Conformer Generation Research Articles

Marine macrolides as an efficient source of FMS-like tyrosine kinase 3 inhibitors: A comprehensive approach of in silico virtual screening

Marine organisms are a definitive source of antibiotics and kinase inhibitors which provide cues for discovering novel drug leads. Marine macrolides are getting much attraction due to their enzyme inhibitory potential. The present study comprehensively dealt with the virtual screening and structure-based prediction of macrolide compounds against FMS-like tyrosine kinase 3 receptors (FLT3). The FLT3 was chosen as a biological target against the 990 marine macrolides. Before the virtual screening of macrolide compounds, validation of molecular docking was carried out by re-docking of co-crystallized Gilteritinib within the FLT3. Among the selected 990 candidates of marine macrolides, 311 were failed due to the generation of insufficient conformers. Amongst the successful compounds, 22 compounds were also failed to dock within the receptor, while the remaining 657 marine macrolide entities elicited successful docking. The HYBRID Chemguass4 Score ranged from -10.17 to -0.02. This vast difference in the HYBRID ChemGuass4 score is attributed to the difference in binding potential with the receptor's binding pocket. The top ten compounds were selected based on the HYBRID ChemGuass4 Score lower than -8.0 against FLT3. The pharmacokinetics and ADME properties revealed the drug likeliness of the macrolides.

The Torsion Library: Semiautomated Improvement of Torsion Rules with SMARTScompare.

The Torsion Library is a collection of torsion motifs associated with angle distributions, derived from crystallographic databases. It is used in strain assessment, conformer generation, and geometry optimization. A hierarchical structure of expert curated SMARTS defines the chemical environments of rotatable bonds and associates these with preferred angles. SMARTS can be very complex and full of implications, which make them difficult to maintain manually. Recent developments in automatically comparing SMARTS patterns can be applied to the Torsion Library to ensure its correctness. We specifically discuss the implementation and the limits of such a procedure in the context of torsion motifs and show several examples of how the Torsion Library benefits from this. All automated changes are validated manually and then shown to have an effect on the angle distributions by correcting matching behavior. The corrected Torsion Library itself is available including both PDB as well as CSD histograms in the Supporting Information and can be used to evaluate rotatable bonds at https://torsions.zbh.uni-hamburg.de.

Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods.

Recent years have seen several hybrid simulation methods for exploring the conformational space of proteins and their complexes or assemblies. These methods often combine fast analytical approaches with computationally expensive full atomic molecular dynamics (MD) simulations with the goal of rapidly sampling large and cooperative conformational changes at full atomic resolution. We present here a systematic comparison of the utility and limits of four such hybrid methods that have been introduced in recent years: MD with excited normal modes (MDeNM), collective modes-driven MD (CoMD), and elastic network model (ENM)-based generation, clustering, and relaxation of conformations (ClustENM) as well as its updated version integrated with MD simulations (ClustENMD). We analyzed the predicted conformational spaces using each of these four hybrid methods, applied to four well-studied proteins, triosephosphate isomerase (TIM), 3-phosphoglycerate kinase (PGK), HIV-1 protease (PR) and HIV-1 reverse transcriptase (RT), which provide extensive ensembles of experimental structures for benchmarking and comparing the methods. We show that a rigorous multi-faceted comparison and multiple metrics are necessary to properly assess the differences between conformational ensembles and provide an optimal protocol for achieving good agreement with experimental data. While all four hybrid methods perform well in general, being especially useful as computationally efficient methods that retain atomic resolution, the systematic analysis of the same systems by these four hybrid methods highlights the strengths and limitations of the methods and provides guidance for parameters and protocols to be adopted in future studies.

Incorporating NOE-Derived Distances in Conformer Generation of Cyclic Peptides with Distance Geometry.

