There is a lot more to drug design than maximization of affinity and the key to successful design is actually that drugs form high quality interactions with their targets. Before the epiphany of ligand efficiency, measurement of interaction quality was a very inexact science. Ground-breaking research from the Budapest Enthalpomics Group (BEG) now puts the concept on a firm theoretical footing by unequivocally demonstrating that individual interactions can be localized on the affinity-quality axis in a unique manner that is completely independent of the standard state definition.
The essence of this novel approach is that, in addition to to its contributions to enthalpy and entropy of binding, each molecular interaction will now be awarded points for the artistic elements of the contact between ligand and target. This industry-leading application of Big Data uses the Blofeld-Auric Normalized Zeta Artificial Intelligence (BANZAI) algorithm to score aesthetic aspects of molecular interactions. This revolutionary machine learning application uses variable-depth, convolutional networks to model the covariance structure of the reduced efficiency tensor. Commenting on these seminal and disruptive findings the institute director, Prof. Kígyó Olaj, noted that "the algorithm is particularly accurate for scoring synchronization of vibrational modes and is even able to determine whether or not a hydrogen bond has made deliberate use of the bottom of the pool to assist another hydrogen bond during the binding routine".