We report new results on the translational-rotational (T-R) states of the CO2 molecule inside the sI clathrate-hydrate cages. We adopted the multiconfiguration time-dependent Hartree methodology to solve the nuclear molecular Hamiltonian, and to address issues on the T-R couplings. Motivated by experimental X-ray observations on the CO2 orientation in the D and T sI cages, we aim to evaluate the effect of the CO2–water interaction on quantum dynamics. Thus, we first compared semiempirical and ab initio-based pair interaction model potentials against first-principles DFT-D calculations for ascertaining the importance of nonadditive many-body effects on such guest–host interactions. Our results reveal that the rotational and translational excited states quantum dynamics is remarkably different, with the pattern and density of states clearly affected by the underlying potential model. By analyzing the corresponding the probability density distributions of the calculated T-R eigenstates on both semiempirical and ab initio pair CO2–water nanocage potentials, we have extracted information on the altered CO2 guest local structure, and we discussed it in connection with experimental data on the orientation of the CO2 molecule in the D and T sI clathrate cages available from neutron diffraction and 13 C solid-state NMR studies, as well as in comparison with previous molecular dynamics simulations. Our calculations provide a very sensitive test of the potential quality by predicting the low-lying T-R states and corresponding transitions for the encapsulated CO2 molecule. As such spectroscopic observables have not been measured so far, our results could trigger further detailed experimental and theoretical investigations leading to a quantitative description of the present guest–host interactions.

Designing movesets providing high quality protein conformations remains a hard problem, especially when it comes to deform a long protein backbone segment, and a key building block to do so is the so-called tripeptide loop closure (TLC). Consider a tripeptide whose first and last bonds ( N 1 C α ; 1 and C α ; 3 C 3 ) are fixed, and so are all internal coordinates except the six ϕ ψ i = 1,2,3 dihedral angles associated to the three C α carbons. Under these conditions, the TLC algorithm provides all possible values for these six dihedral angles–there exists at most 16 solutions. TLC moves atoms up to ∼ 5 Å in one step and retains low energy conformations, whence its pivotal role to design move sets sampling protein loop conformations. In this work, we relax the previous constraints, allowing the last bond ( C α ; 3 C 3 ) to freely move in 3D space–or equivalently in a 5D configuration space. We exhibit necessary geometric constraints in this 5D space for TLC to admit solutions. Our analysis provides key insights on the geometry of solutions for TLC. Most importantly, when using TLC to sample loop conformations based on m consecutive tripeptides along a protein backbone, we obtain an exponential gain in the volume of the 5 m-dimensional configuration space to be explored.

The ongoing COVID-19 pandemic, and constant demand for new therapies in unmet clinical needs, necessitates strategies to identify drug candidates for rapid clinical deployment. Over the years, fragment-based drug design (FBDD) has emerged as a mainstream lead discovery strategy in academia, biotechnology start-ups, and large pharma. Chemical building block libraries are the fundamental component of virtually any FBDD campaign. Current trends focus on smaller and smarter libraries that offer synthetically amenable starting points for rational lead generation. Therefore, there remains an ever-increasing need for new methods to generate fragment libraries to seed early-stage drug discovery programs. Here, we present FRAGMENTISE—a new user-friendly, cross-platform tool for user-tunable retrosynthetic small-molecule fragmentation. FRAGMENTISE allows for visualization, similarity search, annotation, and in-depth analysis of the fragment databases in the medicinal chemistry context. FRAGMENTISE is available as standalone software for Linux, Windows, and macOS users, with a graphical interface or command-line version.

The Molecular Fractionation with Conjugate Caps (MFCC) method is a popular fragmentation method for the quantum-chemical treatment of proteins. However, it does not account for interactions between the amino acid fragments, such as intramolecular hydrogen bonding. Here, we present a combination of the MFCC fragmentation scheme with a second-order many-body expansion (MBE) that consistently accounts for all fragment–fragment, fragment–cap, and cap–cap interactions, while retaining the overall simplicity of the MFCC scheme with its chemically meaningful fragments. We show that with the resulting MFCC-MBE(2) scheme, the errors in the total energies of selected polypeptides and proteins can be reduced by up to one order of magnitude and relative energies of different protein conformers can be predicted accurately.

