One of the goals of contemporary AI-driven drug design is to predict physiochemical properties of molecules from their structures. Based on atomic trajectories obtained via Molecular Dynamics simulations, QCM (Quantitative Complexity Management) technology has been utilized to measure and compare the complexity of the molecules of two commercially available and widely used anti-coagulants with very similar side effects. It has been found that the dynamics of one of the two molecules to be significantly more complex. Also, the way information content is distributed in the molecules is quite different. QCM allows to measure how much information is encoded in the structure of a given molecule (small molecule drugs, proteins) as well as a measure of its structural robustness. It is hypothesized that molecular complexity may be a proxy of certain physiochemical properties of drugs, such as toxicity, helping in removal of non-promising compounds at an early stage of drug development.
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