Structures Of Small Organic Molecules Research Articles

Rapid and Automated Ab Initio Metabolite Collisional Cross Section Prediction from SMILES Input.

We implemented an ab initio CCS prediction workflow which incrementally refines generated structures using molecular mechanics, a deep learning potential, conformational clustering, and quantum mechanics (QM). Automating intermediate steps for a high performance computing (HPC) environment allows users to input the SMILES structure of small organic molecules and obtain a Boltzmann averaged collisional cross section (CCS) value as output. The CCS of a molecular species is a metric measured by ion mobility spectrometry (IMS) which can improve annotation of untargeted metabolomics experiments. We report only a minor drop in accuracy when we expedite the CCS calculation by replacing the QM geometry refinement step with a single-point energy calculation. Even though the workflow involves stochastic steps (i.e., conformation generation and clustering), the final CCS value was highly reproducible for multiple iterations on L-carnosine. Finally, we illustrate that the gas phase ensembles modeled for the workflow are intermediate files which can be used for the prediction of other properties such as aqueous phase nuclear magnetic resonance chemical shift prediction. The software is available at the following link: https://github.com/DasSusanta/snakemake_ccs.

Computation of CCSD(T)-Quality NMR Chemical Shifts via Δ-Machine Learning from DFT.

NMR spectroscopy undoubtedly plays a central role in determining molecular structures across different chemical disciplines, and the accurate computational prediction of NMR parameters is highly desirable. In this work, a new Δ-machine learning approach is presented to correct DFT-computed NMR chemical shifts using input features from the calculation and in addition highly accurate reference data at the CCSD(T)/pcSseg-2 level of theory with a basis set extrapolation scheme. The model is trained on a data set containing 1000 optimized and geometrically distorted structures of small organic molecules comprising most elements of the first three periods and containing data for 7090 1H and 4230 13C NMR chemical shifts. Applied to the PBE0/pcSseg-2 method, the mean absolute deviation (MAD) on the internal NMR shift test set is reduced by 81% for 1H and 92% for 13C at virtually no additional computational cost. For 12 different DFT functional and basis set combinations, the MAD of the ML-corrected NMR shifts ranges from 0.021 to 0.039 ppm (1H) and from 0.38 to 1.07 ppm (13C). Importantly, the new method consistently outperforms the simple and widely used linear regression correction technique. This behavior is reproduced on three different external benchmark sets, confirming the generality and robustness of the correction scheme, which can easily be applied in DFT-based spectral simulations.

Atomic-Resolution Imaging of Small Organic Molecules on Graphene

Here, we demonstrate atomic-resolution scanning transmission electron microscopy (STEM) imaging of light elements in small organic molecules on graphene. We use low-dose, room-temperature, aberration-corrected STEM to image 2D monolayer and bilayer molecular crystals, followed by advanced image processing methods to create high-quality composite images from ∼102-104 individual molecules. In metalated porphyrin and phthalocyanine derivatives, these images contain an elementally sensitive contrast with up to 1.3 Å resolution─sufficient to distinguish individual carbon and nitrogen atoms. Importantly, our methods can be applied to molecules with low masses (∼0.6 kDa) and nanocrystalline domains containing just a few hundred molecules, making it possible to study systems for which large crystals cannot easily be grown. Our approach is enabled by low-background graphene substrates, which we show increase the molecules' critical dose by 2-7×. These results indicate a new route for low-dose, atomic-resolution electron microscopy imaging to solve the structures of small organic molecules.

Geometry meta-optimization.

Recent work has demonstrated the promise of using machine-learned surrogates, in particular, Gaussian process (GP) surrogates, in reducing the number of electronic structure calculations (ESCs) needed to perform surrogate model based (SMB) geometry optimization. In this paper, we study geometry meta-optimization with GP surrogates where a SMB optimizer additionally learns from its past "experience" performing geometry optimization. To validate this idea, we start with the simplest setting where a geometry meta-optimizer learns from previous optimizations of the same molecule with different initial-guess geometries. We give empirical evidence that geometry meta-optimization with GP surrogates is effective and requires less tuning compared to SMB optimization with GP surrogates on the ANI-1 dataset of off-equilibrium initial structures of small organic molecules. Unlike SMB optimization where a surrogate should be immediately useful for optimizing a given geometry, a surrogate in geometry meta-optimization has more flexibility because it can distribute its ESC savings across a set of geometries. Indeed, we find that GP surrogates that preserve rotational invariance provide increased marginal ESC savings across geometries. As a more stringent test, we also apply geometry meta-optimization to conformational search on a hand-constructed dataset of hydrocarbons and alcohols. We observe that while SMB optimization and geometry meta-optimization do save on ESCs, they also tend to miss higher energy conformers compared to standard geometry optimization. We believe that further research into characterizing the divergence between GP surrogates and potential energy surfaces is critical not only for advancing geometry meta-optimization but also for exploring the potential of machine-learned surrogates in geometry optimization in general.

