A quantum-mechanical perspective on linear response theory within polarizable embedding

The derivation of linear response theory within polarizable embedding is carried out from a rigorous quantum-mechanical treatment of a composite system. Two different subsystem decompositions (symmetric and nonsymmetric) of the linear response function are presented, and the pole structures as well as residues of the individual terms are analyzed and discussed. This theoretical analysis clarifies which form of the response function to use in polarizable embedding, and we highlight complications in separating out subsystem contributions to molecular properties. For example, based on the nonsymmetric decomposition of the complex linear response function, we derive conservation laws for integrated absorption cross sections, providing a solid basis for proper calculations of the intersubsystem intensity borrowing inherent to coupled subsystems and how that can lead to negative subsystem intensities. We finally identify steps and approximations required to achieve the transition from a quantum-mechanical description of the composite system to polarizable embedding with a classical treatment of the environment, thus providing a thorough justification for the descriptions used in polarizable embedding models

How Far Does a Receptor Influence Vibrational Properties of an Odorant?

The biophysical mechanism of the sense of smell, or olfaction, is still highly debated. The mainstream explanation argues for a shape-based recognition of odorant molecules by olfactory receptors, while recent investigations suggest the primary olfactory event to be triggered by a vibrationally-assisted electron transfer reaction. We consider this controversy by studying the influence of a receptor on the vibrational properties of an odorant in atomistic details as the coupling between electronic degrees of freedom of the receptor and the vibrations of the odorant is the key parameter of the vibrationally-assisted electron transfer. Through molecular dynamics simulations we elucidate the binding specificity of a receptor towards acetophenone odorant. The vibrational properties of acetophenone inside the receptor are then studied by the polarizable embedding density functional theory approach, allowing to quantify protein-odorant interactions. Finally, we judge whether the effects of the protein provide any indications towards the existing theories of olfaction

Predictive glycoengineering of biosimilars using a Markov chain glycosylation model

Biosimilar drugs must closely resemble the pharmacological attributes of innovator products to ensure safety and efficacy to obtain regulatory approval. Glycosylation is one critical quality attribute that must be matched, but it is inherently difficult to control due to the complexity of its biogenesis. This usually implies that costly and time-consuming experimentation is required for clone identification and optimization of biosimilar glycosylation. Here, we describe a computational method that utilizes a Markov model of glycosylation to predict optimal glycoengineering strategies to obtain a specific glycosylation profile with desired properties. The approach uses a genetic algorithm to find the required quantities to perturb glycosylation reaction rates that lead to the best possible match with a given glycosylation profile. Furthermore, the approach can be used to identify cell lines and clones that will require minimal intervention while achieving a glycoprofile that is most similar to the desired profile. Thus, this approach can facilitate biosimilar design by providing computational glycoengineering guidelines that can be generated with a minimal time and cost