The topological framework of circuit topology has recently been introduced to complement knot theory and help in understanding the physics molecular folding. Naturally evolved linear chains, such as proteins nucleic acids, often fold into 3D conformations with critical chain entanglements local or global structural symmetries stabilised by formation contacts between different parts chain. Circu...

A total of 1099 data points consisting of alcohol-alcohol, alcohol-alkane, alkane-alkane, alcohol-amine and acid-acid binary solutions were collected from scientific literature to develop an appropriate artificial neural network (ANN) model. Temperature, molecular weight of the pure components, mole fraction of one component and the structural groups of the components were used as input paramet...

Abstract: Scientific visualization typically depends upon piecewise linear (PL) geometry. Dynamic visualization of molecular simulations is often discussed, informally, as “molecular animation”. Some of these molecules are mathematically modeled as knots and computationally instantiated as splines. Questions arise of topological consistency between the geometry and its PL approximation, with co...

T o a large extent, the eld of “molecular machines” started aer several groups were able to prepare reasonably easily interlocking ring compounds (named catenanes for compounds consisting of interlocking rings and rotaxanes for rings threaded by molecular laments or axes). Important families of molecular machines not belonging to the interlocking world were also designed, prepared and studied ...

Recently, graph neural networks (GNNs) have been successfully applied to predicting molecular properties, which is one of the most classical cheminformatics tasks with various applications. Despite their effectiveness, we empirically observe that training a single GNN model for diverse molecules distinct structural patterns limits its prediction performance. In this paper, motivated by observat...