Macrocycle Conformational Sampling by DFT-D3/COSMO-RS Methodology

Photochemical Transformations of Peptides Containing the N-(2-Selenoethyl)glycine Moiety

The diselenide bond has attracted considerable attention due to its ability to undergo the metathesis reaction in response to visible light. In our previous study, we demonstrated visible-light-induced diselenide metathesis of selenocysteine-containing linear peptides, allowing for the convenient generation of peptide libraries. Here, we investigated the transformation of linear and cyclic peptides containing the N-(2-selenoethyl)glycine moiety. The linear peptides were highly susceptible to the metathesis reaction, whereas the cyclic systems gave only limited conversion yields of the metathesis product. In both cases, side reactions leading to the formation of mono-, di-, and polyselenides were observed upon prolonged irradiation. To confirm the radical mechanism of the reaction, the radical initiator 2,2'-azobis[2-(2-imidazolin-2-yl)propane] dihydrochloride (VA-044) was tested, and it was found to induce diselenide metathesis without photochemical activation. The data were interpreted in the light of quantum-chemical simulations based on density functional theory (DFT). The simulations were performed at the B3LYP-D3BJ/def2-TZVP level of theory using a continuum solvation model (IEF-PCM) and methanol as a solvent.

Comprehensive Mechanistic View of the Hydrolysis of Oxadiazole-Based Inhibitors by Histone Deacetylase 6 (HDAC6)

Histone deacetylase (HDAC) inhibitors used in the clinic typically contain a hydroxamate zinc-binding group (ZBG). However, more recent work has shown that the use of alternative ZBGs, and, in particular, the heterocyclic oxadiazoles, can confer higher isoenzyme selectivity and more favorable ADMET profiles. Herein, we report on the synthesis and biochemical, crystallographic, and computational characterization of a series of oxadiazole-based inhibitors selectively targeting the HDAC6 isoform. Surprisingly, but in line with a very recent finding reported in the literature, a crystal structure of the HDAC6/inhibitor complex revealed that hydrolysis of the oxadiazole ring transforms the parent oxadiazole into an acylhydrazide through a sequence of two hydrolytic steps. An identical cleavage pattern was also observed both in vitro using the purified HDAC6 enzyme as well as in cellular systems. By employing advanced quantum and molecular mechanics (QM/MM) and QM calculations, we elucidated the mechanistic details of the two hydrolytic steps to obtain a comprehensive mechanistic view of the double hydrolysis of the oxadiazole ring. This was achieved by fully characterizing the reaction coordinate, including identification of the structures of all intermediates and transition states, together with calculations of their respective activation (free) energies. In addition, we ruled out several (intuitively) competing pathways. The computed data (ΔG^‡ ≈ 21 kcal·mol^-1 for the rate-determining step of the overall dual hydrolysis) are in very good agreement with the experimentally determined rate constants, which a posteriori supports the proposed reaction mechanism. We also clearly (and quantitatively) explain the role of the -CF₃ or -CHF₂ substituent on the oxadiazole ring, which is a prerequisite for hydrolysis to occur. Overall, our data provide compelling evidence that the oxadiazole warheads can be efficiently transformed within the active sites of target metallohydrolases to afford reaction products possessing distinct selectivity and inhibition profiles.

Molecular dynamics simulations provide structural insight into binding of cyclic dinucleotides to human STING protein

