Electrostatic versus Resonance Interactions in Photoreceptor Proteins: The Case of Rhodopsin

Light sensing in photoreceptor proteins is subtly modulated by the multiple interactions between the chromophoric unit and its binding pocket. Many theoretical and experimental studies have tried to uncover the fundamental origin of these interactions but reached contradictory conclusions as to whether electrostatics, polarization, or intrinsically quantum effects prevail. Here, we select rhodopsin as a prototypical photoreceptor system to reveal the molecular mechanism underlying these interactions and regulating the spectral tuning. Combining a multireference perturbation method and density functional theory with a classical but atomistic and polarizable embedding scheme, we show that accounting for electrostatics only leads to a qualitatively wrong picture, while a responsive environment can successfully capture both the classical and quantum dominant effects. Several residues are found to tune the excitation by both differentially stabilizing ground and excited states and through nonclassical 'inductive resonance' interactions. The results obtained with such a quantum-in-classical model are validated against both experimental data and fully quantum calculations

Introducing QMC/MMpol: Quantum Monte Carlo in Polarizable Force Fields for Excited States

We present for the first time a quantum mechanics/molecular mechanics scheme which combines quantum Monte Carlo with the reaction field of classical polarizable dipoles (QMC/MMpol). In our approach, the optimal dipoles are self-consistently generated at the variational Monte Carlo level and then used to include environmental effects in diffusion Monte Carlo. We investigate the performance of this hybrid model in describing the vertical excitation energies of prototypical small molecules solvated in water, namely, methylenecyclopropene and s-trans acrolein. Two polarization regimes are explored where either the dipoles are optimized with respect to the ground-state solute density (polGS) or different sets of dipoles are separately brought to equilibrium with the states involved in the electronic transition (polSS). By comparing with reference supermolecular calculations where both solute and solvent are treated quantum mechanically, we find that the inclusion of the response of the environment to the excitation of the solute leads to superior results than the use of a frozen environment (point charges or polGS), in particular, when the solute-solvent coupling is dominated by electrostatic effects which are well recovered in the polSS condition. QMC/MMpol represents therefore a robust scheme to treat important environmental effects beyond static point charges, combining the accuracy of QMC with the simplicity of a classical approach

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and objectives: It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19-related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population. Methods: Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score > 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ2 test, and the risk excess was quantified by risk ratios (RRs). Results: The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p < 0.001), RR = 2.19 for ICU admission (p < 0.001), and RR = 2.43 for death (p < 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04). Discussion: Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

The lowest singlet states of hexatriene revisited

The two lowest excited singlet states of trans-hexatriene and cis-hexatriene are studied by multireference perturbation theory approaches (NEVPT2 and CASPT2) in their quasi-degenerate version (QD-NEVPT2 and MS-CASPT2). For these states, we report spectroscopic properties such as the vertical and adiabatic excitation energies, some features of the topology of the potential energy surfaces (PES), and the emission energies. The theoretical vertical excitation energies for the 2 1 A − g and 1 1 B + u states of trans-hexatriene are found to be almost degenerate, with a value, ≃ 5.5–5.6 eV, higher than that normally accepted in the literature, 5.2 eV and 5.1 eV, respectively. The 2 1 A 1 and 1 1 B 2 states of cis-hexatriene are also almost degenerate and are estimated to be at ≃ 5.4–5.5 and ≃ 5.5 eV, respectively, again higher than the accepted values. The adiabatic excitation energies to the 2 1 A − g and 2 1 A 1 states can be observed experimentally (in particular for the cis isomer), and our results are in excellent agreement with the experimental values. On the contrary, the vertical excitation energies for these states are not directly observable in the experimental spectra and the “experimental” values are obtained by educated guesses. We show that the hypotheses underlying these guesses are not entirely grounded

Ground- and Excited-State Geometry Optimization of Small Organic Molecules with Quantum Monte Carlo