Norman C. Craig

Norman C. Craig, 89, died March 7 in Oberlin, Ohio. “Over a 63-year career, Norm Craig championed undergraduate research and teaching, as recognized by multiple ACS awards. With students, he characterized the gas phase structures of small organic molecules, using ultrahigh resolution infrared and microwave spectroscopy and quantum chemical calculations, and found new synthetic routes to isotopomers and fluorinated variants. For achievements in chemical science and service to the society, he was inducted as an inaugural ACS Fellow. Among his outstanding contributions to chemical education was his book Entropy Analysis. He was a trusted mentor of junior colleagues and an expert on the Charles Martin Hall aluminum discovery.”—Manish A. Mehta, colleague and friend Most recent title: Professor of chemistry, Oberlin college Education: BA, chemistry, Oberlin College, 1953; PhD, physical chemistry, Harvard University, 1957 Survivors: Wife, Ann; daughters, Julie and Mary; son, David; five grandchildren To recognize your late loved one

Recent Developments Toward Integrated Metabolomics Technologies (UHPLC-MS-SPE-NMR and MicroED) for Higher-Throughput Confident Metabolite Identifications.

Metabolomics has emerged as a powerful discipline to study complex biological systems from a small molecule perspective. The success of metabolomics hinges upon reliable annotations of spectral features obtained from MS and/or NMR. In spite of tremendous progress with regards to analytical instrumentation and computational tools, < 20% of spectral features are confidently identified in most untargeted metabolomics experiments. This article explores the integration of multiple analytical instruments such as UHPLC-MS/MS-SPE-NMR and the cryo-EM method MicroED to achieve large-scale and confident metabolite identifications in a higher-throughput manner. UHPLC-MS/MS-SPE allows for the simultaneous automated purification of metabolites followed by offline structure elucidation and structure validation by NMR and MicroED. Large-scale study of complex metabolomes such as that of the model plant legume Medicago truncatula can be achieved using an integrated UHPLC-MS/MS-SPE-NMR metabolomics platform. Additionally, recent developments in MicroED to study structures of small organic molecules have enabled faster, easier and precise structure determinations of metabolites. A MicroED small molecule structure elucidation workflow (e.g., crystal screening, sample preparation, data collection and data processing/structure determination) has been described. Ongoing MicroED methods development and its future scope related to structure elucidation of specialized metabolites and metabolomics are highlighted. The incorporation of MicroED with a UHPLC-MS/MS-SPE-NMR instrumental ensemble offers the potential to accelerate and achieve higher rates of metabolite identification.

QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules

We introduce QM7-X, a comprehensive dataset of 42 physicochemical properties for ≈4.2 million equilibrium and non-equilibrium structures of small organic molecules with up to seven non-hydrogen (C, N, O, S, Cl) atoms. To span this fundamentally important region of chemical compound space (CCS), QM7-X includes an exhaustive sampling of (meta-)stable equilibrium structures—comprised of constitutional/structural isomers and stereoisomers, e.g., enantiomers and diastereomers (including cis-/trans- and conformational isomers)—as well as 100 non-equilibrium structural variations thereof to reach a total of ≈4.2 million molecular structures. Computed at the tightly converged quantum-mechanical PBE0+MBD level of theory, QM7-X contains global (molecular) and local (atom-in-a-molecule) properties ranging from ground state quantities (such as atomization energies and dipole moments) to response quantities (such as polarizability tensors and dispersion coefficients). By providing a systematic, extensive, and tightly-converged dataset of quantum-mechanically computed physicochemical properties, we expect that QM7-X will play a critical role in the development of next-generation machine-learning based models for exploring greater swaths of CCS and performing in silico design of molecules with targeted properties.

