Dataset for quantum-mechanical exploration of conformers and solvent effects in large drug-like molecules.

We here introduce the Aquamarine (AQM) dataset, an extensive quantum-mechanical (QM) dataset that contains the structural and electronic information of 59,783 low-and high-energy conformers of 1,653 molecules with a total number of atoms ranging from 2 to 92 (mean: 50.9), and containing up to 54 (mean: 28.2) non-hydrogen atoms. To gain insights into the solvent effects as well as collective dispersion interactions for drug-like molecules, we have performed QM calculations supplemented with a treatment of many-body dispersion (MBD) interactions of structures and properties in the gas phase and implicit water. Thus, AQM contains over 40 global and local physicochemical properties (including ground-state and response properties) per conformer computed at the tightly converged PBE0+MBD level of theory for gas-phase molecules, whereas PBE0+MBD with the modified Poisson-Boltzmann (MPB) model of water was used for solvated molecules. By addressing both molecule-solvent and dispersion interactions, AQM dataset can serve as a challenging benchmark for state-of-the-art machine learning methods for property modeling and de novo generation of large (solvated) molecules with pharmaceutical and biological relevance.

Gram matrix: an efficient representation of molecular conformation and learning objective for molecular pretraining.

Accurate prediction of molecular properties is fundamental in drug discovery and development, providing crucial guidance for effective drug design. A critical factor in achieving accurate molecular property prediction lies in the appropriate representation of molecular structures. Presently, prevalent deep learning-based molecular representations rely on 2D structure information as the primary molecular representation, often overlooking essential three-dimensional (3D) conformational information due to the inherent limitations of 2D structures in conveying atomic spatial relationships. In this study, we propose employing the Gram matrix as a condensed representation of 3D molecular structures and for efficient pretraining objectives. Subsequently, we leverage this matrix to construct a novel molecular representation model, Pre-GTM, which inherently encapsulates 3D information. The model accurately predicts the 3D structure of a molecule by estimating the Gram matrix. Our findings demonstrate that Pre-GTM model outperforms the baseline Graphormer model and other pretrained models in the QM9 and MoleculeNet quantitative property prediction task. The integration of the Gram matrix as a condensed representation of 3D molecular structure, incorporated into the Pre-GTM model, opens up promising avenues for its potential application across various domains of molecular research, including drug design, materials science, and chemical engineering.

Structural characterization and keto-enol tautomerization of 4-substituted pyrazolone derivatives with DFT approach.

The synthesis of two pyrazolone derivative compounds, PYR-I(4-Acetyl-1-(4-chlorophenyl)-3-isopropyl-1H-pyrazol-5(4H)-one) and PYR-II1-(4-Chlorophenyl))-3-isopropyl-5-oxo-4,5-5-dihydro-1H-pyrazole-4-carbaldehyde, their characterization by FT-IR, NMR, UV-Vis and GC-MS techniques, and the evaluation of the keto-enol tautomerization process of the structures along with the DFT approach and spectral data were reported in this paper. Spectral findings indicated that PYR-I was stable at the keto state. The IR spectrum recorded in solid form showed that the PYR-II structure was stable in the enol state, while the NMR spectrum in the solution medium showed that it was stable in the keto state. DFT-based analyses were realized with the B3LYP hybrid functional and the 6-311++G(d,p) basis set. The modelled keto, transition and enol state molecular geometries of structures were optimized in the gas phase and different solvent media and the total energy and dipole moment values were investigated at the specified theoretical level. The possible keto-enol tautomerism mechanism of the structures was evaluated through some thermodynamic parameters such as the difference in free Gibbs energy (ΔG), enthalpy (ΔH), entropy (ΔS), and predictive tautomeric equilibrium constants (Keq), acidity constants (pKa) and percentages of tautomers at 298.15 K and 1 atm pressure. The results of these analyses based on the DFT approach indicated that the keto-enol tautomer equilibrium heavily favours the keto form for PYR-I and the enol form for PYR-II in all cases. Moreover, natural bond orbital (NBO) analysis was performed for the tautomers, and the chemical reactivity profiles of the most stable tautomers were examined with the values of frontier molecular orbital energy and some reactivity descriptors.

