Fragment-Based Quantum Mechanical Calculation of Excited-State Properties of Fluorescent RNAs

Fluorescent RNA aptamers have been successfully applied to track and tag RNA in a biological system. However, it is still challenging to predict the excited-state properties of the RNA aptamer–fluorophore complex with the traditional electronic structure methods due to expensive computational costs. In this study, an accurate and efficient fragmentation quantum mechanical (QM) approach of the electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) scheme was applied for calculations of excited-state properties of the RNA aptamer–fluorophore complex. In this method, the excited-state properties were first calculated with one-body fragment quantum mechanics/molecular mechanics (QM/MM) calculation (the excited-state properties of the fluorophore) and then corrected with a series of two-body fragment QM calculations for accounting for the QM effects from the RNA on the excited-state properties of the fluorophore. The performance of the EE-GMFCC on prediction of the absolute excitation energies, the corresponding transition electric dipole moment (TEDM), and atomic forces at both the TD-HF and TD-DFT levels was tested using the Mango-II RNA aptamer system as a model system. The results demonstrate that the calculated excited-state properties by EE-GMFCC are in excellent agreement with the traditional full-system time-dependent ab initio calculations. Moreover, the EE-GMFCC method is capable of providing an accurate prediction of the relative conformational excited-state energies for different configurations of the Mango-II RNA aptamer system extracted from the molecular dynamics (MD) simulations. The fragmentation method further provides a straightforward approach to decompose the excitation energy contribution per ribonucleotide around the fluorophore and then reveals the influence of the local chemical environment on the fluorophore. The applications of EE-GMFCC in calculations of excitation energies for other RNA aptamer–fluorophore complexes demonstrate that the EE-GMFCC method is a general approach for accurate and efficient calculations of excited-state properties of fluorescent RNAs.

Accurate Prediction of Absorption Spectral Shifts of Proteorhodopsin Using a Fragment-Based Quantum Mechanical Method

Many experiments have been carried out to display different colors of Proteorhodopsin (PR) and its mutants, but the mechanism of color tuning of PR was not fully elucidated. In this study, we applied the Electrostatically Embedded Generalized Molecular Fractionation with Conjugate Caps (EE-GMFCC) method to the prediction of excitation energies of PRs. Excitation energies of 10 variants of Blue Proteorhodopsin (BPR-PR105Q) in residue 105GLN were calculated with the EE-GMFCC method at the TD-B3LYP/6-31G* level. The calculated results show good correlation with the experimental values of absorption wavelengths, although the experimental wavelength range among these systems is less than 50 nm. The ensemble-averaged electric fields along the polyene chain of retinal correlated well with EE-GMFCC calculated excitation energies for these 10 PRs, suggesting that electrostatic interactions from nearby residues are responsible for the color tuning. We also utilized the GMFCC method to decompose the excitation energy contribution per residue surrounding the chromophore. Our results show that residues ASP97 and ASP227 have the largest contribution to the absorption spectral shift of PR among the nearby residues of retinal. This work demonstrates that the EE-GMFCC method can be applied to accurately predict the absorption spectral shifts for biomacromolecules.

Exploring human porphobilinogen synthase metalloprotein by quantum biochemistry and evolutionary methods

Previous studies have shown the porphobilinogen synthase (PBGS) zinc-binding mechanism and its conservation among the living cells. However, the precise molecular interaction of zinc with the active center of the enzyme is unknown. In particular, quantum chemistry techniques within the density functional theory (DFT) framework have been the key methodology to describe metalloproteins, when one is looking for a compromise between accuracy and computational feasibility. Considering this, we used DFT-based models within the molecular fractionation with conjugate caps scheme to evaluate the binding energy features of zinc interacting with the human PBGS. Besides, phylogenetic and clustering analyses were successfully employed in extracting useful information from protein sequences to identify groups of conserved residues that build the ions-binding site. Our results also report a conservative assessment of the relevant amino acids, as well as the benchmark analysis of the calculation models used. The most relevant intermolecular interactions in Zn2+–PBGS are due to the amino acids CYS0122, CYS0124, CYS0132, ASP0169, SER0168, ARG0221, HIS0131, ASP0120, GLY0133, VAL0121, ARG0209, and ARG0174. Among these residues, we highlighted ASP0120, GLY0133, HIS0131, SER0168, and ARG0209 by co-occurring in all clusters generated by unsupervised clustering analysis. On the other hand, the triple cysteines at 2.5 Å from zinc (CYS0122, CYS0124, and CYS0132) have the highest energy attraction and are absent in the taxa Viridiplantae, Sar, Rhodophyta, and some Bacteria. Additionally, the performance of the DFT-based models shows that the processing time-dependence is more associated with the choice of the basis set than the exchange–correlation functional.

