Fragment Localized Molecular Orbitals

Abstract

We introduce the concept of fragment localized molecular orbitals (FLMOs), which are Hartree–Fock molecular orbitals localized in specific fragments constituting a molecular system. In physical terms, we minimize the local electronic energies of the different fragments, at the cost of maximizing the repulsion between them. To showcase the approach, we rationalize the main interactions occurring in large biological systems in terms of interactions between the fragments of the system. In particular, we study an anticancer drug intercalated within DNA and retinal in anabaena sensory rhodopsin as prototypes of molecular systems embedded in biological matrixes. Finally, the FLMOs are exploited to rationalize the formation of two oligomers, prototypes of amyloid diseases, such as Parkinson and Alzheimer.

Linear response properties of solvated systems: a computational study

“…In this way, the occupied MOs of both fragments are localized in their specific spatial regions. If a full HF optimization is performed before the localization procedure, FLMOs are obtained, 50 yielding the HF FLMOs approach. Note that, if an additional MM layer is included in the modeling, it does not affect the minimization procedure: the total density matrix remains fixed, and so does the MLHF-MM interaction.…”

“…If such a procedure is applied to an HF optimized wave function, fully accounting for solute-solvent interactions, the resulting MOs are denoted as fragment localized MOs (FLMOs). 50 To minimize its computational cost, MLHF(-AB) can be coupled to an external MM layer (MLHF(-AB)/MM). 39 To calculate the linear response properties, we use the aforementioned two-and three-layer wave functions as the reference for a post-HF description of the solute.…”

“…If such a procedure is applied to an HF optimized wave function, fully accounting for solute–solvent interactions, the resulting MOs are denoted as fragment localized MOs (FLMOs). 50 To minimize its computational cost, MLHF(-AB) can be coupled to an external MM layer (MLHF(-AB)/MM). 39…”

Deterministic/Fragmented-Stochastic Exchange for Large-Scale Hybrid DFT Calculations

“…17,18 Multilevel fragmented approaches have also recently improved scaling, especially in spatially localized cases. 16 Modern graphical processing units also contribute to unlocking larger and larger calculations with RI methods. 19,20 Separately, we introduced a stochastic formalism for Hartree−Fock or long-range exchange for grid-based DFT codes.…”

Machine‐learning assisted scheduling optimization and its application in quantum chemical calculations

“…Thus, the quantum chemical (QM)-based calculations on the MM results can be an excellent alternative for studying biopharmaceutical systems. The QM models can be used only for reasonably modest system sizes (i.e., tens of atoms), while the fragment-based approaches [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] or linear scaling strategies, [32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47] which a good loadbalancing scheme can benefit, are used to increase the reach of QM methods largely. For instance, there are many outstanding studies on analyzing the interactions, recognition of SARS-CoV-2 spike protein in QM level using fragment molecular orbital (FMO) approach [48][49][50][51][52] and molecular fractionation with conjugate caps (MFCC) approaches.…”