The chain-of-states (CoS) constant advance replicas (CAR) method and its climbing image variant (CI-CAR) for locating minimum energy paths (MEPs) and transition states are reported. The CAR algorithm applies the Lagrange multiplier method for imposing holonomic constraints on a chain-of-replicas, aiming to maintain equal mass-weighted/scaled root-mean-square (RMS) distances between the adjacent replicas by removing the sliding-down displacements contributed by the potential gradients during path optimization. Two contextual regularization schemes with clear geometrical interpretations are implemented to jointly promote high convergence and numerical robustness of the CAR algorithm. We show that the constrained reaction path can be solved normally within 5 steps of Lagrange multiplier updates with remarkably high numerical precision via the CAR approach. The efficacy of the CAR methods is demonstrated by testing on multiple analytical, classical, and quantum mechanical transition paths: the Müller potential, the alanine dipeptide isomerization, the helix unwinding of the VIVITLVMLKKK 12-mer peptide, and the Baker set of reactions. We also explore the potential of applying adaptive momentum (AdaM) optimizers for locating optimal transition paths under complex conformational changes. Most importantly, we discuss extensively the differences and connections between our newly proposed CAR methods and several related methods, with focuses on the reaction path with holonomic constraints (RPCons) approach of Brokaw et al. [J. Chem. Theory Comput. 2009, 5 (8), 2050-2061] and the state-of-the-art string method (SM) of E et al. [J. Chem. Phys. 2007, 126 (16), 164103]. The CAR approach represents a latest update to the general theoretical framework of reaction path finding algorithms in the two-ended CoS regime.

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 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 H2 O2 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 H2 O2 to accumulate around iron ion through hydrogen bonding. This promotes the quenching of Fe(IV)O by H2 O2 , rationalizing why the Fe(IV)O species is hardly detected in the NTA-assisted Fenton system.

The main protease (Mpro) of SARS-CoV-2 plays an essential role in the virus life cycle and is considered a key target for therapeutic development. This study explores the inhibition mechanism of SARS-CoV-2 Mpro by ebselen, an organoselenium drug that shows potent inhibitory activity. By using a combination of multiple computational methods including molecular docking, molecular dynamics simulations, and density functional theory calculations, the complete covalent inhibition process of ebselen is simulated for the first time. Two possible pathways with different bound conformations of ebselen are identified. The hydrolysis of the enzyme-ebselen adduct is found to be the rate-determining step. The simulation results show that the behavior of water molecules at the hydrolysis site is crucial to distinguish the two paths energetically. Our simulations, which are in agreement with existing experimental results, provide a theoretical basis for the rational design and mechanism exploration of ebselen-based inhibitors.

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.

Polymer-grafted hybrid materials have been ubiquitously employed in various engineering applications. The design of these hybrid materials with superior performances requires a molecularly detailed understanding of the structure and dynamics of the polymer brushes and their interactions with the grafting substrate. Molecular dynamics (MD) simulations are very well suited for the study of these materials which can provide molecular insights into the effects of polymer composition and length, grafting density, substrate composition and curvatures, and nanoconfinement. However, few existing tools are available to generate such systems, which would otherwise reduce the barrier of preparation for such systems to enable high throughput simulations. Here polyGraft, a general, flexible, and easy to use Python program, is introduced for automated generation of molecular structure and topology of polymer grafted hybrid materials for MD simulations purposes, ranging from polymer brushes grafted to hard substrates, to densely grafted bottlebrush polymers. polyGraft is openly accessible on GitHub (https://github.com/nanogchen/polyGraft).

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. In this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

A computational study of the mechanisms and kinetics of the aqueous reactions of a hydrogen atom with haloacetates is presented. Several mechanisms in the close competition are observed, such as proton-coupled electron transfer (PCET), hydrogen atom transfer (HAT), and halogen abstraction (XA). Computations predict that dechlorination takes place via PCET mechanisms and not via XA, as stated earlier, while XA is the fastest mechanism for IAc- . The reaction rate constants are reasonably well predicted within the theoretically most reliable canonical variational transition state theory with small curvature tunneling corrections and compared with the experimental ones. To reproduce the experimental rate constants of the debromination process it is necessary to include the PCET and XA cumulative values. Small curvature tunneling corrections to the rate constants are the highest for HAT and PCET mechanisms, up to 70 times larger than the Wigner, while variational effects for XA mechanisms are very small.