Nuclear magnetic resonance (NMR) data from NOESY (nuclear Overhauser enhancement spectroscopy) and ROESY (rotating frame Overhauser enhancement spectroscopy) experiments can easily be combined with distance geometry (DG) based conformer generators by modifying the molecular distance bounds matrix. In this work, we extend the modern DG based conformer generator ETKDG, which has been shown to reproduce experimental crystal structures from small molecules to large macrocycles well, to include NOE-derived interproton distances. In noeETKDG, the experimentally derived interproton distances are incorporated into the distance bounds matrix as loose upper (or lower) bounds to generate large conformer sets. Various subselection techniques can subsequently be applied to yield a conformer bundle that best reproduces the NOE data. The approach is benchmarked using a set of 24 (mostly) cyclic peptides for which NOE-derived distances as well as reference solution structures obtained by other software are available. With respect to other packages currently available, the advantages of noeETKDG are its speed and that no prior force-field parametrization is required, which is especially useful for peptides with unnatural amino acids. The resulting conformer bundles can be further processed with the use of structural refinement techniques to improve the modeling of the intramolecular nonbonded interactions. The noeETKDG code is released as a fully open-source software package available at www.github.com/rinikerlab/customETKDG.

High-Performance Conformal Thermoelectric Generator for Environmental Monitoring

High-Performance Conformal Thermoelectric Generator for Environmental Monitoring

Cosmological Scattering Equations.

We propose a world sheet formula for tree-level correlation functions describing a scalar field with arbitrary mass and quartic self-interaction in de Sitter space, which is a simple model for inflationary cosmology. The correlation functions are located on the future boundary of the spacetime and are Fourier-transformed to momentum space. Our formula is supported on mass-deformed scattering equations involving conformal generators in momentum space and reduces to the CHY formula for ϕ^{4} amplitudes in the flat space limit. Using the global residue theorem, we verify that it reproduces the Witten diagram expansion at four and six points, and sketch the extension to n points.

Tripeptide loop closure: A detailed study of reconstructions based on Ramachandran distributions.

Tripeptide loop closure (TLC) is a standard procedure to reconstruct protein backbone conformations, by solving a zero-dimensional polynomial system yielding up to 16 solutions. In this work, we first show that multiprecision is required in a TLC solver to guarantee the existence and the accuracy of solutions. We then compare solutions yielded by the TLC solver against tripeptides from the Protein Data Bank. We show that these solutions are geometrically diverse (up to Root mean square deviation with respect to the data) and sound in terms of potential energy. Finally, we compare Ramachandran distributions of data and reconstructions for the three amino acids. The distribution of reconstructions in the second angular space stands out, with a rather uniform distribution leaving a central void. We anticipate that these insights, coupled to our robust implementation in the Structural Bioinformatics Library ( https://sbl.inria.fr/doc/Tripeptide_loop_closure-user-manual.html), will help understanding the properties of TLC reconstructions, with potential applications to the generation of conformations of flexible loops in particular.

Enhanced Molecular Dynamics Method to Efficiently Increase the Discrimination Capability of Computational Protein-Protein Docking.

Protein–protein docking typically consists of the generation of putative binding conformations, which are subsequently ranked by fast heuristic scoring functions. The simplicity of these functions allows for computational efficiency but has severe repercussions on their discrimination capabilities. In this work, we show the effectiveness of suitable descriptors calculated along short scaled molecular dynamics runs in recognizing the nearest-native bound conformation among a set of putative structures generated by the HADDOCK tool for eight protein–protein systems.

A new Fe3+ colorimetric sensor: Nitrophenyl bispyrazole derivative synthesis using Fe3O4@SiO2@Si-Pr-NH-(CH2)2-NH2 and its DFT study

The efficient synthesis of bispyrazole derivatives was reported in the presence of Fe3O4@SiO2@Si-Pr-NH-(CH2)2-NH2 as a nanomagnetic catalyst in solvent-free conditions. The UV–Vis spectroscopy study of 4,4'-((3-nitrophenyl)methylene)bis(3-methyl-1H-pyrazol-5-ol) derivative 6a was demonstrated that it could be used as a Fe3+ ion colorimetric chemosensor, which was shown an apparent color change from white to orange with high selectivity toward the addition of Fe3+ ion in CH3CN/H2O (1:9 v/v) as a solvent. The UV–Vis absorption was increased linearly, and its detection limit was calculated 2.19 × 10−6 M.The orientations of hydroxyl groups for 5-membered and 6-membered rings of the most stable configurations of the bispyrazoles cause generation of T-shaped conformations based on Independent Gradient Model (IGM) analysis, conformational stability of the considered complexes can be related to the formation of σ-π molecular interaction heterocyclic rings which confirms with the vibrational stretching modes of hydroxyl groups and the character of the Kohn-Sham HOMO and LUMO orbitals.

Exploring ligand dynamics in protein crystal structures with ensemble refinement.

