Challenges and frontiers of computational modelling of biomolecular recognition. (19th August 2022)

• Record Type: Journal Article
• Authors: Wang, Jinan; Bhattarai, Apurba; Do, Hung N.; Miao, Yinglong
• Is Part Of: QRB discovery. Volume 3(2022)
• Publication Date: 2022-08-19
• Subjects: biomolecular recognition -- enhanced sampling -- kinetics -- machine learning -- molecular dynamics -- thermodynamics; Biophysics -- Periodicals; 571.4
• DOI: 10.1017/qrd.2022.11
• Languages: English
• ISSNs: 2633-2892

Abstract

Abstract: Abstract: Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have presented challenges for computational modelling. Here, we review the challenges and computational approaches developed to characterise biomolecular binding, including molecular docking, molecular dynamics simulations (especially enhanced sampling) and machine learning. Further improvements are still needed in order to accurately and efficiently characterise binding structures, mechanisms, thermodynamics and kinetics of biomolecules in the future.