Towards a converged strategy for including microsolvation in reaction mechanism calculations

Exploring borderline SN1-SN2 mechanisms: the role of explicit solvation protocols in the DFT investigation of isopropyl chloride

Nucleophilic substitution at saturated carbon is a crucial class of organic reactions, playing a pivotal role in various chemical transformations that yield valuable compounds for society. Despite the well-established SN1 and SN2 mechanisms, secondary substrates, particularly in solvolysis reactions, often exhibit a borderline pathway. A molecular-level understanding of these processes is fundamental for developing more efficient chemical transformations. Typically, quantum-chemical simulations of the solvent medium combine explicit and implicit solvation methods. The configuration of explicit molecules can be defined through top-down approaches, such as Monte Carlo (MC) calculations for generating initial configurations, and bottom-up methods that involve user-dependent protocols to add solvent molecules around the substrate. Herein, we investigated the borderline mechanism of the hydrolysis of a secondary substrate, isopropyl chloride (iPrCl), at DFT-M06-2X/aug-cc-pVDZ level, employing explicit and explicit + implicit protocols. Top-down and bottom-up approaches were employed to generate substrate-solvent complexes of varying number (n = 1, 3, 5, 7, 9, and 12) and configurations of H2O molecules. Our findings consistently reveal that regardless of the solvation approach, the hydrolysis of iPrCl follows a loose-SN2-like mechanism with nucleophilic solvent assistance. Increasing the water cluster around the substrate in most cases led to reaction barriers of ΔH‡ ≈ 21 kcal mol-1, with nine water molecules from MC configurations sufficient to describe the reaction. The More O'Ferrall-Jencks plot demonstrates an SN1-like character for all transition state structures, showing a clear merged profile. The fragmentation activation strain analyses indicate that energy barriers are predominantly controlled by solvent-substrate interactions, supported by the leaving group stabilization assessed through CHELPG atomic charges.

COSMO Models for the Pharmaceutical Development of Parenteral Drug Formulations

The aqueous solubility of active pharmaceutical ingredients is one of the most important features to be considered during the development of parenteral formulations in the pharmaceutical industry. Computational modelling has become in the last years an integral part of pharmaceutical development. In this context, ab initio computational models, such as COnductor-like Screening MOdel (COSMO), have been proposed as promising tools for the prediction of results without the effective use of resources. Nevertheless, despite the clear evaluation of computational resources, some authors had not achieved satisfying results and new calculations and algorithms have been proposed over the years to improve the outcomes. In the development and production of aqueous parenteral formulations, the solubility of Active Pharmaceutical Ingredients (APIs) in an aqueous and biocompatible vehicle is a decisive step. This work aims to study the hypothesis that COSMO models could be useful in the development of new parenteral formulations, mainly aqueous ones.

Impacts of noncovalent interactions involving sulfur atoms on protein stability, structure, folding, and bioactivity

This review discusses the various types of noncovalent interactions in which sulfur atoms participate and their effects on protein stability, structure, folding and bioactivity. Current approaches and recommendations for modelling these noncovalent interactions (in terms of both geometries and interaction energies) are highlighted.

Reactivity of Covalent Fragments and Their Role in Fragment Based Drug Discovery

Fragment based drug discovery has long been used for the identification of new ligands and interest in targeted covalent inhibitors has continued to grow in recent years, with high profile drugs such as osimertinib and sotorasib gaining FDA approval. It is therefore unsurprising that covalent fragment-based approaches have become popular and have recently led to the identification of novel targets and binding sites, as well as ligands for targets previously thought to be 'undruggable'. Understanding the properties of such covalent fragments is important, and characterizing and/or predicting reactivity can be highly useful. This review aims to discuss the requirements for an electrophilic fragment library and the importance of differing warhead reactivity. Successful case studies from the world of drug discovery are then be examined.

Best-Practice DFT Protocols for Basic Molecular Computational Chemistry

Nowadays, many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share of these quantum-chemical calculations applies density functional theory (DFT) evaluated in atomic-orbital basis sets. This work provides best-practice guidance on the numerous methodological and technical aspects of DFT calculations in three parts: Firstly, we set the stage and introduce a step-by-step decision tree to choose a computational protocol that models the experiment as closely as possible. Secondly, we present a recommendation matrix to guide the choice of functional and basis set depending on the task at hand. A particular focus is on achieving an optimal balance between accuracy, robustness, and efficiency through multi-level approaches. Finally, we discuss selected representative examples to illustrate the recommended protocols and the effect of methodological choices.