Cyclopropane ring is a very common motif in organic/bio-organic compounds. The chemical bonding of this strained ring is taught to all chemistry students. This three-membered cyclic, C3 ring is quite reactive which has attracted both, synthetic and theoretical chemists to rationalize/correlate its stability and bonding with its reactivity and physical properties over a century. There are a few bonding models (mainly the Bent-Bond model and Walsh model) of this C3 ring that are debated to date. Herein, we have carried out energy decomposition analysis coupled with natural orbital for chemical valence (EDA-NOCV) to study the two most reactive bonds of cyclopropane rings of 49 different organic compounds containing different functional groups to obtain a much deeper bonding insight toward a more general bonding model of this class of compounds. The EDA-NOCV analyses of fragment orbitals and susequent bond formation revealed that the nature of the CC bond of the cyclopropane (splitting two bonds at a time out of three CC bonds) ring is preferred to form two dative covalent CC bonds (between a singlet olefin-fragment and an excited singlet carbene-fragment with a vacant sp2 orbital and a filled p-orbital) for the majority (37/49) of compounds over two covalent electron sharing bonds in some (7/49) compounds (between an excited triplet olefin and triplet carbene), while a few (5/49) compounds show flexibility to adopt either the electron sharing or dative covalent bond as both are equally possible. The effects of functional groups on the nature of chemical bond in cyclopropane rings have been studied in detail. Our bonding analyses are in line with the QTAIM analyses which produce small negative values of the Laplacian, significantly positive values of bond ellipticity, and accumulation of electron densities around the ring critical point of C3 -rings. These corresponding QTAIM parameters of C3 -rings are quite different for CC single bonds of normal hydrocarbons as expected. The chemical bonding in the majority of cyclopropane rings can be very similar to those of metal-olefin systems.

We comment on an excited-state localization method recently proposed by Blanc et al. (J. Comput. Chem. 2023, 44, 105). Elaborate comparisons are made to demonstrate that their method is a less-comprehensive version of the diabatization method proposed by us 2 years earlier (J. Phys. Chem. Lett. 2021, 12, 1032).

The semiempirical GFNn-xTB ( 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.

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.

As emphasized in a recent review article (Chem. Rev. 2022, 122, 14180), organic solar cell (OSC) photoconversion efficiency has been rapidly evolving with results increasingly comparable to those of traditional inorganic solar cells. Historically, OSC performance improvement focused first on the morphology of P3HT: PC61 BM solar cells then went through different stages to shift lately interest towards nonfullerene acceptors (NFAs) as a replacement of PC61 BM acceptor (ACC) molecule. Here, we use density-functional theory (DFT) and time-dependent DFT to investigate four novel NFAs of A-D-A (acceptor-donor-acceptor) form derived from the recently synthesized IDIC-4Cl (Dyes Pigm. 2019, 166, 196). Our level of theory is carefully evaluated for IDIC-4Cl and then applied to the four novel NFAs in order to understand how chemical modifications lead to physical changes in cyclic voltammetry (CV) frontier molecular orbital energies and absorption spectra in solution. Finally we design and apply a new type of Scharber plot for NFAs based upon some simple but we think reasonable assumptions. Unlike the original Scharber plots where a larger DON band gap favors a larger PCE, our modified Scharber plot reflects the fact that a smaller ACC band gap may favor PCE by filling in gaps in the DON acceptor spectrum. We predict that only the candidate molecule with the least good acceptor A, with the highest frontier molecular orbital energies, and one of the larger CV lowest unoccupied molecular orbital (LUMO) -  highest unoccupied molecular orbital (HOMO) gaps, will yield a PM6:ACC PCE exceeding that of the parent IDIC-4Cl ACC. This candidate also shows the largest oscillator strength for the primary 1 (HOMO, LUMO) charge- transfer transition and the largest degree of delocalization of charge transfer of any of the ACC molecules investigated here.

The junChS-F12 composite method has been improved by means of the latest implementation of the CCSD(F12*)(T+) ansatz and validated for the thermochemistry of molecules containing atoms of the first three rows of the periodic table. A thorough benchmark showed that this model, in conjunction with cost-effective revDSD-PBEP86-D3(BJ) reference geometries, offers an optimal compromise between accuracy and computational cost. If improved geometries are sought, the most effective option is to add MP2-F12 core-valence correlation corrections to CCSD(T)-F12b/jun-cc-pVTZ geometries without the need of performing any extrapolation to the complete basis set limit. In the same vein, CCSD(T)-F12b/jun-cc-pVTZ harmonic frequencies are remarkably accurate without any additional contribution. Pilot applications to noncovalent intermolecular interactions, conformational landscapes, and tautomeric equilibria confirm the effectiveness and reliability of the model.