Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review

VT Sabe, T Ntombela, LA Jhamba… - European Journal of …, 2021 - Elsevier
Computer-aided drug design (CADD) is one of the pivotal approaches to contemporary pre-
clinical drug discovery, and various computational techniques and software programs are …

Drug design by pharmacophore and virtual screening approach

D Giordano, C Biancaniello, MA Argenio, A Facchiano - Pharmaceuticals, 2022 - mdpi.com
Computer-aided drug discovery techniques reduce the time and the costs needed to
develop novel drugs. Their relevance becomes more and more evident with the needs due …

Machine learning methods in drug discovery

L Patel, T Shukla, X Huang, DW Ussery, S Wang - Molecules, 2020 - mdpi.com
The advancements of information technology and related processing techniques have
created a fertile base for progress in many scientific fields and industries. In the fields of drug …

Bioinformatics approaches to discovering food-derived bioactive peptides: Reviews and perspectives

Z Du, J Comer, Y Li - TrAC Trends in Analytical Chemistry, 2023 - Elsevier
Food-derived bioactive peptides (FBPs) are gaining interest due to their great potential in
agricultural byproduct valorization and high-activity peptide screening. The introduction of …

Protein–ligand docking in the machine-learning era

C Yang, EA Chen, Y Zhang - Molecules, 2022 - mdpi.com
Molecular docking plays a significant role in early-stage drug discovery, from structure-
based virtual screening (VS) to hit-to-lead optimization, and its capability and predictive …

HyperAttentionDTI: improving drug–protein interaction prediction by sequence-based deep learning with attention mechanism

Q Zhao, H Zhao, K Zheng, J Wang - Bioinformatics, 2022 - academic.oup.com
Motivation Identifying drug–target interactions (DTIs) is a crucial step in drug repurposing
and drug discovery. Accurately identifying DTIs in silico can significantly shorten …

Drugclip: Contrasive protein-molecule representation learning for virtual screening

B Gao, B Qiang, H Tan, Y Jia, M Ren… - Advances in …, 2024 - proceedings.neurips.cc
Virtual screening, which identifies potential drugs from vast compound databases to bind
with a particular protein pocket, is a critical step in AI-assisted drug discovery. Traditional …

Molecular simulation for food protein–ligand interactions: A comprehensive review on principles, current applications, and emerging trends

Z Jin, Z Wei - Comprehensive Reviews in Food Science and …, 2024 - Wiley Online Library
In recent years, investigations on molecular interaction mechanisms between food proteins
and ligands have attracted much interest. The interaction mechanisms can supply much …

Application of variational graph encoders as an effective generalist algorithm in computer-aided drug design

HYI Lam, R Pincket, H Han, XE Ong, Z Wang… - Nature Machine …, 2023 - nature.com
Although there has been considerable progress in molecular property prediction in
computer-aided drug design, there is a critical need to have fast and accurate models. Many …

Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery

W Wilman, S Wróbel, W Bielska… - Briefings in …, 2022 - academic.oup.com
Antibodies are versatile molecular binders with an established and growing role as
therapeutics. Computational approaches to developing and designing these molecules are …