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Yang Z, Wang Y, Ablise M, Maimaiti A, Mutalipu Z, Yan T, Liu ZY, Aihaiti A. Design, synthesis, and ex vivo anti-drug resistant cervical cancer activity of novel molecularly targeted chalcone derivatives. Bioorg Chem 2024; 149:107498. [PMID: 38805911 DOI: 10.1016/j.bioorg.2024.107498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 05/12/2024] [Accepted: 05/23/2024] [Indexed: 05/30/2024]
Abstract
Chemotherapy toxicity and tumor multidrug resistance remain the main reasons for clinical treatment failure in cervical cancer. In this study, 79 novel chalcone derivatives were designed and synthesized using the principle of active substructure splicing with the parent nucleus of licorice chalcone as the lead compound and VEGFR-2 and P-gp as the target of action and their potentials for anticervical cancer activity were preliminarily evaluated. The results showed that the IC50 values of candidate compound B20 against HeLa and HeLa/DDP cells were 3.66 ± 0.10 and 4.35 ± 0.21 μΜ, respectively, with a resistance index (RI) of 1.18, which was significantly higher than that of the positive drug cisplatin (IC50:13.60 ± 1.63, 100.03 ± 7.94 μΜ, RI:7.36). In addition, B20 showed significant inhibitory activity against VEGFR-2 kinase and P-gp-mediated rhodamine 123 efflux, as well as the ability to inhibit the phosphorylation of VEGFR-2 and downstream PI3K/AKT signaling pathway proteins, inducing apoptosis, blocking cells in the S-phase, and inhibiting invasive migration and tubule generation by HUVEC cells. Acceptable safety was demonstrated in acute toxicity tests when B20 was at 200 mg/kg. In the nude mouse HeLa/DDP cell xenograft tumor model, the inhibition rate of transplanted tumors was 39.2 % and 79.2 % when B20 was at 10 and 20 mg/kg, respectively. These results suggest that B20 is a potent VEGFR-2 and P-gp inhibitor with active potential for treating cisplatin-resistant cervical cancer.
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Affiliation(s)
- Zheng Yang
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi 830011, China
| | - Yu Wang
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi 830011, China
| | - Mourboul Ablise
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi 830011, China.
| | - Aikebaier Maimaiti
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi 830011, China
| | - Zuohelaguli Mutalipu
- Department of Gynecological Radiation Therapy Ⅱ Ward, The 3rd Affiliated Teaching Hospital of Xinjiang Medical University (Affiliated Cancer Hospital), Urumqi, Xinjiang 830011, China
| | - Tong Yan
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi 830011, China
| | - Zheng-Ye Liu
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi 830011, China
| | - Aizitiaili Aihaiti
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi 830011, China
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2
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Bai YR, Seng DJ, Xu Y, Zhang YD, Zhou WJ, Jia YY, Song J, He ZX, Liu HM, Yuan S. A comprehensive review of small molecule drugs approved by the FDA in 2023: Advances and prospects. Eur J Med Chem 2024; 276:116706. [PMID: 39053188 DOI: 10.1016/j.ejmech.2024.116706] [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: 06/03/2024] [Accepted: 07/21/2024] [Indexed: 07/27/2024]
Abstract
In 2023, the U.S. Food and Drug Administration has approved 55 novel medications, consisting of 17 biologics license applications and 38 new molecular entities. Although the biologics license applications including antibody and enzyme replacement therapy set a historical record, the new molecular entities comprising small molecule drugs, diagnostic agent, RNA interference therapy and biomacromolecular peptide still account for over 50 % of the newly approved medications. The novel and privileged scaffolds derived from drugs, active molecules and natural products are consistently associated with the discovery of new mechanisms, the expansion of clinical indications and the reduction of side effects. Moreover, the structural modifications based on the promising scaffolds can provide the clinical candidates with the improved biological activities, bypass the patent protection and greatly shorten the period of new drug discovery. Therefore, conducting an appraisal of drug approval experience and related information will expedite the identification of more potent drug molecules. In this review, we comprehensively summarized the pertinent information encompassing the clinical application, mechanism, elegant design and development processes of 28 small molecule drugs, and expected to provide the promising structural basis and design inspiration for pharmaceutical chemists.
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Affiliation(s)
- Yi-Ru Bai
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China; School of Pharmaceutical Sciences & Key Laboratory of Advanced Drug Preparation Technologies, Zhengzhou University, Zhengzhou, 450001, China
| | - Dong-Jie Seng
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Ying Xu
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Yao-Dong Zhang
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Wen-Juan Zhou
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Yang-Yang Jia
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Jian Song
- School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, 450001, China
| | - Zhang-Xu He
- Pharmacy College, Henan University of Chinese Medicine, Zhengzhou, 450046, China.
| | - Hong-Min Liu
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China; School of Pharmaceutical Sciences & Key Laboratory of Advanced Drug Preparation Technologies, Zhengzhou University, Zhengzhou, 450001, China.
| | - Shuo Yuan
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China; School of Pharmaceutical Sciences & Key Laboratory of Advanced Drug Preparation Technologies, Zhengzhou University, Zhengzhou, 450001, China.
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3
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Singh S, Kaur N, Gehlot A. Application of artificial intelligence in drug design: A review. Comput Biol Med 2024; 179:108810. [PMID: 38991316 DOI: 10.1016/j.compbiomed.2024.108810] [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: 03/18/2024] [Revised: 05/31/2024] [Accepted: 06/24/2024] [Indexed: 07/13/2024]
Abstract
Artificial intelligence (AI) is a field of computer science that involves acquiring information, developing rule bases, and mimicking human behaviour. The fundamental concept behind AI is to create intelligent computer systems that can operate with minimal human intervention or without any intervention at all. These rule-based systems are developed using various machine learning and deep learning models, enabling them to solve complex problems. AI is integrated with these models to learn, understand, and analyse provided data. The rapid advancement of Artificial Intelligence (AI) is reshaping numerous industries, with the pharmaceutical sector experiencing a notable transformation. AI is increasingly being employed to automate, optimize, and personalize various facets of the pharmaceutical industry, particularly in pharmacological research. Traditional drug development methods areknown for being time-consuming, expensive, and less efficient, often taking around a decade and costing billions of dollars. The integration of artificial intelligence (AI) techniques addresses these challenges by enabling the examination of compounds with desired properties from a vast pool of input drugs. Furthermore, it plays a crucial role in drug screening by predicting toxicity, bioactivity, ADME properties (absorption, distribution, metabolism, and excretion), physicochemical properties, and more. AI enhances the drug design process by improving the efficiency and accuracy of predicting drug behaviour, interactions, and properties. These approaches further significantly improve the precision of drug discovery processes and decrease clinical trial costs leading to the development of more effective drugs.
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Affiliation(s)
- Simrandeep Singh
- Department of Electronics & Communication Engineering, UCRD, Chandigarh University, Gharuan, Punjab, India.
| | - Navjot Kaur
- Department of Pharmacognosy, Amar Shaheed Baba Ajit Singh Jujhar Singh Memorial College of Pharmacy, Bela, Ropar, India
| | - Anita Gehlot
- Uttaranchal Institute of technology, Uttaranchal University, Dehradun, India
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Zhou Y, Zhou F, Xu S, Shi D, Ding D, Wang S, Poongavanam V, Tang K, Liu X, Zhan P. Hydrophobic tagging of small molecules: an overview of the literature and future outlook. Expert Opin Drug Discov 2024; 19:799-813. [PMID: 38825802 DOI: 10.1080/17460441.2024.2360416] [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: 01/04/2024] [Accepted: 05/23/2024] [Indexed: 06/04/2024]
Abstract
INTRODUCTION Hydrophobic tagging (HyT) technology presents a distinct therapeutic strategy diverging from conventional small molecule drugs, providing an innovative approach to drug design. This review aims to provide an overview of the HyT literature and future outlook to offer guidance for drug design. AREAS COVERED In this review, the authors introduce the composition, mechanisms and advantages of HyT technology, as well as summarize the detailed applications of HyT technology in anti-cancer, neurodegenerative diseases (NDs), autoimmune disorders, cardiovascular diseases (CVDs), and other fields. Furthermore, this review discusses key aspects of the future development of HyT molecules. EXPERT OPINION HyT emerges as a highly promising targeted protein degradation (TPD) strategy, following the successful development of proteolysis targeting chimeras (PROTAC) and molecular glue. Based on exploring new avenues, modification of the HyT molecule itself potentially enhances the technology. Improved synthetic pathways and emphasis on pharmacokinetic (PK) properties will facilitate the development of HyT. Furthermore, elucidating the biochemical basis by which the compound's hydrophobic moiety recruits the protein homeostasis network will enable the development of more precise assays that can guide the optimization of the linker and hydrophobic moiety.
