Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …
companies and chemical scientists. However, low efficacy, off-target delivery, time …
Machine learning for synergistic network pharmacology: a comprehensive overview
Network pharmacology is an emerging area of systematic drug research that attempts to
understand drug actions and interactions with multiple targets. Network pharmacology has …
understand drug actions and interactions with multiple targets. Network pharmacology has …
[HTML][HTML] Discovery and resupply of pharmacologically active plant-derived natural products: A review
AG Atanasov, B Waltenberger… - Biotechnology …, 2015 - Elsevier
Medicinal plants have historically proven their value as a source of molecules with
therapeutic potential, and nowadays still represent an important pool for the identification of …
therapeutic potential, and nowadays still represent an important pool for the identification of …
Counting on natural products for drug design
Natural products and their molecular frameworks have a long tradition as valuable starting
points for medicinal chemistry and drug discovery. Recently, there has been a revitalization …
points for medicinal chemistry and drug discovery. Recently, there has been a revitalization …
Using PyMOL as a platform for computational drug design
PyMOL, a cross‐platform molecular graphics tool, has been widely used for three‐
dimensional (3D) visualization of proteins, nucleic acids, small molecules, electron …
dimensional (3D) visualization of proteins, nucleic acids, small molecules, electron …
Protein–ligand docking in the machine-learning era
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 …
based virtual screening (VS) to hit-to-lead optimization, and its capability and predictive …
Advancements in docking and molecular dynamics simulations towards ligand-receptor interactions and structure-function relationships
Protein-ligand interaction is an imperative subject in structure-based drug design and
protein function prediction process. Molecular docking is a computational method which …
protein function prediction process. Molecular docking is a computational method which …
Virtual screening: an endless staircase?
G Schneider - Nature Reviews Drug Discovery, 2010 - nature.com
Computational chemistry—in particular, virtual screening—can provide valuable
contributions in hit-and lead-compound discovery. Numerous software tools have been …
contributions in hit-and lead-compound discovery. Numerous software tools have been …
On various metrics used for validation of predictive QSAR models with applications in virtual screening and focused library design
K Roy, I Mitra - Combinatorial chemistry & high throughput …, 2011 - ingentaconnect.com
Quantitative structure-activity relationships (QSARs) have important applications in drug
discovery research, environmental fate modeling, property prediction, etc. Validation has …
discovery research, environmental fate modeling, property prediction, etc. Validation has …
PASS-assisted exploration of new therapeutic potential of natural products
The use of drug substances derived from plants, fungi, bacteria, and marine organisms are
“Mother Nature Gift” for diseases of mankind. Many of these are discovered serendipitously …
“Mother Nature Gift” for diseases of mankind. Many of these are discovered serendipitously …