, Liao W, Nie Y. Virtual screening and activity evaluation of multitargeting inhibitors for idiopathic pulmonary fibrosis. Front Pharmacol 2022; 13:998245. [PMID: 36160399 PMCID: PMC9493029 DOI: 10.3389/fphar.2022.998245] [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: 07/19/2022] [Accepted: 08/17/2022] [Indexed: 11/17/2022] Open
Abstract
Transforming growth factor β receptor (TGF-β1R) and receptor tyrosine kinases (RTKs), such as VEGFRs, PDGFRs and FGFRs are considered important therapeutic targets in blocking myofibroblast migration and activation of idiopathic pulmonary fibrosis (IPF). To screen and design innovative prodrug to simultaneously target these four classes of receptors, we proposed an approach based on network pharmacology combining virtual screening and machine learning activity prediction, followed by efficient in vitro and in vivo models to evaluate drug activity. We first constructed Collagen1A2-A549 cells with type I collagen as the main biomarker and evaluated the activity of compounds to inhibit collagen expression at the cellular level. The data from the first round of Collagen1A2-A549 cell screening were substituted into the machine learning model, and the model was optimized accordingly. As a result, the false positive rate of the model was reduced from 85.0% to 66.7%, and two prospective compounds, Z103080500 and Z104578368, were finally selected. Collagen levels were reduced effectively by both Z103080500 (67.88% reduction) and Z104578368 (69.54% reduction). Moreover, these two compounds showed low cellular cytotoxicity. Subsequently, the effect of Z103080500 and Z104578368 was evaluated in a bleomycin-induced C57BL/6 mouse IPF model. These results showed that 50 mg/kg Z103080500 and Z104578368 could effectively reduce the number of inflammatory cells and the expression level of α-SMA. Meanwhile, Z103080500 and Z104578368 reduced the expression of major markers and inflammatory factors of IPF, such as collagen, IFN-γ, IL-17 and HYP, indicating that these screened Z103080500 and Z104578368 effectively delayed lung tissue inflammation and had a potential therapeutic effect on IPF. Our findings demonstrate that a screening and evaluation model for prodrug against IPF has been successfully established. It is of great significance to further modify these compounds to enhance their potency and activity.
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Affiliation(s)
- Rui Wang
- Clinical Research Institute, The First People’s Hospital of Foshan, Foshan, China
| | - Jian Xu
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Rong Yan
- Clinical Research Institute, The First People’s Hospital of Foshan, Foshan, China
| | - Huanbin Liu
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Jingxin Zhao
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Yuan Xie
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Wenbin Deng
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Weiping Liao
- Foshan Fourth People’s Hospital, Foshan, China
- *Correspondence: Weiping Liao, ; Yichu Nie,
| | - Yichu Nie
- Clinical Research Institute, The First People’s Hospital of Foshan, Foshan, China
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- *Correspondence: Weiping Liao, ; Yichu Nie,
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Kumar S, Ayyannan SR. Identification of new small molecule monoamine oxidase-B inhibitors through pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation studies. J Biomol Struct Dyn 2022:1-22. [PMID: 35983603 DOI: 10.1080/07391102.2022.2112082] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Abstract
The discovery of a safe and efficacious drug is a complex, time-consuming, and expensive process. Computational methodologies driven by cheminformatics tools play a central role in the high-throughput lead discovery and optimization process especially when the structure of the biological target is known. Monoamine oxidases are the membrane-bound FAD-containing enzymes and the isoform monoamine oxidase-B (MAO-B) is an attractive target for treating diseases like Alzheimer's disease, Parkinson's disease, glioma, etc. In the current study, we have used a pharmacophore-based virtual screening technique for the identification of new small molecule MAO-B inhibitors. Safinamide was used for building a pharmacophore model and the developed model was used to probe the ZINC database for potential hits. The obtained hits were filtered against drug-likeness and PAINS. Out of the hit's library, two compounds ZINC02181408, ZINC08853942 (most active), and ZINC53327382 (least active) were further subjected to molecular docking and dynamics simulation studies to assess their virtual binding affinities and stability of the resultant protein-ligand complex. The docking studies revealed that active ligands were well accommodated within the active site of MAO-B and interacted with both substrate and entrance cavity residues. MD simulation studies unveiled additional hydrogen bond interactions with the substrate cavity residues, Tyr398 and Tyr435 that are crucial for the catalytic role of MAO-B. Moreover, the predicted ADMET parameters suggest that the compounds ZINC08853942 and ZINC02181408 are suitable for CNS penetration. Thus, the attempted computational campaign yielded two potential MAO-B inhibitors that merit further experimental investigation.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Sandeep Kumar
- Pharmaceutical Chemistry Research Laboratory II, Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi, India
| | - Senthil Raja Ayyannan
- Pharmaceutical Chemistry Research Laboratory II, Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi, India
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27
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Alzahrani A. A New Investigation into the Molecular Mechanism of Andrographolide towards Reducing Cytokine Storm. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27144555. [PMID: 35889428 PMCID: PMC9319373 DOI: 10.3390/molecules27144555] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 07/12/2022] [Accepted: 07/14/2022] [Indexed: 12/17/2022]
Abstract
Cytokine storm is a condition in which the immune system produces an excessive number of inflammatory signals, which can result in organ failure and death. It is also known as cytokine release syndrome, CRS, or simply cytokine storm, and it has received a lot of attention recently because of the COVID-19 pandemic. It appears to be one of the reasons why some people experience life-threatening symptoms from COVID-19, a medical condition induced by SARS-CoV-2 infection. In situations where natural substances can be exploited as therapeutics to reduce cytokine storm, the drug development process has come to the rescue. In the present study, we tested the potentiality of Andrographolide, labdane diterpenoid targeting several key cytokines that are secreted as a result of cytokine storm. We used molecular docking analyses, molecular dynamics simulations, and pharmacokinetic properties to test the stability of the complexes. The compound’s binding energy with some cytokines was over −6.5 Kcal/mol. Furthermore, a post-molecular dynamics (MD) study revealed that Andrographolide was extremely stable with these cytokines. The compound’s pharmacokinetic measurements demonstrated excellent properties in terms of adsorption, distribution, metabolism, and excretion. Our research revealed that this compound may be effective in lowering cytokine storm and treating severe symptoms.