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Affiliation(s)
- Yang Zhou
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, PR China
| | - Fan Zhou
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, PR China
| | - Shujing Xu
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, PR China
| | - Dazhou Shi
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, PR China
| | - Dang Ding
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, PR China
| | - Shuo Wang
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, PR China
| | | | - Kai Tang
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, PR China
| | - Xinyong Liu
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, PR China
| | - Peng Zhan
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, PR China
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Bekono BD, Onguéné PA, Simoben CV, Owono LCO, Ntie-Kang F. Computational discovery of dual potential inhibitors of SARS-CoV-2 spike/ACE2 and M pro: 3D-pharmacophore, docking-based virtual screening, quantum mechanics and molecular dynamics. EUROPEAN BIOPHYSICS JOURNAL : EBJ 2024:10.1007/s00249-024-01713-z. [PMID: 38907013 DOI: 10.1007/s00249-024-01713-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 06/01/2024] [Accepted: 06/02/2024] [Indexed: 06/23/2024]
Abstract
To find drugs against COVID-19, caused by the SARS-CoV-2, promising targets include the fusion of the viral spike with the human angiotensin-converting enzyme 2 (ACE2) as well as the main protease (Mpro). These proteins are responsible for viral entry and replication, respectively. We combined several state-of-the-art computational methods, including, protein-ligand interaction fingerprint, 3D-pharmacophores, molecular-docking, MM-GBSA, DFT, and MD simulations to explore two databases: ChEMBL and NANPDB to identify molecules that could both block spike/ACE2 fusion and inhibit Mpro. A total of 1,690,649 compounds from the two databases were screened using the pharmacophore model obtained from PLIF analysis. Five recent complexes of Mpro co-crystallized with different ligands were used to generate the pharmacophore model, allowing 4,829 compounds that passed this prefilter. These were then submitted to molecular docking against Mpro. The 5% top-ranked docking hits from docking result having scores < -8.32 kcal mol-1 were selected and then docked against spike/ACE2. Only four compounds: ChEMBL244958, ChEMBL266531, ChEMBL3680003, and 1-methoxy-3-indolymethyl glucosinolate (4) displayed binding energies < - 8.21 kcal mol-1 (for the native ligand) were considered as putative dual-target inhibitors. Furthermore, predictive ADMET, MM-GBSA and DFT/6-311G(d,p) were performed on these compounds and compared with those of well-known antivirals. DFT calculations showed that ChEMBL244958 and compound 4 had significant predicted reactivity values. Molecular dynamics simulations of the docked complexes were run for 100 ns and used to validate the stability docked poses and to confirm that these hits are putative dual binders of the spike/ACE2 and the Mpro.
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Affiliation(s)
- Boris D Bekono
- Department of Physics, Ecole Normale Supérieure, University of Yaoundé I, P. O. Box 47, Yaoundé, CM-00237, Cameroon.
- Center for Drug Discovery, Faculty of Science, University of Buea, P.O. Box 63, Buea, CM-00237, Cameroon.
| | - Pascal Amoa Onguéné
- Center for Drug Discovery, Faculty of Science, University of Buea, P.O. Box 63, Buea, CM-00237, Cameroon
- Department of Chemistry, University of Yaoundé I Institute of Wood Technology Mbalmayo, University of Yaoundé I, BP 50, Mbalmayo, Cameroon
| | - Conrad V Simoben
- Center for Drug Discovery, Faculty of Science, University of Buea, P.O. Box 63, Buea, CM-00237, Cameroon
- Structural Genomics Consortium, University of Toronto, Toronto, ON, M5G 1L7, Canada
| | - Luc C O Owono
- Department of Physics, Ecole Normale Supérieure, University of Yaoundé I, P. O. Box 47, Yaoundé, CM-00237, Cameroon
- CEPAMOQ, Faculty of Science, University of Douala, CM-00237, Douala, Cameroon
| | - Fidele Ntie-Kang
- Center for Drug Discovery, Faculty of Science, University of Buea, P.O. Box 63, Buea, CM-00237, Cameroon.
- Department of Chemistry, Faculty of Science, University of Buea, CM-00237, Buea, Cameroon.
- Institute of Pharmacy, Martin-Luther University Halle-Wittenberg, 06120, Halle (Saale), Germany.
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Kudo G, Hirao T, Yoshino R, Shigeta Y, Hirokawa T. Site Identification and Next Choice Protocol for Hit-to-Lead Optimization. J Chem Inf Model 2024; 64:4475-4484. [PMID: 38768949 PMCID: PMC11167593 DOI: 10.1021/acs.jcim.3c02036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 04/11/2024] [Accepted: 04/11/2024] [Indexed: 05/22/2024]
Abstract
Time efficiency and cost savings are major challenges in drug discovery and development. In this process, the hit-to-lead stage is expected to improve efficiency because it primarily exploits the trial-and-error approach of medicinal chemists. This study proposes a site identification and next choice (SINCHO) protocol to improve the hit-to-lead efficiency. This protocol selects an anchor atom and growth site pair, which is desirable for a hit-to-lead strategy starting from a 3D complex structure. We developed and fine-tuned the protocol using a training data set and assessed it using a test data set of the preceding hit-to-lead strategy. The protocol was tested for experimentally determined structures and molecular dynamics (MD) ensembles. The protocol had a high prediction accuracy for applying MD ensembles, owing to the consideration of protein flexibility. The SINCHO protocol enables medicinal chemists to visualize and modify functional groups in a hit-to-lead manner.
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Affiliation(s)
- Genki Kudo
- Physics
Department, Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8571, Japan
| | - Takumi Hirao
- Doctoral
Program in Medical Sciences, Graduate School of Comprehensive Human
Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8575, Japan
- Division
of Biomedical Science, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan
| | - Ryunosuke Yoshino
- Division
of Biomedical Science, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan
- Transborder
Medical Research Center, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan
| | - Yasuteru Shigeta
- Center
for Computational Sciences, University of
Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Takatsugu Hirokawa
- Division
of Biomedical Science, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan
- Transborder
Medical Research Center, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan
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Crouzet A, Lopez N, Riss Yaw B, Lepelletier Y, Demange L. The Millennia-Long Development of Drugs Associated with the 80-Year-Old Artificial Intelligence Story: The Therapeutic Big Bang? Molecules 2024; 29:2716. [PMID: 38930784 PMCID: PMC11206022 DOI: 10.3390/molecules29122716] [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: 03/29/2024] [Revised: 05/30/2024] [Accepted: 05/31/2024] [Indexed: 06/28/2024] Open
Abstract
The journey of drug discovery (DD) has evolved from ancient practices to modern technology-driven approaches, with Artificial Intelligence (AI) emerging as a pivotal force in streamlining and accelerating the process. Despite the vital importance of DD, it faces challenges such as high costs and lengthy timelines. This review examines the historical progression and current market of DD alongside the development and integration of AI technologies. We analyse the challenges encountered in applying AI to DD, focusing on drug design and protein-protein interactions. The discussion is enriched by presenting models that put forward the application of AI in DD. Three case studies are highlighted to demonstrate the successful application of AI in DD, including the discovery of a novel class of antibiotics and a small-molecule inhibitor that has progressed to phase II clinical trials. These cases underscore the potential of AI to identify new drug candidates and optimise the development process. The convergence of DD and AI embodies a transformative shift in the field, offering a path to overcome traditional obstacles. By leveraging AI, the future of DD promises enhanced efficiency and novel breakthroughs, heralding a new era of medical innovation even though there is still a long way to go.
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Affiliation(s)
- Aurore Crouzet
- UMR 8038 CNRS CiTCoM, Team PNAS, Faculté de Pharmacie, Université Paris Cité, 4 Avenue de l’Observatoire, 75006 Paris, France
- W-MedPhys, 128 Rue la Boétie, 75008 Paris, France
| | - Nicolas Lopez
- W-MedPhys, 128 Rue la Boétie, 75008 Paris, France
- ENOES, 62 Rue de Miromesnil, 75008 Paris, France
- Unité Mixte de Recherche «Institut de Physique Théorique (IPhT)» CEA-CNRS, UMR 3681, Bat 774, Route de l’Orme des Merisiers, 91191 St Aubin-Gif-sur-Yvette, France
| | - Benjamin Riss Yaw
- UMR 8038 CNRS CiTCoM, Team PNAS, Faculté de Pharmacie, Université Paris Cité, 4 Avenue de l’Observatoire, 75006 Paris, France
| | - Yves Lepelletier
- W-MedPhys, 128 Rue la Boétie, 75008 Paris, France
- Université Paris Cité, Imagine Institute, 24 Boulevard Montparnasse, 75015 Paris, France
- INSERM UMR 1163, Laboratory of Cellular and Molecular Basis of Normal Hematopoiesis and Hematological Disorders: Therapeutical Implications, 24 Boulevard Montparnasse, 75015 Paris, France
| | - Luc Demange
- UMR 8038 CNRS CiTCoM, Team PNAS, Faculté de Pharmacie, Université Paris Cité, 4 Avenue de l’Observatoire, 75006 Paris, France
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8
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Wu Z, Chen S, Wang Y, Li F, Xu H, Li M, Zeng Y, Wu Z, Gao Y. Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis. Int J Surg 2024; 110:3848-3878. [PMID: 38502850 PMCID: PMC11175770 DOI: 10.1097/js9.0000000000001289] [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: 11/08/2023] [Accepted: 02/22/2024] [Indexed: 03/21/2024]
Abstract
AIM Computer-aided drug design (CADD) is a drug design technique for computing ligand-receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics. METHODS A systematic review of studies published between 2000 and 20 July 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analyzed using software such as Excel, VOSviewer, RStudio, and CiteSpace. RESULTS A total of 2031 publications were included. These publications primarily originated from 99 countries or regions led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and the greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications. CONCLUSIONS Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modeling, pharmacophore modeling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics that will influence future development. Furthermore, this paper will be helpful in better understanding the frontiers and hotspots of CADD.
