Optimal π-Stacking Interaction Energies in Parallel-Displaced Aryl/Aryl Dimers are Predicted by the Dimer Heavy Atom Count

Small-Basis Set Density-Functional Theory Methods Corrected with Atom-Centered Potentials

Density functional theory (DFT) is currently the most popular method for modeling noncovalent interactions and thermochemistry. The accurate calculation of noncovalent interaction energies, reaction energies, and barrier heights requires choosing an appropriate functional and, typically, a relatively large basis set. Deficiencies of the density-functional approximation and the use of a limited basis set are the leading sources of error in the calculation of noncovalent and thermochemical properties in molecular systems. In this article, we present three new DFT methods based on the BLYP, M06-2X, and CAM-B3LYP functionals in combination with the 6-31G* basis set and corrected with atom-centered potentials (ACPs). ACPs are one-electron potentials that have the same form as effective-core potentials, except they do not replace any electrons. The ACPs developed in this work are used to generate energy corrections to the underlying DFT/basis-set method such that the errors in predicted chemical properties are minimized while maintaining the low computational cost of the parent methods. ACPs were developed for the elements H, B, C, N, O, F, Si, P, S, and Cl. The ACP parameters were determined using an extensive training set of 118655 data points, mostly of complete basis set coupled-cluster level quality. The target molecular properties for the ACP-corrected methods include noncovalent interaction energies, molecular conformational energies, reaction energies, barrier heights, and bond separation energies. The ACPs were tested first on the training set and then on a validation set of 42567 additional data points. We show that the ACP-corrected methods can predict the target molecular properties with accuracy close to complete basis set wavefunction theory methods, but at a computational cost of double-ζ DFT methods. This makes the new BLYP/6-31G*-ACP, M06-2X/6-31G*-ACP, and CAM-B3LYP/6-31G*-ACP methods uniquely suited to the calculation of noncovalent, thermochemical, and kinetic properties in large molecular systems.

Fast and Accurate Quantum Mechanical Modeling of Large Molecular Systems Using Small Basis Set Hartree-Fock Methods Corrected with Atom-Centered Potentials

There has been significant interest in developing fast and accurate quantum mechanical methods for modeling large molecular systems. In this work, by utilizing a machine learning regression technique, we have developed new low-cost quantum mechanical approaches to model large molecular systems. The developed approaches rely on using one-electron Gaussian-type functions called atom-centered potentials (ACPs) to correct for the basis set incompleteness and the lack of correlation effects in the underlying minimal or small basis set Hartree-Fock (HF) methods. In particular, ACPs are proposed for ten elements common in organic and bioorganic chemistry (H, B, C, N, O, F, Si, P, S, and Cl) and four different base methods: two minimal basis sets (MINIs and MINIX) plus a double-ζ basis set (6-31G*) in combination with dispersion-corrected HF (HF-D3/MINIs, HF-D3/MINIX, HF-D3/6-31G*) and the HF-3c method. The new ACPs are trained on a very large set (73 832 data points) of noncovalent properties (interaction and conformational energies) and validated additionally on a set of 32 048 data points. All reference data are of complete basis set coupled-cluster quality, mostly CCSD(T)/CBS. The proposed ACP-corrected methods are shown to give errors in the tenths of a kcal/mol range for noncovalent interaction energies and up to 2 kcal/mol for molecular conformational energies. More importantly, the average errors are similar in the training and validation sets, confirming the robustness and applicability of these methods outside the boundaries of the training set. In addition, the performance of the new ACP-corrected methods is similar to complete basis set density functional theory (DFT) but at a cost that is orders of magnitude lower, and the proposed ACPs can be used in any computational chemistry program that supports effective-core potentials without modification. It is also shown that ACPs improve the description of covalent and noncovalent bond geometries of the underlying methods and that the improvement brought about by the application of the ACPs is directly related to the number of atoms to which they are applied, allowing the treatment of systems containing some atoms for which ACPs are not available. Overall, the ACP-corrected methods proposed in this work constitute an alternative accurate, economical, and reliable quantum mechanical approach to describe the geometries, interaction energies, and conformational energies of systems with hundreds to thousands of atoms.