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Affiliation(s)
- Abdulaziz Alzahrani
- Pharmaceuticals Chemistry Department, Faculty of Clinical Pharmacy, Al Baha University, Al Baha 65779, Saudi Arabia
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28
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Hasan MR, Alsaiari AA, Fakhurji BZ, Molla MHR, Asseri AH, Sumon MAA, Park MN, Ahammad F, Kim B. Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process. Molecules 2022; 27:4169. [PMID: 35807415 PMCID: PMC9268380 DOI: 10.3390/molecules27134169] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 01/18/2023] Open
Abstract
The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure-activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible.
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Affiliation(s)
- Md Rifat Hasan
- Department of Mathematics, Faculty of Science, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia;
- Department of Applied Mathematics, Faculty of Science, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
| | - Ahad Amer Alsaiari
- College of Applied Medical Science, Clinical Laboratories Science Department, Taif University, Taif 21944, Saudi Arabia;
| | - Burhan Zain Fakhurji
- iGene Medical Training and Molecular Research Center, Jeddah 21589, Saudi Arabia;
| | | | - Amer H. Asseri
- Biochemistry Department, Faculty of Science, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia;
- Centre for Artificial Intelligence in Precision Medicines, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia
| | - Md Afsar Ahmed Sumon
- Department of Marine Biology, Faculty of Marine Sciences, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia;
| | - Moon Nyeo Park
- College of Korean Medicine, Kyung Hee University, Hoigidong, Dongdaemungu, Seoul 02453, Korea;
| | - Foysal Ahammad
- Department of Biological Sciences, Faculty of Science, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia;
| | - Bonglee Kim
- College of Korean Medicine, Kyung Hee University, Hoigidong, Dongdaemungu, Seoul 02453, Korea;
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Kandi V, Vundecode A, Godalwar TR, Dasari S, Vadakedath S, Godishala V. The Current Perspectives in Clinical Research: Computer-Assisted Drug Designing, Ethics, and Good Clinical Practice. BORNEO JOURNAL OF PHARMACY 2022. [DOI: 10.33084/bjop.v5i2.3013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
In the era of emerging microbial and non-communicable diseases and re-emerging microbial infections, the medical fraternity and the public are plagued by under-preparedness. It is evident by the severity of the Coronavirus disease (COVID-19) pandemic that novel microbial diseases are a challenge and are challenging to control. This is mainly attributed to the lack of complete knowledge of the novel microbe’s biology and pathogenesis and the unavailability of therapeutic drugs and vaccines to treat and control the disease. Clinical research is the only answer utilizing which can handle most of these circumstances. In this review, we highlight the importance of computer-assisted drug designing (CADD) and the aspects of molecular docking, molecular superimposition, 3D-pharmacophore technology, ethics, and good clinical practice (GCP) for the development of therapeutic drugs, devices, and vaccines.
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Lee YCJ, Shirkey JD, Park J, Bisht K, Cowan AJ. An Overview of Antiviral Peptides and Rational Biodesign Considerations. BIODESIGN RESEARCH 2022; 2022:9898241. [PMID: 37850133 PMCID: PMC10521750 DOI: 10.34133/2022/9898241] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 04/04/2022] [Indexed: 10/19/2023] Open
Abstract
Viral diseases have contributed significantly to worldwide morbidity and mortality throughout history. Despite the existence of therapeutic treatments for many viral infections, antiviral resistance and the threat posed by novel viruses highlight the need for an increased number of effective therapeutics. In addition to small molecule drugs and biologics, antimicrobial peptides (AMPs) represent an emerging class of potential antiviral therapeutics. While AMPs have traditionally been regarded in the context of their antibacterial activities, many AMPs are now known to be antiviral. These antiviral peptides (AVPs) have been shown to target and perturb viral membrane envelopes and inhibit various stages of the viral life cycle, from preattachment inhibition through viral release from infected host cells. Rational design of AMPs has also proven effective in identifying highly active and specific peptides and can aid in the discovery of lead peptides with high therapeutic selectivity. In this review, we highlight AVPs with strong antiviral activity largely curated from a publicly available AMP database. We then compile the sequences present in our AVP database to generate structural predictions of generic AVP motifs. Finally, we cover the rational design approaches available for AVPs taking into account approaches currently used for the rational design of AMPs.