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Affiliation(s)
- Zhenhui Wu
- School of Pharmacy, Jiangxi University of Chinese Medicine
- School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
| | - Shupeng Chen
- School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang
| | - Yihao Wang
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
| | - Fangyang Li
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
| | - Huanhua Xu
- School of Pharmacy, Jiangxi University of Chinese Medicine
| | - Maoxing Li
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
| | - Yingjian Zeng
- School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang
| | - Zhenfeng Wu
- School of Pharmacy, Jiangxi University of Chinese Medicine
| | - Yue Gao
- School of Pharmacy, Jiangxi University of Chinese Medicine
- Beijing Institute of Radiation Medicine, Academy of Military Sciences, Beijing, People’s Republic of China
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9
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Waseem T, Rajput TA, Mushtaq MS, Babar MM, Rajadas J. Computational biology approaches for drug repurposing. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2024; 205:91-109. [PMID: 38789189 DOI: 10.1016/bs.pmbts.2024.03.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2024]
Abstract
The drug discovery and development (DDD) process greatly relies on the data available in various forms to generate hypotheses for novel drug design. The complex and heterogeneous nature of biological data makes it difficult to utilize or gather meaningful information as such. Computational biology techniques have provided us with opportunities to better understand biological systems through refining and organizing large amounts of data into actionable and systematic purviews. The drug repurposing approach has been utilized to overcome the expansive time periods and costs associated with traditional drug development. It deals with discovering new uses of already approved drugs that have an established safety and efficacy profile, thereby, requiring them to go through fewer development phases. Thus, drug repurposing through computational biology provides a systematic approach to drug development and overcomes the constraints of traditional processes. The current chapter covers the basics, approaches and tools of computational biology that can be employed to effectively develop repurposing profile of already approved drug molecules.
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Affiliation(s)
- Tanya Waseem
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan
| | - Tausif Ahmed Rajput
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan
| | | | - Mustafeez Mujtaba Babar
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan; Advanced Drug Delivery and Regenerative Biomaterials Laboratory, Cardiovascular Institute and Pulmonary and Critical Care Medicine, Stanford University School of Medicine, Stanford University, Palo Alto, CA, United States.
| | - Jayakumar Rajadas
- Advanced Drug Delivery and Regenerative Biomaterials Laboratory, Cardiovascular Institute and Pulmonary and Critical Care Medicine, Stanford University School of Medicine, Stanford University, Palo Alto, CA, United States
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10
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Nandi S, Bhaduri S, Das D, Ghosh P, Mandal M, Mitra P. Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence. Mol Pharm 2024; 21:1563-1590. [PMID: 38466810 DOI: 10.1021/acs.molpharmaceut.3c01161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biological processes and diseases. Targeting protein binding hot spots, which regulate signaling and growth, with rational drug design is promising. Rational drug design uses structural data and computational tools to study protein binding sites and protein interfaces to design inhibitors that can change these interactions, thereby potentially leading to therapeutic approaches. Artificial intelligence (AI), such as machine learning (ML) and deep learning (DL), has advanced drug discovery and design by providing computational resources and methods. Quantum chemistry is essential for drug reactivity, toxicology, drug screening, and quantitative structure-activity relationship (QSAR) properties. This review discusses the methodologies and challenges of identifying and characterizing hot spots and binding sites. It also explores the strategies and applications of artificial-intelligence-based rational drug design technologies that target proteins and protein-protein interaction (PPI) binding hot spots. It provides valuable insights for drug design with therapeutic implications. We have also demonstrated the pathological conditions of heat shock protein 27 (HSP27) and matrix metallopoproteinases (MMP2 and MMP9) and designed inhibitors of these proteins using the drug discovery paradigm in a case study on the discovery of drug molecules for cancer treatment. Additionally, the implications of benzothiazole derivatives for anticancer drug design and discovery are deliberated.
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Affiliation(s)
- Suvendu Nandi
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Soumyadeep Bhaduri
- Centre for Computational and Data Sciences, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Debraj Das
- Centre for Computational and Data Sciences, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Priya Ghosh
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Mahitosh Mandal
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Pralay Mitra
- Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
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11
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Lee KH, Won SJ, Oyinloye P, Shi L. Unlocking the Potential of High-Quality Dopamine Transporter Pharmacological Data: Advancing Robust Machine Learning-Based QSAR Modeling. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.06.583803. [PMID: 38558976 PMCID: PMC10979915 DOI: 10.1101/2024.03.06.583803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The dopamine transporter (DAT) plays a critical role in the central nervous system and has been implicated in numerous psychiatric disorders. The ligand-based approaches are instrumental to decipher the structure-activity relationship (SAR) of DAT ligands, especially the quantitative SAR (QSAR) modeling. By gathering and analyzing data from literature and databases, we systematically assemble a diverse range of ligands binding to DAT, aiming to discern the general features of DAT ligands and uncover the chemical space for potential novel DAT ligand scaffolds. The aggregation of DAT pharmacological activity data, particularly from databases like ChEMBL, provides a foundation for constructing robust QSAR models. The compilation and meticulous filtering of these data, establishing high-quality training datasets with specific divisions of pharmacological assays and data types, along with the application of QSAR modeling, prove to be a promising strategy for navigating the pertinent chemical space. Through a systematic comparison of DAT QSAR models using training datasets from various ChEMBL releases, we underscore the positive impact of enhanced data set quality and increased data set size on the predictive power of DAT QSAR models.
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Affiliation(s)
- Kuo Hao Lee
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse – Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Sung Joon Won
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse – Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Precious Oyinloye
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse – Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Lei Shi
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse – Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
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12
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Mondal I, Halder AK, Pattanayak N, Mandal SK, Cordeiro MNDS. Shaping the Future of Obesity Treatment: In Silico Multi-Modeling of IP6K1 Inhibitors for Obesity and Metabolic Dysfunction. Pharmaceuticals (Basel) 2024; 17:263. [PMID: 38399478 PMCID: PMC10891520 DOI: 10.3390/ph17020263] [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: 12/22/2023] [Revised: 02/14/2024] [Accepted: 02/16/2024] [Indexed: 02/25/2024] Open
Abstract
Recent research has uncovered a promising approach to addressing the growing global health concern of obesity and related disorders. The inhibition of inositol hexakisphosphate kinase 1 (IP6K1) has emerged as a potential therapeutic strategy. This study employs multiple ligand-based in silico modeling techniques to investigate the structural requirements for benzisoxazole derivatives as IP6K1 inhibitors. Firstly, we developed linear 2D Quantitative Structure-Activity Relationship (2D-QSAR) models to ensure both their mechanistic interpretability and predictive accuracy. Then, ligand-based pharmacophore modeling was performed to identify the essential features responsible for the compounds' high activity. To gain insights into the 3D requirements for enhanced potency against the IP6K1 enzyme, we employed multiple alignment techniques to set up 3D-QSAR models. Given the absence of an available X-ray crystal structure for IP6K1, a reliable homology model for the enzyme was developed and structurally validated in order to perform structure-based analyses on the selected dataset compounds. Finally, molecular dynamic simulations, using the docked poses of these compounds, provided further insights. Our findings consistently supported the mechanistic interpretations derived from both ligand-based and structure-based analyses. This study offers valuable guidance on the design of novel IP6K1 inhibitors. Importantly, our work exclusively relies on non-commercial software packages, ensuring accessibility for reproducing the reported models.
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Affiliation(s)
- Ismail Mondal
- Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, India; (I.M.); (A.K.H.); (N.P.); (S.K.M.)
| | - Amit Kumar Halder
- Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, India; (I.M.); (A.K.H.); (N.P.); (S.K.M.)
- LAQV@REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
| | - Nirupam Pattanayak
- Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, India; (I.M.); (A.K.H.); (N.P.); (S.K.M.)
| | - Sudip Kumar Mandal
- Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, India; (I.M.); (A.K.H.); (N.P.); (S.K.M.)
| | - Maria Natalia D. S. Cordeiro
- LAQV@REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
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13
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Li H, Sun X, Cui W, Xu M, Dong J, Ekundayo BE, Ni D, Rao Z, Guo L, Stahlberg H, Yuan S, Vogel H. Computational drug development for membrane protein targets. Nat Biotechnol 2024; 42:229-242. [PMID: 38361054 DOI: 10.1038/s41587-023-01987-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 09/13/2023] [Indexed: 02/17/2024]
Abstract
The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have limitations for development of drugs that target membrane proteins. Structural transitions of membrane proteins have a central role during transmembrane signaling and are often influenced by therapeutic compounds. Resolving the structural and functional basis of dynamic transmembrane signaling networks, especially within the native membrane or cellular environment, remains a central challenge for drug development. Tackling this challenge will require an interplay between experimental and computational tools, such as super-resolution optical microscopy for quantification of the molecular interactions of cellular signaling networks and their modulation by potential drugs, cryo-electron microscopy for determination of the structural transitions of proteins in native cell membranes and entire cells, and computational tools for data analysis and prediction of the structure and function of cellular signaling networks, as well as generation of promising drug candidates.