Human stimulator of interferon genes (hSTING) is a signaling adaptor protein that triggers innate immune system by response to cytosolic DNA and second messenger cyclic dinucleotides (CDNs). Natural CDNs contain purine nucleobase with different phosphodiester linkage types (3'-3', 2'-2' or mixed 2'-3'-linkages) and exhibit different binding affinity towards hSTING, ranging from micromolar to nanomolar. High-affinity CDNs are considered as suitable candidates for treatment of chronic hepatitis B and cancer. We have used molecular dynamics simulations to investigate dynamical aspects of binding of natural CDNs (specifically, 2'-2'-cGAMP, 2'-3'-cGAMP, 3'-3'-cGAMP, 3'-3'-c-di-AMP, and 3'-3'-c-di-GMP) with hSTING^wt protein. Our results revealed that CDN/hSTING^wt interactions are controlled by the balance between fluctuations (conformational changes) in the CDN ligand and the protein dynamics. Binding of different CDNs induces different degrees of conformational/dynamics changes in hSTING^wt ligand binding cavity, especially in α₁-helices, the so-called lid region and α₂-tails. The ligand residence time in hSTING^wt protein pocket depends on different contribution of R232 and R238 residues interacting with oxygen atoms of phosphodiester groups in ligand, water distribution around interacting charged centers (in protein residues and ligand) and structural stability of closed conformation state of hSTING^wt protein. These findings may perhaps guide design of new compounds modulating hSTING activity.Communicated by Ramaswamy H. Sarma.

Evaluating the Conformations and Dynamics of Peptoid Macrocycles

Peptoid macrocycles are versatile and chemically diverse peptidomimetic oligomers. However, the conformations and dynamics of these macrocycles have not been evaluated comprehensively and require extensive further investigation. Recent studies indicate that two degrees of freedom, and four distinct conformations, adequately describe the behavior of each monomer backbone unit in most peptoid oligomers. On the basis of this insight, we conducted molecular dynamics simulations of model macrocycles using an exhaustive set of idealized possible starting conformations. Simulations of various sizes of peptoid macrocycles yielded a limited set of populated conformations. In addition to reproducing all relevant experimentally determined conformations, the simulations accurately predicted a cyclo-octamer conformation for which we now present the first experimental observation. Sets of three adjacent dihedral angles (ϕ_i, ψ_i, ω_i+1) exhibited correlated crankshaft motions over the course of simulation for peptoid macrocycles of six residues and larger. These correlated motions may occur in the form of an inversion of one amide bond and the concerted rotation of the preceding ϕ and ψ angles to their mirror-image conformation, a variation on "crankshaft flip" motions studied in polymers and peptides. The energy landscape of these peptoid macrocycles can be described as a network of conformations interconnected by transformations of individual crankshaft flips. For macrocycles of up to eight residues, our mapping of the landscape is essentially complete.

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.

Quantifying soft degrees of freedom in volatile organic compounds: insight from quantum chemistry and focused single molecule experiments

Sampling of the vast conformational landscape of organic compounds remains a challenging task in computational chemistry, especially when it comes to the characterization of soft-degrees of freedom and relatively small energy barriers between different local minima. Therefore, studying the intrinsic properties of isolated molecules using focused experiments such as high-resolution molecular spectroscopy provides a powerful approach to validate and improve available quantum chemical methods. Here, we report on the most abundant gas-phase structure of ethyl 2-methyl pentanoate under molecular jet conditions, which we used to benchmark several exchange-correlation functionals and ab initio methods at the quantum chemical level. The observed conformer of ethyl 2-methyl pentanoate in the gas-phase is of C1 symmetry and exhibits a large amplitude motion around the C-C bond in proximity to the carbonyl moiety, which, unlike in the case of its structural isomer ethyl 2-ethyl butyrate, is very sensitive to the applied quantum chemical method and basis set. Depending on the applied quantum chemical method, the dihedral angle of the lowest energy conformer is optimized to absolute values of ±20°. This is far above the usual convergence error of the theoretical methods and has a tremendous impact on the rotational constants of this conformer, which complicates the prediction of rotational spectra and the assignment of experimental data. We show that the loss of symmetry in the aliphatic chain bound to the carboxylic moiety of ethyl esters results in a shift of the dihedral angle value due to a flat potential well around the corresponding C-C bond. Our benchmark calculations further indicate the potential relevance of the wB97X-D functional for this ethyl pentanoate and other related ethyl esters.