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Affiliation(s)
- Ying-Chiang J. Lee
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
| | - Jaden D. Shirkey
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
| | - Jongbeom Park
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
| | - Karishma Bisht
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
| | - Alexis J. Cowan
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
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31
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Shanmugarajan D, David C. Estrogen receptor potentially stable conformations from molecular dynamics as a structure-based pharmacophore model for mapping, screening, and identifying ligands-a new paradigm shift in pharmacophore screening. J Biomol Struct Dyn 2022:1-10. [PMID: 35543232 DOI: 10.1080/07391102.2022.2074543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Despite rigorous research on breast cancer has increased in recent decades, only few drugs are in practice to combat against the disease. Due to excessive usage, these drugs attain resistance is an avertable phenomenon resulting from inadequate treatment. A novel, and real-time approaches are expected to overcome to find the solution for the drug resistance. The molecular dynamics based multi-conformational sampling technique via computer-aided drug-designing approach, may be a promising route to identify the lead candidates from real-time generated frames. The estrogenic receptor, being one of the most widely targeted receptors for various breast cancer drugs namely, tamoxifen, raloxifene and GW5 (tamoxifen-resistance inhibitor) was used for simulating the molecular dynamics to obtain various real time frames. The energetically stable frames were funnelled based on Gibbs free binding energy, interaction energy and active site interaction to generate pharmacophores model for virtual screening of compounds. Generated pharmacophores are validated by receiver operating characteristic area under curve greater than 0.8. Further, screening of compounds with validated structure-based pharmacophore model of different estrogen bound drug complex conformations and binding orientations are complement for tamoxifen and tamoxifen-resistance inhibitor frames. Moreover, the best mapped compounds were docked and probed for ADMET, TopKat® and Lipinski's rule of five is more favourable for compound Andrographidine F sourced from medicinal herbal plant Andrographis paniculata. Hence, this compound had to be further analysed in in-vitro and in-vivo to prove the same.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Dhivya Shanmugarajan
- Department of Biotechnology, Vignan's Foundation for Science, Technology and Research (Deemed to be University), Guntur, Andhra Pradesh, India
| | - Charles David
- Department of Biotechnology, Vignan's Foundation for Science, Technology and Research (Deemed to be University), Guntur, Andhra Pradesh, India
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32
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Bošković J, Ružić D, Čudina O, Nikolic K, Dobričić V. Design of Dual COX-2 and 5-LOX Inhibitors with Iron-Chelating Properties
Using Structure-Based and Ligand-Based Methods. LETT DRUG DES DISCOV 2022. [DOI: 10.2174/1570180818666210714161908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background:
Inflammation is a critical component of many disease progressions, such as malignancy,
cardiovascular and rheumatic diseases. The inhibition of inflammatory mediators synthesis by
modulation of cyclooxygenase (COX) and lipoxygenase (LOX) pathways provides challenging strategy
for development of more effective drugs.
Objective:
The aim of this study was to design dual COX-2 and 5-LOX inhibitors with iron-chelating
properties using a combination of ligand-based (three-dimensional quantitative structure-activity relationship
(3D-QSAR)) and structure-based (molecular docking) methods.
Methods:
The 3D-QSAR analysis was applied on a literature dataset consisting of 28 dual COX-2 and 5-
LOX inhibitors in Pentacle software. The quality of developed COX-2 and 5-LOX 3D-QSAR models
were evaluated by internal and external validation methods. The molecular docking analysis was performed
in GOLD software, while selected ADMET properties were predicted in ADMET predictor software.
Results:
According to the molecular docking studies, the class of sulfohydroxamic acid analogues, previously
designed by 3D-QSAR, were clustered as potential dual COX-2 and 5-LOX inhibitors with ironchelating
properties. Based on the 3D-QSAR and molecular docking, 1j, 1g and 1l were selected as the
most promising dual COX-2 and 5-LOX inhibitors. According to the in silico ADMET predictions, all
compounds had ADMET_Risk score less than 7 and CYP_Risk score lower than 2.5. Designed compounds
were not estimated as hERG inhibitors and 1j had improved intrinsic solubility (8.704) in comparison
to the dataset compounds (0.411-7.946).
Conclusion:
By combining 3D-QSAR and molecular docking, three compounds (1j, 1g and 1l) were
selected as the most promising designed dual COX-2 and 5-LOX inhibitors, for which good activity, as
well as favourable ADMET properties and toxicity, are expected.
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Affiliation(s)
- Jelena Bošković
- Department of Pharmaceutical Chemistry, University of Belgrade – Faculty of Pharmacy, Belgrade, Serbia
| | - Dušan Ružić
- Department of Pharmaceutical Chemistry, University of Belgrade – Faculty of Pharmacy, Belgrade, Serbia
| | - Olivera Čudina
- Department of Pharmaceutical Chemistry, University of Belgrade – Faculty of Pharmacy, Belgrade, Serbia
| | - Katarina Nikolic
- Department of Pharmaceutical Chemistry, University of Belgrade – Faculty of Pharmacy, Belgrade, Serbia
| | - Vladimir Dobričić
- Department of Pharmaceutical Chemistry, University of Belgrade – Faculty of Pharmacy, Belgrade, Serbia
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33
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Huang W, Zhang L, Li Z. Advances in computer-aided drug design for type 2 diabetes. Expert Opin Drug Discov 2022; 17:461-472. [PMID: 35254188 DOI: 10.1080/17460441.2022.2047644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION The number of diabetic patients is increasing, posing a heavy social and economic burden worldwide. Traditional drug development technology is time-consuming and costly, and the emergence of computer-aided drug design (CADD) has changed this situation. This study reviews the applications of CADD in diabetic drug designing. AREAS COVERED In this article, the authors focus on the advance in CADD in diabetic drug design by elaborating the discovery, including peroxisome proliferator-activated receptor (PPAR), G protein-coupled receptor 40 (GPR40), dipeptidyl peptidase-IV (DDP-IV), protein tyrosine phosphatase 1B (PTP1B), sodium-dependent glucose transporter 2 (SGLT-2), and glucokinase (GK). Some drug discovery of these targets is related to CADD strategies. EXPERT OPINION There is no doubt that CADD has contributed to the discovery of novel anti-diabetic agents. However, there are still many limitations and challenges, such as lack of co-crystal complex, dynamic simulations, water, and metal ion treatment. In the near future, artificial intelligence (AI) may be a promising strategy to accelerate drug discovery and reduce costs by identifying candidates. Moreover, AlphaFold, a deep learning model that predicts the 3D structure of proteins, represents a considerable advancement in the structural prediction of proteins, especially in the absence of homologous templates for protein structures.
