[HTML][HTML] Drug discovery for enzymes
AC Rufer - Drug discovery today, 2021 - Elsevier
Highlights•Enzymes are highly druggable due to the presence of discrete substrate
pockets.•Enzymology contributes throughout the value chain of lead discovery.•Quantitative …
pockets.•Enzymology contributes throughout the value chain of lead discovery.•Quantitative …
[HTML][HTML] Matched molecular pair analysis in short: algorithms, applications and limitations
C Tyrchan, E Evertsson - Computational and structural biotechnology …, 2017 - Elsevier
Molecular matched pair (MMP) analysis has been used for more than 40 years within
molecular design and is still an important tool to analyse potency data and other compound …
molecular design and is still an important tool to analyse potency data and other compound …
Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data
Background In recent years, research in artificial neural networks has resurged, now under
the deep-learning umbrella, and grown extremely popular. Recently reported success of DL …
the deep-learning umbrella, and grown extremely popular. Recently reported success of DL …
Computational modeling of β-secretase 1 (BACE-1) inhibitors using ligand based approaches
G Subramanian, B Ramsundar, V Pande… - Journal of chemical …, 2016 - ACS Publications
The binding affinities (IC50) reported for diverse structural and chemical classes of human β-
secretase 1 (BACE-1) inhibitors in literature were modeled using multiple in silico ligand …
secretase 1 (BACE-1) inhibitors in literature were modeled using multiple in silico ligand …
Rapid, accurate, precise, and reliable relative free energy prediction using ensemble based thermodynamic integration
The accurate prediction of the binding affinities of ligands to proteins is a major goal in drug
discovery and personalized medicine. The time taken to make such predictions is of similar …
discovery and personalized medicine. The time taken to make such predictions is of similar …
Emerging electrochemical, optical, electrochemiluminescence and photoelectrochemical bio (sensing) approaches for detection of vitamins in the food …
Vitamins are types of natural compounds that help cell growth and body metabolism. Living
organisms, especially humans, need a small number of vitamins for their survival and health …
organisms, especially humans, need a small number of vitamins for their survival and health …
TIES 20: Relative binding free energy with a flexible superimposition algorithm and partial ring morphing
The TIES (Thermodynamic Integration with Enhanced Sampling) protocol is a formally exact
alchemical approach in computational chemistry to the calculation of relative binding free …
alchemical approach in computational chemistry to the calculation of relative binding free …
QPHAR: Quantitative pharmacophore activity relationship: Method and validation
QSAR methods are widely applied in the drug discovery process, both in the hit‐to‐lead and
lead optimization phase, as well as in the drug-approval process. Most QSAR algorithms are …
lead optimization phase, as well as in the drug-approval process. Most QSAR algorithms are …
Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty
Measurements of protein–ligand interactions have reproducibility limits due to experimental
errors. Any model based on such assays will consequentially have such unavoidable errors …
errors. Any model based on such assays will consequentially have such unavoidable errors …
[HTML][HTML] Best practices for machine learning in antibody discovery and development
In the past 40 years, therapeutic antibody discovery and development have advanced
considerably, with machine learning (ML) offering a promising way to speed up the process …
considerably, with machine learning (ML) offering a promising way to speed up the process …