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Affiliation(s)
- Haijian Li
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
| | - Xiaolin Sun
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
| | - Wenqiang Cui
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Marc Xu
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Junlin Dong
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Babatunde Edukpe Ekundayo
- Laboratory of Biological Electron Microscopy, IPHYS, SB, EPFL and Department of Fundamental Microbiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Dongchun Ni
- Laboratory of Biological Electron Microscopy, IPHYS, SB, EPFL and Department of Fundamental Microbiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Zhili Rao
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
| | - Liwei Guo
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China
| | - Henning Stahlberg
- Laboratory of Biological Electron Microscopy, IPHYS, SB, EPFL and Department of Fundamental Microbiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.
| | - Shuguang Yuan
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China.
| | - Horst Vogel
- Center for Computer-Aided Drug Discovery, Faculty of Pharmaceutical Sciences, Shenzhen Institute of Advanced Technology/Chinese Academy of Sciences (SIAT/CAS), Shenzhen, China.
- Institut des Sciences et Ingénierie Chimiques (ISIC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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14
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Alzain AA, Elbadwi FA, Shoaib TH, Sherif AE, Osman W, Ashour A, Mohamed GA, Ibrahim SRM, Roh EJ, Hassan AHE. Integrating computational methods guided the discovery of phytochemicals as potential Pin1 inhibitors for cancer: pharmacophore modeling, molecular docking, MM-GBSA calculations and molecular dynamics studies. Front Chem 2024; 12:1339891. [PMID: 38318109 PMCID: PMC10839060 DOI: 10.3389/fchem.2024.1339891] [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: 11/17/2023] [Accepted: 01/08/2024] [Indexed: 02/07/2024] Open
Abstract
Pin1 is a pivotal player in interactions with a diverse array of phosphorylated proteins closely linked to critical processes such as carcinogenesis and tumor suppression. Its axial role in cancer initiation and progression, coupled with its overexpression and activation in various cancers render it a potential candidate for the development of targeted therapeutics. While several known Pin1 inhibitors possess favorable enzymatic profiles, their cellular efficacy often falls short. Consequently, the pursuit of novel Pin1 inhibitors has gained considerable attention in the field of medicinal chemistry. In this study, we employed the Phase tool from Schrödinger to construct a structure-based pharmacophore model. Subsequently, 449,008 natural products (NPs) from the SN3 database underwent screening to identify compounds sharing pharmacophoric features with the native ligand. This resulted in 650 compounds, which then underwent molecular docking and binding free energy calculations. Among them, SN0021307, SN0449787 and SN0079231 showed better docking scores with values of -9.891, -7.579 and -7.097 kcal/mol, respectively than the reference compound (-6.064 kcal/mol). Also, SN0021307, SN0449787 and SN0079231 exhibited lower free binding energies (-57.12, -49.81 and -46.05 kcal/mol, respectively) than the reference ligand (-37.75 kcal/mol). Based on these studies, SN0021307, SN0449787, and SN0079231 showed better binding affinity that the reference compound. Further the validation of these findings, molecular dynamics simulations confirmed the stability of the ligand-receptor complex for 100 ns with RMSD ranging from 0.6 to 1.8 Å. Based on these promising results, these three phytochemicals emerge as promising lead compounds warranting comprehensive biological screening in future investigations. These compounds hold great potential for further exploration regarding their efficacy and safety as Pin1 inhibitors, which could usher in new avenues for combating cancer.
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Affiliation(s)
- Abdulrahim A. Alzain
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Gezira, Sudan
| | - Fatima A. Elbadwi
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Gezira, Sudan
| | - Tagyedeen H. Shoaib
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Gezira, Sudan
| | - Asmaa E. Sherif
- Department of Pharmacognosy, Faculty of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
- Department of Pharmacognosy, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt
| | - Wadah Osman
- Department of Pharmacognosy, Faculty of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
- Department of Pharmacognosy, Faculty of Pharmacy, University of Khartoum, Khartoum, Sudan
| | - Ahmed Ashour
- Department of Pharmacognosy, Faculty of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
- Department of Pharmacognosy, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt
| | - Gamal A. Mohamed
- Department of Natural Products and Alternative Medicine, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Sabrin R. M. Ibrahim
- Preparatory Year Program, Department of Chemistry, Batterjee Medical College, Jeddah, Saudi Arabia
- Department of Pharmacognosy, Faculty of Pharmacy, Assiut University, Assiut, Egypt
| | - Eun Joo Roh
- Chemical and Biological Integrative Research Center, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
- Division of Bio-Medical Science and Technology, University of Science and Technology, Daejeon, Republic of Korea
| | - Ahmed H. E. Hassan
- Department of Medicinal Chemistry, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt
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15
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Zhao R, Zhu J, Jiang X, Bai R. Click chemistry-aided drug discovery: A retrospective and prospective outlook. Eur J Med Chem 2024; 264:116037. [PMID: 38101038 DOI: 10.1016/j.ejmech.2023.116037] [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: 10/22/2023] [Revised: 11/20/2023] [Accepted: 12/08/2023] [Indexed: 12/17/2023]
Abstract
Click chemistry has emerged as a valuable tool for rapid compound synthesis, presenting notable advantages and convenience in the exploration of potential drug candidates. In particular, in situ click chemistry capitalizes on enzymes as reaction templates, leveraging their favorable conformation to selectively link individual building blocks and generate novel hits. This review comprehensively outlines and introduces the extensive use of click chemistry in compound library construction, and hit and lead discovery, supported by specific research examples. Additionally, it discusses the limitations and precautions associated with the application of click chemistry in drug discovery. Our intention for this review is to contribute to the development of a modular synthetic approach for the rapid identification of drug candidates.
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Affiliation(s)
- Rui Zhao
- School of Pharmacy, Hangzhou Normal University, Hangzhou, 311121, PR China; Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, 311121, PR China
| | - Junlong Zhu
- School of Pharmacy, Hangzhou Normal University, Hangzhou, 311121, PR China; Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, 311121, PR China
| | - Xiaoying Jiang
- School of Pharmacy, Hangzhou Normal University, Hangzhou, 311121, PR China; Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, 311121, PR China
| | - Renren Bai
- School of Pharmacy, Hangzhou Normal University, Hangzhou, 311121, PR China; Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou, 311121, PR China.
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Chen C, Zhang B, Tu J, Peng Y, Zhou Y, Yang X, Yu Q, Tan X. Discovery of 4-aminophenylacetamide derivatives as intestine-specific farnesoid X receptor antagonists for the potential treatment of nonalcoholic steatohepatitis. Eur J Med Chem 2024; 264:115992. [PMID: 38043493 DOI: 10.1016/j.ejmech.2023.115992] [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: 11/21/2023] [Accepted: 11/21/2023] [Indexed: 12/05/2023]
Abstract
Farnesoid X receptor (FXR) plays a key role in bile acid homeostasis, inflammation, fibrosis, lipid and glucose metabolism and is emerging as a promising therapeutic target for nonalcoholic steatohepatitis (NASH). Emerging evidence suggested that intestine-specific FXR antagonists exhibited remarkable metabolic improvements and slowed NASH progression. In this study, we discovered several potent FXR antagonists using a multistage ligand- and structure-based virtual screening approach. Notably, compound V023-9340, which possesses a 4-aminophenylacetamide scaffold, emerged as the most potent FXR antagonist with an IC50 value of 4.27 μM. In vivo, V023-9340 demonstrated selective accumulation in the intestine, substantially ameliorating high-fat diet (HFD)-induced NASH in mice by mitigating hepatic steatosis and inflammation. Mechanistic studies revealed that V023-9340 strongly inhibited intestinal FXR while concurrently feedback-activated hepatic FXR. Further structure-activity relationship optimization employing V023-9340 has resulted in the synthesis of a more efficacious compound V02-8 with an IC50 value of 0.89 μM, which exhibited a 4.8-fold increase in FXR antagonistic activity compared to V023-9340. In summary, 4-aminophenylacetamide derivative V023-9340 represented a novel intestine-specific FXR antagonist and showed improved effects against HFD-induced NASH in mice, which may serve as a promising lead in discovering potential therapeutic drugs for NASH treatment.
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Affiliation(s)
- Cong Chen
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Bing Zhang
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Jiaojiao Tu
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Yanfen Peng
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Yihuan Zhou
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Xinping Yang
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China
| | - Qiming Yu
- Guangxi Key Laboratory of Environmental Exposure Omics and Life Cycle Health, College of Public Health, Guilin Medical University, Guilin 541199, China.
| | - Xiangduan Tan
- Guangxi Key Laboratory of Drug Discovery and Optimization, College of Pharmacy, Guilin Medical University, Guilin 541199, China.