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Affiliation(s)
- Wanqiu Huang
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou, PR China.,Key Laboratory of New Drug Discovery and Evaluation, Guangdong Pharmaceutical University, Guangzhou, PR China.,Guangzhou Key Laboratory of Construction and Application of New Drug Screening Model Systems, Guangdong Pharmaceutical University, Guangzhou, PR China
| | - Luyong Zhang
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou, PR China.,Key Laboratory of New Drug Discovery and Evaluation, Guangdong Pharmaceutical University, Guangzhou, PR China.,Guangzhou Key Laboratory of Construction and Application of New Drug Screening Model Systems, Guangdong Pharmaceutical University, Guangzhou, PR China.,Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing, PR China
| | - Zheng Li
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou, PR China.,Key Laboratory of New Drug Discovery and Evaluation, Guangdong Pharmaceutical University, Guangzhou, PR China
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34
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Pavan M, Bassani D, Bolcato G, Bissaro M, Sturles M, Moro S. Computational strategies to identify new drug candidates against neuroinflammation. Curr Med Chem 2022; 29:4756-4775. [PMID: 35135446 DOI: 10.2174/0929867329666220208095122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 12/09/2021] [Accepted: 12/13/2021] [Indexed: 11/22/2022]
Abstract
The even more increasing application of computational approaches in these last decades has deeply modified the process of discovery and commercialization of new therapeutic entities. This is especially true in the field of neuroinflammation, in which both the peculiar anatomical localization and the presence of the blood-brain barrier makeit mandatory to finely tune the candidates' physicochemical properties from the early stages of the discovery pipeline. The aim of this review is therefore to provide a general overview to the readers about the topic of neuroinflammation, together with the most common computational strategies that can be exploited to discover and design small molecules controlling neuroinflammation, especially those based on the knowledge of the three-dimensional structure of the biological targets of therapeutic interest. The techniques used to describe the molecular recognition mechanisms, such as molecular docking and molecular dynamics, will therefore be eviscerated, highlighting their advantages and their limitations. Finally, we report several case studies in which computational methods have been applied in drug discovery on neuroinflammation, focusing on the last decade's research.
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Affiliation(s)
- Matteo Pavan
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Davide Bassani
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Giovanni Bolcato
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Maicol Bissaro
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Mattia Sturles
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Stefano Moro
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
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35
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Verma S, Pathak RK. Discovery and optimization of lead molecules in drug designing. Bioinformatics 2022. [DOI: 10.1016/b978-0-323-89775-4.00004-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
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36
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Heinrich L, Booijink R, Khurana A, Weiskirchen R, Bansal R. Lipoxygenases in chronic liver diseases: current insights and future perspectives. Trends Pharmacol Sci 2021; 43:188-205. [PMID: 34961619 DOI: 10.1016/j.tips.2021.12.001] [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] [Received: 09/01/2021] [Revised: 11/19/2021] [Accepted: 12/01/2021] [Indexed: 02/07/2023]
Abstract
Chronic liver diseases (CLDs) caused by viral infections, alcohol/drug abuse, or metabolic disorders affect millions of people globally and have increased mortality owing to the lack of approved therapies. Lipoxygenases (LOXs) are a family of multifaceted enzymes that are responsible for the oxidation of polyunsaturated fatty acids (PUFAs) and are implicated in the pathogenesis of multiple disorders including liver diseases. This review describes the three main LOX signaling pathways - 5-, 12-, and 15-LOX - and their involvement in CLDs. We also provide recent insights and future perspectives on LOX-related hepatic pathophysiology, and discuss the potential of LOXs and LOX-derived metabolites as diagnostic biomarkers and therapeutic targets in CLDs.
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Affiliation(s)
- Lena Heinrich
- Translational Liver Research, Department of Medical Cell BioPhysics, Faculty of Science and Technology, Technical Medical Center, University of Twente, Enschede 7500 AE, The Netherlands
| | - Richell Booijink
- Translational Liver Research, Department of Medical Cell BioPhysics, Faculty of Science and Technology, Technical Medical Center, University of Twente, Enschede 7500 AE, The Netherlands
| | - Amit Khurana
- Translational Liver Research, Department of Medical Cell BioPhysics, Faculty of Science and Technology, Technical Medical Center, University of Twente, Enschede 7500 AE, The Netherlands; Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry (IFMPEGKC), Rheinisch-Westfälische Technische Hochschule (RWTH) University Hospital Aachen, Aachen 52074, Germany; Centre for Biomedical Engineering (CBME), Indian Institute of Technology (IIT), Hauz Khas, New Delhi 110016, India
| | - Ralf Weiskirchen
- Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry (IFMPEGKC), Rheinisch-Westfälische Technische Hochschule (RWTH) University Hospital Aachen, Aachen 52074, Germany
| | - Ruchi Bansal
- Translational Liver Research, Department of Medical Cell BioPhysics, Faculty of Science and Technology, Technical Medical Center, University of Twente, Enschede 7500 AE, The Netherlands.
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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.
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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.
