The Renin (REN, HNFJ2) is an aspartic protease (also known as an angiotensinogenase). It participates in arterial vasoconstriction and the body's renin–angiotensin–aldosterone system (RAAS) that mediates the volume of extracellular fluid (blood plasma, lymph and interstitial fluid). Thus, it regulates the body's mean arterial blood pressure. An over-active RAAS leads to vasoconstriction and retention of sodium and water. These effects cause hypertension. Therefore, renin inhibitors can be used for the treatment of hypertension.

OTAVAchemicals offers Renin Targeted Library. It contains 933 compounds with predicted inhibiting activity against REN. The library has been studiously designed with application of machine learning (Bayesian statistics, artificial neural networks and k-nearest neighbors algorithm (k-NN)) and molecular docking. The combination of such ligand-based and receptor-based virtual screening methods should allow increasing the number of active compounds identified during screening.

For the library design known REN inhibitors were clustered into eight clusters. Then compounds of each cluster were classified as active or inactive using k-NN based on molecular fingerprints to achieve more homogeneous sets and randomly divided into training and test sets. The training sets were used for development and parameterization of artificial neural networks and Bayesian models. Both methods were based on different molecular descriptors - LogP, molecular weight, number of rotatable bonds, number of rings, number of hydrogen donors and acceptors, PSA, fingerprints, topological descriptors and other. Also the training sets were used as a template for compounds selection with k-NN algorithm based on ECFP4, FCFP4, ECFP6, FCFP6 fingerprints. The test sets were used for validation of Bayesian models and neural networks. Top-scored compounds obtained by application of machine learning methods were crossed with top-scored compounds obtained with molecular docking (PDB ID: 2V0Z). Final selection of compounds has been made with inspection of intermolecular hydrogen bonds and hydrophobic contacts with key amino acid residues of renin active site.

The designed Renin Targeted Library comprises only drug-like compounds (PAINS compounds are filtered off). It provides a perfect basis for drug discovery projects related with hypertension.

The summary of the Renin Targeted Library characteristics:

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