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Pala D, Clark DE. Caught between a ROCK and a hard place: current challenges in structure-based drug design. Drug Discov Today 2024; 29:104106. [PMID: 39029868 DOI: 10.1016/j.drudis.2024.104106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 06/27/2024] [Accepted: 07/13/2024] [Indexed: 07/21/2024]
Abstract
The discipline of structure-based drug design (SBDD) is several decades old and it is tempting to think that the proliferation of experimental structures for many drug targets might make computer-aided drug design (CADD) straightforward. However, this is far from true. In this review, we illustrate some of the challenges that CADD scientists face every day in their work, even now. We use Rho-associated protein kinase (ROCK), and public domain structures and data, as an example to illustrate some of the challenges we have experienced during our project targeting this protein. We hope that this will help to prevent unrealistic expectations of what CADD can accomplish and to educate non-CADD scientists regarding the challenges still facing their CADD colleagues.
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Affiliation(s)
- Daniele Pala
- Medicinal Chemistry and Drug Design Technologies Department, Chiesi Farmaceutici S.p.A, Research Center, Largo Belloli 11/a, 43122 Parma, Italy
| | - David E Clark
- Charles River, 6-9 Spire Green Centre, Flex Meadow, Harlow CM19 5TR, UK.
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Li X, Dong Z, Li J, Dou C, Tian D, Ma Z, Liu W, Gao GF, Bi Y. Genetic characteristics of H1N1 influenza virus outbreak in China in early 2023. Virol Sin 2024; 39:520-523. [PMID: 38768710 PMCID: PMC11280127 DOI: 10.1016/j.virs.2024.05.003] [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: 10/25/2023] [Accepted: 05/09/2024] [Indexed: 05/22/2024] Open
Abstract
•H1N1 strains were collected from Hunan and Jiangsu provinces in early 2023 following the optimized COVID-19 strategy. •Phylogenic analysis revealed that the epidemic H1N1 viruses fell into different HA clades compared to vaccine strains. •Mutations on HA antigenic sites suggest antigenic drift in the epidemic H1N1 viruses versus vaccine strains. •A potential mismatch was found between recommended vaccine strains and the epidemic H1N1 viruses. •The expeditious, precise, and personalized vaccine update program for influenza virus may need to be put on the agenda.
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Affiliation(s)
- Xuanxuan Li
- College of Life Science and Technology, Xinjiang University, Urumchi, 830046, China; CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Center for Influenza Research and Early-warning (CASCIRE), CAS-TWAS Center of Excellence for Emerging Infectious Diseases (CEEID), Chinese Academy of Sciences, Beijing, 100101, China
| | - Zefeng Dong
- Suzhou Center for Disease Control and Prevention, Suzhou, 215004, China
| | - Jiaming Li
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Center for Influenza Research and Early-warning (CASCIRE), CAS-TWAS Center of Excellence for Emerging Infectious Diseases (CEEID), Chinese Academy of Sciences, Beijing, 100101, China
| | | | - Deyu Tian
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Center for Influenza Research and Early-warning (CASCIRE), CAS-TWAS Center of Excellence for Emerging Infectious Diseases (CEEID), Chinese Academy of Sciences, Beijing, 100101, China
| | - Zhenghai Ma
- College of Life Science and Technology, Xinjiang University, Urumchi, 830046, China
| | - Wenjun Liu
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Center for Influenza Research and Early-warning (CASCIRE), CAS-TWAS Center of Excellence for Emerging Infectious Diseases (CEEID), Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - George F Gao
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Center for Influenza Research and Early-warning (CASCIRE), CAS-TWAS Center of Excellence for Emerging Infectious Diseases (CEEID), Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China; D. H. Chen School of Universal Health, Zhejiang University, Hangzhou 310058, China
| | - Yuhai Bi
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Center for Influenza Research and Early-warning (CASCIRE), CAS-TWAS Center of Excellence for Emerging Infectious Diseases (CEEID), Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
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Kotev M, Diaz Gonzalez C. Molecular Dynamics and Other HPC Simulations for Drug Discovery. Methods Mol Biol 2024; 2716:265-291. [PMID: 37702944 DOI: 10.1007/978-1-0716-3449-3_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
High performance computing (HPC) is taking an increasingly important place in drug discovery. It makes possible the simulation of complex biochemical systems with high precision in a short time, thanks to the use of sophisticated algorithms. It promotes the advancement of knowledge in fields that are inaccessible or difficult to access through experimentation and it contributes to accelerating the discovery of drugs for unmet medical needs while reducing costs. Herein, we report how computational performance has evolved over the past years, and then we detail three domains where HPC is essential. Molecular dynamics (MD) is commonly used to explore the flexibility of proteins, thus generating a better understanding of different possible approaches to modulate their activity. Modeling and simulation of biopolymer complexes enables the study of protein-protein interactions (PPI) in healthy and disease states, thus helping the identification of targets of pharmacological interest. Virtual screening (VS) also benefits from HPC to predict in a short time, among millions or billions of virtual chemical compounds, the best potential ligands that will be tested in relevant assays to start a rational drug design process.
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Affiliation(s)
- Martin Kotev
- Evotec SE, Integrated Drug Discovery, Molecular Architects, Campus Curie, Toulouse, France
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Xu H. The slow but steady rise of binding free energy calculations in drug discovery. J Comput Aided Mol Des 2023; 37:67-74. [PMID: 36469232 DOI: 10.1007/s10822-022-00494-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 11/28/2022] [Indexed: 12/12/2022]
Abstract
Binding free energy calculations are increasingly used in drug discovery research to predict protein-ligand binding affinities and to prioritize candidate drug molecules accordingly. It has taken decades of collective effort to transform this academic concept into a technology adopted by the pharmaceutical and biotech industry. Having personally witnessed and taken part in this transformation, here I recount the (incomplete) list of problems that had to be solved to make this computational tool practical and suggest areas of future development.
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Affiliation(s)
- Huafeng Xu
- Roivant Discovery, 151 West 42nd Street, New York, NY, 10036, USA.
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Unravelling viral dynamics through molecular dynamics simulations - A brief overview. Biophys Chem 2022; 291:106908. [DOI: 10.1016/j.bpc.2022.106908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 09/28/2022] [Accepted: 10/05/2022] [Indexed: 11/24/2022]
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