Generalized replica exchange with solute tempering (gREST) is one of the enhanced sampling algorithms for proteins or other systems with rugged energy landscapes. Unlike the replica-exchange molecular dynamics (REMD) method, solvent temperatures are the same in all replicas, while solute temperatures are different and are exchanged frequently between replicas for exploring various solute structures. Here, we apply the gREST scheme to large biological systems containing over one million atoms using a large number of processors in a supercomputer. First, communication time on a multi-dimensional torus network is reduced by matching each replica to MPI processors optimally. This is applicable not only to gREST but also to other multi-copy algorithms. Second, energy evaluations, which are necessary for the multistate bennet acceptance ratio (MBAR) method for free energy estimations, are performed on-the-fly during the gREST simulations. Using these two advanced schemes, we observed 57.72 ns/day performance in 128-replica gREST calculations with 1.5 million atoms system using 16,384 nodes in Fugaku. These schemes implemented in the latest version of GENESIS software could open new possibilities to answer unresolved questions on large biomolecular complex systems with slow conformational dynamics.

The symmetry-decomposed Voronoi deformation density (VDD) charge analysis is an insightful and robust computational tool to aid the understanding of chemical bonding throughout all fields of chemistry. This method quantifies the atomic charge flow associated with chemical-bond formation and enables decomposition of this charge flow into contributions of (1) orbital interaction types, that is, Pauli repulsive or bonding orbital interactions; (2) per irreducible representation (irrep) of any point-group symmetry of interacting closed-shell molecular fragments; and now also (3) interacting open-shell (i.e., radical) molecular fragments. The symmetry-decomposed VDD charge analysis augments the symmetry-decomposed energy decomposition analysis (EDA) so that the charge flow associated with Pauli repulsion and orbital interactions can be quantified both per atom and per irrep, for example, for σ, π, and δ electrons. This provides detailed insights into fundamental aspects of chemical bonding that are not accessible from EDA.

The surfaces of waimirite β- YF 3 $$ {\mathrm{YF}}_3 $$ have been studied for their fluorine and chlorine versus water affinity. Bonding patterns of HF, HCl, and H 2 O $$ {\mathrm{H}}_2\mathrm{O} $$ chemically adsorbed onto surfaces of (010), (100), (011), and (101) have been quantified by density functional theory applying energy decomposition analysis. We found that the adsorption of H 2 O $$ {\mathrm{H}}_2\mathrm{O} $$ is dominated by about 65% of electrostatics, which causes a low surface sensitivity and weak interactions. On the contrary, the adsorptions of HF and HCl are driven by strong hydrogen bonds resulting in a highly surface-dependent ratio of 30–60% electrostatic versus orbital contribution. Among the stoichiometric surfaces, the shortest and strongest hydrogen bonds and consequently most covalent bonding patterns are found within YF 3 · $$ {\mathrm{YF}}_3\cdotp $$ HCl. However, when including the preparation energy, each surface favors the adsorption of HF over HCl, which reproduces the higher affinity of yttrium towards fluoride over chloride, previously known for solutions, also for the solid state.

The numerical ill-conditioning associated with approximating an electron density with a convex sum of Gaussian or Slater-type functions is overcome by using the (extended) Kullback–Leibler divergence to measure the deviation between the target and approximate density. The optimized densities are non-negative and normalized, and they are accurate enough to be used in applications related to molecular similarity, the topology of the electron density, and numerical molecular integration. This robust, efficient, and general approach can be used to fit any non-negative normalized functions (e.g., the kinetic energy density and molecular electron density) to a convex sum of non-negative basis functions. We present a fixed-point iteration method for optimizing the Kullback–Leibler divergence and compare it to conventional gradient-based optimization methods. These algorithms are released through the free and open-source BFit package, which also includes a L2-norm squared optimization routine applicable to any square-integrable scalar function.

UV–VIS photoinduced events of tzA and tzG embedded into DNA and RNA are described by combining the Extended Multi-State Second-Order Perturbation Theory (XMS-CASPT2) and electrostatic embedding molecular mechanics methods (QM/MM). Our results point out that the S1 1(ππ* La) state is the bright state in both environments. After the photoexcitation to the S1 1(ππ* La) state, the electronic population evolves barrierless towards its minimum, from where the excess of energy can be dissipated by fluorescence. As the minimum energy crossing point structure between the ground and first bright states lies in a high-energy region, the direct internal conversion to the ground state is an unviable mechanism. Other spectroscopic properties (for instance, absorption and Stokes shifts) and comparisons with photochemical properties of canonical nucleobases are also provided.