Understanding the dynamics of ligands bound to proteins is an important task in medicinal chemistry and drug design. However, the dominant technique for determining protein-ligand structures, X-ray crystallography, does not fully account for dynamics and cannot accurately describe the movements of ligands in protein binding sites. In this article, an alternative method, ensemble refinement, is used on six protein-ligand complexes with the aim of understanding the conformational diversity of ligands in protein crystal structures. The results show that ensemble refinement sometimes indicates that the flexibility of parts of the ligand and some protein side chains is larger than that which can be described by a single conformation and atomic displacement parameters. However, since the electron-density maps are comparable and Rfree values are slightly increased, the original crystal structure is still a better model from a statistical point of view. On the other hand, it is shown that molecular-dynamics simulations and automatic generation of alternative conformations in crystallographic refinement confirm that the flexibility of these groups is larger than is observed in standard refinement. Moreover, the flexible groups in ensemble refinement coincide with groups that give high atomic displacement parameters or non-unity occupancy if optimized in standard refinement. Therefore, the conformational diversity indicated by ensemble refinement seems to be qualitatively correct, indicating that ensemble refinement can be an important complement to standard crystallographic refinement as a tool to discover which parts of crystal structures may show extensive flexibility and therefore are poorly described by a single conformation. However, the diversity of the ensembles is often exaggerated (probably partly owing to the rather poor force field employed) and the ensembles should not be trusted in detail.

Conformal heat energy harvester on Steam4 pipelines for powering IoT sensors

This paper discusses a novel design and analysis of a conformal thermoelectric generator (cTEG), which can be used for powering the internet-of-things (IoT) wireless sensors for continuous monitoring of steam pipelines operation and maintenance. This conformal device is designed to be directly attached to a cylindrical steam pipe, therefore has a mechanical flexibility to bending align to the pipe curvature (conformality), and which transports superheated steam at 200 °C or around. Lack of continuous monitoring of underground pipelines have resulted in a significant loss of money, time, and resources. This primarily is due to limited access for reading data or replacing batteries. This issue can be addressed using cTEG which can directly convert wasted heat from pipeline to electricity for continuous powering of IoT sensors. The cTEG can be made from a classical bulk bismuth telluride (Bi2Te3) for sintered TEG legs. In the analysis, the material properties of the legs are expected be constant and independent to the temperature where the figure-of-merit is near 1.0 at room temperature. A roll-to-roll thermoelectric module is considered by using Kapton film as the substrates with PDMS for filling the gap to achieving low cost and high performance. The electro-thermal device optimization was conducted by using analytical model. Available heat flow in the system is determined by the device design and the hot and cold side heat exchange. Hence these heat transfer limit the power output per device footprint. The moderate passive air convection can be enhanced by extending surface areas by fins to improve the power output. This work particularly focused on the optimization of the module design while the thickness is limited by the requirement of maintaining the mechanical conformability to a pipe surface. Variational conditions (steam temperature, flow rate, pipe diameter) and design parameters (fill factor and leg length) were investigated. In addition, this approach can be applied to other TEG designs with such dimension limitations. The upper limit of power output per device footprint is found at 19.5 W/m2 with fill factor of 20%, where cTEG could achieve to 35 W/m2 at the optimum with few centimeters thickness. The material cost to manufacture the cTEG was estimated and was found to be closer to a comparable range of the first set of primary batteries. The novel modeling method presented here can also be applied to other energy-related fields, such as geothermal, deep sea monitoring field in which heat and electricity co-optimization is of vital importance.

ClustENMD: efficient sampling of biomolecular conformational space at atomic resolution.

SummaryEfficient sampling of conformational space is essential for elucidating functional/allosteric mechanisms of proteins and generating ensembles of conformers for docking applications. However, unbiased sampling is still a challenge especially for highly flexible and/or large systems. To address this challenge, we describe a new implementation of our computationally efficient algorithm ClustENMD that is integrated with ProDy and OpenMM softwares. This hybrid method performs iterative cycles of conformer generation using elastic network model for deformations along global modes, followed by clustering and short molecular dynamics simulations. ProDy framework enables full automation and analysis of generated conformers and visualization of their distributions in the essential subspace.Availability and implementationClustENMD is open-source and freely available under MIT License from https://github.com/prody/ProDy.Supplementary information Supplementary data are available at Bioinformatics online.

