New insights and innovation from a million crystal structures in the Cambridge Structural Database

dMXP: A De Novo Small-Molecule 3D Structure Predictor with Graph Attention Networks

Generating the three-dimensional (3D) structure of small molecules is crucial in both structure- and ligand-based drug design. Structure-based drug design needs bioactive conformations of compounds for lead identification and optimization. Ligand-based drug design techniques, such as 3D shape similarity search, 3D pharmacophore model, 3D-QSAR, etc., all require high-quality small-molecule ligand conformations to obtain reliable results. Although predicting a small molecular bioactive conformer requires information from the receptor, a crystal structure of the molecule is a proper approximation to its bioactive conformer in a specific receptor because the binding pose of a small molecule in its receptor's binding pockets should be energetically close to the crystal structures. This study presents a de novo small molecular structure predictor (dMXP) with graph attention networks based on crystal data derived from the Cambridge Structural Database (CSD) combined with molecular electrostatic information calculated by density-functional theory (DFT). Two featuring strategies (topological and atomic partial change features) were employed to explore the relation between these features and the 3D crystal structure of a small molecule. These features were then assembled to construct the holistic 3D crystal structure of a molecule. Molecular graphs were encoded using a graph attention mechanism to deal with the issues of the inconsistencies of local substructures contributing to the entire molecular structure. The root-mean-square deviation (RMSDs) of approximately 80% dMXP predicted structures and the native binding poses within receptors are less than 2.0 Å.

Thiazolyl-isatin derivatives: Synthesis, in silico studies, in vitro biological profile against breast cancer cells, mRNA expression, P-gp modulation, and interactions of Akt2 and VIM proteins

The literature reports that thiazole and isatin nuclei present a range of biological activities, with an emphasis on anticancer activity. Therefore, our proposal was to make a series of compounds using the molecular hybridization strategy, which has been used by our research group, producing hybrid molecules containing the thiazole and isatin nuclei. After structural planning and synthesis, the compounds were characterized and evaluated in vitro against breast cancer cell lines (T-47D, MCF-7 and MDA-MB-231) and against normal cells (PBMC). The activity profile on membrane proteins involved in chemoresistance and tumorigenic signaling proteins was also evaluated. Among the compounds tested, the compounds 4c and 4a stood out with IC50 values of 1.23 and 1.39 μM, respectively, against the MDA-MB-231 cell line. Both compounds exhibited IC50 values of 0.45 μM for the MCF-7 cell line. Compounds 4a and 4c significantly decreased P-gp mRNA expression levels in MCF-7, 4 and 2 folds respectively. Regarding the impact on tumorigenic signaling proteins, compound 4a inhibited Akt2 in MDA-MB-231 and compound 4c inhibited the mRNA expression of VIM in MCF-7.

The Cambridge Structural Database and structural dynamics

With the availability of the computer readable information in the Cambridge Structural Database (CSD), wide ranging, largely automated comparisons of fragment, molecular, and crystal structures have become possible. They show that the distributions of interatomic distances, angles, and torsion angles for a given structural fragment occurring in different environments are highly correlated among themselves and with other observables such as spectroscopic signals, reaction and activation energies. The correlations often extend continuously over large ranges of parameter values. They are reminiscent of bond breaking and forming reactions, polyhedral rearrangements, and conformational changes. They map-qualitatively-the regions of the structural parameter space in which molecular dynamics take place, namely, the low energy regions of the respective (free) energy surfaces. The extension and continuous nature of the correlations provides an organizing principle of large groups of structural data and suggests a reconsideration of traditional definitions and descriptions of bonds, "nonbonded" and "noncovalent" interactions in terms of Lewis acids interacting with Lewis bases. These aspects are illustrated with selected examples of historic importance and with some later developments. It seems that the amount of information in the CSD (and other structural databases) and the knowledge on the nature of, and the correlations within, this body of information should allow one-in the near future-to make credible interpolations and possibly predictions of structures and their properties with machine learning methods.

