RESUMEN
Relative binding free energy (RBFE) calculations have emerged as a powerful tool that supports ligand optimization in drug discovery. Despite many successes, the use of RBFEs can often be limited by automation problems, in particular, the setup of such calculations. Atom mapping algorithms are an essential component in setting up automatic large-scale hybrid-topology RBFE calculation campaigns. Traditional algorithms typically employ a 2D subgraph isomorphism solver (SIS) in order to estimate the maximum common substructure. SIS-based approaches can be limited by time-intensive operations and issues with capturing geometry-linked chemical properties, potentially leading to suboptimal solutions. To overcome these limitations, we have developed Kartograf, a geometric-graph-based algorithm that uses primarily the 3D coordinates of atoms to find a mapping between two ligands. In free energy approaches, the ligand conformations are usually derived from docking or other previous modeling approaches, giving the coordinates a certain importance. By considering the spatial relationships between atoms related to the molecule coordinates, our algorithm bypasses the computationally complex subgraph matching of SIS-based approaches and reduces the problem to a much simpler bipartite graph matching problem. Moreover, Kartograf effectively circumvents typical mapping issues induced by molecule symmetry and stereoisomerism, making it a more robust approach for atom mapping from a geometric perspective. To validate our method, we calculated mappings with our novel approach using a diverse set of small molecules and used the mappings in relative hydration and binding free energy calculations. The comparison with two SIS-based algorithms showed that Kartograf offers a fast alternative approach. The code for Kartograf is freely available on GitHub (https://github.com/OpenFreeEnergy/kartograf). While developed for the OpenFE ecosystem, Kartograf can also be utilized as a standalone Python package.
RESUMEN
We present a simple multiscale model for polymer chains in which it is possible to selectively remove degrees of freedom. The model integrates all-atom and coarse-grained potentials in a simple and systematic way and allows a fast sampling of the complex conformational energy surface typical of polymers whilst maintaining a realistic description of selected atomistic interactions. In particular, we show that it is possible to simultaneously reproduce the structure of highly directional non-bonded interactions such as hydrogen bonds and efficiently explore the large number of conformations accessible to the polymer chain. We apply the method to a melt of polyamide removing from the model only the degrees of freedom associated to the aliphatic segments and keeping at atomistic resolution the amide groups involved in the formation of the hydrogen bonds. The results show that the multiscale model produces structural properties that are comparable with the fully atomistic model despite being five times faster to simulate.
RESUMEN
In hybrid particle models where coarse-grained beads and atoms are used simultaneously, two clearly separate time scales are mixed. If such models are used in molecular dynamics simulations, a multiple time step (MTS) scheme can therefore be used. In this manuscript, we propose a simple MTS algorithm which approximates for a specific number of integration steps the slow coarse-grained bead-bead interactions with a Taylor series approximation while the atom-atom ones are integrated every time step. The procedure is applied to a previously developed hybrid model of a melt of atactic polystyrene (di Pasquale, Marchisio, and Carbone, J. Chem. Phys. 2012, 137, 164111). The results show that structure, local dynamics, and free diffusion of the model are not altered by the application of the integration scheme which can confidently be used to simulate multiresolved models of polymer melts.