Pseudocyclic Form of 4-Hydroxypyrrolidine-2-carboxanilide Podands with Trioxyethylene Chain: Modeling, Conformational Search, and NMR Analysis.

The 4-hydroxypyrrolidine-2-carboxanilide podand salt demonstrates catalytic activity in asymmetric Biginelli reaction. The systematic search for prevalent conformational state of the cation was carried out by computer simulations in combination with one- and two-dimensional NMR experiments. For that purpose, we proposed a novel algorithm for the generation and selection of conformers based on molecular dynamics and clustering in the space of principal components. The search had found an important trend of the podand to form a pseudocyclic structure with a horseshoe-shaped conformation of the oligooxyethylene fragment. This conformation is stabilized by different types of intramolecular hydrogen bonds between the acidic and basic centers of the two 4-hydroxypyrrolidine-2-carboxanilide residuals (branches). The proposed approach had made it possible to identify the major structural factors, providing a correlation between the calculated and experimental chemical shifts of hydrogen atoms in the 1H NMR spectra of the protonated podand.

AutoGraph: Autonomous Graph-Based Clustering of Small-Molecule Conformations.

While accurately modeling the conformational ensemble is required for predicting properties of flexible molecules, the optimal method of obtaining the conformational ensemble appears as varied as their applications. Ensemble structures have been modeled by generation, refinement, and clustering of conformations with a sufficient number of samples. We present a conformational clustering algorithm intended to automate the conformational clustering step through the Louvain algorithm, which requires minimal hyperparameters and importantly no predefined number of clusters or threshold values. The conformational graphs produced by this method for O-succinyl-l-homoserine, oxidized nicotinamide adenine dinucleotide, and 200 representative metabolites each preserved the geometric/energetic correlation expected for points on the potential energy surface. Clustering based on these graphs provides partitions informed by the potential energy surface. Automating conformational clustering in a workflow with AutoGraph may mitigate human biases introduced by guess and check over hyperparameter selection while allowing flexibility to the result by not imposing predefined criteria other than optimizing the model's loss function. Associated codes are available at https://github.com/TanemuraKiyoto/AutoGraph.

Computation of host-guest binding free energies with a new quantum mechanics based mining minima algorithm.

A new method called QM-VM2 is presented that efficiently combines statistical mechanics with quantum mechanical (QM) energy potentials in order to calculate noncovalent binding free energies of host-guest systems. QM-VM2 efficiently couples the use of semi-empirical QM (SEQM) energies and geometry optimizations with an underlying molecular mechanics (MM) based conformational search, to find low SEQM energy minima, and allows for processing of these minima at higher levels of ab initio QM theory. A progressive geometry optimization scheme is introduced as a means to increase conformational sampling efficiency. The newly implemented QM-VM2 is used to compute the binding free energies of the host molecule cucurbit[7]uril and a set of 15 guest molecules. The results are presented along with comparisons to experimentally determined binding affinities. For the full set of 15 host-guest complexes, which have a range of formal charges from +1 to +3, SEQM-VM2 based binding free energies show poor correlation with experiment, whereas for the ten +1 complexes only, a significant correlation (R2 = 0.8) is achieved. SEQM-VM2 generation of conformers followed by single-point ab initio QM calculations at the dispersion corrected restricted Hartree-Fock-D3(BJ) and TPSS-D3(BJ) levels of theory, as post-processing corrections, yields a reasonable correlation with experiment for the full set of host-guest complexes (R2 = 0.6 and R2 = 0.7, respectively) and an excellent correlation for the +1 formal charge set (R2 = 1.0 and R2 = 0.9, respectively), as long as a sufficiently large basis set (triple-zeta quality) is employed. The importance of the inclusion of configurational entropy, even at the MM level, for the achievement of good correlation with experiment was demonstrated by comparing the calculated ΔE values with experiment and finding a considerably poorer correlation with experiment than for the calculated free energy ΔE - TΔS. For the complete set of host-guest systems with the range of formal charges, it was observed that the deviation of the predicted binding free energy from experiment correlates somewhat with the net charge of the systems. This observation leads to a simple empirical interpolation scheme to improve the linear regression of the full set.

Large-Scale Analysis of Bioactive Ligand Conformational Strain Energy by Ab Initio Calculation.

