Universal QM/MM Approaches for General Nanoscale Applications

Hybrid quantum mechanics/molecular mechanics (QM/MM) hybrid models allow one to address chemical phenomena in complex molecular environments. However, they are tedious to construct and they usually require significant manual preprocessing and expertise. As a result, these models may not be easily transferable to new application areas and the many parameters are not easy to adjust to reference data that are typically scarce. Therefore, it has been difficult to devise automated procedures of controllable accuracy, which makes such type of modelling far from being standardized or of black-box type. Although diverse best-practice protocols have been set up for the construction of individual components of a QM/MM model (e.g., the MM potential, the type of embedding, the choice of the QM region), no automated procedures are available for all steps of the QM/MM model construction. Here, we review the state of the art of QM/MM modeling with a focus on automation. We elaborate on the MM model parametrization, on atom-economical physically-motivated QM region selection, and on embedding schemes that incorporate mutual polarization as critical components of the QM/MM model. In view of the broad scope of the field, we mostly restrict the discussion to methodologies that build de novo models based on first-principles data, on uncertainty quantification, and on error mitigation with a high potential for automation. Ultimately, it is desirable to be able to set up reliable QM/MM models in a fast and efficient automated way without being constrained by some specific chemical or technical limitations.Comment: 54 pages, 3 figures, 1 tabl

Muscular myostatin gene expression and plasma concentrations are decreased in critically ill patients.

BACKGROUND The objective was to investigate the role of gene expression and plasma levels of the muscular protein myostatin in intensive care unit-acquired weakness (ICUAW). This was performed to evaluate a potential clinical and/or pathophysiological rationale of therapeutic myostatin inhibition. METHODS A retrospective analysis from pooled data of two prospective studies to assess the dynamics of myostatin plasma concentrations (day 4, 8 and 14) and myostatin gene (MSTN) expression levels in skeletal muscle (day 15) was performed. Associations of myostatin to clinical and electrophysiological outcomes, muscular metabolism and muscular atrophy pathways were investigated. RESULTS MSTN gene expression (median [IQR] fold change: 1.00 [0.68-1.54] vs. 0.26 [0.11-0.80]; p = 0.004) and myostatin plasma concentrations were significantly reduced in all critically ill patients when compared to healthy controls. In critically ill patients, myostatin plasma concentrations increased over time (median [IQR] fold change: day 4: 0.13 [0.08/0.21] vs. day 8: 0.23 [0.10/0.43] vs. day 14: 0.40 [0.26/0.61]; p < 0.001). Patients with ICUAW versus without ICUAW showed significantly lower MSTN gene expression levels (median [IQR] fold change: 0.17 [0.10/0.33] and 0.51 [0.20/0.86]; p = 0.047). Myostatin levels were directly correlated with muscle strength (correlation coefficient 0.339; p = 0.020) and insulin sensitivity index (correlation coefficient 0.357; p = 0.015). No association was observed between myostatin plasma concentrations as well as MSTN expression levels and levels of mobilization, electrophysiological variables, or markers of atrophy pathways. CONCLUSION Muscular gene expression and systemic protein levels of myostatin are downregulated during critical illness. The previously proposed therapeutic inhibition of myostatin does therefore not seem to have a pathophysiological rationale to improve muscle quality in critically ill patients. TRIAL REGISTRATION ISRCTN77569430 -13th of February 2008 and ISRCTN19392591 17th of February 2011

Automated preparation of nanoscopic structures: Graph-based sequence analysis, mismatch detection, and pH-consistent protonation with uncertainty estimates

Structure and function in nanoscale atomistic assemblies are tightly coupled, andevery atom with its specific position and even every electron will have a decisiveeffect on the electronic structure, and hence, on the molecular properties. Molec-ular simulations of nanoscopic atomistic structures therefore require accuratelyresolved three-dimensional input structures. If extracted from experiment, thesestructures often suffer from severe uncertainties, of which the lack of informationon hydrogen atoms is a prominent example. Hence, experimental structuresrequire careful review and curation, which is a time-consuming and error-proneprocess. Here, we present a fast and robust protocol for the automated structureanalysis and pH-consistent protonation, in short, ASAP. For biomolecules as atarget, the ASAP protocol integrates sequence analysis and error assessment of agiven input structure. ASAP allows for pKₐ prediction from reference data throughGaussian process regression including uncertainty estimation and connects tosystem-focused atomistic modeling described in Brunken and Reiher (J. Chem. TheoryComput.16, 2020, 1646). Although focused on biomolecules, ASAP can be extendedto other nanoscopic objects, because most of its design elements rely on a generalgraph-based foundation guaranteeing transferability. The modular character ofthe underlying pipeline supports different degrees of automation, which allows for(i) efficient feedback loops for human-machine interaction with a low entrance barrierand for (ii) integration into autonomous procedures such as automated force fieldparametrizations. This facilitates fast switching of the pH-state through on-the-flysystem-focused reparametrization during a molecular simulation at virtually no extracomputational cost.ISSN:0192-8651ISSN:1096-987

