Intermolecular Non-Bonded Interactions from Machine Learning Datasets

Accurate determination of intermolecular non-covalent-bonded or non-bonded interactions is the key to potentially useful molecular dynamics simulations of polymer systems. However, it is challenging to balance both the accuracy and computational cost in force field modelling. One of the main difficulties is properly representing the calculated energy data as a continuous force function. In this paper, we employ well-developed machine learning techniques to construct a general purpose intermolecular non-bonded interaction force field for organic polymers. The original ab initio dataset SOFG-31 was calculated by us and has been well documented, and here we use it as our training set. The CLIFF kernel type machine learning scheme is used for predicting the interaction energies of heterodimers selected from the SOFG-31 dataset. Our test results show that the overall errors are well below the chemical accuracy of about 1 kcal/mol, thus demonstrating the promising feasibility of machine learning techniques in force field modelling.

A molecular dynamics investigation on transporting mechanism of glucose through a cyclic peptide nanotube

Cyclic peptide nanotubes (CPNTs) are open-ended, hollow, and tubular structures that are made of several cyclic peptide rings. These structures can act as a transmembrane channel and transport ions or small molecules. In this work, we studied the stability of a cyclic peptide nanotube 8 × [(Trp-D-Leu)4-Gln-D-Leu] into a fully hydrated membrane composed of DPPC/POPC/POPS/cholesterol and also the transport mechanism of β-D-glucose through this nanotube was investigated. Our findings revealed that the CPNT was stable in the lipid bilayer during the simulation time and non-bonded interactions, especially hydrogen bonding have an important role to form a stable CPNT in the membrane. The glucose jumps from a Cα-region into the mid-Cα region and spends more time in this region because of its more desirable interactions with water molecules and the CPNT. In the transport pathway, non-bonded interactions between glucose, water molecules and the CPNT facilitate the transport of the glucose through the CPNT. The collaboration of hydrogen bonds, electrostatic and van der Waals interactions change the pulling force and lead to transport glucose through the CPNT. Potential of mean force (PMF) calculations revealed that the glucose has a minimum value of binding free energy and maximum configurational entropy in MPR regions. These findings can be used to design more CPNTs with different goals such as drug delivery.Communicated by Ramaswamy H. Sarma.

Melting of DNA oligomers: dynamical models and comparison with experimental results

We compare experimental melting curves of short heterogeneous DNA oligomers with theoretical curves derived from statistical mechanics. Partition functions are computed with the one-dimensional Peyrard-Bishop (PB) Hamiltonian, already used in the study of the melting of long DNA chains. Working with short chains we take into account, in the computations, not only the breaking of the interstrand hydrogen bonds, but also the complete dissociation of the double helix into separate single strands. Since this dissociation equilibrium is of general relevance, independent of the particular microscopic model, we give some details of its treatment. We discuss how the non bonded three-dimensional interactions, not explicitly considered in the one-dimensional PB model, are taken into account through the treatment of the dissociation equilibrium. We also evaluate the relevance of the dissociation as a function of the chain length.