Investigation on the Mechanisms of Synchronous Interaction of K3Cit with Melamine and Uric Acid That Avoids the Formation of Large Clusters

Stabilization of uric acid mixed crystals by melamine

Melamine stabilizes heterogeneous nucleation of calcium crystals by increasing the retention time and decreasing the rate of dissolution. Stabilization of such mixed crystals limit the efficacy of non-invasive treatment options for kidney stones. Crystalline forms of uric acid (UA) are also involved in urolithiasis or UA kidney stones; however, its interactions with contaminating melamine and the resulting effects on the retention of kidney stones remain unknown. Since melamine augments calcium crystal formation, it provides an avenue for us to understand the stability of UA-calcium phosphate (CaP) crystals. We show here that melamine facilitates UA+CaP crystal formation, resulting in greater aggregates. Moreover, melamine induced mixed crystal retention through a time-dependent manner in presence and/or absence of hydroxycitrate (crystal inhibitor), indicating its abridged effectiveness as conventional remedy. CaP was also shown to modify optical properties of UA+CaP mixed crystals. Differential staining of individual crystals revealed enhanced co-aggregation of UA and CaP. The dissolution rate of UA in presence of melamine was faster than its heterogeneous crystallization form with CaP, although the size was comparatively much smaller, suggesting disparity in regulation between UA and CaP crystallization. While melamine stabilized UA, CaP and mixed crystals in relatively physiological conditions (artificial urine), the retentions of those crystals were further augmented by melamine, even in presence of hydroxycitrate, thus reducing treatment efficacy.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.