Evaluation of fluorine-mediated intermolecular interactions in tetrafluorinated tetrahydroisoquinoline derivatives: synthesis and computational studies.

Intermolecular interactions involving the aromatic C-F group in the absence of other strong hydrogen bond acceptors is the theme of this article. Weak interactions involving fluorine are known to generate various supramolecular synthons, thereby altering the crystal structures of small organic molecules. It is demonstrated that the weak interactions involving organic fluorine play a major role in directing crystal packing of highly flexible organic molecules like diphenyl tetrahydroisoquinolines reported herein. The intramolecular C-H...F hydrogen bonds are found to be significant in controlling the molecular conformation in specific cases wheras the intermolecular interactions involving the C-F groups result in a wide range of supramolecular synthons involving C-H...F and C-F...F-C interactions. The interactions are studied computationally to provide insight into their energies and the topology of the interactions is studied using Atoms in Molecules. C-H...F-C interactions are found to be quite stabilizing in nature with the stabilization energy of -13.9 kcal mol-1.

ISpec: A Web-Based Activity for Spectroscopy Teaching

Students’ skills in structure elucidation of organic molecules are developed by training them to understand advanced spectroscopic measurements and elucidate structures of small organic molecules from mass spectrometry (MS) and infrared (IR), ultraviolet (UV), and 1H and 13C nuclear magnetic resonance (NMR) spectroscopic data. The present work puts a specific focus on developing student skills to ensure that the students (i) are aware of the resources involved in obtaining the spectral data and (ii) obtain the skills necessary to handle spectra which have not been processed by experts, to better reflect the use of spectroscopic techniques in their later work life. This is achieved through the web-based spectroscopy activity iSpec, in which the basic idea is that every action costs resources. The cost of a resource is given in the form of resource points (RPs), such that different experimental data can be “purchased” for a number of RPs.

ChemInform Abstract: Automated Interpretation of NMR Spectra for Small Organic Molecules in Solution

AbstractReview: 40 refs.

Fast experiments for structure elucidation of small molecules: Hadamard NMR with multiple receivers.

We propose several significant improvements to the PANSY (Parallel NMR SpectroscopY) experiments-PANSY COSY and PANSY-TOCSY. The improved versions of these experiments provide sufficient spectral information for structure elucidation of small organic molecules from just two 2D experiments. The PANSY-TOCSY-Q experiment has been modified to allow for simultaneous acquisition of three different types of NMR spectra-1D C-13 of non-protonated carbon sites, 2D TOCSY and multiplicity edited 2D HETCOR. In addition the J-filtered 2D PANSY-gCOSY experiment records a 2D HH gCOSY spectrum in parallel with a (1) J-filtered HC long-range HETCOR spectrum as well as offers a simplified data processing. In addition to parallel acquisition, further time savings are feasible because of significantly smaller F1 spectral windows as compared to the indirect detection experiments. Use of cryoprobes and multiple receivers can significantly alleviate the sensitivity issues that are usually associated with the so called direct detection experiments. In cases where experiments are sampling limited rather than sensitivity limited further reduction of experiment time is achieved by using Hadamard encoding. In favorable cases the total recording time for the two PANSY experiments can be reduced to just 40 s. The proposed PANSY experiments provide sufficient information to allow the CMCse software package (Bruker) to solve structures of small organic molecules.

A crystallographic perspective on sharing data and knowledge.

The crystallographic community is in many ways an exemplar of the benefits and practices of sharing data. Since the inception of the technique, virtually every published crystal structure has been made available to others. This has been achieved through the establishment of several specialist data centres, including the Cambridge Crystallographic Data Centre, which produces the Cambridge Structural Database. Containing curated structures of small organic molecules, some containing a metal, the database has been produced for almost 50 years. This has required the development of complex informatics tools and an environment allowing expert human curation. As importantly, a financial model has evolved which has, to date, ensured the sustainability of the resource. However, the opportunities afforded by technological changes and changing attitudes to sharing data make it an opportune moment to review current practices.