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Jana R, Begam HM, Dinda E. The emergence of the C-H functionalization strategy in medicinal chemistry and drug discovery. Chem Commun (Camb) 2021; 57:10842-10866. [PMID: 34596175 DOI: 10.1039/d1cc04083a] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Owing to the market competitiveness and urgent societal need, an optimum speed of drug discovery is an important criterion for successful implementation. Despite the rapid ascent of artificial intelligence and computational and bioanalytical techniques to accelerate drug discovery in big pharma, organic synthesis of privileged scaffolds predicted in silico for in vitro and in vivo studies is still considered as the rate-limiting step. C-H activation is the latest technology added into an organic chemist's toolbox for the rapid construction and late-stage modification of functional molecules to achieve the desired chemical and physical properties. Particularly, elimination of prefunctionalization steps, exceptional functional group tolerance, complexity-to-diversity oriented synthesis, and late-stage functionalization of privileged medicinal scaffolds expand the chemical space. It has immense potential for the rapid synthesis of a library of molecules, structural modification to achieve the required pharmacological properties such as absorption, distribution, metabolism, excretion, toxicology (ADMET) and attachment of chemical reporters for proteome profiling, metabolite synthesis, etc. for preclinical studies. Although heterocycle synthesis, late-stage drug modification, 18F labelling, methylation, etc. via C-H functionalization have been reviewed from the synthetic standpoint, a general overview of these protocols from medicinal and drug discovery aspects has not been reviewed. In this feature article, we will discuss the recent trends of C-H activation methodologies such as synthesis of medicinal scaffolds through C-H activation/annulation cascade; C-H arylation for sp2-sp2 and sp2-sp3 cross-coupling; C-H borylation/silylation to introduce a functional linchpin for further manipulation; C-H amination for N-heterocycles and hydrogen bond acceptors; C-H fluorination/fluoroalkylation to tune polarity and lipophilicity; C-H methylation: methyl magic in drug discovery; peptide modification and macrocyclization for therapeutics and biologics; fluorescent labelling and radiolabelling for bioimaging; bioconjugation for chemical biology studies; drug-metabolite synthesis for biodistribution and excretion studies; late-stage diversification of drug-molecules to increase efficacy and safety; cutting-edge DNA encoded library synthesis and improved synthesis of drug molecules via C-H activation in medicinal chemistry and drug discovery.
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Affiliation(s)
- Ranjan Jana
- Organic and Medicinal Chemistry Division, CSIR-Indian Institute of Chemical Biology, 4 Raja S. C. Mullick Road, Kolkata-700032, India.
| | - Hasina Mamataj Begam
- Organic and Medicinal Chemistry Division, CSIR-Indian Institute of Chemical Biology, 4 Raja S. C. Mullick Road, Kolkata-700032, India.
| | - Enakshi Dinda
- Department of Chemistry and Environment, Heritage Institute of Technology, Kolkata-700107, India
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Begum S, Shareef MZ, Bharathi K. Part-II- in silico drug design: application and success. PHYSICAL SCIENCES REVIEWS 2021. [DOI: 10.1515/psr-2018-0160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
In silico tools have indeed reframed the steps involved in traditional drug discovery and development process and the term in silico has become a familiar term in pharmaceutical sector like the terms in vitro and in vivo. The successful design of HIV protease inhibitors, Saquinavir, Indinavir and other important medicinal agents, initiated interest of researchers in structure based drug design approaches (SBDD). The interactions between biomolecules and a ligand, binding energy, free energy and stability of biomolecule-ligand complex can be envisioned and predicted by applying molecular docking studies. Protein-ligand, protein-protein, DNA-ligand interactions etc. aid in elucidating molecular level mechanisms of drug molecules. In the Ligand based drug design (LBDD) approaches, QSAR studies have tremendously contributed to the development of antimicrobial, anticancer, antimalarial agents. In the recent years, multiQSAR (mt-QSAR) approaches have been successfully employed for designing drugs against multifactorial diseases. Output of a research in several instances is rewarding when both SBDD and LBDD approaches are combined. Application of in silico studies for prediction of pharmacokinetics was once a real challenge but one can see unlimited number publications comprising tools, data bases which can accurately predict almost all the pharmacokinetic parameters. Absorption, distribution, metabolism, transporters, blood brain barrier permeability, hERG toxicity, P-gp affinity and several toxicological end points can be accurately predicted for a candidate molecule before its synthesis. In silico approaches are greatly encouraged a result of growing limitations and new legislations related to the animal use for research. The combined use of in vitro data and in silico tools will definitely decrease the use of animal testing in the future.In this chapter, in silico approaches and their applications are reviewed and discussed giving suitable examples.
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Affiliation(s)
- Shaheen Begum
- Institute of Pharmaceutical Technology , Sri Padmavati Mahila Visvavidyalayam , 517501 Tirupati , Andhra Pradesh , India
| | - Mohammad Zubair Shareef
- Institute of Pharmaceutical Technology , Sri Padmavati Mahila Visvavidyalayam , 517501 Tirupati , Andhra Pradesh , India
| | - Koganti Bharathi
- Institute of Pharmaceutical Technology , Sri Padmavati Mahila Visvavidyalayam , 517501 Tirupati , Andhra Pradesh , India
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Piroozmand F, Mohammadipanah F, Sajedi H. Spectrum of deep learning algorithms in drug discovery. Chem Biol Drug Des 2021; 96:886-901. [PMID: 33058458 DOI: 10.1111/cbdd.13674] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 02/11/2020] [Accepted: 02/19/2020] [Indexed: 12/16/2022]
Abstract
Deep learning (DL) algorithms are a subset of machine learning algorithms with the aim of modeling complex mapping between a set of elements and their classes. In parallel to the advance in revealing the molecular bases of diseases, a notable innovation has been undertaken to apply DL in data/libraries management, reaction optimizations, differentiating uncertainties, molecule constructions, creating metrics from qualitative results, and prediction of structures or interactions. From source identification to lead discovery and medicinal chemistry of the drug candidate, drug delivery, and modification, the challenges can be subjected to artificial intelligence algorithms to aid in the generation and interpretation of data. Discovery and design approach, both demand automation, large data management and data fusion by the advance in high-throughput mode. The application of DL can accelerate the exploration of drug mechanisms, finding novel indications for existing drugs (drug repositioning), drug development, and preclinical and clinical studies. The impact of DL in the workflow of drug discovery, design, and their complementary tools are highlighted in this review. Additionally, the type of DL algorithms used for this purpose, and their pros and cons along with the dominant directions of future research are presented.