Automated Molecular Cluster Growing for Explicit Solvation by Efficient Force Field and Tight Binding Methods

An automated and broadly applicable workflow for the description of solvation effects in an explicit manner is introduced. This method, termed quantum cluster growth (QCG), is based on the semiempirical GFN2-xTB/GFN-FF methods, enabling efficient geometry optimizations and MD simulations. Fast structure generation is provided using the intermolecular force field xTB-IFF. Additionally, the approach uses an efficient implicit solvation model for the electrostatic embedding of the growing clusters. The novel QCG procedure presents a robust cluster generation tool for subsequent application of higher-level (e.g., DFT) methods to study solvation effects on molecular geometries explicitly or to average spectroscopic properties over cluster ensembles. Furthermore, the computation of the solvation free energy with a supermolecular approach can be carried out with QCG. The underlying growing process is physically motivated by computing the leading-order solute-solvent interactions first and can account for conformational and chemical changes due to solvation for low-energy barrier processes. The conformational space is explored with the NCI-MTD algorithm as implemented in the CREST program, using a combination of metadynamics and MD simulations. QCG with GFN2-xTB yields realistic solution geometries and reasonable solvation free energies for various systems without introducing many empirical parameters. Computed IR spectra of some solutes with QCG show a better match to the experimental data compared to well-established implicit solvation models.

Solvation Free Energies in Subsystem Density Functional Theory

For many chemical processes the accurate description of solvent effects are vitally important. Here, we describe a hybrid ansatz for the explicit quantum mechanical description of solute-solvent and solvent-solvent interactions based on subsystem density functional theory and continuum solvation schemes. Since explicit solvent molecules may compromise the scalability of the model and transferability of the predicted solvent effect, we aim to retain both, for different solutes as well as for different solvents. The key for the transferability is the consistent subsystem decomposition of solute and solvent. The key for the scalability is the performance of subsystem DFT for increasing numbers of subsystems. We investigate molecular dynamics and stationary point sampling of solvent configurations and compare the resulting (Gibbs) free energies to experiment and theoretical methods. We can show that with our hybrid model reaction barriers and reaction energies are accurately reproduced compared to experimental data.

Selective Acid-Catalyzed Hydroarylation of Nonactivated Alkenes with Aniline Assisted by Hexafluoroisopropanol

The catalytic hydroarylation of nonactivated alkenes with aniline is a reaction of high interest, aiming at providing C-functionalized aniline derivatives that are important precursors for the fabrication of polyurethanes. However, this reaction remains a longstanding goal of catalysis, as it requires one to simultaneously address two important goals: (1) the very low reactivity of nonactivated alkenes and (2) control of the hydroarylation/hydroamination selectivity. As a result, the hydroarylation of aniline is mostly restricted to activated alkenes (i.e., featuring ring strain, conjugation, or activation with electron-donating or -withdrawing groups). Here we show that the combination of bismuth triflate and hexafluoroisopropanol (HFIP) leads to the formation of highly active catalytic species capable of promoting the hydroarylation of various nonactivated alkenes, such as 1-octene, 1-heptene, and 1-undecene, among others, with aniline with high selectivity (71-92%). Through a combined experimental and computational investigation, we propose a reaction pathway where HFIP stabilizes the rate-determining transition state through a H-bond interaction with the triflate anion, thus assisting the acid catalyst in the hydroarylation of nonactivated alkenes. From a practical point of view, this work opens a catalytic access to C-functionalized aniline derivatives from two cheap and abundant feedstocks in a 100% atom-economical fashion.

Beyond Continuum Solvent Models in Computational Homogeneous Catalysis

In homogeneous catalysis solvent is an inherent part of the catalytic system. As such, it must be considered in the computational modeling. The most common approach to include solvent effects in quantum mechanical calculations is by means of continuum solvent models. When they are properly used, average solvent effects are efficiently captured, mainly those related with solvent polarity. However, neglecting atomistic description of solvent molecules has its limitations, and continuum solvent models all alone cannot be applied to whatever situation. In many cases, inclusion of explicit solvent molecules in the quantum mechanical description of the system is mandatory. The purpose of this article is to highlight through selected examples what are the reasons that urge to go beyond the continuum models to the employment of micro-solvated (cluster-continuum) of fully explicit solvent models, in this way setting the limits of continuum solvent models in computational homogeneous catalysis. These examples showcase that inclusion of solvent molecules in the calculation not only can improve the description of already known mechanisms but can yield new mechanistic views of a reaction. With the aim of systematizing the use of explicit solvent models, after discussing the success and limitations of continuum solvent models, issues related with solvent coordination and solvent dynamics, solvent effects in reactions involving small, charged species, as well as reactions in protic solvents and the role of solvent as reagent itself are successively considered.

Melding of Experiment and Theory Illuminates Mechanisms of Metal-Catalyzed Rearrangements: Computational Approaches and Caveats

This review summarizes approaches and caveats in computational modeling of transition-metal-catalyzed sigmatropic rearrangements involving carbene transfer. We highlight contemporary examples of combined synthetic and theoretical investigations that showcase the synergy achievable by integrating experiment and theory.