Accurately Computing the Interacted Volume of Molecules over Their 3D Mesh Models.

For quickly predicting the rational arrangement of catalysts and substrates, we previously proposed a method to calculate the interacted volumes of molecules over their 3D point cloud models. However, the nonuniform density in molecular point clouds may lead to incomplete contours in some slices, reducing the accuracy of the previous method. In this paper, we propose a two-step method for more accurately computing molecular interacted volumes. First, by employing a prematched mesh slicing method, we layer the 3D triangular mesh models of the electrostatic potential isosurfaces of two molecules globally, transforming the volume calculation into finding the intersecting areas in each layer. Next, by subdividing polygonal edges, we accurately identify intersecting parts within each layer, ensuring precise calculation of interacted volumes. In addition, we present a concise overview for computing intersecting areas in cases of multiple contour intersections and for improving computational efficiency by incorporating bounding boxes at three stages. Experimental results demonstrate that our method maintains high accuracy in different experimental data sets, with an average relative error of 0.16%. On the same experimental setup, our average relative error is 0.07%, which is lower than the previous algorithm's 1.73%, improving the accuracy and stability in calculating interacted volumes.

CageCavityCalc (C3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages.

Organic(porous) and metal-organic cages are promising biomimetic platforms with diverse applications spanning recognition, sensing, and catalysis. The key to the emergence of these functions is the presence of well-defined inner cavities capable of binding a wide range of guest molecules and modulating their properties. However, despite the myriad cage architectures currently available, the rational design of structurally diverse and functional cages with specific host-guest properties remains challenging. Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce CageCavityCalc (C3), a Python-based tool for calculating the cavity size of molecular cages. The code is available on GitHub at https://github.com/VicenteMartiCentelles/CageCavityCalc. C3 utilizes a novel algorithm that enables the rapid calculation of cavity sizes for a wide range of molecular structures and porous systems. Moreover, C3 facilitates easy visualization of the computed cavity size alongside hydrophobic and electrostatic potentials, providing insights into host-guest interactions within the cage. Furthermore, the calculated cavity can be visualized using widely available visualization software, such as PyMol, VMD, or ChimeraX. To enhance user accessibility, a PyMol plugin has been created, allowing nonspecialists to use this tool without requiring computer programming expertise. We anticipate that the deployment of this computational tool will significantly streamline cage cavity calculations, thereby accelerating the discovery of functional cages.

Sequence-Dependent Surface Coverage of ssDNA Coatings on Single-Wall Carbon Nanotubes.

A combination of experimental measurements and molecular dynamics (MD) simulations was used to investigate how the surfaces of single-wall carbon nanotubes (SWCNTs) are covered by adsorbed ssDNA oligos with different base compositions and lengths. By analyzing the UV absorption spectra of ssDNA-coated SWCNTs before and after coating displacement by a transparent surfactant, the mass ratios of adsorbed ssDNA to SWCNTs were determined for poly-T, poly-C, GT-containing, and AT-containing ssDNA oligos. Based on the measured mass ratios, it is estimated that an average of 20, 22, 26, or 32 carbon atoms are covered by one adsorbed thymine, cytosine, adenine, or guanine nucleotide, respectively. In addition, the UV spectra revealed electronic interactions of varying strengths between the nucleobase aromatic rings and the nanotube π-systems. Short poly-T DNA oligos show stronger π-π stacking interactions with SWCNT surfaces than do short poly-C DNA oligos, whereas both long poly-C and poly-T DNA oligos show strong interactions. These experiments were complemented by MD computations on simulated systems that were constrained to match the measured ssDNA/SWCNT mass ratios. The surface coverages computed from the MD results varied with oligo composition in a pattern that correlates higher measured yields of nanotube fluorescence with greater surface coverage.