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Affiliation(s)
- Firoozeh Piroozmand
- Pharmaceutical Biotechnology Lab, Department of Microbiology, School of Biology and Center of Excellence in Phylogeny of Living Organisms, College of Science, University of Tehran, Tehran, Iran
| | - Fatemeh Mohammadipanah
- Pharmaceutical Biotechnology Lab, Department of Microbiology, School of Biology and Center of Excellence in Phylogeny of Living Organisms, College of Science, University of Tehran, Tehran, Iran
| | - Hedieh Sajedi
- Department of Computer Science, School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran
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From pan-genome to protein dynamics: A computational hierarchical quest to identify drug target in multi-drug resistant Burkholderia cepacia. J Mol Liq 2020. [DOI: 10.1016/j.molliq.2020.113904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Alharbi A, Alshaghdali K, Saeed A. Molecular docking based design of Inhibitors for viral Non-Nucleosidase as potential anti-retroviral agents. Bioinformation 2020; 16:736-741. [PMID: 34675458 PMCID: PMC8503775 DOI: 10.6026/97320630016736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Revised: 08/22/2020] [Accepted: 08/22/2020] [Indexed: 11/23/2022] Open
Abstract
Reverse Transcriptase (RT) inhibitors are highly promising agents for use as an effective anti-retroviral therapy (HAART) which is typically a combination of three or four antiretroviral drugs. We used direct drug design approach to discover new chemical entities for the target protein. The validated template of the protein targeting reverse transcriptase PDB ID 1JKH was extracted for three sites hydrophobic, steric, and electronic parameters explain the interactions at the active site by the inhibitors. We used the Zinc library of compounds to explore the possible leads for HAART through RT inhibition. We report 12 new chemical entities with possible activity against the targeted viral protein. These leads will provide new therapeutic means in antiretroviral therapy.
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Affiliation(s)
- Ahmed Alharbi
- Collage of Applied Medical Sciences, Department of Laboratory Sciences, University of Hail, Hail, Kingdom of Saudi Arabia
| | - Khalid Alshaghdali
- Collage of Applied Medical Sciences, Department of Laboratory Sciences, University of Hail, Hail, Kingdom of Saudi Arabia
| | - Amir Saeed
- Collage of Applied Medical Sciences, Department of Laboratory Sciences, University of Hail, Hail, Kingdom of Saudi Arabia
- Department of Medical Microbiology, Faculty of Medical Laboratory Sciences, University of Medical Sciences & Technology, Khartoum, Sudan
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Chaudhary N, Aparoy P. Application of per-residue energy decomposition to identify the set of amino acids critical for in silico prediction of COX-2 inhibitory activity. Heliyon 2020; 6:e04944. [PMID: 33083581 PMCID: PMC7550918 DOI: 10.1016/j.heliyon.2020.e04944] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 05/31/2020] [Accepted: 09/11/2020] [Indexed: 12/29/2022] Open
Abstract
The enormous magnitude of scientific research carried out in the field of NSAIDs and cyclooxygenases (COXs) is known. They are crucial in pain management. COX-2 inhibitors have evolved over the years; from traditional NSAIDs to isoform-specific. The present study is aimed to identify a cluster of amino acids in the catalytic site whose energy contribution can better explain COX-2 inhibitory activity accurately than the binding energy of the whole protein. Initially, MD simulations (25 ns) and MM-PBSA calculations were performed for 8 diarylheterocyclic inhibitors. Per-residue energy decomposition studies were carried out to elucidate the energy contribution of each amino acid, and their correlation with COX-2 inhibitory activity was enumerated. A cluster of catalytic amino acids whose free energy sum has a high correlation with biological data was identified. The cluster of Gln178, Ser339, Tyr341, Arg499, Phe504, Val509 and Ala513 showed the correlation of -0.60. Further, the study was extended to a total of 26 COX-2 inhibitors belonging to different classes to validate the applicability of the cluster of amino acids identified. Results clearly suggest that the cluster of amino acids identified provide accurate screening method, and can be applied to predict COX-2 inhibitory activity of small molecules.
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Affiliation(s)
- Neha Chaudhary
- Centre for Computational Biology and Bioinformatics, School of Life Sciences, Central University of Himachal Pradesh, Dharamshala, Himachal Pradesh, 176215, India
| | - Polamarasetty Aparoy
- Centre for Computational Biology and Bioinformatics, School of Life Sciences, Central University of Himachal Pradesh, Dharamshala, Himachal Pradesh, 176215, India.,Faculty of Biology, Indian Institute of Petroleum & Energy, Visakhapatnam, Andhra Pradesh, India
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Ikwu FA, Isyaku Y, Obadawo BS, Lawal HA, Ajibowu SA. In silico design and molecular docking study of CDK2 inhibitors with potent cytotoxic activity against HCT116 colorectal cancer cell line. J Genet Eng Biotechnol 2020; 18:51. [PMID: 32930901 PMCID: PMC7492310 DOI: 10.1186/s43141-020-00066-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 09/02/2020] [Indexed: 11/23/2022]
Abstract
BACKGROUND Colorectal cancer is common to both sexes; third in terms of morbidity and second in terms of mortality, accounting for 10% and 9.2% of cancer cases in men and women globally. Although drugs such as bevacizumab, Camptosar, and cetuximab are being used to manage colorectal cancer, the efficacy of the drugs has been reported to vary from patient to patient. These drugs have also been reported to have varying degrees of side effects; thus, the need for novel drug therapies with better efficacy and lesser side effects. In silico drugs design methods provide a faster and cost-effect method for lead identification and optimization. The aim of this study, therefore, was to design novel imidazol-5-ones via in silico design methods. RESULTS A QSAR model was built using the genetic function algorithm method to model the cytotoxicity of the compounds against the HCT116 colorectal cancer cell line. The built model had statistical parameters; R2 = 0.7397, R2adj = 0.6712, Q2cv = 0.5547, and R2ext. = 0.7202 and revealed the cytotoxic activity of the compounds to be dependent on the molecular descriptors nS, GATS5s, VR1_Dze, ETA_dBetaP, and L3i. These molecular descriptors were poorly correlated (VIF < 4.0) and made unique contributions to the built model. The model was used to design a novel set of derivatives via the ligand-based drug design approach. Compounds e, h, j, and l showed significantly better cytotoxicity (IC50 < 5.0 μM) compared to the template. The interaction of the compounds with the CDK2 enzyme (PDB ID: 6GUE) was investigated via molecular docking study. The compounds were potent inhibitors of the enzyme having binding affinity of range -10.8 to -11.0 kcal/mol and primarily formed hydrogen bond interaction with lysine, aspartic acid, leucine, and histidine amino acid residues of the enzyme. CONCLUSION The QSAR model built was stable, robust, and had a good predicting ability. Thus, predictions made by the model were reliably employed in further in silico studies. The compounds designed were more active than the template and showed better inhibition of the CDK2 enzyme compared to the standard drugs sorafenib and kenpaullone.