Sixth blind test of organic crystal-structure prediction methods

Over the past 15 years progress in predicting crystal structures of small organic molecules has been charted by a series of blind tests hosted by the Cambridge Crystallographic Data Centre. This letter announces a sixth blind test to take place between September 2014 and August 2015, giving details of the target systems and the revised procedure. We hope that as many methods as possible will be assessed and benchmarked in this new blind test.

Recent advances in the structure elucidation of small organic molecules by the LSD software

The LSD software proposes the structures of small organic molecules that fit with structural constraints from 1D and 2D NMR spectroscopy. Its initial design introduced limits that needed to be eliminated to extend its scope and help its users choose the most likely structure among those proposed. The LSD software code has been improved, so that it recognizes a wider set of atom types to build molecules. More flexibility has been given in the interpretation of 2D NMR data, including the automatic detection of very long-range correlations. A program named pyLSD was written to deal with problems in which atom types are ambiguously defined. It also provides a (13)C NMR chemical shift-based solution ranking algorithm. PyLSD was able to propose the correct structure of hexacyclinol, a natural product whose structure determination has been highly controversal. The solution was ranked first within a list of ten structures that were produced by pyLSD from the literature NMR data. The structure of an aporphin natural product was determined by pyLSD, taking advantage of the possibility of handling electrically charged atoms. The structure generation of the insect antifeedant azadirachtin by LSD was reinvestigated by pyLSD, considering that three (13)C resonances did not lead to univocal hybridization states.

Optical Waveguides Based on Single‐Crystalline Organic Micro‐Tiles

Surface waveguides are an important topic because of their ability to transmit sub-wavelength information, [ 1 ] that is, details with dimensions less than the wavelength of visible light, which holds promise for utilization in faster and more compact optoelectronic communications and sensors. [ 2 ] Great effort has been put into optical waveguides based on onedimensional (1D) inorganic nanostructures. For example, Lieber’s group [ 3 , 4 ] and Yang and coworkers [ 5 , 6 ] have demonstrated that crystalline wireand ribbon-like nanomaterials of inorganic semiconductors can successfully serve as waveguides for light with wavelengths less than that of visible light. Then, Redmond and coworkers reported the waveguiding property of conjugated polymer nanowires. [ 7 ] Very recently, optical waveguides based on 1D structures of small organic molecules have been realized using nanowires, nanoribbons, and nanofi bers. [ 8–14 ] However, optical waveguides based on small organic molecules with 2D structures are still in their infancy. [ 15 ] They are expected to display waveguiding behavior different from that of 1D materials owing to their different microstructures. Furthermore, it should be of great scientifi c interest to extend the relevant research from solid 1D nanorods/wires/ tubes to 2D micro-tiles, because the 2D tile structures are more suitable for the application of controlling directional waveguides. Here, we report the preparation of 2D crystalline microstructures, that is, micro-tiles, from hexaphenylsiloles (HPSs), small organic compounds, by self-assembly. Characterization of single micro-tiles indicates that the 2D HPS microstructures can serve as active optical waveguides that allow locally excited photoluminescence to propagate along the abscissa of the 2D structures and out-couple at the ridge tips. The unique 2D optical waveguiding phenomenon of HPS micro-tiles might be useful

Comparison of the molecular structures of five benzene derivatives as determined independently by gas-phase electron diffraction in two different laboratories: a perspective

The merits and limitations of gas-phase electron diffraction as a technique for determining accurately the structures of small organic molecules are demonstrated by comparing the molecular structures of five benzene derivatives studied in two different laboratories. The existence of many possible representations of the structure of a molecule (r a, r g, r α, r α 0 , r e, …), implying differences in the physical meaning of geometrical parameters, is discussed in some detail as it may cause difficulties in a comparison. Also illustrated are different ways of estimating and expressing uncertainties in the geometrical parameters from a gas-phase electron diffraction study.

