Structural bioinformatics for rational drug design
A State of the Art lecture titled “structural bioinformatics technologies for rational drug design: from in silico to in vivo” was presented at the International Society on Thrombosis and Haemostasis (ISTH) Congress in 2024. Drug discovery remains a resource-intensive and complex endeavor, which usu...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Research and Practice in Thrombosis and Haemostasis |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2475037925000159 |
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| author | Soroush Mozaffari Agnethe Moen Che Yee Ng Gerry A.F. Nicolaes Kanin Wichapong |
| author_facet | Soroush Mozaffari Agnethe Moen Che Yee Ng Gerry A.F. Nicolaes Kanin Wichapong |
| author_sort | Soroush Mozaffari |
| collection | DOAJ |
| description | A State of the Art lecture titled “structural bioinformatics technologies for rational drug design: from in silico to in vivo” was presented at the International Society on Thrombosis and Haemostasis (ISTH) Congress in 2024. Drug discovery remains a resource-intensive and complex endeavor, which usually takes over a decade and costs billions to bring a new therapeutic agent to market. However, the landscape of drug discovery has been transformed by the recent advancements in bioinformatics and cheminformatics. Key techniques, including structure- and ligand-based virtual screening, molecular dynamics simulations, and artificial intelligence–driven models are allowing researchers to explore vast chemical spaces, investigate molecular interactions, predict binding affinity, and optimize drug candidates with unprecedented accuracy and efficiency. These computational methods complement experimental techniques by accelerating the identification of viable drug candidates and refining lead compounds. Artificial intelligence models, alongside traditional physics-based simulations, now play an important role in predicting key properties such as binding affinity and toxicity, contributing to more informed decision-making, particularly early in the drug discovery process. Despite these advancements, challenges remain in terms of accuracy, interpretability, and the needed computational power. This review explores the state of the art in computational drug discovery, examining the latest methods and technologies, their transformative impact on the drug development pipeline, and the future directions needed to overcome remaining limitations. Finally, we summarize relevant data and highlight cases where various computational approaches were successfully applied to develop novel inhibitors, as presented during the ISTH 2024 Congress. |
| format | Article |
| id | doaj-art-521ef5f3c98944cc80f11213225cd102 |
| institution | Kabale University |
| issn | 2475-0379 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Research and Practice in Thrombosis and Haemostasis |
| spelling | doaj-art-521ef5f3c98944cc80f11213225cd1022025-02-12T05:31:38ZengElsevierResearch and Practice in Thrombosis and Haemostasis2475-03792025-01-0191102691Structural bioinformatics for rational drug designSoroush Mozaffari0Agnethe Moen1Che Yee Ng2Gerry A.F. Nicolaes3Kanin Wichapong4Department of Biochemistry, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the NetherlandsDepartment of Biochemistry, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the NetherlandsHillmark B.V., Maastricht, the NetherlandsDepartment of Biochemistry, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands; Hillmark B.V., Maastricht, the NetherlandsDepartment of Biochemistry, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands; Hillmark B.V., Maastricht, the Netherlands; Correspondence Kanin Wichapong, Department of Biochemistry, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Universiteitssingel 50, Maastricht 6229 ER, the Netherlands.A State of the Art lecture titled “structural bioinformatics technologies for rational drug design: from in silico to in vivo” was presented at the International Society on Thrombosis and Haemostasis (ISTH) Congress in 2024. Drug discovery remains a resource-intensive and complex endeavor, which usually takes over a decade and costs billions to bring a new therapeutic agent to market. However, the landscape of drug discovery has been transformed by the recent advancements in bioinformatics and cheminformatics. Key techniques, including structure- and ligand-based virtual screening, molecular dynamics simulations, and artificial intelligence–driven models are allowing researchers to explore vast chemical spaces, investigate molecular interactions, predict binding affinity, and optimize drug candidates with unprecedented accuracy and efficiency. These computational methods complement experimental techniques by accelerating the identification of viable drug candidates and refining lead compounds. Artificial intelligence models, alongside traditional physics-based simulations, now play an important role in predicting key properties such as binding affinity and toxicity, contributing to more informed decision-making, particularly early in the drug discovery process. Despite these advancements, challenges remain in terms of accuracy, interpretability, and the needed computational power. This review explores the state of the art in computational drug discovery, examining the latest methods and technologies, their transformative impact on the drug development pipeline, and the future directions needed to overcome remaining limitations. Finally, we summarize relevant data and highlight cases where various computational approaches were successfully applied to develop novel inhibitors, as presented during the ISTH 2024 Congress.http://www.sciencedirect.com/science/article/pii/S2475037925000159artificial intelligencecomputer-aided molecular designdrug discoverymachine learningmolecular dockingmolecular dynamics simulation |
| spellingShingle | Soroush Mozaffari Agnethe Moen Che Yee Ng Gerry A.F. Nicolaes Kanin Wichapong Structural bioinformatics for rational drug design Research and Practice in Thrombosis and Haemostasis artificial intelligence computer-aided molecular design drug discovery machine learning molecular docking molecular dynamics simulation |
| title | Structural bioinformatics for rational drug design |
| title_full | Structural bioinformatics for rational drug design |
| title_fullStr | Structural bioinformatics for rational drug design |
| title_full_unstemmed | Structural bioinformatics for rational drug design |
| title_short | Structural bioinformatics for rational drug design |
| title_sort | structural bioinformatics for rational drug design |
| topic | artificial intelligence computer-aided molecular design drug discovery machine learning molecular docking molecular dynamics simulation |
| url | http://www.sciencedirect.com/science/article/pii/S2475037925000159 |
| work_keys_str_mv | AT soroushmozaffari structuralbioinformaticsforrationaldrugdesign AT agnethemoen structuralbioinformaticsforrationaldrugdesign AT cheyeeng structuralbioinformaticsforrationaldrugdesign AT gerryafnicolaes structuralbioinformaticsforrationaldrugdesign AT kaninwichapong structuralbioinformaticsforrationaldrugdesign |