1 Introduction

2 Mechanistic Models

3 Theoretical Approaches and Caveats

3.1 Recommended Computational Tools

3.2 Choice of Functional and Basis Set

3.3 Conformations and Ligand-Binding Modes

3.4 Solvation

4 Synergy of Experiment and Theory – Case Studies

4.1 Metal-Bound or Free Ylides?

4.2 Conformations and Ligand-Binding Modes of Paddlewheel Complexes

4.3 No Metal, Just Light

4.4 How To ‘Cope’ with Nonstatistical Dynamic Effects

5 Outlook

Disentangling the complex network of non-covalent interactions in fenchone hydrates via rotational spectroscopy and quantum chemistry

The hydrates of the monoterpenoid fenchone (C₁₀H₁₆O)·(H₂O)_n (n = 1, 2, 3) were investigated by both computational chemistry and microwave spectroscopy. Two monohydrates, three dihydrates and for the first time three trihydrates were identified through the observation of the parent and ¹⁸O isotopologues in the rotational spectrum from 2 to 20 GHz. For each hydrate, the sets of rotational constants enabled the determination of the substitution coordinates of the oxygen water atoms as well as an effective structure accounting for the arrangement of the water molecules around fenchone. The hydrates consist of water chains anchored to fenchone by a -CO⋯H-O hydrogen bond and further stabilized by numerous -H-O⋯H-C- secondary hydrogen bonds with the alkyl hydrogen atoms of fenchone.

Efficient Quantum-Chemical Calculations of Acid Dissociation Constants from Free-Energy Relationships

The calculation of acid dissociation constants (pK_a) is an important task in computational chemistry and chemoinformatics. Theoretically and with minimal empiricism, this is possible from computed acid dissociation free energies via so-called linear free-energy relationships. In this study some modifications are introduced to the latter, providing a straightforward, broadly applicable protocol with an adjustable degree of sophistication for quantum chemistry-based calculations of pK_a in water. It targets a wide pK_a range (∼70 units) and medium-sized, flexible molecules. Herein, a focus is set on the recently published r²SCAN-3c and related efficient composite density functionals and the semiempirical GFN2-xTB method, including a newly introduced energy correction for heterolytic dissociation, both in combination with implicit solvation models. The performance is evaluated in comparison with experimental data, showing mean errors often smaller than a targeted 1 pK_a unit accuracy. Larger deviations are observed only upon inclusion of challenging highly negative (<-5) or positive (>15) pK_a values. Among all those tested, it is found that B97-3c is the best performing functional, although rather independently of the density functional theory (DFT) method used; low root-mean-square errors of 0.8-1.0 pK_a units for typical drugs are obtained. For optimal performance, it is recommended to employ DFT functional specific free-energy relationship parameters. Additionally, a significant conformational dependence of the pK_a values is revealed and quantified for some nonrigid drug molecules.

Mechanisms of a Cyclobutane-Fused Lactone Hydrolysis in Alkaline and Acidic Conditions

Searching for functional polyesters with stability and degradability is important due to their potential applications in biomedical supplies, biomass fuel, and environmental protection. Recently, a cyclobutane-fused lactone (CBL) polymer was experimentally found to have superior stability and controllable degradability through hydrolysis reactions after activation by mechanical force. In order to provide a theoretical basis for developing new functional degradable polyesters, in this work, we performed a detailed quantum chemical study of the alkaline and acidic hydrolysis of CBL using dispersion-corrected density functional theory (DFT-D3) and mixed implicit/explicit solvent models. Various possible hydrolysis mechanisms were found: B_AC2 and B_AL2 in the alkaline condition and A_AC2, A_AL2, and A_AL1 in the acidic condition. Our calculations indicated that CBL favors the B_AC2 and A_AC2 mechanisms in alkaline and acidic conditions, respectively. In addition, we found that incorporating explicit water solvent molecules is highly necessary because of their strong hydrogen-bonding with reactant/intermediate/product molecules.

Quantum Chemical Microsolvation by Automated Water Placement

We developed a quantitative approach to quantum chemical microsolvation. Key in our methodology is the automatic placement of individual solvent molecules based on the free energy solvation thermodynamics derived from molecular dynamics (MD) simulations and grid inhomogeneous solvation theory (GIST). This protocol enabled us to rigorously define the number, position, and orientation of individual solvent molecules and to determine their interaction with the solute based on physical quantities. The generated solute-solvent clusters served as an input for subsequent quantum chemical investigations. We showcased the applicability, scope, and limitations of this computational approach for a number of small molecules, including urea, 2-aminobenzothiazole, (+)-syn-benzotriborneol, benzoic acid, and helicene. Our results show excellent agreement with the available ab initio molecular dynamics data and experimental results.

Efficient Quantum Chemical Calculation of Structure Ensembles and Free Energies for Nonrigid Molecules

The application of quantum chemical, automatic multilevel modeling workflows for the determination of thermodynamic (e.g., conformation equilibria, partition coefficients, pK_a values) and spectroscopic properties of relatively large, nonrigid molecules in solution is described. Key points are the computation of rather complete structure (conformer) ensembles with extremely fast but still reasonable GFN2-xTB or GFN-FF semiempirical methods in the CREST searching approach and subsequent refinement at a recently developed, accurate r²SCAN-3c DFT composite level. Solvation effects are included in all steps by accurate continuum solvation models (ALPB, (D)COSMO-RS). Consistent inclusion of thermostatistical contributions in the framework of the modified rigid-rotor-harmonic-oscillator approximation (mRRHO) based on xTB/FF computed PES is also recommended.