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Hong B, Yang E, Su D, Ju J, Cui X, Wang Q, Tong F, Zhao J, Yang S, Cheng C, Xin L, Xiao M, Yi K, Zhan Q, Ding Y, Xu H, Cui L, Kang C. EPIC-1042 as a potent PTRF/Cavin1-caveolin-1 interaction inhibitor to induce PARP1 autophagic degradation and suppress temozolomide efflux for glioblastoma. Neuro Oncol 2024; 26:100-114. [PMID: 37651725 PMCID: PMC10768988 DOI: 10.1093/neuonc/noad159] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND Temozolomide (TMZ) treatment efficacy in glioblastoma is determined by various mechanisms such as TMZ efflux, autophagy, base excision repair (BER) pathway, and the level of O6-methylguanine-DNA methyltransferase (MGMT). Here, we reported a novel small-molecular inhibitor (SMI) EPIC-1042 (C20H28N6) with the potential to decrease TMZ efflux and promote PARP1 degradation via autolysosomes in the early stage. METHODS EPIC-1042 was obtained from receptor-based virtual screening. Co-immunoprecipitation and pull-down assays were applied to verify the blocking effect of EPIC-1042. Western blotting, co-immunoprecipitation, and immunofluorescence were used to elucidate the underlying mechanisms of EPIC-1042. In vivo experiments were performed to verify the efficacy of EPIC-1042 in sensitizing glioblastoma cells to TMZ. RESULTS EPIC-1042 physically interrupted the interaction of PTRF/Cavin1 and caveolin-1, leading to reduced secretion of small extracellular vesicles (sEVs) to decrease TMZ efflux. It also induced PARP1 autophagic degradation via increased p62 expression that more p62 bound to PARP1 and specially promoted PARP1 translocation into autolysosomes for degradation in the early stage. Moreover, EPIC-1042 inhibited autophagy flux at last. The application of EPIC-1042 enhanced TMZ efficacy in glioblastoma in vivo. CONCLUSION EPIC-1042 reinforced the effect of TMZ by preventing TMZ efflux, inducing PARP1 degradation via autolysosomes to perturb the BER pathway and recruitment of MGMT, and inhibiting autophagy flux in the later stage. Therefore, this study provided a novel therapeutic strategy using the combination of TMZ with EPIC-1042 for glioblastoma treatment.
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Affiliation(s)
- Biao Hong
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Eryan Yang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Dongyuan Su
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Jiasheng Ju
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Xiaoteng Cui
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Qixue Wang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Fei Tong
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Jixing Zhao
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Shixue Yang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Chunchao Cheng
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Lei Xin
- Department of Neurosurgery, Affiliated Hospital of Hebei University, Baoding, China
| | - Menglin Xiao
- Department of Neurosurgery, Affiliated Hospital of Hebei University, Baoding, China
| | - Kaikai Yi
- Department of Neuro-Oncology and Neurosurgery, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Qi Zhan
- Tianjin Key Laboratory of Composite and Functional Materials, School of Materials Science and Engineering, Tianjin University, Tianjin, China
| | - Yaqing Ding
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Hanyi Xu
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Longtao Cui
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Chunsheng Kang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
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18
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Verma A, Awasthi A. Revolutionizing Drug Discovery: The Role of Artificial Intelligence and Machine Learning. Curr Pharm Des 2024; 30:807-810. [PMID: 38409722 DOI: 10.2174/0113816128298691240222054120] [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: 12/14/2023] [Revised: 01/29/2024] [Accepted: 02/12/2024] [Indexed: 02/28/2024]
Affiliation(s)
- Abhishek Verma
- Department of Pharmaceutics, ISF College of Pharmacy, Moga, Punjab 142001, India
| | - Ankit Awasthi
- Department of Pharmaceutics, ISF College of Pharmacy, Moga, Punjab 142001, India
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19
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Dos Santos Nascimento IJ, Albino SL, da Silva Menezes KJ, de Azevedo Teotônio Cavalcanti M, de Oliveira MS, Mali SN, de Moura RO. Targeting SmCB1: Perspectives and Insights to Design Antischistosomal Drugs. Curr Med Chem 2024; 31:2264-2284. [PMID: 37921174 DOI: 10.2174/0109298673255826231011114249] [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: 03/31/2023] [Revised: 09/01/2023] [Accepted: 09/14/2023] [Indexed: 11/04/2023]
Abstract
Neglected tropical diseases (NTDs) are prevalent in tropical and subtropical countries, and schistosomiasis is among the most relevant diseases worldwide. In addition, one of the two biggest problems in developing drugs against this disease is related to drug resistance, which promotes the demand to develop new drug candidates for this purpose. Thus, one of the drug targets most explored, Schistosoma mansoni Cathepsin B1 (SmCB1 or Sm31), provides new opportunities in drug development due to its essential functions for the parasite's survival. In this way, here, the latest developments in drug design studies targeting SmCB1 were approached, focusing on the most promising analogs of nitrile, vinyl sulphones, and peptidomimetics. Thus, it was shown that despite being a disease known since ancient times, it remains prevalent throughout the world, with high mortality rates. The therapeutic arsenal of antischistosomal drugs (ASD) consists only of praziquantel, which is widely used for this purpose and has several advantages, such as efficacy and safety. However, it has limitations, such as the impossibility of acting on the immature worm and exploring new targets to overcome these limitations. SmCB1 shows its potential as a cysteine protease with a catalytic triad consisting of Cys100, His270, and Asn290. Thus, design studies of new inhibitors focus on their catalytic mechanism for designing new analogs. In fact, nitrile and sulfonamide analogs show the most significant potential in drug development, showing that these chemical groups can be better exploited in drug discovery against schistosomiasis. We hope this manuscript guides the authors in searching for promising new antischistosomal drugs.
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Affiliation(s)
- Igor José Dos Santos Nascimento
- Pharmacy Department, Cesmac University Center, Maceió, 57051-160, Brazil
- Laboratório de Desenvolvimento e Síntese de Fármacos, Departamento de Farmácia, Universidade Estadual da Paraíba, Campina Grande 58429-500, Brazil
- Programa de Pós Graduação em Ciências Farmacêuticas, Universidade Estadual da Paraíba, Campina Grande, 58429-500, Brazil
| | - Sonaly Lima Albino
- Laboratório de Desenvolvimento e Síntese de Fármacos, Departamento de Farmácia, Universidade Estadual da Paraíba, Campina Grande 58429-500, Brazil
| | - Karla Joane da Silva Menezes
- Laboratório de Desenvolvimento e Síntese de Fármacos, Departamento de Farmácia, Universidade Estadual da Paraíba, Campina Grande 58429-500, Brazil
- Programa de Pós Graduação em Ciências Farmacêuticas, Universidade Estadual da Paraíba, Campina Grande, 58429-500, Brazil
| | - Misael de Azevedo Teotônio Cavalcanti
- Laboratório de Desenvolvimento e Síntese de Fármacos, Departamento de Farmácia, Universidade Estadual da Paraíba, Campina Grande 58429-500, Brazil
- Programa de Pós Graduação em Ciências Farmacêuticas, Universidade Estadual da Paraíba, Campina Grande, 58429-500, Brazil
| | - Mozaniel Santana de Oliveira
- Coordination of Botany-Laboratory Adolpho Ducke, Avenida Perimetral, Museu Paraense Emílio Goeldi, 1901, Belém, 66077-530, PA Brazil
| | - Suraj N Mali
- Department of Pharmaceutical Sciences and Technology, Institute of Chemical Technology, Matunga East, Mumbai, 400019, India
| | - Ricardo Olimpio de Moura
- Laboratório de Desenvolvimento e Síntese de Fármacos, Departamento de Farmácia, Universidade Estadual da Paraíba, Campina Grande 58429-500, Brazil
- Programa de Pós Graduação em Ciências Farmacêuticas, Universidade Estadual da Paraíba, Campina Grande, 58429-500, Brazil
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20
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Li C, Ye G, Jiang Y, Wang Z, Yu H, Yang M. Artificial Intelligence in battling infectious diseases: A transformative role. J Med Virol 2024; 96:e29355. [PMID: 38179882 DOI: 10.1002/jmv.29355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 12/01/2023] [Accepted: 12/17/2023] [Indexed: 01/06/2024]
Abstract
It is widely acknowledged that infectious diseases have wrought immense havoc on human society, being regarded as adversaries from which humanity cannot elude. In recent years, the advancement of Artificial Intelligence (AI) technology has ushered in a revolutionary era in the realm of infectious disease prevention and control. This evolution encompasses early warning of outbreaks, contact tracing, infection diagnosis, drug discovery, and the facilitation of drug design, alongside other facets of epidemic management. This article presents an overview of the utilization of AI systems in the field of infectious diseases, with a specific focus on their role during the COVID-19 pandemic. The article also highlights the contemporary challenges that AI confronts within this domain and posits strategies for their mitigation. There exists an imperative to further harness the potential applications of AI across multiple domains to augment its capacity in effectively addressing future disease outbreaks.