Explaining SARS-CoV-2 3CL Mpro binding to peptidyl Michael acceptor and a ketone-based inhibitors using Molecular fractionation with conjugate caps method

The main protease SARS-CoV-2 3CL Mpro (3CL-Mpro) is an attractive target for developing antiviral inhibitors due to its essential role in processing the polyproteins translated from viral coronavirus RNA. In this work, it was obtained non-covalent complexes of this protease with two distinct ligands, a peptidyl Michael acceptor (N3) and a ketone-based compound (V2M). The complexes were modeled from processed crystallographic data (PDB id: 6LU7 and 6XHM respectively) using combined quantum mechanics/molecular mechanics (QM/MM) calculations. The QM region was treated at the PBE-def2-SV(P) level, while the Amber-ff19SB force field was used to describe the MM region. The obtained models were used to perform calculations for describing the protease/ligand binding, based in the framework of the Density Functional Theory (DFT) and within the Molecular Fractionation with Conjugated Caps (MFCC) scheme. Our results have shown values for the total interaction energies of -111.84 and -111.64 kcal mol-1 having as ligands a N3 and V2M, respectively. Most importantly, it was possible to assess the relative individual amino acid energy contribution for the binding of both ligands considering residues around them up to 10 Å of radial distance. Residues Gln189, Met165, Glu166, His164, and Asn142 were identified as main interacting amino acid residues for both complexes, being their negative interaction energy contributions higher than -5.0 kcal mol-1. In the case of 3CL-Mpro/ V2M complex, we should add His41, Ser144, and Cys145 as main contributing residues. Our data also have shown that interactions of type π-amide, π-alkyl and alkyl-alkyl and carbon hydrogen bonds should be also considered in order to explain the binding of 3CL-Mpro with the selected inhibitors. Our results also determined that the carbonyl-L-leucinamide scaffold of both inhibitors is its main determinant of binding with a contribution to the energy of interaction of 54.51 and 50.69 kcal mol-1 for N3 and V2M, respectively.

Polarizable Density Embedding for Large Biomolecular Systems

We present an efficient and robust fragment-based quantum–classical embedding model capable of accurately capturing effects from complex environments such as proteins and nucleic acids. This is realized by combining the molecular fractionation with conjugate caps (MFCC) procedure with the polarizable density embedding (PDE) model at the level of Fock matrix construction. Thereby we avoid complications associated with the application of the fragmentation procedure on environment quantities such as density matrices and molecular orbital energies. We analyze the performance of the resulting model in terms of the reproduction of electrostatic potentials of an insulin monomer protein and further in the context of solving problems related to electron spill-out. Finally, we showcase the model for the calculation of one- and two-photon properties of the Nile Red molecule in protein environments. Based on our analyses, we find that the combination of the MFCC approach with the PDE model is an efficient yet accurate approach for calculating molecular properties of molecules embedded in structured biomolecular environments.

MOLECULAR FRACTIONATION WITH CONJUGATE CAPS STUDY OF THE INTERACTION OF THE ANACARDIC ACID WITH THE ACTIVE SITE OF TRYPANOSOMA CRUZI GAPDH ENZYME: A QUANTUM INVESTIGATION

Objective: The objective of this study was to use the molecular fractionation with conjugate caps (MFCC) method to elucidate the possible interaction mechanism of anacardic acid (AA) with the saturated alkyl chain (AA0) in the Trypanosoma cruzi glyceraldehyde-3-phosphate dehydrogenase (TcGAPHD) enzyme. Methods: Initially, the geometry optimization of the AA three-dimensional structure (with the pentadecyl chain) was performed using density functional theory (B3LYP) calculations. With the AA0 optimization data, it was possible to plot the molecular electrostatic potential (MESP) surface. Molecular docking simulation was performed using automated coupling with the AutoDock Vina program. The best-fit conformation in the docking simulation of AA0 is the binding site used for the construction of the TcGAPHD-AA0 complex. Interaction energies between the AA0 molecule and the amino acid residues of the TcGAPHD enzyme were estimated using the MFCC strategy. Results: To obtain more reliable quantitative information on the interaction of AA with the active site of the TcGAPHD enzyme, the fragmentation method was combined with conjugated layers (MFCC) and molecular docking. It can be observed that the AA0 molecule occupies a region near the active site of the chalepin molecule in the TcGAPHD enzyme, and the Ile13 residue has the strongest binding energy of approximately 25 kcal/mol with AA0, through a strong Van der Waals interaction. Conclusion: The paper presents an improved quantitative analysis approach for assessing the contribution of individual amino acids to the free energy of interaction between AA and TcGAPHD. Specifically, the paper illustrates the advantageous approach of combining molecular docking with the MFCC method.