We present a comparative study of the geometry optimization in the gas phase of acrolein, acetone, methylenecyclopropene, and the propenoic acid anion with special emphasis on their excited-state structures, using quantum Monte Carlo (QMC), multireference perturbation theory (CASPT2 and NEVPT2), second-order approximate coupled cluster (CC2), and time-dependent density functional theory (TDDFT). We find that, for all molecules, the geometries optimized with QMC in its simplest variational (VMC) flavor are in very good agreement with the perturbation results both in the ground and the excited states of either <i>n</i> → π* or π → π* character. Furthermore, the quality of the QMC structures is superior to those obtained with the CC2 method, which overestimates the CO bond in all <i>n</i> → π* excitations, or to the symmetry-adapted-cluster configuration interaction (SAC–CI) approach, which gives a poorer description of the CC bonds in the excited states. Finally, the spread in the TDDFT structures obtained with several current exchange-correlation functionals is large and does not reveal a clear relation between the defining features of the functionals and the quality of the optimized structures. In summary, our findings demonstrate the good performance of QMC in optimizing the geometries of these molecules, also in cases where other correlated or TDDFT approaches are inaccurate, and indicate that the method represents a robust reference approach for future structural studies also of larger systems

Solvent effects on excited-state structures: A quantum Monte Carlo and density functional study

We present the first application of quantum Monte Carlo (QMC) in its variational flavor combined with the polarizable continuum model (PCM) to perform excited-state geometry optimization in solution. Our implementation of the PCM model is based on a reaction field that includes both volume and surface polarization charges and is determined self-consistently with the molecular wave function during the QMC optimization of the solute geometry. For acrolein, acetone, methylenecyclopropene, and the propenoic acid anion, we compute the optimal exited-state geometries in water and compare our results with the structures obtained with second-order perturbation theory (CASPT2) and other correlated methods, and with time-dependent density functional theory (TDDFT). We find that QMC predicts a structural response to solvation in good agreement with CASPT2 with the only exception of the π → π* state of acrolein where the robustness of the QMC geometry must be contrasted to the sensitivity of the perturbation result to the details of the calculation. As regards TDDFT, we show that all investigated functionals systematically overestimate the geometrical changes from the gas phase to solution, sometimes giving bond variations opposite in trend to QM

Electrostatic versus Resonance Interactions in Photoreceptor Proteins: The Case of Rhodopsin

Light sensing in photoreceptor proteins is subtly modulated by the multiple interactions between the chromophoric unit and its binding pocket. Many theoretical and experimental studies have tried to uncover the fundamental origin of these interactions but reached contradictory conclusions as to whether electrostatics, polarization, or intrinsically quantum effects prevail. Here, we select rhodopsin as a prototypical photoreceptor system to reveal the molecular mechanism underlying these interactions and regulating the spectral tuning. Combining a multireference perturbation method and density functional theory with a classical but atomistic and polarizable embedding scheme, we show that accounting for electrostatics only leads to a qualitatively wrong picture, while a responsive environment can successfully capture both the classical and quantum dominant effects. Several residues are found to tune the excitation by both differentially stabilizing ground and excited states and through nonclassical "inductive resonance" interactions. The results obtained with such a quantum-in-classical model are validated against both experimental data and fully quantum calculations

Structural Prediction of the Dimeric Form of the Mammalian Translocator Membrane Protein TSPO: A Key Target for Brain Diagnostics

Positron emission tomography (PET) radioligands targeting the human translocatormembrane protein (TSPO) are broadly used for the investigations of neuroinflammatory conditionsassociated with neurological disorders. Structural information on the mammalian proteinhomodimers—the suggested functional state of the protein—is limited to a solid-state nuclearmagnetic resonance (NMR) study and to a model based on the previously-deposited solution NMRstructure of the monomeric mouse protein. Computational studies performed here suggest thatthe NMR-solved structure in the presence of detergents is not prone to dimer formation and isfurthermore unstable in its native membrane environment. We, therefore, propose a new modelof the functionally-relevant dimeric form of the mouse protein, based on a prokaryotic homologue.The model, fully consistent with solid-state NMR data, is very different from the previous predictions.Hence, it provides, for the first time, structural insights into this pharmaceutically-important targetwhich are fully consistent with experimental data