Understanding the solubilization of Ca acetylide with a new computational model for ionic pairs

The unique reactivity of the acetylenic unit in DMSO gives rise to ubiquitous synthetic methods. We theoretically consider CaC2 solubility and protolysis in DMSO and formulate a strategy for CaC2 activation in solution-phase chemical transformations. For this, we use a new strategy for the modeling of ionic compounds in strongly coordinating solvents combining Born-Oppenheimer molecular dynamics with the DFTB3-D3(BJ) Hamiltonian and static DFT computations at the PBE0-D3(BJ)/pob-TZVP-gCP level. We modeled the thermodynamics of CaC2 protolysis under ambient conditions, taking into account its known heterogeneity and considering three polymorphs of CaC2. We give a theoretical basis for the existence of the elusive intermediate HC[triple bond, length as m-dash]C-Ca-OH and show that CaC2 insolubility in DMSO is of thermodynamic nature. We confirm the unique role of water and specific properties of DMSO in CaC2 activation and explain how the activation is realized. The proposed strategy for the utilization of CaC2 in sustainable organic synthesis is outlined.

Automated exploration of the low-energy chemical space with fast quantum chemical methods

We propose and discuss an efficient scheme for the in silico sampling for parts of the molecular chemical space by semiempirical tight-binding methods combined with a meta-dynamics driven search algorithm. The focus of this work is set on the generation of proper thermodynamic ensembles at a quantum chemical level for conformers, but similar procedures for protonation states, tautomerism and non-covalent complex geometries are also discussed. The conformational ensembles consisting of all significantly populated minimum energy structures normally form the basis of further, mostly DFT computational work, such as the calculation of spectra or macroscopic properties. By using basic quantum chemical methods, electronic effects or possible bond breaking/formation are accounted for and a very reasonable initial energetic ranking of the candidate structures is obtained. Due to the huge computational speedup gained by the fast low-cost quantum chemical methods, overall short computation times even for systems with hundreds of atoms (typically drug-sized molecules) are achieved. Furthermore, specialized applications, such as sampling with implicit solvation models or constrained conformational sampling for transition-states, metal-, surface-, or noncovalently bound complexes are discussed, opening many possible applications in modern computational chemistry and drug discovery. The procedures have been implemented in a freely available computer code called CREST, that makes use of the fast and reliable GFNn-xTB methods.

Conformational analysis of macrocycles: comparing general and specialized methods

Abstract

Macrocycles represent an important class of medicinally relevant small molecules due to their interesting biological properties. Therefore, a firm understanding of their conformational preferences is important for drug design. Given the importance of macrocycle-protein modelling in drug discovery, we envisaged that a systematic study of both classical and recent specialized methods would provide guidance for other practitioners within the field. In this study we compare the performance of the general, well established conformational analysis methods Monte Carlo Multiple Minimum (MCMM) and Mixed Torsional/Low-Mode sampling (MTLMOD) with two more recent and specialized macrocycle sampling techniques: MacroModel macrocycle Baseline Search (MD/LLMOD) and Prime macrocycle conformational sampling (PRIME-MCS). Using macrocycles extracted from 44 macrocycle-protein X-ray crystallography complexes, we evaluated each method based on their ability to (i) generate unique conformers, (ii) generate unique macrocycle ring conformations, (iii) identify the global energy minimum, (iv) identify conformers similar to the X-ray ligand conformation after Protein Preparation Wizard treatment (X-ray_ppw), and (v) to the X-ray_ppw ring conformation. Computational speed was also considered. In addition, conformational coverage, as defined by the number of conformations identified, was studied. In order to study the relative energies of the bioactive conformations, the energy differences between the global energy minima and the energy minimized X-ray_ppw structures and, the global energy minima and the MCMM-Exhaustive (1,000,000 search steps) generated conformers closest to the X-ray_ppw structure, were calculated and analysed. All searches were performed using relatively short run times (10,000 steps for MCMM, MTLMOD and MD/LLMOD). To assess the performance of the methods, they were compared to an exhaustive MCMM search using 1,000,000 search steps for each of the 44 macrocycles (requiring ca 200 times more CPU time). Prior to our analysis, we also investigated if the general search methods MCMM and MTLMOD could also be optimized for macrocycle conformational sampling. Taken together, our work concludes that the more general methods can be optimized for macrocycle modelling by slightly adjusting the settings around the ring closure bond. In most cases, MCMM and MTLMOD with either standard or enhanced settings performed well in comparison to the more specialized macrocycle sampling methods MD/LLMOD and PRIME-MCS. When using enhanced settings for MCMM and MTLMOD, the X-ray_ppw conformation was regenerated with the greatest accuracy. The, MD/LLMOD emerged as the most efficient method for generating the global energy minima.