Identification of potential inhibitors targeting Ebola virus VP35 protein: a computational strategy

Ebola virus (EBOV) poses a severe threat as a highly infectious pathogen, causing devastating hemorrhagic fever in both humans and animals. The EBOV virus VP35 protein plays a crucial role in viral replication and exhibits the ability to suppress the host interferon cascade, leading to immune system depletion. As a potential drug target, VP35 protein inhibition holds promise for combating EBOV. To discover new drug candidates, we employed a computer-aided drug design approach, focusing on compounds capable of inhibiting VP35 protein replication. In this connection, a pharmacophore model was generated using molecular interactions between the VP35 protein and its inhibitor. ZINC and Cambridge database were screened using validated pharmacophore model. Further the compounds were filtered based on Lipinski's rule of five and subjected to MD simulation and relative binding free energy calculation. Six compounds manifest a significant docking score and strong binding interaction towards VP35 protein. MD simulations further confirmed the remarkable stability of these six complexes. Relative binding free energy calculations also showed significant ΔG value in the range of -132.3 and -49.3 kcal/mol. This study paves the way for further optimization of these compounds as potential inhibitors of VP35, facilitating subsequent experimental in vitro studies.Communicated by Ramaswamy H. Sarma.

Data-Driven Materials Innovation and Applications

Owing to the rapid developments to improve the accuracy and efficiency of both experimental and computational investigative methodologies, the massive amounts of data generated have led the field of materials science into the fourth paradigm of data-driven scientific research. This transition requires the development of authoritative and up-to-date frameworks for data-driven approaches for material innovation. A critical discussion on the current advances in the data-driven discovery of materials with a focus on frameworks, machine-learning algorithms, material-specific databases, descriptors, and targeted applications in the field of inorganic materials is presented. Frameworks for rationalizing data-driven material innovation are described, and a critical review of essential subdisciplines is presented, including: i) advanced data-intensive strategies and machine-learning algorithms; ii) material databases and related tools and platforms for data generation and management; iii) commonly used molecular descriptors used in data-driven processes. Furthermore, an in-depth discussion on the broad applications of material innovation, such as energy conversion and storage, environmental decontamination, flexible electronics, optoelectronics, superconductors, metallic glasses, and magnetic materials, is provided. Finally, how these subdisciplines (with insights into the synergy of materials science, computational tools, and mathematics) support data-driven paradigms is outlined, and the opportunities and challenges in data-driven material innovation are highlighted.

Nonplanar porphyrins: synthesis, properties, and unique functionalities

Porphyrins are variously substituted tetrapyrrolic macrocycles, with wide-ranging biological and chemical applications derived from metal chelation in the core and the 18π aromatic surface. Under suitable conditions, the porphyrin framework can deform significantly from regular planar shape, owing to steric overload on the porphyrin periphery or steric repulsion in the core, among other structure modulation strategies. Adopting this nonplanar porphyrin architecture allows guest molecules to interact directly with an exposed core, with guest-responsive and photoactive electronic states of the porphyrin allowing energy, information, atom and electron transfer within and between these species. This functionality can be incorporated and tuned by decoration of functional groups and electronic modifications, with individual deformation profiles adapted to specific key sensing and catalysis applications. Nonplanar porphyrins are assisting breakthroughs in molecular recognition, organo- and photoredox catalysis; simultaneously bio-inspired and distinctly synthetic, these molecules offer a new dimension in shape-responsive host-guest chemistry. In this review, we have summarized the synthetic methods and design aspects of nonplanar porphyrin formation, key properties, structure and functionality of the nonplanar aromatic framework, and the scope and utility of this emerging class towards outstanding scientific, industrial and environmental issues.

Feasibility of p-Doped Molecular Crystals as Transparent Conductive Electrodes via Virtual Screening

