Machine learning based predictions of protein⁻protein interactions (PPIs) could provide valuable insights into protein functions, disease occurrence, and therapy design on a large scale. The intensive feature engineering in most of these methods make...
Estrogen receptor α (ERα) plays a significant role in occurrence of breast cancer and may cause various adverse side-effects when ERα is an off-target protein. A theoretical model was derived to predict the binding affinity of ERα using the pharmacop...
The Journal of steroid biochemistry and molecular biology
Jul 22, 2018
The vitamin D-modulated transcriptome of highly responsive human cells, such as THP-1 monocytes, comprises more than 500 genes, half of which are primary targets. Recently, we proposed a chromatin model of vitamin D signaling demonstrating that nearl...
Journal of computer-aided molecular design
Jul 10, 2018
We assess the ability of our convolutional neural network (CNN)-based scoring functions to perform several common tasks in the domain of drug discovery. These include correctly identifying ligand poses near and far from the true binding mode when giv...
BACKGROUND: RNA regulation is significantly dependent on its binding protein partner, known as the RNA-binding proteins (RBPs). Unfortunately, the binding preferences for most RBPs are still not well characterized. Interdependencies between sequence ...
RNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these meth...
Engineering of GPCR constructs with improved thermostability is a key for successful structural and biochemical studies of this transmembrane protein family, targeted by 40% of all therapeutic drugs. Here we introduce a comprehensive computational ap...
Journal of molecular graphics & modelling
Jun 18, 2018
Protein-ligand scoring is an important step in a structure-based drug design pipeline. Selecting a correct binding pose and predicting the binding affinity of a protein-ligand complex enables effective virtual screening. Machine learning techniques c...
The possibility of using the atomic coordinates of protein-ligand complexes to assess binding affinity has a beneficial impact in the early stages of drug development and design. From the computational view, the creation of reliable scoring functions...
The journal of physical chemistry letters
Apr 17, 2018
Predicting the activity of chemicals for a given odorant receptor is a longstanding challenge. Here the activity of 258 chemicals on the human G-protein-coupled odorant receptor (OR)51E1, also known as prostate-specific G-protein-coupled receptor 2 (...