Ligand conformational strain energy (LCSE) plays an important role in virtual screening and lead optimization. While various studies have provided insights into LCSE for small-molecule ligands in the Protein Data Bank (PDB), conclusions are inconsistent mainly due to small datasets, poor quality control of crystal structures, and molecular mechanics (MM) or low-level quantum mechanics (QM) calculations. Here, we built a high-quality dataset (LigBoundConf) of 8145 ligand-bound conformations from PDB crystal structures and calculated LCSE at the M062X-D3/ma-TZVPP (SMD)//M062X-D3/def2-SVP(SMD) level for each case in the dataset. The mean/median LCSE is 4.6/3.7 kcal/mol for 6672 successfully calculated cases, which is significantly lower than the estimates based on molecular mechanics in many previous analyses. Especially, when removing ligands with nonaromatic ring(s) that are prone to have large LCSEs due to electron density overfitting, the mean/median LCSE was reduced to 3.3/2.5 kcal/mol. We further reveal that LCSE is correlated with several ligand properties, including formal atomic charge, molecular weight, number of rotatable bonds, and number of hydrogen-bond donors and acceptors. In addition, our results show that although summation of torsion strains is a good approximation of LCSE for most cases, for a small fraction (about 6%) of our dataset, it underestimates LCSEs if ligands could form nonlocal intramolecular interactions in the unbound state. Taken together, our work provides a comprehensive profile of LCSE for ligands in PDB, which could help ligand conformation generation, ligand docking pose evaluation, and lead optimization.

Exploring the Impacts of Conformer Selection Methods on Ion Mobility Collision Cross Section Predictions.

The prediction of structure dependent molecular properties, such as collision cross sections as measured using ion mobility spectrometry, are crucially dependent on the selection of the correct population of molecular conformers. Here, we report an in-depth evaluation of multiple conformation selection techniques, including simple averaging, Boltzmann weighting, lowest energy selection, low energy threshold reductions, and similarity reduction. Generating 50 000 conformers each for 18 molecules, we used the In Silico Chemical Library Engine (ISiCLE) to calculate the collision cross sections for the entire data set. First, we employed Monte Carlo simulations to understand the variability between conformer structures as generated using simulated annealing. Then we employed Monte Carlo simulations to the aforementioned conformer selection techniques applied on the simulated molecular property: the ion mobility collision cross section. Based on our analyses, we found Boltzmann weighting to be a good trade-off between precision and theoretical accuracy. Combining multiple techniques revealed that energy thresholds and root-mean-squared deviation-based similarity reductions can save considerable computational expense while maintaining property prediction accuracy. Molecular dynamic conformer generation tools like AMBER can continue to generate new lowest energy conformers even after tens of thousands of generations, decreasing precision between runs. This reduced precision can be ameliorated and theoretical accuracy increased by running density functional theory geometry optimization on carefully selected conformers.

Heisenberg spin chain as a worldsheet coordinate for lightcone quantized string

Although the energy spectrum of the Heisenberg spin chain on a circle defined byH=14∑k=1Mσkxσk+1x+σkyσk+1y+Δσkzσk+1z\\documentclass[12pt]{minimal}\t\t\t\t\\usepackage{amsmath}\t\t\t\t\\usepackage{wasysym}\t\t\t\t\\usepackage{amsfonts}\t\t\t\t\\usepackage{amssymb}\t\t\t\t\\usepackage{amsbsy}\t\t\t\t\\usepackage{mathrsfs}\t\t\t\t\\usepackage{upgreek}\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\t\t\t\t\\begin{document}$$ H=\\frac{1}{4}\\sum \\limits_{k=1}^M\\left({\\sigma}_k^x{\\sigma}_{k+1}^x+{\\sigma}_k^y{\\sigma}_{k+1}^y+\\Delta {\\sigma}_k^z{\\sigma}_{k+1}^z\\right) $$\\end{document}is well known for any fixed M, the boundary conditions vary according to whether M ∈ 4ℕ + r, where r = −1, 0, 1, 2, and also according to the parity of the number of overturned spins in the state, In string theory all these cases must be allowed because interactions involve a string with M spins breaking into strings with M1< M and M − M1 spins (or vice versa). We organize the energy spectrum and degeneracies of H in the case ∆ = 0 where the system is equivalent to a system of free fermions. In spite of the multiplicity of special cases, in the limit M → ∞ the spectrum is that of a free compactified worldsheet field. Such a field can be interpreted as a compact transverse string coordinate x(σ) ≡ x(σ) + R0. We construct the bosonization formulas explicitly in all separate cases, and for each sector give the Virasoro conformal generators in both fermionic and bosonic formulations. Furthermore from calculations in the literature for selected classes of excited states, there is strong evidence that the only change for ∆ ≠ 0 is a change in the compactification radius R0→ R∆. As ∆ → −1 this radius goes to infinity, giving a concrete example of noncompact space emerging from a discrete dynamical system. Finally we apply our work to construct the three string vertex implied by a string whose bosonic coordinates emerge from this mechanism.