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Affiliation(s)
- Chunhui Li
- School of Life Science, Advanced Research Institute of Multidisciplinary Science, Key Laboratory of Molecular Medicine and Biotherapy, Beijing Institute of Technology, Beijing, People's Republic of China
| | - Guoguo Ye
- Shenzhen Key Laboratory of Pathogen and Immunity, National Clinical Research Center for Infectious Disease, The Third People's Hospital of Shenzhen, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Yinghan Jiang
- School of Life Science, Advanced Research Institute of Multidisciplinary Science, Key Laboratory of Molecular Medicine and Biotherapy, Beijing Institute of Technology, Beijing, People's Republic of China
| | - Zhiming Wang
- School of Life Science, Advanced Research Institute of Multidisciplinary Science, Key Laboratory of Molecular Medicine and Biotherapy, Beijing Institute of Technology, Beijing, People's Republic of China
| | - Haiyang Yu
- Hangzhou Yalla Information Technology Service Co., Ltd., Hangzhou, People's Republic of China
| | - Minghui Yang
- School of Life Science, Advanced Research Institute of Multidisciplinary Science, Key Laboratory of Molecular Medicine and Biotherapy, Beijing Institute of Technology, Beijing, People's Republic of China
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21
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Lu J, Xing H, Wang C, Tang M, Wu C, Ye F, Yin L, Yang Y, Tan W, Shen L. Mpox (formerly monkeypox): pathogenesis, prevention, and treatment. Signal Transduct Target Ther 2023; 8:458. [PMID: 38148355 PMCID: PMC10751291 DOI: 10.1038/s41392-023-01675-2] [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: 07/25/2023] [Revised: 09/14/2023] [Accepted: 09/21/2023] [Indexed: 12/28/2023] Open
Abstract
In 2022, a global outbreak of Mpox (formerly monkeypox) occurred in various countries across Europe and America and rapidly spread to more than 100 countries and regions. The World Health Organization declared the outbreak to be a public health emergency of international concern due to the rapid spread of the Mpox virus. Consequently, nations intensified their efforts to explore treatment strategies aimed at combating the infection and its dissemination. Nevertheless, the available therapeutic options for Mpox virus infection remain limited. So far, only a few numbers of antiviral compounds have been approved by regulatory authorities. Given the high mutability of the Mpox virus, certain mutant strains have shown resistance to existing pharmaceutical interventions. This highlights the urgent need to develop novel antiviral drugs that can combat both drug resistance and the potential threat of bioterrorism. Currently, there is a lack of comprehensive literature on the pathophysiology and treatment of Mpox. To address this issue, we conducted a review covering the physiological and pathological processes of Mpox infection, summarizing the latest progress of anti-Mpox drugs. Our analysis encompasses approved drugs currently employed in clinical settings, as well as newly identified small-molecule compounds and antibody drugs displaying potential antiviral efficacy against Mpox. Furthermore, we have gained valuable insights from the process of Mpox drug development, including strategies for repurposing drugs, the discovery of drug targets driven by artificial intelligence, and preclinical drug development. The purpose of this review is to provide readers with a comprehensive overview of the current knowledge on Mpox.
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Affiliation(s)
- Junjie Lu
- Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Hubei Province, Xiangyang, 441021, China
| | - Hui Xing
- Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Hubei Province, Xiangyang, 441021, China
| | - Chunhua Wang
- Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Hubei Province, Xiangyang, 441021, China
| | - Mengjun Tang
- Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Hubei Province, Xiangyang, 441021, China
| | - Changcheng Wu
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Fan Ye
- Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Hubei Province, Xiangyang, 441021, China
| | - Lijuan Yin
- College of Biotechnology, Tianjin University of Science & Technology, Tianjin, 300457, China
| | - Yang Yang
- Shenzhen Key Laboratory of Pathogen and Immunity, National Clinical Research Center for infectious disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China.
| | - Wenjie Tan
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Liang Shen
- Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Hubei Province, Xiangyang, 441021, China.
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22
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Ruankham W, Songtawee N, Prachayasittikul V, Worachartcheewan A, Suwanjang W, Pingaew R, Prachayasittikul V, Prachayasittikul S, Phopin K. Promising 8-Aminoquinoline-Based Metal Complexes in the Modulation of SIRT1/3-FOXO3a Axis against Oxidative Damage-Induced Preclinical Neurons. ACS OMEGA 2023; 8:46977-46988. [PMID: 38107906 PMCID: PMC10720006 DOI: 10.1021/acsomega.3c06764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/31/2023] [Accepted: 11/13/2023] [Indexed: 12/19/2023]
Abstract
The discovery of novel bioactive molecules as potential multifunctional neuroprotective agents has clinically drawn continual interest due to devastating oxidative damage in the pathogenesis and progression of neurodegenerative diseases. Synthetic 8-aminoquinoline antimalarial drug is an attractive pharmacophore in drug development and chemical modification owing to its wide range of biological activities, yet the underlying molecular mechanisms are not fully elucidated in preclinical models for oxidative damage. Herein, the neuroprotective effects of two 8-aminoquinoline-uracil copper complexes were investigated on the hydrogen peroxide-induced human neuroblastoma SH-SY5Y cells. Both metal complexes markedly restored cell survival, alleviated apoptotic cascades, maintained antioxidant defense, and prevented mitochondrial function by upregulating the sirtuin 1 (SIRT1)/3-FOXO3a signaling pathway. Intriguingly, in silico molecular docking and pharmacokinetic prediction suggested that these synthetic compounds acted as SIRT1 activators with potential drug-like properties, wherein the uracil ligands (5-iodoracil and 5-nitrouracil) were essential for effective binding interactions with the target protein SIRT1. Taken together, the synthetic 8-aminoquinoline-based metal complexes are promising brain-targeting drugs for attenuating neurodegenerative diseases.
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Affiliation(s)
- Waralee Ruankham
- Center
for Research Innovation and Biomedical Informatics, Faculty of Medical
Technology, Mahidol University, Bangkok 10700, Thailand
| | - Napat Songtawee
- Department
of Clinical Chemistry, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand
| | - Veda Prachayasittikul
- Center
for Research Innovation and Biomedical Informatics, Faculty of Medical
Technology, Mahidol University, Bangkok 10700, Thailand
| | - Apilak Worachartcheewan
- Department
of Community Medical Technology, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand
| | - Wilasinee Suwanjang
- Center
for Research Innovation and Biomedical Informatics, Faculty of Medical
Technology, Mahidol University, Bangkok 10700, Thailand
| | - Ratchanok Pingaew
- Department
of Chemistry, Faculty of Science, Srinakharinwirot
University, Bangkok 10110, Thailand
| | - Virapong Prachayasittikul
- Department
of Clinical Microbiology and Applied Technology, Faculty of Medical
Technology, Mahidol University, Bangkok 10700, Thailand
| | - Supaluk Prachayasittikul
- Center
for Research Innovation and Biomedical Informatics, Faculty of Medical
Technology, Mahidol University, Bangkok 10700, Thailand
| | - Kamonrat Phopin
- Center
for Research Innovation and Biomedical Informatics, Faculty of Medical
Technology, Mahidol University, Bangkok 10700, Thailand
- Department
of Clinical Microbiology and Applied Technology, Faculty of Medical
Technology, Mahidol University, Bangkok 10700, Thailand
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23
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Yang J, Jiang C, Chen J, Qin L, Cheng G. Predicting GPR40 Agonists with A Deep Learning-Based Ensemble Model. ChemistryOpen 2023; 12:e202300051. [PMID: 37404062 PMCID: PMC10661831 DOI: 10.1002/open.202300051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/23/2023] [Indexed: 07/06/2023] Open
Abstract
Recent studies have identified G protein-coupled receptor 40 (GPR40) as a promising target for treating type 2 diabetes mellitus, and GPR40 agonists have several superior effects over other hypoglycemic drugs, including cardiovascular protection and suppression of glucagon levels. In this study, we constructed an up-to-date GPR40 ligand dataset for training models and performed a systematic optimization of the ensemble model, resulting in a powerful ensemble model (ROC AUC: 0.9496) for distinguishing GPR40 agonists and non-agonists. The ensemble model is divided into three layers, and the optimization process is carried out in each layer. We believe that these results will prove helpful for both the development of GPR40 agonists and ensemble models. All the data and models are available on GitHub. (https://github.com/Jiamin-Yang/ensemble_model).