π-Extended dibenzo[g,p]chrysenes

Two different series of π-extended dibenzo[g,p]chrysenes are synthesized. The experimental and DFT data showed the significant effects of both position and substituent on the optoelectronic and charge delocalization behavior.

Physical Mechanisms Governing Substituent Effects on Arene-Arene Interactions in a Protein Milieu

Arene-arene interactions play important roles in protein-ligand complex formation. Here, we investigate the characteristics of arene-arene interactions between small organic molecules and aromatic amino acids in protein interiors. The study is based on X-ray crystallographic data and quantum mechanical calculations using the enzyme acetylcholinesterase and selected inhibitory ligands as a model system. It is shown that the arene substituents of the inhibitors dictate the strength of the interaction and the geometry of the resulting complexes. Importantly, the calculated interaction energies correlate well with the measured inhibitor potency. Non-hydrogen substituents strengthened all interaction types in the protein milieu, in keeping with results for benzene dimer model systems. The interaction energies were dispersion-dominated, but substituents that induced local dipole moments increased the electrostatic contribution and thus yielded more strongly bound complexes. These findings provide fundamental insights into the physical mechanisms governing arene-arene interactions in the protein milieu and thus into molecular recognition between proteins and small molecules.

Tuning Stacking Interactions between Asp-Arg Salt Bridges and Heterocyclic Drug Fragments

Stacking interactions can play an integral role in the strength and selectivity of protein-drug binding and are of particular interest given the ubiquity and variety of heterocyclic fragments in drugs. In addition to traditional stacking interactions between aromatic rings, stacking interactions involving heterocyclic drug fragments and protein salt bridges have also been observed. These "salt-bridge stacking interactions" can be quite strong but are not well understood. We studied stacked dimers of the acetate···guanidinium ion pair with a diverse set of 63 heterocycles using robust ab initio methods. The computed interaction energies span more than 10 kcal mol^-1, indicating the sensitivity of these salt-bridge stacking interactions to heterocycle features. Trends in both the strength and preferred geometry of these interactions can be understood through analyses of the electrostatic potentials and electric fields above the heterocycles. We have developed new heterocycle descriptors that quantify these effects and used them to create robust predictors of the strength of salt-bridge stacking interactions both in the gas phase and a protein-like dielectric environment. These predictive tools, combined with a set of qualitative guidelines, should facilitate the choice of heterocycles that maximize salt-bridge stacking interactions in drug binding sites.

Anisotropic lattice softening near the structural phase transition in the thermosalient crystal 1,2,4,5-tetrabromobenzene

The thermosalient effect (crystal jumping on heating) attracts much attention as both an intriguing academic phenomenon and in relation to its potential for the development of molecular actuators but its mechanism remains unclear. 1,2,4,5-Tetrabromobenzene (TBB) is one of the most extensively studied thermosalient compounds that has been shown previously to undergo a phase transition on heating, accompanied by crystal jumping and cracking. The difference in the crystal structures and intermolecular interaction energies of the low- and high-temperature phases is, however, too small to account for the large stress that arises over the course of the transformation. The energy is released spontaneously, and crystals jump across distances that exceed the crystal size by orders of magnitude. In the present work, the anisotropy of lattice strain is followed across the phase transition by single-crystal X-ray diffraction, focusing on the structural evolution from 273 to 343 K. A pronounced lattice softening is observed close to the transition point, with the structure becoming more rigid immediately after the phase transition. The diffraction studies are further supported by theoretical analysis of pairwise intermolecular energies and zone-centre lattice vibrations. Only three modes are found to monotonically soften up to the phase transition, with complex behaviour exhibited by the remaining lattice modes. The thermosalient effect is delayed with respect to the structural transformation itself. This can originate from the martensitic mechanism of the transformation, and the accumulation of stress associated with vibrational switching across the phase transition. The finding of this study sheds more light on the nature of the thermosalient effect in 1,2,4,5-tetrabromobenzene and can be applicable also to other thermosalient compounds.