From mundane to surprising nonadditivity: drivers and impact on ML models.

Nonadditivity (NA) in Structure-Activity and Structure-Property Relationship (SAR) data is a rare but very information rich phenomenon. It can indicate conformational flexibility, structural rearrangements, and errors in assay results and structural assignment. While purely ligand-based conformational causes of NA are rather well understood and mundane, other factors are less so and cause surprising NA that has a huge influence on SAR analysis and ML model performance. We here report a systematic analysis across a wide range of properties (20 on-target biological activities and 4 physicochemical ADME-related properties) to understand the frequency of various different phenomena that may lead to NA. A set of novel descriptors were developed to characterize double transformation cycles and identify trends in NA. Double transformation cycles were classified into "surprising" and "mundane" categories, with the majority being classed as mundane. We also examined commonalities among surprising cycles, finding LogP differences to have the most significant impact on NA. A distinct behavior of NA for on-target sets compared to ADME sets was observed. Finally, we show that machine learning models struggle with highly nonadditive data, indicating that a better understanding of NA is an important future research direction.

Stereoselective Solid-State Synthesis of Biologically Active Cyclobutane and Dicyclobutane Isomers via Conformation Blocking and Transference.

Conformations in the solid state are typically fixed during crystallization. Transference of "frozen" C=C conformations in 3,5-bis((E)-2-(pyridin-4-yl)vinyl)methylbenzene (CH3-3,5-bpeb) by photodimerization selectively yielded cyclobutane and dicyclobutane isomers, one of which (Isomer 2) exhibited excellent in vitro anti-cancer activity towards T-24, 7402, MGC803, HepG-2, and HeLa cells.

Synthesis of Thiazolidin-4-Ones Derivatives, Evaluation of Conformation in Solution, Theoretical Isomerization Reaction Paths and Discovery of Potential Biological Targets.

Thiazolin-4-ones and their derivatives represent important heterocyclic scaffolds with various applications in medicinal chemistry. For that reason, the synthesis of two 5-substituted thiazolidin-4-one derivatives was performed. Their structure assignment was conducted by NMR experiments (2D-COSY, 2D-NOESY, 2D-HSQC and 2D-HMBC) and conformational analysis was conducted through Density Functional Theory calculations and 2D-NOESY. Conformational analysis showed that these two molecules adopt exo conformation. Their global minimum structures have two double bonds (C=N, C=C) in Z conformation and the third double (C=N) in E. Our DFT results are in agreement with the 2D-NMR measurements. Furthermore, the reaction isomerization paths were studied via DFT to check the stability of the conformers. Finally, some potential targets were found through the SwissADME platform and docking experiments were performed. Both compounds bind strongly to five macromolecules (triazoloquinazolines, mglur3, Jak3, Danio rerio HDAC6 CD2, acetylcholinesterase) and via SwissADME it was found that these two molecules obey Lipinski's Rule of Five.

Absolute Configuration of 4-Chloroisoleucine in Cyclolithistide A: An Antifungal Peptide Lactone Discovered in Marine Lithistid Sponges.

Cyclolithistide A is a peptide lactone isolated from marine lithistid sponges. Its entire structure, including absolute configurations, has been reported except the relative and absolute configurations of its characteristic residue, 4-chloroisoleucine (4-CIle). We synthesized four isomers of 4-CIle from furfural-derived N-Boc imine and propionaldehyde. Analysis of the acid hydrolysate of cyclolithistide A and the synthetic samples of 4-CIle after derivatization with l- and d-FDAA permitted us to propose the absolute configuration of the 4-chloroisoleucine residue in cyclolithistide A as 2S,3R,4R.

Rational Design of Molecularly Imprinted Polymers for Curcuminoids Binding: Computational and Experimental Approaches for the Selection of Functional Monomers.