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Affiliation(s)
- Fabian Adakole Ikwu
- Department of Chemistry, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria
| | - Yusuf Isyaku
- Department of Chemistry, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria
| | | | | | - Samuel Akolade Ajibowu
- Department of Chemistry, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria
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Structure-based design and activity modeling of novel epidermal growth factor receptor kinase inhibitors; an in silico approach. SCIENTIFIC AFRICAN 2020. [DOI: 10.1016/j.sciaf.2020.e00503] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
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Nazar A, Abbas G, Azam SS. Deciphering the Inhibition Mechanism of under Trial Hsp90 Inhibitors and Their Analogues: A Comparative Molecular Dynamics Simulation. J Chem Inf Model 2020; 60:3812-3830. [PMID: 32659088 DOI: 10.1021/acs.jcim.9b01134] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Heat shock protein 90 (Hsp90) performs functions in cellular activities together with other signaling pathways. Hsp90 is evolutionarily conserved and universally articulated as a human cancer-causing agent involved in lung cancer and breast cancer followed by colon and rectum cancers. It has emerged as an effective drug candidate, and inhibition may affect several signaling pathways associated with cancer spread. Therefore, in-silico approaches, molecular docking, molecular dynamics simulation, and binding free energy calculations were applied to create insights into the inhibition mechanism against Hsp90 to identify new cancer therapeutic drugs. Top-docked Hsp90-inhibitor complexes with their analogues were selected as the best complexes based on the GOLD fitness score and orientation. The significant interaction of Hsp90 inhibitors and their analogues were observed to be bound with active site residues as well as residing within the same cavity region. System stability factors RMSD, RMSF, beta-factor, and radius of gyration were analyzed for top-docked complexes and ensure strong binding interaction between inhibitors and the Hsp90 cavity. Cavity bound inhibitors were found to retain consistent hydrogen bonding during the simulation. The radial distribution function (RDF) illustrated that interacting active site residues drive the binding and stability of the inhibitors. Similarly, the axial frequency distribution, which is an indigenously developed analytical tool, produced noteworthy knowledge of the hydrogen-bonding pattern. Results yielded new insights into the design of cancer therapeutic drugs against Hsp90. This finding suggests that under trial Hsp90 inhibitors MPC-3100 could be a potential starting point into the development of potential anticancer agents with the possibility of future directions for the improvement of early existing Hsp90 inhibitors CNF-2024 and SNX-5422 as an anticancer agent.
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Affiliation(s)
- Asma Nazar
- Computational Biology Lab, National Center for Bioinformatics (NCB), Quaid-i-Azam University, Islamabad 45320, Pakistan
| | - Ghulam Abbas
- Computational Biology Lab, National Center for Bioinformatics (NCB), Quaid-i-Azam University, Islamabad 45320, Pakistan
| | - Syed Sikander Azam
- Computational Biology Lab, National Center for Bioinformatics (NCB), Quaid-i-Azam University, Islamabad 45320, Pakistan
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Ahamed TKS, Muraleedharan K. A cheminformatic study on chemical space characterization and diversity analysis of 5-LOX inhibitors. J Mol Graph Model 2020; 100:107699. [PMID: 32799052 DOI: 10.1016/j.jmgm.2020.107699] [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: 04/18/2020] [Revised: 06/19/2020] [Accepted: 07/10/2020] [Indexed: 10/23/2022]
Abstract
The process of blocking 5-lipoxygenase (5-LOX) catalyzed leukotriene biosynthesis has been recognized for the past few decades as a promising therapeutic strategy for acute inflammatory, allergic, and respiratory diseases. Due to the toxicity effect of FDA approved 5-LOX inhibitor zileuton, novel 5-LOX inhibitors have been sought by the scientific community. As a result, a significant and relevant amount of information on the structure-activity of 5-LOX inhibitors has been released and stored in public databases. In this study, we aimed at the comprehensive cheminformatic characterization of the diversity and complexity of the chemical space of 5-LOX inhibitors and its activating protein FLAP inhibitors by comparing it with the Approved drug space and virtual LOX library. The visual representation of the property space indicates some compounds in the 5-LOX inhibitors space broaden the traditional medicinal space. The structural diversity of the databases is computed using complementary approaches, including Physicochemical Property (PCP) descriptors, molecular fingerprints, and molecular scaffold. With the apparent exception of approved drugs, the 5-LOX dataset shows more diversity compared to FLAP and LOX virtual library set. This study was able to identify the underlying patterns in the chemical and pharmacological properties space that were decisive for the drug discovery and development of 5-LOX inhibitors.
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Affiliation(s)
| | - K Muraleedharan
- Department of Chemistry, University of Calicut, Malappuram, 673635, India.