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Affiliation(s)
- Jiamin Yang
- School of Pharmaceutical SciencesZhejiang Chinese Medical UniversityHangzhouP. R. China310053
| | - Chen Jiang
- School of Pharmaceutical SciencesZhejiang Chinese Medical UniversityHangzhouP. R. China310053
| | - Jing Chen
- School of Pharmaceutical SciencesZhejiang Chinese Medical UniversityHangzhouP. R. China310053
| | - Lu‐Ping Qin
- School of Pharmaceutical SciencesZhejiang Chinese Medical UniversityHangzhouP. R. China310053
| | - Gang Cheng
- School of Pharmaceutical SciencesZhejiang Chinese Medical UniversityHangzhouP. R. China310053
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24
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Shamsian S, Sokouti B, Dastmalchi S. Benchmarking different docking protocols for predicting the binding poses of ligands complexed with cyclooxygenase enzymes and screening chemical libraries. BIOIMPACTS : BI 2023; 14:29955. [PMID: 38505677 PMCID: PMC10945300 DOI: 10.34172/bi.2023.29955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/09/2023] [Accepted: 08/23/2023] [Indexed: 03/21/2024]
Abstract
Introduction Non-steroidal anti-inflammatory drugs (NSAIDs) constitute an important class of pharmaceuticals acting on cyclooxygenase COX-1 and COX-2 enzymes. Due to their numerous severe side effects, it is necessary to search for new selective, safe, and effective anti-inflammatory drugs. In silico design of novel therapeutics plays an important role in nowadays drug discovery pipelines. In most cases, the design strategies require the use of molecular docking calculations. The docking procedure may require case-specific condition for a successful result. Additionally, many different docking programs are available, which highlights the importance of identifying the most proper docking method and condition for a given problem. Methods In the current work, the performances of five popular molecular docking programs, namely, GOLD, AutoDock, FlexX, Molegro Virtual Docker (MVD) and Glide to predict the binding mode of co- crystallized inhibitors in the structures of known complexes available for cyclooxygenases were evaluated. Furthermore, the best performers, Glide, AutoDock, GOLD and FlexX, were further evaluated in docking-based virtual screening of libraries consisted of active ligands and decoy molecules for cyclooxygenase enzymes and the obtained docking scores were assessed by receiver operating characteristics (ROC) analysis. Results The results of docking experiments indicated that Glide program outperformed other docking programs by correctly predicting the binding poses (RMSD less than 2 Å) of all studied co-crystallized ligands of COX-1 and COX-2 enzymes (i.e., the performance was 100%). However, the performances of the other studied docking methods for correctly predicting the binding poses of the ligands were between 59% to 82%. Virtual screening results treated by ROC analysis revealed that all tested methods are useful tools for classification and enrichment of molecules targeting COX enzymes. The obtained AUCs range between 0.61-0.92 with enrichment factors of 8 - 40 folds. Conclusion The obtained results support the importance of choosing appropriate docking method for predicting ligand-receptor binding modes, and provide specific information about docking calculations on COXs ligands.
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Affiliation(s)
- Sara Shamsian
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz, 5165665931, Iran
- Department of Medicinal Chemistry, School of Pharmacy, Tabriz University of Medical Sciences, Tabriz, 5166414766, Iran
| | - Babak Sokouti
- Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, 5165665813, Iran
| | - Siavoush Dastmalchi
- Department of Medicinal Chemistry, School of Pharmacy, Tabriz University of Medical Sciences, Tabriz, 5166414766, Iran
- Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, 5165665813, Iran
- Faculty of Pharmacy, Near East University, POBOX:99138, Nicosia, North Cyprus, Mersin 10, Turkey
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25
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Han R, Yoon H, Kim G, Lee H, Lee Y. Revolutionizing Medicinal Chemistry: The Application of Artificial Intelligence (AI) in Early Drug Discovery. Pharmaceuticals (Basel) 2023; 16:1259. [PMID: 37765069 PMCID: PMC10537003 DOI: 10.3390/ph16091259] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/24/2023] [Accepted: 09/04/2023] [Indexed: 09/29/2023] Open
Abstract
Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical industry and research, where it has been utilized to efficiently identify new chemical entities with desirable properties. The application of AI algorithms to drug discovery presents both remarkable opportunities and challenges. This review article focuses on the transformative role of AI in medicinal chemistry. We delve into the applications of machine learning and deep learning techniques in drug screening and design, discussing their potential to expedite the early drug discovery process. In particular, we provide a comprehensive overview of the use of AI algorithms in predicting protein structures, drug-target interactions, and molecular properties such as drug toxicity. While AI has accelerated the drug discovery process, data quality issues and technological constraints remain challenges. Nonetheless, new relationships and methods have been unveiled, demonstrating AI's expanding potential in predicting and understanding drug interactions and properties. For its full potential to be realized, interdisciplinary collaboration is essential. This review underscores AI's growing influence on the future trajectory of medicinal chemistry and stresses the importance of ongoing synergies between computational and domain experts.
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Affiliation(s)
| | | | | | | | - Yoonji Lee
- College of Pharmacy, Chung-Ang University, Seoul 06974, Republic of Korea
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26
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Cools R, Kerkhofs K, Leitao RCF, Bormans G. Preclinical Evaluation of Novel PET Probes for Dementia. Semin Nucl Med 2023; 53:599-629. [PMID: 37149435 DOI: 10.1053/j.semnuclmed.2023.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 03/24/2023] [Indexed: 05/08/2023]
Abstract
The development of novel PET imaging agents that selectively bind specific dementia-related targets can contribute significantly to accurate, differential and early diagnosis of dementia causing diseases and support the development of therapeutic agents. Consequently, in recent years there has been a growing body of literature describing the development and evaluation of potential new promising PET tracers for dementia. This review article provides a comprehensive overview of novel dementia PET probes under development, classified by their target, and pinpoints their preclinical evaluation pathway, typically involving in silico, in vitro and ex/in vivo evaluation. Specific target-associated challenges and pitfalls, requiring extensive and well-designed preclinical experimental evaluation assays to enable successful clinical translation and avoid shortcomings observed for previously developed 'well-established' dementia PET tracers are highlighted in this review.
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Affiliation(s)
- Romy Cools
- Laboratory for Radiopharmaceutical Research, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Kobe Kerkhofs
- Laboratory for Radiopharmaceutical Research, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium; NURA, Belgian Nuclear Research Centre (SCK CEN), Mol, Belgium
| | - Renan C F Leitao
- Laboratory for Radiopharmaceutical Research, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Guy Bormans
- Laboratory for Radiopharmaceutical Research, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.
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27
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Alzain AA, Mukhtar RM, Abdelmoniem N, Shoaib TH, Osman W, Alsulaimany M, Aljohani AKB, Almadani SA, Alsaadi BH, Althubyani MM, Mohamed SGA, Mohamed GA, Ibrahim SRM. Modulation of NRF2/KEAP1-Mediated Oxidative Stress for Cancer Treatment by Natural Products Using Pharmacophore-Based Screening, Molecular Docking, and Molecular Dynamics Studies. Molecules 2023; 28:6003. [PMID: 37630254 PMCID: PMC10459127 DOI: 10.3390/molecules28166003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 07/31/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023] Open
Abstract
Oxidative stress plays a significant role in the development of cancer. Inhibiting the protein-protein interaction (PPI) between Keap1 and Nrf2 offers a promising strategy to activate the Nrf2 antioxidant pathway, which is normally suppressed by the binding of Keap1 to Nrf2. This study aimed to identify natural compounds capable of targeting the kelch domain of KEAP1 using structure-based drug design methods. A pharmacophore model was constructed based on the KEAP1-inhibitor complex, leading to the selection of 6178 compounds that matched the model. Subsequently, docking and MM/GBSA analyses were conducted, resulting in the identification of 10 compounds with superior binding energies compared to the reference compound. From these, three compounds (ZINC000002123788, ZINC000002111341, and ZINC000002125904) were chosen for further investigation. Ligand-residue interaction analysis revealed specific interactions between these compounds and key residues, indicating their stability within the binding site. ADMET analysis confirmed that the selected compounds possessed desirable drug-like properties. Furthermore, molecular dynamics simulations were performed, demonstrating the stability of the ligand-protein complexes over a 100 ns duration. These findings underscore the potential of the selected natural compounds as agents targeting KEAP1 and provide valuable insights for future experimental studies.