General Purpose Structure-Based Drug Discovery Neural Network Score Functions with Human-Interpretable Pharmacophore Maps.

The BioChemical Library (BCL) is an academic open-source cheminformatics toolkit comprising ligand-based virtual high-throughput screening (vHTS) tools such as quantitative structure–activity/property relationship (QSAR/QSPR) modeling, small molecule flexible alignment, small molecule conformer generation, and more. Here, we expand the capabilities of the BCL to include structure-based virtual screening. We introduce two new score functions, BCL-AffinityNet and BCL-DockANNScore, based on novel distance-dependent signed protein–ligand atomic property correlations. Both metrics are conventional feed-forward dropout neural networks trained on the new descriptors. We demonstrate that BCL-AffinityNet is one of the top performing score functions on the comparative assessment of score functions 2016 affinity prediction and affinity ranking tasks. We also demonstrate that BCL-AffinityNet performs well on the CSAR-NRC HiQ I and II test sets. Furthermore, we demonstrate that BCL-DockANNScore is competitive with multiple state-of-the-art methods on the docking power and screening power tasks. Finally, we show how our models can be decomposed into human-interpretable pharmacophore maps to aid in hit/lead optimization. Altogether, our results expand the utility of the BCL for structure-based scoring to aid small molecule discovery and design. BCL-AffinityNet, BCL-DockANNScore, and the pharmacophore mapping application, as well as the remainder of the BCL cheminformatics toolkit, are freely available with an academic license at the BCL Commons site hosted on http://meilerlab.org/.

Theoretical study on conformational energies of transition metal complexes.

Conformational energies are an important chemical property for which a performance assessment of theoretical methods is mandatory. Existing benchmark sets are often limited to biochemical or main group element containing molecules, while organometallic systems are generally less studied. A key problem herein is to routinely generate conformers for these molecules due to their complexity and manifold of possible coordination patterns. In this study we used our recently published CREST protocol [Pracht et al., Phys. Chem. Chem. Phys., 2020, 22, 7169-7192] to generate conformer ensembles for a variety of 40 challenging transition metal containing molecules, which were then used to form a comprehensive conformational energy benchmark set termed TMCONF40. Several low-cost semiempirical, density functional theory (DFT) and force-field methods were compared to high level DLPNO-CCSD(T1) and double-hybrid DFT reference values. Close attention was paid to the energetic ordering of the conformers in the statistical evaluation. With respect to the double-hybrid references, both tested low-cost composite DFT methods produce high Pearson correlation coefficients of rp,mean,B97-3c//B97-3c = 0.922 and rp,mean,PBEh-3c//B97-3c = 0.890, with mean absolute deviations close to or below 1 kcal mol-1. This good performance also holds for a comparison to DLPNO-CCSD(T1) reference energies for a smaller subset termed TMCONF5. Based on DFT geometries, the GFNn-xTB methods yield reasonable Pearson correlation coefficients of rp,mean,GFN1-xTB//B97-3c = 0.617 (MADmean = 2.15 kcal mol-1) and rp,mean,GFN2-xTB//B97-3c = 0.567 (MADmean = 2.68 kcal mol-1), outperforming the widely used PMx methods on the TMCONF40 test set. Employing the low-cost composite DFT method B97-3c on GFN2-xTB geometries yields an slightly improved correlation of rp,mean,B97-3c//GFN2-xTB = 0.632. Furthermore, for 68% of the investigated complexes at least one low-energy conformer was found that is more stable than the respective crystal structure conformation, which signals the importance of conformational studies. General recommendations for the application of the CREST protocol and DFT methods for transition metal conformational energies are given.