Design and Diversity Analysis of Chemical Libraries in Drug Discovery

Abstract

Chemical libraries and compound data sets are among the main inputs to start the drug discovery process at universities, research institutes, and the pharmaceutical industry. The approach used in the design of compound libraries, the chemical information they possess, and the representation of structures, play a fundamental role in the development of studies: chemoinformatics, food informatics, in silico pharmacokinetics, computational toxicology, bioinformatics, and molecular modeling to generate computational hits that will continue the optimization process of drug candidates. The prospects for growth in drug discovery and development processes in chemical, biotechnological, and pharmaceutical companies began a few years ago by integrating computational tools with artificial intelligence methodologies. It is anticipated that it will increase the number of drugs approved by regulatory agencies shortly.

Exploiting Vector Pattern Diversity of Molecular Scaffolds for Cheminformatics Tasks in Drug Discovery

“…As evidenced in Figure 7a, the most recurrent EVP in this dataset is [2,5,7] followed by [2,5] and [2,3,5]. In turn, the dEVP with the highest probability, namely the number of simultaneous substitutions, is tri-substitution, followed by disubstitution (Figure 7b).…”

“…We then computed the EVP descriptors for the dataset, with the results presented in Figure 6. Figure 6 exemplifies the probability distributions of the most common EVPs, with [2], [2,6], and [2,3,6] being the most exploited patterns within the indole dataset for mono-, di-, and tri-substitutions, respectively. When it comes to the diverse sampling of compounds for testing, it might be possible to include an example of each EVP for the scaffold of interest, in a simple setting.…”

“…Of note, we consider compounds as active when the pChEMBL value is greater than 7, corresponding to a Ki of 100nM. EVP [2,3,5,7] has the highest observed median pChEMBL value (around 7.15) and the most recurrent EVP [2,5,7] has a median pChEMBL value of 6.5. Figure 7d, confirms that compounds with 4 substitutions, such as [2,3,5,7], have the highest median pChEMBL value.…”

“…The concept of chemical diversity has long been at the forefront of the drug discovery process. 1,2 From screening to patent busting, access to diverse, original chemical matter is of paramount importance. Chemical diversity is however often challenging to describe objectively.…”

Exploiting Vector Pattern Diversity of Molecular Scaffolds for Cheminformatics Tasks in Drug Discovery

“…The concept of chemical diversity has long been at the forefront of the drug discovery process. , From screening to patent busting, access to diverse original chemical matter is of paramount importance. Chemical diversity is however often challenging to describe objectively .…”