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s10822-020-00277-2) contains supplementary material, which is available to authorized users.

Conformational Searching with Quantum Mechanics

Estimating the range of three-dimensional structures (conformations) that are available to a molecule is a key component of computer-aided drug design. Quantum mechanical simulation offers improved accuracy over forcefield methods, but at a high computational cost. The question is whether this increased cost can be justified in a context in which high-throughput analysis of large numbers of molecules is often key. This chapter discusses the application of quantum mechanics to conformational searching, with a focus on three key challenges: (1) the generation of ensembles that include a good approximation to a molecule's bioactive conformation at as prominent a ranking as possible; (2) rational analysis and modification of a pre-established bioactive conformation in terms of its energetics; and (3) approximation of real solution-phase conformational ensembles in tandem with NMR data. The impact of QM on the high-throughput application (1) is debatable, meaning that for the moment its primary application is still lower-throughput applications such as (2) and (3). The optimal choice of QM method is also discussed. Rigorous benchmarking suggests that DFT methods are only acceptable when used with large basis sets, but a trickle of papers continue to obtain useful results with relatively low-cost methods, leading to a dilemma that the literature has yet to fully resolve.

Impressive Enrichment of Semiempirical Quantum Mechanics-Based Scoring Function: HSP90 Protein with 4541 Inhibitors and Decoys

This paper describes the excellent performance of a newly developed scoring function (SF), based on the semiempirical QM (SQM) PM6-D3H4X method combined with the conductor-like screening implicit solvent model (COSMO). The SQM/COSMO, Amber/GB and nine widely used SFs have been evaluated in terms of ranking power on the HSP90 protein with 72 biologically active compounds and 4469 structurally similar decoys. Among conventional SFs, the highest early and overall enrichment measured by EF₁ and AUC% obtained using single-scoring-function ranking has been found for Glide SP and Gold-ASP SFs, respectively (7, 75 % and 3, 76 %). The performance of other standard SFs has not been satisfactory, mostly even decreasing below random values. The SQM/COSMO SF, where P-L structures were optimised at the advanced Amber level, has resulted in a dramatic enrichment increase (47, 98 %), almost reaching the best possible receiver operator characteristic (ROC) curve. The best SQM frame thus inserts about seven times more active compounds into the selected dataset than the best standard SF.

Factors Stabilizing β-Sheets in Protein Structures from a Quantum-Chemical Perspective

Protein folds are determined by the interplay between various (de)stabilizing forces, which can be broadly divided into a local strain of the protein chain and intramolecular interactions. In contrast to the α-helix, the β-sheet secondary protein structure is significantly stabilized by long-range interactions between the individual β-strands. It has been observed that quite diverse amino acid sequences can form a very similar small β-sheet fold, such as in the three-β-strand WW domain. Employing "calibrated" quantum-chemical methods, we show herein on two sequentially diverse examples of the WW domain that the internal strain energy is higher in the β-strands and lower in the loops, while the interaction energy has an opposite trend. Low strain energy computed for peptide sequences in the loop 1 correlates with its postulated early formation in the folding process. The relatively high strain energy within the β-strands (up to 8 kcal mol^-1 per amino acid residue) is compensated by even higher intramolecular interaction energy (up to 15 kcal mol^-1 per residue). It is shown in a quantitative way that the most conserved residues across the structural family of WW domains have the highest contributions to the intramolecular interaction energy. On the other hand, the residues in the regions with the lowest strain are not conserved. We conclude that the internal interaction energy is the physical quantity tuned by evolution to define the β-sheet protein fold.