Discovery of Potent Succinate-Ubiquinone Oxidoreductase Inhibitors via Pharmacophore-linked Fragment Virtual Screening Approach

Succinate-ubiquinone oxidoreductase (SQR) is an attractive target for fungicide discovery. Herein, we report the discovery of novel SQR inhibitors using a pharmacophore-linked fragment virtual screening approach, a new drug design method developed in our laboratory. Among newly designed compounds, compound 9s was identified as the most potent inhibitor with a Ki value of 34 nM against porcine SQR, displaying approximately 10-fold higher potency than that of the commercial control penthiopyrad. Further inhibitory kinetics studies revealed that compound 9s is a noncompetitive inhibitor with respect to the substrate cytochrome c and DCIP. Interestingly, compounds 8a, 9h, 9j, and 9k exhibited good in vivo preventive effects against Rhizoctonia solani. The results obtained from molecular modeling showed that the orientation of the R(2) group had a significant effect on binding with the protein.

Molecular recognition in chemical and biological systems

Structure-based ligand design in medicinal chemistry and crop protection relies on the identification and quantification of weak noncovalent interactions and understanding the role of water. Small-molecule and protein structural database searches are important tools to retrieve existing knowledge. Thermodynamic profiling, combined with X-ray structural and computational studies, is the key to elucidate the energetics of the replacement of water by ligands. Biological receptor sites vary greatly in shape, conformational dynamics, and polarity, and require different ligand-design strategies, as shown for various case studies. Interactions between dipoles have become a central theme of molecular recognition. Orthogonal interactions, halogen bonding, and amide⋅⋅⋅π stacking provide new tools for innovative lead optimization. The combination of synthetic models and biological complexation studies is required to gather reliable information on weak noncovalent interactions and the role of water.

Efficient stacking on protein amide fragments

The less polar π-surface of protein amide groups is exposed in many receptor binding sites, either as part of the backbone or in Gln/Asn side chains. Using quantum chemical calculations and Protein Data Bank (PDB) searches on model systems, we investigate the energetics and geometric preferences for the stacking on amide groups of a large number of heteroarenes that are relevant to medicinal chemistry. From this study, we discern that the stacking energy of an aromatic ligand substituent can be improved by: 1) orienting the fragment dipole vector such that it is aligned in an antiparallel fashion with the dipole of the interacting protein amide group, 2) increasing its dipole moment, and 3) decreasing its π-electron density. These guidelines should be helpful to more rationally exploit this interaction type in future structure-based drug design.

Computational discovery of picomolar Q(o) site inhibitors of cytochrome bc1 complex

A critical challenge to the fragment-based drug discovery (FBDD) is its low-throughput nature due to the necessity of biophysical method-based fragment screening. Herein, a method of pharmacophore-linked fragment virtual screening (PFVS) was successfully developed. Its application yielded the first picomolar-range Q(o) site inhibitors of the cytochrome bc(1) complex, an important membrane protein for drug and fungicide discovery. Compared with the original hit compound 4 (K(i) = 881.80 nM, porcine bc(1)), the most potent compound 4f displayed 20 507-fold improved binding affinity (K(i) = 43.00 pM). Compound 4f was proved to be a noncompetitive inhibitor with respect to the substrate cytochrome c, but a competitive inhibitor with respect to the substrate ubiquinol. Additionally, we determined the crystal structure of compound 4e (K(i) = 83.00 pM) bound to the chicken bc(1) at 2.70 Å resolution, providing a molecular basis for understanding its ultrapotency. To our knowledge, this study is the first application of the FBDD method in the discovery of picomolar inhibitors of a membrane protein. This work demonstrates that the novel PFVS approach is a high-throughput drug discovery method, independent of biophysical screening techniques.

Substituent effects on non-covalent interactions with aromatic rings: insights from computational chemistry

Non-covalent interactions with aromatic rings pervade modern chemical research. The strength and orientation of these interactions can be tuned and controlled through substituent effects. Computational studies of model complexes have provided a detailed understanding of the origin and nature of these substituent effects, and pinpointed flaws in entrenched models of these interactions in the literature. Here, we provide a brief review of efforts over the last decade to unravel the origin of substituent effects in π-stacking, XH/π, and ion/π interactions through detailed computational studies. We highlight recent progress that has been made, while also uncovering areas where future studies are warranted.