Central nervous system drugs
Nowadays, the rational design of such compounds is heavily reliant on numerous mathematical algorithms based on the analysis of descriptors of known CNS drugs. Some of these descriptors are simple to compute using merely a compound's structure: molecular weight, number of hydrogen bond donors, and acceptors. The other may be difficult to obtain, so specialized algorithms are used to estimate them: cLogP and cLogD are two well-known examples.
Predicting CNS-permeability is an important aspect of an efficient drug discovery program; fortunately, a variety of approaches to this task have been published in recent years. MPO  and BBB-score , the two methods addressed in these papers, are of particular interest due to their computational simplicity and reasonable accuracy.
• The “BBB Score” is a weighted function of several stepwise and polynomial functions of molecular descriptors such as number of aromatic rings, number of heavy atoms, topological surfaces area, and pKa. In addition to "prime", the following composite descriptor is used: MWHBN (comprising molecular weight, hydrogen bond donor, and hydrogen bond acceptors).
• MPO (multiparameter optimization) scoring functions take a more straightforward approach, applying statically determined boundaries to the main molecular descriptors.
Combining many properties into a single value helps to avoid hard cut-offs and enhances compound quality overall. ChemDiv is pleased to offer its own custom libraries of BBB permeable compounds selected by using the above-mentioned methods:
• CNS MPO Library (https://www.chemdiv.com/catalog/focused-and-targeted-libraries/cns-mpo-library/)
• CNS BBB Library (https://www.chemdiv.com/catalog/focused-and-targeted-libraries/cns-bbb-library/)
1. Gunaydin H. Probabilistic Approach to Generating MPOs and Its Application as a Scoring Function for CNS Drugs. ACS Med Chem Lett. 2015 Dec 2;7(1):89-93. doi: 10.1021/acsmedchemlett.5b00390.
2. Gupta M, Lee HJ, Barden CJ, Weaver DF. The Blood-Brain Barrier (BBB) Score. J Med Chem. 2019 Nov 14;62(21):9824-9836. doi: 10.1021/acs.jmedchem.9b01220.