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Affiliation(s)
- Abdulrahim A. Alzain
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani 21111, Sudan (N.A.); (T.H.S.)
| | - Rua M. Mukhtar
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani 21111, Sudan (N.A.); (T.H.S.)
| | - Nihal Abdelmoniem
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani 21111, Sudan (N.A.); (T.H.S.)
| | - Tagyedeen H. Shoaib
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani 21111, Sudan (N.A.); (T.H.S.)
| | - Wadah Osman
- Department of Pharmacognosy, Faculty of Pharmacy, Prince Sattam bin Abdulaziz University, Alkharj 11942, Saudi Arabia;
- Department of Pharmacognosy, Faculty of Pharmacy, University of Khartoum, Khartoum 11115, Sudan
| | - Marwa Alsulaimany
- Department of Pharmacognosy & Pharmaceutical Chemistry, College of Pharmacy, Taibah University, Medina 42353, Saudi Arabia; (M.A.); (A.K.B.A.)
| | - Ahmed K. B. Aljohani
- Department of Pharmacognosy & Pharmaceutical Chemistry, College of Pharmacy, Taibah University, Medina 42353, Saudi Arabia; (M.A.); (A.K.B.A.)
| | - Sara A. Almadani
- Department of Pharmacology and Toxicology, College of Pharmacy, Taibah University, Medina 42353, Saudi Arabia;
| | - Baiaan H. Alsaadi
- Department of Clinical Services, Pharmaceutical Care Services, King Salman Medical City, MOH, Al-Madinah Al-Munawwarah 11176, Saudi Arabia; (B.H.A.); (M.M.A.)
| | - Maryam M. Althubyani
- Department of Clinical Services, Pharmaceutical Care Services, King Salman Medical City, MOH, Al-Madinah Al-Munawwarah 11176, Saudi Arabia; (B.H.A.); (M.M.A.)
| | - Shaimaa G. A. Mohamed
- Faculty of Dentistry, British University, El Sherouk City, Suez Desert Road, Cairo 11837, Egypt;
| | - Gamal A. Mohamed
- Department of Natural Products and Alternative Medicine, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia;
| | - Sabrin R. M. Ibrahim
- Department of Chemistry, Preparatory Year Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia;
- Department of Pharmacognosy, Faculty of Pharmacy, Assiut University, Assiut 71526, Egypt
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28
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Scaini MC, Piccin L, Bassani D, Scapinello A, Pellegrini S, Poggiana C, Catoni C, Tonello D, Pigozzo J, Dall’Olmo L, Rosato A, Moro S, Chiarion-Sileni V, Menin C. Molecular Modeling Unveils the Effective Interaction of B-RAF Inhibitors with Rare B-RAF Insertion Variants. Int J Mol Sci 2023; 24:12285. [PMID: 37569660 PMCID: PMC10418914 DOI: 10.3390/ijms241512285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 07/27/2023] [Accepted: 07/29/2023] [Indexed: 08/13/2023] Open
Abstract
The Food and Drug Administration (FDA) has approved MAPK inhibitors as a treatment for melanoma patients carrying a mutation in codon V600 of the BRAF gene exclusively. However, BRAF mutations outside the V600 codon may occur in a small percentage of melanomas. Although these rare variants may cause B-RAF activation, their predictive response to B-RAF inhibitor treatments is still poorly understood. We exploited an integrated approach for mutation detection, tumor evolution tracking, and assessment of response to treatment in a metastatic melanoma patient carrying the rare p.T599dup B-RAF mutation. He was addressed to Dabrafenib/Trametinib targeted therapy, showing an initial dramatic response. In parallel, in-silico ligand-based homology modeling was set up and performed on this and an additional B-RAF rare variant (p.A598_T599insV) to unveil and justify the success of the B-RAF inhibitory activity of Dabrafenib, showing that it could adeptly bind both these variants in a similar manner to how it binds and inhibits the V600E mutant. These findings open up the possibility of broadening the spectrum of BRAF inhibitor-sensitive mutations beyond mutations at codon V600, suggesting that B-RAF V600 WT melanomas should undergo more specific investigations before ruling out the possibility of targeted therapy.
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Affiliation(s)
- Maria Chiara Scaini
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (M.C.S.); (S.P.); (C.P.); (C.C.); (D.T.); (A.R.); (C.M.)
| | - Luisa Piccin
- Melanoma Unit, Oncology 2 Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (L.P.); (J.P.); (V.C.-S.)
| | - Davide Bassani
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, 35131 Padua, Italy;
| | - Antonio Scapinello
- Anatomy and Pathological Histology Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy;
| | - Stefania Pellegrini
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (M.C.S.); (S.P.); (C.P.); (C.C.); (D.T.); (A.R.); (C.M.)
| | - Cristina Poggiana
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (M.C.S.); (S.P.); (C.P.); (C.C.); (D.T.); (A.R.); (C.M.)
| | - Cristina Catoni
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (M.C.S.); (S.P.); (C.P.); (C.C.); (D.T.); (A.R.); (C.M.)
| | - Debora Tonello
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (M.C.S.); (S.P.); (C.P.); (C.C.); (D.T.); (A.R.); (C.M.)
| | - Jacopo Pigozzo
- Melanoma Unit, Oncology 2 Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (L.P.); (J.P.); (V.C.-S.)
| | - Luigi Dall’Olmo
- Soft-Tissue, Peritoneum and Melanoma Surgical Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy
- Department of Surgery, Oncology and Gastroenterology (DISCOG), University of Padua, 35128 Padua, Italy
| | - Antonio Rosato
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (M.C.S.); (S.P.); (C.P.); (C.C.); (D.T.); (A.R.); (C.M.)
- Department of Surgery, Oncology and Gastroenterology (DISCOG), University of Padua, 35128 Padua, Italy
| | - Stefano Moro
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, 35131 Padua, Italy;
| | - Vanna Chiarion-Sileni
- Melanoma Unit, Oncology 2 Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (L.P.); (J.P.); (V.C.-S.)
| | - Chiara Menin
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy; (M.C.S.); (S.P.); (C.P.); (C.C.); (D.T.); (A.R.); (C.M.)
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Martin MP, Endicott JA, Noble MEM, Tatum NJ. Crystallographic fragment screening in academic cancer drug discovery. Methods Enzymol 2023; 690:211-234. [PMID: 37858530 DOI: 10.1016/bs.mie.2023.06.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Fragment-based drug discovery (FBDD) has brought several drugs to the clinic, notably to target proteins once considered to be challenging, or even undruggable. Screening in FBDD relies upon observing and/or measuring weak (millimolar-scale) binding events using biophysical techniques or crystallographic fragment screening. This latter structural approach provides no information about binding affinity but can reveal binding mode and atomic detail on protein-fragment interactions to accelerate hit-to-lead development. In recent years, high-throughput platforms have been developed at synchrotron facilities to screen thousands of fragment-soaked crystals. However, using accessible manual techniques it is possible to run informative, smaller-scale screens within an academic lab setting. This chapter describes general protocols for home laboratory-scale fragment screening, from fragment soaking through to structure solution and, where appropriate, signposts to background, protocols or alternatives elsewhere.
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Affiliation(s)
- Mathew P Martin
- Cancer Research Horizons Therapeutic Innovation, Newcastle Drug Discovery Unit, Newcastle University Centre for Cancer, Translation and Clinical Research Institute, Newcastle University, Paul O'Gorman Building, Framlington Place, Newcastle upon Tyne, United Kingdom
| | - Jane A Endicott
- Cancer Research Horizons Therapeutic Innovation, Newcastle Drug Discovery Unit, Newcastle University Centre for Cancer, Translation and Clinical Research Institute, Newcastle University, Paul O'Gorman Building, Framlington Place, Newcastle upon Tyne, United Kingdom
| | - Martin E M Noble
- Cancer Research Horizons Therapeutic Innovation, Newcastle Drug Discovery Unit, Newcastle University Centre for Cancer, Translation and Clinical Research Institute, Newcastle University, Paul O'Gorman Building, Framlington Place, Newcastle upon Tyne, United Kingdom
| | - Natalie J Tatum
- Cancer Research Horizons Therapeutic Innovation, Newcastle Drug Discovery Unit, Newcastle University Centre for Cancer, Translation and Clinical Research Institute, Newcastle University, Paul O'Gorman Building, Framlington Place, Newcastle upon Tyne, United Kingdom.
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30
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A New Anticancer Semisynthetic Theobromine Derivative Targeting EGFR Protein: CADDD Study. LIFE (BASEL, SWITZERLAND) 2023; 13:life13010191. [PMID: 36676140 PMCID: PMC9867533 DOI: 10.3390/life13010191] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/25/2022] [Accepted: 01/06/2023] [Indexed: 01/10/2023]
Abstract
A new lead compound has been designed as an antiangiogenic EGFR inhibitor that has the pharmacophoric characteristics to bind with the catalytic pocket of EGFR protein. The designed lead compound is a (para-chloro)acetamide derivative of the alkaloid, theobromine, (T-1-PCPA). At first, we started with deep density functional theory (DFT) calculations for T-1-PCPA to confirm and optimize its 3D structure. Additionally, the DFT studies identified the electrostatic potential, global reactive indices and total density of states expecting a high level of reactivity for T-1-PCPA. Secondly, the affinity of T-1-PCPA to bind and inhibit the EGFR protein was studied and confirmed through detailed structure-based computational studies including the molecular docking against EGFRWT and EGFRT790M, Molecular dynamics (MD) over 100 ns, MM-GPSA and PLIP experiments. Before the preparation, the computational ADME and toxicity profiles of T-1-PCPA have been investigated and its safety and the general drug-likeness predicted. Accordingly, T-1-PCPA was semi-synthesized to scrutinize the proposed design and the obtained in silico results. Interestingly, T-1-PCPA inhibited in vitro EGFRWT with an IC50 value of 25.35 nM, comparing that of erlotinib (5.90 nM). Additionally, T-1-PCPA inhibited the growth of A549 and HCT-116 malignant cell lines with IC50 values of 31.74 and 20.40 µM, respectively, comparing erlotinib that expressed IC50 values of 6.73 and 16.35 µM, respectively.
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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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