The process of structure-based drug design.

By Amy C. Anderson. 2003

841 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Sheng Wang
2. Jianzhu Ma
3. Shitong Luo
4. Jonathan Romero
5. Alán Aspuru-Guzik
6. Xin Gao
7. Jian Peng
8. Sun Choi

In Molecular Biology

1. Sheng Wang
2. Jinbo Xu
3. Jianzhu Ma
4. Xin Gao
5. Jian Peng
6. Jonathan Romero
7. Alán Aspuru-Guzik
8. Sun Choi

Citations in the corpus

• TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction (2022, background): “Due to its good interpretability and usability, docking has been integrated in drug development process for a long time and a number of successful cases have been reported [11].”
• Potential of quantum computing for drug discovery (2018, background): “Extensive sampling of conformations is often required in structured-based CADD approaches to account for the mobility of protein and ligands in biological conditions (aqueous solutions at room temperature) [17].”
• Retrieval-Augmented Generation for AI-Generated Content: A Survey (2024, neutral): “Based on a constructed RAG system, enhancements are helpful to improve the effectiveness of certain components or the entire pipeline.”
• Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases (2018, neutral): “Structure-based VS methods are out of the scope of this study, and information about this field can be obtained from the literature [31, 32, 52, 56, 57].”
• A Structure-Based Drug Discovery Paradigm (2019, methodology): “Briefly, automation of all the steps in an SBDD process has shortened the SBDD timeline [8].”
• How accurately can one predict drug binding modes using AlphaFold models? (2023, background): “The vast majority of drug targets are proteins, and structures play a critical role in rational drug design ( Anderson, 2003 ; Kolb et al., 2009 ).”
• Role of computer-aided drug design in modern drug discovery (2015, background): “…from structural and computational biology aided in the generation of protein structures with the use of X-ray crystallography, nuclear magnetic resonance (NMR), cryo-electron microscopy (EM), homology modeling, and molecular dynamic (MD) simulations (Anderson 2003; Kalyaanamoorthy and Chen 2011).”
• 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (2023, background): “Rational drug design against a known protein binding pocket is an efficient and economical approach for finding lead molecules (Anderson, 2003; Batool et al., 2019) and has attracted growing attention from the research community.”
• In silico methods and tools for drug discovery (2021, methodology): “SBDD methods have also been successfully employed to predict binding sites in AmpC β -lactamase, which was important for designing small molecules [11].”
• PointSite: a point cloud segmentation tool for identification of protein ligand binding atoms (2019, background): “The accurate identification of LBS on protein surfaces is critical for understanding the functions of the protein [19], and in turn an indispensable step for rational structure-based drug design (SBDD) [2].”
• A 3D Generative Model for Structure-Based Drug Design (2022, background): “Designing molecules that bind to a specific protein binding site, also known as structure-based drug design, is one of the most challenging tasks in drug discovery [2].”