A recursive scheme was proposed to calculate two-electron integrals of frequency-dependent Breit interactions in electronic structure calculations using Gaussian basis functions. As shown in a previous study [R. Ahlrichs, Phys. Chem. Chem. Phys. 8 (2006) 3072–3077], the vertical recurrence relation for the two-electron integrals of the general two-body potential is valid. In addition, the authors have shown that the horizontal case is also valid. Explicit expressions for generalized molecular incomplete gamma function corresponding to the frequency-dependent Gaunt and gauge potentials were then derived, along with their asymptotic formulas. In addition, an implementation for computing the generalized molecular incomplete gamma function was proposed. Through numerical calculations, the shape of the curves of the generalized molecular incomplete gamma functions were found to vary significantly from that of the zero-energy case with the increase in the energy variable.

We introduce a fermionic potential, v f , as a comprehensive measure of electron (de)localization in atomic-molecular systems. Unlike other common descriptors as ELF, LOL, etc., it characterizes all physical effects responsible for (de)localization of electrons, namely: an exchange hole depth, its tendency to change, a sensitivity of an exchange correlation hidden in a pair density and kinetic potential to local variations in electron density. Wells in the v f distribution correspond to the domains of maximum electron localization, while the potential's barriers prevent delocalization of electrons through them. It also estimates bond orders and successfully reveals the impact of chemical modifications or environmental effects on the delocalization of electrons in molecules and crystals. The v f components provide a unique opportunity to compare the influence of the mentioned physical effects on electron (de)localization. This merges physical and chemical views of electron delocalization using functions appearing in density functional theory.

A nonionizing ultrafast laser pulse of 20-fs duration with a peak amplitude electric-field ±E = 200 × 10−4 a.u. was simulated. It was applied to the ethene molecule to consider its effect on the electron dynamics, both during the application of the laser pulse and for up to 100 fs after the pulse was switched off. Four laser pulse frequencies ω = 0.2692, 0.2808, 0.2830, and 0.2900 a.u. were chosen to correspond to excitation energies mid-way between the (S1,S2), (S2,S3), (S3,S4) and (S4,S5) electronic states, respectively. Scalar quantum theory of atoms in molecules (QTAIM) was used to quantify the shifts of the C1C2 bond critical points (BCPs). Depending on the frequencies ω selected, the C1C2 BCP shifts were up to 5.8 times higher after the pulse was switched off compared with a static E-field with the same magnitude. Next generation QTAIM (NG-QTAIM) was used to visualize and quantify the directional chemical character. In particular, polarization effects and bond strengths, in the form of bond-rigidity vs. bond-flexibility, were found, for some laser pulse frequencies, to increase after the laser pulse was switched off. Our analysis demonstrates that NG-QTAIM, in partnership with ultrafast laser irradiation, is useful as a tool in the emerging field of ultrafast electron dynamics, which will be essential for the design, and control of molecular electronic devices.

A new genetic algorithm has been proposed focusing on direct ab initio potential energy surface (PES) global minima search. Besides the commonly used operators, this new approach uses an operator to: improve the initial cluster generation, classify and compare all generated clusters, and use machine learning to model the quantum PES used in parallel optimization. Part of the validation process for this methodology was done with C u n A u m ( n + m ≤ X for X = 14 , 19 , 38 , 55 ) and A u n A g n ( n = 10 , 20 , 30 , 40 , 50 , 60 , 70 , and 75). The results are in fair agreement with the literature and led to a new global minimum for C u 12 A u 7 . A search has been done for the lowest energies of L i n nanoclusters with 2–8 atoms using the DFT approach and for L i 3 , L i 4 , L i 2 H , L i 3 H using DLPNO-CCSD(T) approach. NQGA successfully performed the MP2 optimizations for ( H 2 O ) 11 cluster. In all cases, the proposed genetic algorithm located the previously reported global minima with very efficient performance. The new proposed methodology makes it possible to optimize cluster geometries directly using high-level ab initio methods relinquishing any bias introduced by a classical approach. Our results show that this proposed method has great potential applications due to its flexibility and efficiency in identifying global minima in the tested atomic systems.

