Yoink: An interaction‐based partitioning API

Abstract

Herein, we describe the implementation details of our interaction-based partitioning API (application programming interface) called Yoink for QM/MM modeling and fragment-based quantum chemistry studies. Interactions are detected by computing density descriptors such as reduced density gradient, density overlap regions indicator, and single exponential decay detector. Only molecules having an interaction with a user-definable QM core are added to the QM region of a hybrid QM/MM calculation. Moreover, a set of molecule pairs having density-based interactions within a molecular system can be computed in Yoink, and an interaction graph can then be constructed. Standard graph clustering methods can then be applied to construct fragments for further quantum chemical calculations. The Yoink API is licensed under Apache 2.0 and can be accessed via yoink.wallerlab.org. © 2018 Wiley Periodicals, Inc.

Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: the Case of Formate Dehydrogenase

“…[55][56][57][58][59][60][61] Regarding the challenges for QM region selection, systematic approaches can provide an unbiased insight toward electronic environment of the enzyme and detection of crucial residues along with improving the accuracy of the QM/MM. [62][63][64][65][66][67][68][69][70] Previous studies on bioinspired catalyst design of FDH mimics found that the enzyme environment primarily affects the geometric properties of the metal center, and terminal chalcogen moieties primarily influence local electronic properties. 71 Here, we apply long-time classical MD and large-scale QM/MM simulation to further analyze the influence of the greater protein environment and metal coordinating residues on electronic properties of the FDH active site.…”

General Many-Body Framework for Data-Driven Potentials with Arbitrary Quantum Mechanical Accuracy: Water as a Case Study

“…This is generally accomplished by introducing transition layers that smooth over the QM/MM boundary discontinuity. 56,57,57,58,[58][59][60][61][62][63][64][65][66][67][68][69][70][71][72][73][74][75][76] This suggests that "elevating" the accuracy of the MM model to the same level as the QM model would effectively remove these discontinuities and significantly improve the realism and predictive power of QM/MM calculations. 77 In this context, pure ML models of the MM region do not lend themselves well to QM/MM simulations since point charges must, at least, be assigned to the MM atoms to capture Coulom-bic interactions between the MM region and the QM electronic density through a minimal electrostatic embedding scheme.…”

A Many-Body, Fully Polarizable Approach to QM/MM Simulations

“…55 These techniques range from simple smoothing functions to more complex distance-based partitioning approaches which have been shown to conserve energy and smooth forces. 4,[53][54][55][56][58][59][60][61][62][63][64][65][66][67][68][69][70][71] Unfortunately, while these adaptive approaches improve energy conservation and alleviate some of the discontinuities in the forces, which, consequently, smooth out boundary artifacts that may occur, they do not solve the underlying issue in that the system is being represented by two different potential energy functions. 55 Furthermore, adoption of transition layers increases the computational cost of QM/MM simulations, as some schemes can result in up to 2 N additional QM calculations for N molecules in the transition layer, though more modern partitioning schemes have been shown to significantly reduce that number.…”