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Dawood M, Elbadawi M, Böckers M, Bringmann G, Efferth T. Molecular docking-based virtual drug screening revealing an oxofluorenyl benzamide and a bromonaphthalene sulfonamido hydroxybenzoic acid as HDAC6 inhibitors with cytotoxicity against leukemia cells. Biomed Pharmacother 2020; 129:110454. [PMID: 32768947 DOI: 10.1016/j.biopha.2020.110454] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 06/19/2020] [Accepted: 06/23/2020] [Indexed: 12/21/2022] Open
Abstract
HDAC6 is a crucial epigenetic modifier that plays a vital role in tumor progression and carcinogenesis due to its multiple biological functions. It is a unique member of class-II HDAC enzymes. It possesses two catalytic domains, which function independently of the overall enzyme activity. Up to date, there are only a few selective HDAC6 inhibitors with anti-cancer activity. In this study, 175,204 ligands obtained from the ZINC15 and OTAVAchemical databases were used for virtual drug screening against HDAC6. Molecular docking studies were performed for 100 selected compounds. Furthermore, the top 10 compounds obtained from docking were tested for their efficacy to inhibit the function of HDAC6. Five compounds (N-(9-oxo-9H-fluoren-3-yl)benzamide, 2-hydroxy-5-[(5-oxo-6-phenyl-4,5-dihydro-1,2,4-triazin-3-yl)amino]benzoic acid, 5-(4-bromonaphthalene-1-sulfonamido)-2-hydroxybenzoic acid, 2-(naphthalen-2-yl)-N-(1H-1,2,3,4-tetrazol-5-yl)cyclopropane-1-carboxamide, and 4-oxa-5,6 diazapentacyclo[10.7.1.0³,⁷.0⁸,²⁰.0¹⁴,¹⁹]icosa-1,3(7),5,8(20),9,11,14,16,18-nonaen-13-one) inhibited enzymatic activity by more than 50 % compared to DMSO as the control. Two candidates, (N-(9-oxo-9H-fluoren-3-yl)benzamide and 5-(4-bromonaphthalene-1-sulfonamido)-2-hydroxybenzoic acid), were identified with considerable cytotoxicity towards drug-sensitive CCRF-CEM and multidrug-resistant CEM/ADR5000 leukemia cells. Microscale thermophoresis revealed the binding of N-(9-oxo-9H-fluoren-3-yl)benzamide and 5-(4-bromonaphthalene-1-sulfonamido)-2-hydroxybenzoic acid to purified HDAC6 protein. Both compounds induced apoptosis in a dose-dependent manner as analyzed by flow cytometry. In conclusion, we demonstrate for the first time that these two compounds bind to HDAC6, inhibit its function, and exert cytotoxic activity by apoptosis induction.
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Affiliation(s)
- Mona Dawood
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, 55128 Mainz, Germany
| | - Mohamed Elbadawi
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, 55128 Mainz, Germany
| | - Madeleine Böckers
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, 55128 Mainz, Germany
| | - Gerhard Bringmann
- Institute of Organic Chemistry, University of Würzburg, Am Hubland, D-97074 Würzburg, Germany
| | - Thomas Efferth
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, 55128 Mainz, Germany.
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Isyaku Y, Uzairu A, Uba S. Computational studies of a series of 2-substituted phenyl-2-oxo-, 2-hydroxyl- and 2-acylloxyethylsulfonamides as potent anti-fungal agents. Heliyon 2020; 6:e03724. [PMID: 32322718 PMCID: PMC7160569 DOI: 10.1016/j.heliyon.2020.e03724] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Revised: 02/13/2020] [Accepted: 03/30/2020] [Indexed: 11/24/2022] Open
Abstract
Botrytis Cinerea is a plant pathogen that affect a large number of plant species like tomatoes, Lettuce, Grapes, and Strawberries among others. Sulfonamides are widely used in pharmaceutical industries as anti-cancer, anti-inflammatory and anti-viral agents. To complement our previous QSAR study, a ligand-based design and ADME/T study were carried out on these sulfonamides compounds for their fungicidal activity toward “Botrytis Cinerea”. With the help of AutoDock Vina version 4.0 in Pyrex software, the docking analysis was performed after optimization of the compounds at DFT/B3LYP/6-31G∗ quantum mechanical method using Spartan 14 softwar. Using the model generated in the previous QSAR work, the descriptors of the chosen model were considered in modifying the most promising compound ‘9’ in which twelve (12) derivatives were designed and found to have better activity than the template (compound 9). With compound 9j having the highest activity that turns out to be about 14 and 15 times more potent than the commercial fungicides “procymidone and chlorothalonil”. Furthermore, ADME/T properties of the designed compounds were calculated using the SwissADME online tool in which all the compounds were found to have good pharmacokinetic profile. Moreover, a molecular docking study on selected compounds of the dataset (compound 8, 13, 14, 19, 20, 21, 22 and 29) revealed that compound ‘20’ turned out to have the highest docking score of -8.5 kJ/mol. This compound has a strong affinity with the macromolecular target point (PDB ID: 3wh1) producing H-bond and hydrophobic interaction at the target point of amino acid residue. The molecular docking analysis gave an insight on the structure-based design of the new compounds with better activity against B. cinerea.
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Affiliation(s)
- Yusuf Isyaku
- Department of Chemistry Ahmadu Bello University, P.M.B. 1044, Zaria, Nigeria
| | - Adamu Uzairu
- Department of Chemistry Ahmadu Bello University, P.M.B. 1044, Zaria, Nigeria
| | - Sani Uba
- Department of Chemistry Ahmadu Bello University, P.M.B. 1044, Zaria, Nigeria
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Pharmacoinformatics and molecular dynamic simulation studies to identify potential small-molecule inhibitors of WNK-SPAK/OSR1 signaling that mimic the RFQV motifs of WNK kinases. ARAB J CHEM 2020. [DOI: 10.1016/j.arabjc.2020.02.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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