The OCNH unit is one of the most frequently encountered structural motifs in rings in drugs which serves dual role as the proton donor through NH bond and proton acceptor through the CO bond. Here, we predicted the HB strength (Eint) of OCNH motif with H2O for commonly observed 37 rings in drugs with DFT method M06L/6-311++G(d,p). The HB strength is rationalized in terms of molecular electrostatic potential (MESP) topology parameters ΔVn(NH) and ΔVn(CO) which describe the relative electron deficient/rich nature of NH and CO, respectively, with respect to the reference formamide. The Eint of formamide is −10.0 kcal/mol whereas the Eint of ring systems is in the range −8.6 to −12.7 kcal/mol—a minor increase/decrease compared to the formamide. The variations in Eint are addressed using the MESP parameters ΔVn(NH) and ΔVn(CO) and proposed the hypothesis that a positive ΔVn(NH) enhances NH…Ow interaction while a negative ΔVn(CO) enhances the CO…Hw interaction. The hypothesis is proved by expressing Eint jointly as ΔVn(NH) and ΔVn(CO) and also verified for twenty FDA approved drugs. The predicted Eint for the drugs using ΔVn(NH) and ΔVn(CO) agreed well with the calculated Eint. The study confirms that even delicate variations in the electronic feature of a molecule can be quantified in terms of MESP parameters and they provide a priori prediction of the HB strength. The MESP topology analysis is recommended to understand the tunability of HB strength in drug motifs.

The Fenton system in the presence of nitrilotriacetate (NTA) ligand is studied by DFT approach. The calculations show that complexation of Fe(II) with NTA significantly facilitates the H2O2 activation. The ferric-hydroperoxo intermediate NTAFe(III)OOH predominantly decays via the disproportionation into NTAFe(II)OH2 and NTAFe(IV)O involving the formation of a μ-1,2-hydroperoxo-bridged biferric intermediate. In this mechanism, the bridged hydroperoxo is reduced by hydroperoxo ligand rather than by Fe(III). On the one hand, the NTAFe(III)OOH is sluggish to undergo hydrogen abstraction; on the other hand, it is a good nucleophile that may perform aldehyde deformylation. The present calculations suggest that both ˙OH and Fe(IV)O are generated in the NTA-assisted Fenton system. However, the polycarboxylate ligand provides a favorable environment for H2O2 to accumulate around iron ion through hydrogen bonding. This promotes the quenching of Fe(IV)O by H2O2, rationalizing why the Fe(IV)O species is hardly detected in the NTA-assisted Fenton system.

Understanding the molecular basis for protein stability requires a thermodynamic analysis of protein folding. Thermodynamic analysis is often performed by sampling many atomistic conformations using molecular simulations that employ either explicit or implicit water models. However, it remains unclear to what extent thermodynamic results from different solvation models are reliable at the molecular level. In this study, we quantify the influence of both solvation models on folding stability at the individual backbone and side chain resolutions. We assess the residue-specific folding free energy components of a β-sheet protein and a helical protein using trajectories resulting from TIP3P explicit and generalized Born/surface area implicit solvent simulations of model proteins. We found that the thermodynamic discrepancy due to the implicit solvent mostly originates from charged side chains, followed by the under-stabilized hydrophobic ones. In contrast, the contributions of backbone residue in both proteins were comparable for explicit and implicit water models. Our study lays out the foundation for detailed thermodynamic assessment of solvation models in the context of protein simulation.

The possibilities and problems to predict excited-state acidities and basicities in water with electronic structure calculations combined with a continuum solvation model are investigated for a test set of photoacids and photobases. Different error sources, like errors in the ground-state p K a values, the excitation energies in solution for the neutral and (de-)protonated species, basis set effects, and contributions beyond implicit solvation are investigated and their contributions to the total error in p K a ∗ are discussed. Density functional theory in combination with the conductor like screening model for real solvents and an empirical linear Gibbs free energy relationship are used to predict the ground-state p K a values. For the test set, this approach gives more accurate p K a values for the acids than for the bases. Time-dependent density-functional theory (TD-DFT) and second-order wave function methods in combination with the conductor like screening model are applied to compute excitation energies in water. Some TD-DFT functionals fail for several species to predict correctly the order of the lowest excitations. Where experimental data for absorption maxima in water is available, the implicit solvation model leads with the applied electronic structure methods in most cases for the excitation energies in water to an overestimation for the protonated and to an underestimation for the deprotonated species. The magnitude and sign of the errors depend on the hydrogen bond donating and accepting ability of the solute. We find that for aqueous solution this results generally in an underestimation in the p K a changes from the ground to the excited state for photoacids and an overestimation for photobases.

