Metalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate b...
While the construction of a dependable force field for performing classical molecular dynamics (MD) simulation is crucial for elucidating the structure and function of biomolecular systems, the attempts to do this for glycans are relatively sparse co...
Five fluorescent positively charged poly(-aryleneethynylene) (-) were designed to construct electrostatic complexes - with negatively charged graphene oxide (). The fluorescence of conjugated polymers was quenched by the quencher . Three electrostati...
Machine learning has the potential to revolutionize the field of molecular simulation through the development of efficient and accurate models of interatomic interactions. Neural networks can model interactions with the accuracy of quantum mechanics-...
Journal of chemical theory and computation
35837736
Existing computational methods for estimating p values in proteins rely on theoretical approximations and lengthy computations. In this work, we use a data set of 6 million theoretically determined p shifts to train deep learning models, which are sh...
Journal of chemical theory and computation
35939826
We present here the first application of the quantum chemical topology force field FFLUX to condensed matter simulations. FFLUX offers many-body potential energy surfaces learnt exclusively from data using Gaussian process regression. FFLUX also inc...
Journal of chemical information and modeling
36099208
Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consumin...
Journal of chemical information and modeling
36069259
In recent years, machine learning (ML) models have been found to quickly predict various molecular properties with accuracy comparable to high-level quantum chemistry methods. One such example is the calculation of electrostatic potential (ESP). Diff...
Materials with electroprogrammable stiffness and adhesion can enhance the performance of robotic systems, but achieving large changes in stiffness and adhesive forces in real time is an ongoing challenge. Electroadhesive clutches can rapidly adhere h...
Electrostatic adhesion (EA) clutches are widely applied in robots, wearable devices, and virtual reality, due to their compliance, lightweight, ultrathin profile, and low power consumption. Higher force density has been constantly perpetuated in the ...