Toward Ab Initio Protein Folding: Inherent Secondary Structure Propensity of Short Peptides from the Bioinformatics and Quantum-Chemical Perspective

By combining bioinformatics with quantum-chemical calculations, we attempt to address quantitatively some of the physical principles underlying protein folding. The former allowed us to identify tripeptide sequences in existing protein three-dimensional structures with a strong preference for either helical or extended structure. The selected representatives of pro-helical and pro-extended sequences were converted into "isolated" tripeptides-capped at N- and C-termini-and these were subjected to an extensive conformational sampling and geometry optimization (typically thousands to tens of thousands of conformers for each tripeptide). For each conformer, the QM(DFT-D3)/COSMO-RS free-energy value was then calculated, G_conf(solv). The Δ G_conf(solv) is expected to provide an objective, unbiased, and quantitatively accurate measure of the conformational preference of the particular tripeptide sequence. It has been shown that irrespective of the helical vs extended preferences of the selected tripeptide sequences in context of the protein, most of the low-energy conformers of isolated tripeptides prefer the R-helical structure. Nevertheless, pro-helical tripeptides show slightly stronger helix preference than their pro-extended counterparts. Furthermore, when the sampling is repeated in the presence of a partner tripeptide to mimic the situation in a β-sheet, pro-extended tripeptides (exemplified by the VIV) show a larger free-energy benefit than pro-helical tripeptides (exemplified by the EAM). This effect is even more pronounced in a hydrophobic solvent, which mimics the less polar parts of a protein. This is in line with our bioinformatic results showing that the majority of pro-extended tripeptides are hydrophobic. The preference for a specific secondary structure by the studied tripeptides is thus governed by the plasticity to adopt to its environment. In addition, we show that most of the "naturally occurring" conformations of tripeptide sequences, i.e., those found in existing three-dimensional protein structures, are within ∼10 kcal·mol^-1 from their global minima. In summary, our "ab initio" data suggest that complex protein structures may start to emerge already at the level of their small oligopeptidic units, which is in line with a hierarchical nature of protein folding.

Structural and computational basis for potent inhibition of glutamate carboxypeptidase II by carbamate-based inhibitors

A series of carbamate-based inhibitors of glutamate carboxypeptidase II (GCPII) were designed and synthesized using ZJ-43, N-[[[(1S)-1-carboxy-3-methylbutyl]amino]carbonyl]-l-glutamic acid, as a molecular template in order to better understand the impact of replacing one of the two nitrogen atoms in the urea-based GCPII inhibitor with an oxygen atom. Compound 7 containing a C-terminal 2-oxypentanedioic acid was more potent than compound 5 containing a C-terminal glutamic acid (2-aminopentanedioic acid) despite GCPII's preference for peptides containing an N-terminal glutamate as substrates. Subsequent crystallographic analysis revealed that ZJ-43 and its two carbamate analogs 5 and 7 with the same (S,S)-stereochemical configuration adopt a nearly identical binding mode while (R,S)-carbamate analog 8 containing a d-leucine forms a less extensive hydrogen bonding network. QM and QM/MM calculations have identified no specific interactions in the GCPII active site that would distinguish ZJ-43 from compounds 5 and 7 and attributed the higher potency of ZJ-43 and compound 7 to the free energy changes associated with the transfer of the ligand from bulk solvent to the protein active site as a result of the lower ligand strain energy and solvation/desolvation energy. Our findings underscore a broader range of factors that need to be taken into account in predicting ligand-protein binding affinity. These insights should be of particular importance in future efforts to design and develop GCPII inhibitors for optimal inhibitory potency.