Stabilizing the exotic chemical species possessing multiple bonds is often extremely challenging due to insufficient orbital overlap, especially involving one heavier element. Bulky aryl groups and/or carbene as ligand have previously stabilized the SiSi, GeGe, and BB triple bonds. Herein, theoretical calculations have been carried out to shed light on the stability and bonding of elusive silaboryne/germaboryne (Si/GeB triple bond) stabilized by donor base ligands ((cAAC)BE(Me)(L); E = Si, L = cAACMe, NHCMe, PMe3; E = Ge, L = cAACMe). The heavier analogues (Sn, Pb) have been further studied for comparison. Additionally, the effects of bulky substituents at the Si and N atoms on the structural parameters and stability of those species have been investigated. Energy decomposition analysis coupled with natural orbital for chemical valence (EDA-NOCV; for Si) showed that cAAC/NHC ligands could stabilize the exotic BSi-Me species more efficiently than PMe3 ligands. The BSi partial triple bond of the corresponding species possesses a mixture of one covalent electron sharing BSi σ-bond and two dative π-bonds (B ← Si, B → Si).

The semiempirical GFNn-xTB ( n = 1 , 2 $$ n=1,2 $$ ) tight-binding methods are extended with a spin-dependent energy term (spin-polarization), enabling the fast and efficient screening of different spin states for transition metal complexes. While GFNn-xTB methods inherently can not differentiate properly between high-spin (HS) and low-spin (LS) states, this shortcoming is corrected with the presented methods termed spGFNn-xTB. The performance of spGFNn-xTB methods for spin state energy splittings is evaluated on a newly compiled benchmark set of 90 complexes (27 HS and 63 LS complexes) containing 3d, 4d, and 5d transition metals (termed TM90S) employing DFT references at the TPSSh-D4/def2-QZVPP level of theory. The challenging TM90S set contains complexes with charges between − $$ - $$ 4 and +3, spin multiplicities between 1 and 6, and spin-splitting energies that range from − $$ - $$ 47.8 to 146.6 kcal/mol with a mean average of 32.2 kcal/mol. On this set the (sp)GFNn-xTB methods, the PM6-D3H4 method, and the PM7 method are evaluated with spGFN1-xTB yielding the lowest MAD of 19.6 kcal/mol followed by spGFN2-xTB with 24.8 kcal/mol. While for the 4d and 5d subsets small or no improvements are observed with spin-polarization, large improvements are obtained for the 3d subset with spGFN1-xTB yielding the smallest MAD of 14.2 kcal/mol followed by spGFN2-xTB with 17.9 kcal/mol and PM6-D3H4 with 28.4 kcal/mol. The correct sign of the spin state splittings is obtained with spGFN2-xTB in 89% of all cases closely followed by spGFN1-xTB with 88%. On the full set, a pure semiempirical vertical spGFN2-xTB//GFN2-xTB-based workflow for screening purposes yields a slightly better MAD of 22.2 kcal/mol due to error compensation, while being qualitative correct for one additional case. In combination with their low computational cost (scanning spin states in seconds), the spGFNn-xTB methods represent robust tools for pre-screening steps of spin state calculations and high-throughput workflows.

This study is carried out using the COGITO force field to determine whether the thermodynamic melting point of pure triacylglyceride crystals can be predicted using molecular dynamics simulations. The triacylglycerides used in this study are both saturated and unsaturated, as well as symmetrical and asymmetrical, to test the robustness of both the force field and the direct heating methodology described in this paper. Given the nonequilibrium nature of a melting system, a larger number of simulations are required to ensure that the results are sufficiently converged, that is, with little fluctuation and a small confidence interval. The study also highlights the importance of the presence of defects, in this case as voids, to lower the melting nucleation energy barrier of the crystals and avoid superheating of the systems being tested. The size of these defects is much larger than what would be found in a physical crystal, however, the simple and robust procedure that was developed allows the accurate prediction of melting points of the different triacylglycerides.