Quantum Magnifying Glass for Chemistry at the Nanoscale

Nanoscopic systems exhibit diverse molecular substructures by which they facilitate spe- cific functions. Theoretical models of them, which aim at describing, understanding, and predicting these capabilities, are difficult to build. Viable quantum-classical hybrid mod- els come with specific challenges regarding atomistic structure construction and quantum region selection. Moreover, if their dynamics are mapped onto a state-to-state mecha- nism such as a chemical reaction network, its exhaustive exploration will be impossible due to the combinatorial explosion of the reaction space. Here, we introduce a quantum magnifying glass that allows one to interactively manipulate nanoscale structures at the quantum level. The quantum magnifying glass seamlessly combines autonomous model parametrization, ultra-fast quantum mechanical calculations, and automated reaction ex- ploration. It represents a unique approach to investigate complex reaction sequences in a physically consistent manner with unprecedented effortlessness in real time. We demon- strate these features for reactions in bio-macromolecules and metal-organic frameworks, diverse systems that highlight general applicability

Nanoscale chemical reaction exploration with a quantum magnifying glass

Abstract Nanoscopic systems exhibit diverse molecular substructures by which they facilitate specific functions. Theoretical models of them, which aim at describing, understanding, and predicting these capabilities, are difficult to build. Viable quantum-classical hybrid models come with specific challenges regarding atomistic structure construction and quantum region selection. Moreover, if their dynamics are mapped onto a state-to-state mechanism such as a chemical reaction network, its exhaustive exploration will be impossible due to the combinatorial explosion of the reaction space. Here, we introduce a “quantum magnifying glass” that allows one to interactively manipulate nanoscale structures at the quantum level. The quantum magnifying glass seamlessly combines autonomous model parametrization, ultra-fast quantum mechanical calculations, and automated reaction exploration. It represents an approach to investigate complex reaction sequences in a physically consistent manner with unprecedented effortlessness in real time. We demonstrate these features for reactions in bio-macromolecules and metal-organic frameworks, diverse systems that highlight general applicability

The Apparently Unreactive Substrate Facilitates the Electron Transfer for Dioxygen Activation in Rieske Dioxygenases

Rieske dioxygenases belong to the non-heme iron family of oxygenases and catalyze important cis-dihydroxylation as well as O-/N-dealkylation and oxidative cyclization reactions for a wide range of substrates. The lack of substrate coordination at the non-heme ferrous iron center, however, makes it particularly challenging to delineate the role of the substrate for productive O2 activation. Here, we studied the role of the substrate in the key elementary reaction leading to O2 activation from a theoretical perspective by systematically considering (i) the 6-coordinate to 5-coordinate conversion of the non-heme Fe-II upon abstraction of a water ligand, (ii) binding of O2 , and (iii) transfer of an electron from the Rieske cluster. We systematically evaluated the spin-state-dependent reaction energies and structural effects at the active site for all combinations of the three elementary processes in the presence and absence of substrate using naphthalene dioxygenase as a prototypical Rieske dioxygenase. We find that reaction energies for the generation of a coordination vacancy at the non-heme FeII center through thermoneutral H2O reorientation and exothermic O2 binding prior to Rieske cluster oxidation are largely insensitive to the presence of naphthalene and do not lead to formation of any of the known reactive Fe-oxygen species. By contrast, the role of the substrate becomes evident after Rieske cluster oxidation and exclusively for the 6-coordinate non-heme FeII sites in that the additional electron is found at the substrate instead of at the iron and oxygen atoms. Our results imply an allosteric control of the substrate on Rieske dioxygenase reactivity to happen prior to changes at the non-heme FeII in agreement with a strategy that avoids unproductive O2 activation.ISSN:0947-6539ISSN:1521-376

qcscine/core: Release 6.0.0

&lt;p&gt;Changes:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Improve support for compilation on Windows (MSVC)&lt;/li&gt; &lt;li&gt;Update address in license&lt;/li&gt; &lt;/ul&gt

qcscine/xtb_wrapper: Release 3.0.0

&lt;p&gt;Changes:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Enable external point charges for QM/MM&lt;/li&gt; &lt;li&gt;Update address in license&lt;/li&gt; &lt;/ul&gt

qcscine/puffin: Release 1.3.0

&lt;p&gt;Changes:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Store found elementary step even if none of the endpoints corresponds to the initial starting structures&lt;/li&gt;&lt;li&gt;Add restart information with valid TS for jobs trying to find new elementary steps, where the IRC failed to produce different endpoints&nbsp;&lt;/li&gt;&lt;li&gt;Consider potential surface structures for label determination of new structures&nbsp;&lt;/li&gt;&lt;li&gt;Logic to transfer indices information and other complex properties from reactants to products&nbsp;&lt;/li&gt;&lt;li&gt;Save close lying spin multiplicities and allow to manipulate exact spin propensity check behavior with added settings&nbsp;&lt;/li&gt;&lt;li&gt;Microkinetic modeling with the program Reaction Mechanism Simulator.&nbsp;&lt;/li&gt;&lt;li&gt;AMS via SCINE AMS Wrapper&nbsp;&lt;/li&gt;&lt;li&gt;MRCC (release version March 2022)&nbsp;&lt;/li&gt;&lt;li&gt;Ensure that only_distance_connectivity is adhered in all reaction jobs&nbsp;&lt;/li&gt;&lt;li&gt;Update address in license&lt;/li&gt;&lt;/ul&gt