Significant progress in predicting the crystal structures of small organic molecules – a report on the fourth blind test

We report on the organization and outcome of the fourth blind test of crystal structure prediction, an international collaborative project organized to evaluate the present state in computational methods of predicting the crystal structures of small organic molecules. There were 14 research groups which took part, using a variety of methods to generate and rank the most likely crystal structures for four target systems: three single-component crystal structures and a 1:1 cocrystal. Participants were challenged to predict the crystal structures of the four systems, given only their molecular diagrams, while the recently determined but as-yet unpublished crystal structures were withheld by an independent referee. Three predictions were allowed for each system. The results demonstrate a dramatic improvement in rates of success over previous blind tests; in total, there were 13 successful predictions and, for each of the four targets, at least two groups correctly predicted the observed crystal structure. The successes include one participating group who correctly predicted all four crystal structures as their first ranked choice, albeit at a considerable computational expense. The results reflect important improvements in modelling methods and suggest that, at least for the small and fairly rigid types of molecules included in this blind test, such calculations can be constructively applied to help understand crystallization and polymorphism of organic molecules.

Cα-H···O=C hydrogen bonds contribute to the specificity of RGD cell-adhesion interactions

BackgroundThe Arg-Gly-Asp (RGD) cell adhesion sequence occurs in several extracellular matrix molecules known to interact with integrin cell-surface receptors. Recently published crystal structures of the extracellular regions of two integrins in complex with peptides containing or mimicking the RGD sequence have identified the Arg and Asp residues as key specificity determinants for integrin recognition, through hydrogen bonding and metal coordination interactions. The central Gly residue also appears to be in close contact with the integrin surface in these structures.ResultsWhen hydrogen atoms are modelled on the central Gly residue with standard stereochemistry, the interaction between this residue and a carbonyl group in the integrin surface shows all the hallmarks of Cα-H···O=C hydrogen bonding, as seen in the collagen triple helix and in many crystal structures of small organic molecules. Moreover, molecular dynamic simulations of the docking of RGD-containing fragments on integrin surfaces support the occurrence of these interactions. There appears to be an array of four weak and conventional hydrogen bonds lining up the RGD residues with main chain carbonyl groups in the integrin surface.ConclusionsThe occurrence of weak Cα-H···O=C hydrogen bonds in the RGD-integrin interaction highlights the importance of the conserved Gly residue in the RGD motif and its contribution to integrin-ligand binding specificity. Our analysis shows how weak hydrogen bonds may also play important biological roles by contributing to the specificity of macromolecular recognition.

Analysis of the less common hydrogen bonds involving ester oxygen sp3 atoms as acceptors in the crystal structures of small organic molecules.

An analysis of hydrogen bonds involving ester Osp3 atoms as acceptors has been performed based on the data extracted from the Cambridge Structural Database [Allen (2002). Acta Cryst. B58, 380-388; version 5.25, November 2003], using the ConQuest package to evaluate the stereochemical and electronic properties of the acceptors. Evidence for the existence of this particular type of hydrogen bond and its structural function in crystal packing is presented. Using a cut-off limit on residual indices of R < 0.05 (for the structures with hydrogen bonds involving an oxygen as part of the donor group) and R < 0.085 (for nitrogen as part of the donor group), 230 structures out of the total CSD entries of 298,100 were found to contain hydrogen bonds with the ester Osp3 atoms as acceptors. The hydrogen-bond donors include water molecules, hydroxyl groups, primary and secondary amines and, in a few cases, imino groups. Four modes of the participation of the ester Osp3 atoms in hydrogen bonding are detected: as a single acceptor, as a double acceptor, as a single acceptor of a H atom involved in an intermolecular bifurcated hydrogen bond, and as a shared acceptor function with the ester Osp2 atom in a bifurcated hydrogen bond. The role of such directed noncovalent interactions in crystal packing is demonstrated by a small gallery of selected structures.

Computer simulations of organic solids and their liquid-state precursors

Representative calculations on 2-pyridone in its crystalline, liquid and solvated form, show the capabilities and the shortcomings of computer simulation techniques for the description of organic molecular systems. Both ‘static’ and ‘dynamic’ computations, meaning without and with the explicit treatment of thermal motion, are employed. Relationships of liquid and solution systems to the structure and thermodynamics of the crystalline solids are investigated as far as possible, with regards to efficient and systematic crystal structure prediction from molecular structure. The thesis to be discussed here is that a reliable theory for the prediction of the solid-state structure of small organic molecules must depend on an accurate thermodynamic and kinetic evaluation of the pathways for evolution from disorder to order, including liquid structuring and nucleation. Dynamic methods, including thermal motion, are indispensable for the accomplishment of this task, which remains today a faraway goal in structural physical chemistry.