Transparent conducting materials are an essential component of optoelectronic devices. It is proven difficult, however, to develop high-performance materials that combine the often-incompatible properties of transparency and conductivity, especially for p-type-doped materials. In this work, we have employed a large set of molecular semiconductors extracted from the Cambridge Structural Database to evaluate the likelihood of transparent conducting material technology based on p-type-doped molecular crystals. Candidates are identified imposing the condition of high highest occupied molecular orbital (HOMO) energy level (for the material to be easily dopable), high charge carrier mobility (for the material to display large conductivity when doped), and a high threshold for energy absorption (for the material to absorb radiation only in the ultraviolet). The latest condition is found to be the most stringent criterion in a virtual screening protocol on a database composed of structures with sufficiently wide two-dimensional (2D) electronic bands. Calculation of excited-state energy is shown to be essential as the HOMO-lowest unoccupied molecular orbital (LUMO) gap cannot be reliably used to predict the transparency of this material class. Molecular semiconductors with desirable mobility are transparent because they display either forbidden electronic transition(s) to the lower excited states or small exchange energy between the frontier orbitals. Both features are difficult to design but can be found in a good number of compounds through virtual screening.

Chemical crystallography by serial femtosecond X-ray diffraction

Inorganic-organic hybrid materials represent a large share of newly reported structures, owing to their simple synthetic routes and customizable properties1. This proliferation has led to a characterization bottleneck: many hybrid materials are obligate microcrystals with low symmetry and severe radiation sensitivity, interfering with the standard techniques of single-crystal X-ray diffraction2,3 and electron microdiffraction4-11. Here we demonstrate small-molecule serial femtosecond X-ray crystallography (smSFX) for the determination of material crystal structures from microcrystals. We subjected microcrystalline suspensions to X-ray free-electron laser radiation12,13 and obtained thousands of randomly oriented diffraction patterns. We determined unit cells by aggregating spot-finding results into high-resolution powder diffractograms. After indexing the sparse serial patterns by a graph theory approach14, the resulting datasets can be solved and refined using standard tools for single-crystal diffraction data15-17. We describe the ab initio structure solutions of mithrene (AgSePh)18-20, thiorene (AgSPh) and tethrene (AgTePh), of which the latter two were previously unknown structures. In thiorene, we identify a geometric change in the silver-silver bonding network that is linked to its divergent optoelectronic properties20. We demonstrate that smSFX can be applied as a general technique for structure determination of beam-sensitive microcrystalline materials at near-ambient temperature and pressure.

Use of molecular docking computational tools in drug discovery

Molecular docking has become an important component of the drug discovery process. Since first being developed in the 1980s, advancements in the power of computer hardware and the increasing number of and ease of access to small molecule and protein structures have contributed to the development of improved methods, making docking more popular in both industrial and academic settings. Over the years, the modalities by which docking is used to assist the different tasks of drug discovery have changed. Although initially developed and used as a standalone method, docking is now mostly employed in combination with other computational approaches within integrated workflows. Despite its invaluable contribution to the drug discovery process, molecular docking is still far from perfect. In this chapter we will provide an introduction to molecular docking and to the different docking procedures with a focus on several considerations and protocols, including protonation states, active site waters and consensus, that can greatly improve the docking results.

Metrical Oxidation States of 1,4-Diazadiene-Derived Ligands

The conventional method of assigning formal oxidation states (FOSs) to metals and ligands is an important tool for understanding and predicting the chemical reactivity, in particular, in catalysis research. For complexes containing redox-noninnocent ligands, the oxidation state of the ligand can be ambiguous (i.e., their spectroscopic oxidation state can differ from the FOS) and thus frustrates the assignment of the oxidation state of the metal. A quantitative correlation between the empirical metric data of redox-active ligands and their oxidation states using a metrical oxidation state (MOS) model has been developed for catecholate- and amidophenoxide-derived ligands by Brown. In the present work, we present a MOS model for 1,4-diazabutadiene (DADⁿ) ligands. This model is based on a similar approach as reported by Brown, correlating the intra-ligand bond lengths of the DADⁿ moiety in a quantitative manner with the MOS using geometrical information from X-ray structures in the Cambridge Crystallographic Data Center (CCDC) database. However, an accurate determination of the MOS of these ligands turned out to be dependent on the coordination mode of the DAD^2– moiety, which can adopt both a planar κ²-N₂-geometry and a η⁴-N₂C₂ π-coordination mode in (transition) metal complexes in its doubly reduced, dianionic enediamide oxidation state. A reliable MOS model was developed taking the intrinsic differences in intra-ligand bond distances between these coordination modes of the DAD^2– ligand into account. Three different models were defined and tested using different geometric parameters (C=C → M distance, M–N–C angle, and M–N–C–C torsion angle) to describe the C=C backbone coordination with the metal in the η⁴-N₂-C₂ π-coordination mode of the DAD^2– ligand. Statistical analysis revealed that the C=C → M distance best describes the η⁴-N₂-C₂ coordination mode using a cutoff value of 2.46 Å for π-coordination. The developed MOS model was used to validate the oxidation state assignment of elements not contained within the training set (Sr, Yb, and Ho), thus demonstrating the applicability of the MOS model to a wide range of complexes. Chromium complexes with complex electronic structures were also shown to be accurately described by MOS analysis. Furthermore, it is shown that a combination of MOS analysis and FOD calculations provides an inexpensive method to gain insight into the electronic structure of singlet spin state (S = 0) [M(trop₂dad)] transition-metal complexes showing (potential) singlet biradical character.

