Exploiting databases and computer softwares in drug formulation: Mining the treasures

Abstract

EditorialIn one of the conversations between me and one of my senior colleagues, she told me "What lucky researchers you are!", interested to know the reason behind this statement, I asked: "Why?!", and she replied: "because in our time we didn't have all these available search engines, scientifi c databases, open resources and data manipulation tools". Later, I had a discussion with one of my colleagues -now we are coauthors -who expressed his interest in examining new aspects of formulation: "we can use computer simulations to examine many aspects of different formulations, literally virtualizing our lab" he said.We gave this conversation some thorough thinking (actually thinking outside the box!) which led us to the interesting conclusion; that though we truly have all these data resources, yet, we still perform our research studies in the most common traditional way. What have we done with all these treasures? Why can't we correlate the results obtained from different studies together? Why can't we start our studies in a different way other than the traditional try-and-error and the wet experimentation screening of the available drugs and/or carriers in different conditions and performing several modifi cations reaching our objectives whether; high loading or sustained release or targeting or whatsoever? We came up with the convincement that the advancement in technology and computer science programs should be refl ected in the drug delivery and formulation sciences in the most intelligent way. This should be attained to fulfi l the ultimate goal for all scientists to leave their experimental results all over the years as footsteps for followers to walk on.According to the questions that were aroused in our mind based on the above conversation, we started performing a new project aiming at exploiting previous results obtained from different research groups and correlating these results through computational pharmaceutics and predictive modelling aiming to reach different and novel conclusions. Indeed, the data available in literature are treasures, but they need mining and effi cient utilization to extract the desired information.The story went as follows with our fi rst research project:we fi rst concentrated on one common carrier viz. solid lipid nanoparticles (SLN) comprising one lipid: Tripalmitin ® , in particular, and adopted "data mining" of already published results to answer the following question: Could we predict the encapsulation effi ciency of a drug in SLN? Through searching the different scientifi c databases such as: Pubmed, ISI web of science and google scholar, we collected the published research results regarding the different drugs loadings. We then 'virtualized' our system by simulating the investigated carrier through molecular dynamics using the open-source software Gromacs. We prepared the chemical structures of the reported drugs and performed energy minimization to search for the lowest energy conformer. The interesting part came up when we docked the constructed drugs on the simulat...