The integration of early ADMET (absorption, distribution, metabolism, excretion and toxicity)
profiling, or simply prediction, of'lead'molecules to speed-up the'lead'selection further for …

In general perturbation methods starts with a known exact solution of a problem and add
“small” variation terms in order to approach to a solution for a related problem without known …

3D QSAR analysis for the 21 molecules of 1, 3, 4-oxadiazoles was carried out by using k-
Nearest Neighbor Molecular Field Analysis (kNN-MFA) combined with various selection …

Determining the target proteins of new anticancer compounds is a very important task in
Medicinal Chemistry. In this sense, chemists carry out preclinical assays with a high number …

In this work, we developed a general perturbation theory and machine learning method for
data mining of proteomes to discover new B-cell epitopes useful for vaccine design. The …

Many drugs with very different affinity to a large number of receptors are described. Thus, in
this work, we selected drug− target pairs (DTPs/nDTPs) of drugs with high affinity/nonaffinity …

Predicting drug–protein interactions (DPIs) for target proteins involved in dopamine
pathways is a very important goal in medicinal chemistry. We can tackle this problem using …

In this communication we carry out an in-depth review of a very versatile QSPR-like method.
The method name is MARCH-INSIDE (MARkov CHains Ivariants for Network Selection and …

Retroviral infections, such as HIV, are, until now, diseases with no cure. Medicine and
pharmaceutical chemistry need and consider it a huge goal to define target proteins of new …

Amino acid mutations may have diverse effects on protein structure and function. Thus
reliable information about the protein sequence variations is essential to gain insights into …