Metabasis's new modeling technology for drug discovery and optimisation

Metabasis Therapeutics, from San Diego, US, has seen the publication of an article entitled: 'Development of a quantum mechanics-based free-energy perturbation Method: Use in the Calculation of Relative Solvation Free Energies' in the Journal of the American Chemical Society¹ (JACS). The publication by M. Rami Reddy et al describes Metabasis' work on a new molecular modeling technology.

Efforts by pharmaceutical companies to design drugs using a combination of structural information on drug targets and computation methods has been hampered by limitations in calculation accuracy, throughput or both. As described in the article published in the JACS, Metabasis, in collaboration with U. Chandra Singh, has developed a method that has the potential to address both limitations. The method, which entails for the first time the integration of quantum mechanics (QM) with a method known as free energy perturbation, was used to predict the relative differences in the solvation free energies of small molecules.

'Metabasis is developing proprietary methods that make use of the findings reported in the publication. If successful, the company expects to use the technology on its discovery programs in an effort to more efficiently find novel leads and convert these leads to drug candidates,' commented Dr Paul Laikind, chairman, president and ceo of Metabasis.

Metabasis executive vice president of r&d, and an author of the publication, Dr. Mark Erion, stated: 'Success in these calculations suggests that the method may soon be useful for predicting relative binding affinities for small molecules against a drug target as well as certain drug properties such as the partition coefficient, solubility and ionisation potential. Moreover, the use of QM may enable future automation of calculations using free energy perturbation. Therefore, it may provide an accurate method for computationally screening compound libraries for new leads and for more efficient lead optimisation.'

Metabasis made extensive use of computer assisted drug design strategies during the development of its proprietary NuMimetic technology, which was subsequently used to discover CS-917. CS-917 is a first-in-class gluconeogenesis inhibitor for the treatment of type 2 diabetes. In a recent Phase II trial, CS-917 appeared to significantly lower blood glucose levels in patients over a 28-day period. The NuMimetic technology was also used to discover MB07803, a 2nd generation gluconeogenesis inhibitor for type 2 diabetes that is expected to enter the clinic next year, as well as a lead compound for an advanced research program focused on the discovery of another first-in-class drug that may be useful for treating hyperlipidemia and diabetes.