Assigning oxidation states to metals and ligands is an important tool for understanding and predicting the chemical reactivity. For complexes containing redox-noninnocent ligands, the oxidation state of the ligand can be ambiguous. We present a metrical oxidation state model for 1,4-diazabutadiene ligands, correlating the intra-ligand bond lengths with the oxidation state using information from X-ray structures. This model accounts for the difference in bond length distances between the different coordination modes of the fully reduced ligand.

A Supramolecular Approach to Structure-Based Design with A Focus on Synthons Hierarchy in Ornithine-Derived Ligands: Review, Synthesis, Experimental and in Silico Studies

The success of innovative drugs depends on an interdisciplinary and holistic approach to their design and development. The supramolecular architecture of living systems is controlled by non-covalent interactions to a very large extent. The latter are prone to extensive cooperation and like a virtuoso play a symphony of life. Thus, the design of effective ligands should be based on thorough knowledge on the interactions at either a molecular or high topological level. In this work, we emphasize the importance of supramolecular structure and ligand-based design keeping the potential of supramolecular H-bonding synthons in focus. In this respect, the relevance of supramolecular chemistry for advanced therapies is appreciated and undisputable. It has developed tools, such as Hirshfeld surface analysis, using a huge data on supramolecular interactions in over one million structures which are deposited in the Cambridge Structure Database (CSD). In particular, molecular interaction surfaces are useful for identification of macromolecular active sites followed by in silico docking experiments. Ornithine-derived compounds are a new, promising class of multi-targeting ligands for innovative therapeutics and cosmeceuticals. In this work, we present the synthesis together with the molecular and supramolecular structure of a novel ornithine derivative, namely N-α,N-δ)-dibenzoyl-(α)-hydroxymethylornithine, 1. It was investigated by modern experimental and in silico methods in detail. The incorporation of an aromatic system into the ornithine core induces stacking interactions, which are vital in biological processes. In particular, rare C=O…π intercontacts have been identified in 1. Supramolecular interactions were analyzed in all structures of ornithine derivatives deposited in the CSD. The influence of substituent was assessed by the Hirshfeld surface analysis. It revealed that the crystal packing is stabilized mainly by H…O, O…H, C…H, Cl (Br, F)…H and O…O interactions. Additionally, π…π, C-H…π and N-O…π interactions were also observed. All relevant H-bond energies were calculated using the Lippincott and Schroeder H-bond model. A library of synthons is provided. In addition, the large synthons (Long-Range Synthon Aufbau Module) were considered. The DFT optimization either in vacuo or in solutio yields very similar molecular species. The major difference with the relevant crystal structure was related to the conformation of terminal benzoyl C15-C20 ring. Furthermore, in silico prediction of the extensive physicochemical ADME profile (absorption, distribution, metabolism and excretion) related to the drug-likeness and medicinal chemistry friendliness revealed that a novel ornithine derivative 1 has the potential to be a new drug candidate. It has shown good in silico absorption and very low toxicity.

Structural analysis of metastable pharmaceutical loratadine form II, by 3D electron diffraction and DFT+D energy minimisation

Coupling 3D electron diffraction and density functional theory provided the metastable pharmaceutical crystal structure within nanometre range, under ambient conditions.