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One of the main applications of atomistic computer simulations is the calculation of ligand binding energies. The accuracy of these calculations depends on the force field quality and on the thoroughness of configuration sampling. Sampling is an obstacle in modern simulations due to the frequent appearance of kinetic bottlenecks in the free energy landscape. Very often this difficulty is circumvented by enhanced sampling techniques. Typically, these techniques depend on the introduction of appropriate collective variables that are meant to capture the systems degrees of freedom. In ligand binding, water has long been known to play a key role, but its complex behaviour has proven difficult to fully capture. In this paper we combine machine learning with physical intuition to build a non-local and highly efficient water-describing collective variable. We use it to study a set of of host-guest systems from the SAMPL5 challenge. We obtain highly accurate binding energies and good agreement with experiments. The role of water during the binding process is then analysed in some detail.
In this work, we study the rotating magnetic field driven domain wall (DW) motion in antiferromagnetic nanowires, using the micromagnetic simulations of the classical Heisenberg spin model. We show that in low frequency region, the rotating field alo
Carbene-metal-amide type photoemitters based on CF$_3$-substituted carbazolate ligands show sky-blue to deep-blue photoluminescence from charge-transfer excited states. They are suitable for incorporation into organic light-emitting diodes (OLEDs) by
We report the results of our participation in the SAMPL8 GDCC Blind Challenge for host-guest binding affinity predictions. Absolute binding affinity prediction is of central importance to the biophysics of molecular association and pharmaceutical dis
Identifying key players in collective dynamics remains a challenge in several research fields, from the efficient dissemination of ideas to drug target discovery in biomedical problems. The difficulty lies at several levels: how to single out the rol
We report on the successful synthesis and hyperpolarization of N unprotected {alpha} amino acid ethyl acrylate esters and extensively, on an alanine derivative hyperpolarized by PHIP (4.4$pm$1% $^{13}$C-polarization), meeting required levels for in v