Molecularly imprinted polymers (MIPs) have emerged as bespoke materials with versatile molecular applications. In this study, we propose a proof of concept for a methodology employing molecular dynamics (MD) simulations to guide the selection of functional monomers for curcuminoid binding in MIPs. Curcumin, demethoxycurcumin, and bisdemethoxycurcumin are phenolic compounds widely employed as spices, pigments, additives, and therapeutic agents, representing the three main curcuminoids of interest. Through MD simulations, we investigated prepolymerization mixtures composed of various functional monomers, including acrylamide (ACA), acrylic acid (AA), methacrylic acid (MAA), and N-vinylpyrrolidone (NVP), with ethylene glycol dimethacrylate (EGDMA) as the cross-linker and acetonitrile as the solvent. Curcumin was selected as the template molecule due to its structural similarity to the other curcuminoids. Notably, the prepolymerization mixture containing NVP as the functional monomer demonstrated superior molecular recognition capabilities toward curcumin. This observation was supported by higher functional monomer molecules surrounding the template, a lower total nonbonded energy between the template and monomer, and a greater number of hydrogen bonds in the aggregate. These findings suggest a stronger affinity between the functional monomer NVP and the template. We synthesized, characterized, and conducted binding tests on the MIPs to validate the MD simulation results. The experimental binding tests confirmed that the MIP-NVP exhibited higher binding capacity. Consequently, based on MD simulations, our computational methodology effectively guided the selection of the functional monomer, leading to MIPs with binding capacity for curcuminoids. The outcomes of this study provide a valuable reference for the rational design of MIPs through MD simulations, facilitating the selection of components for MIPs. This computational approach holds the potential for extension to other templates, establishing a robust methodology for the rational design of MIPs.

Immunosuppressive leucosesterterpane and penta-nor-leucosesterterpane sesterterpenoids from Leucosceptrum canum.

Five undescribed leucosesterterpane sesterterpenoids, leucosceptrines A-E, two undescribed penta-nor-leucosesterterpane (C20) sesterterpenoids, nor-leucosceptrines A and B, and three known analogues, were obtained from the aerial parts of Leucosceptrum canum of Chinese origin. Leucosceptrines A-C are the first examples of leucosesterterpane-type sesterterpenoids with unclosed dihydropyran rings and reverse configurations at chiral centers C-4 and/or C-12. Nor-leucosceptrines A and B possesses an unusual penta-nor-leucosesterterpane skeleton. Their structures were unambiguously elucidated through comprehensive spectroscopic analyses and single-crystal X-ray diffraction. A plausible biogenetic pathway for these sesterterpenoids was proposed. The immunosuppressive effects of these isolates on the secretion of the cytokine IFN-γ by T cells stimulated with anti-CD3/CD28 monoclonal antibodies were observed with different potencies.

Structurally diverse diterpenoids and phenanthrene derivatives from the roots of Baliospermumsolanifolium.

Ten undescribed diterpenoids (1-10) and three undescribed phenanthrene derivatives (11-13), together with seven known compounds, were isolated from the roots of Baliospermum solanifolium. Their structures were determined by a combination of spectroscopic data analysis, electronic circular dichroism calculations and single-crystal X-ray diffraction studies. Compounds 1-7 (baliosperoids A-G) represent the examples of 20-nor-ent-podocarpane class first discovered in nature. In particular, compound 7 possesses a unique 2,3-seco ring system incorporating γ-butanolide moiety. All isolates were assessed for their cytotoxic activities against HT-29, HCT-116, HCT-15, MCF-7, and A549 cell lines as well as their inhibitory effects on lipopolysaccharide-induced NO production in RAW264.7 cells. Compound 1, a 20-nor-ent-podocarpane-type diterpenoid possessing a Δ1,2 double bond, not only exhibited considerable proliferation inhibition against five human cancer cell lines, with IC50 values ranging from 4.13 to 23.45 µM, but also displayed the most potent inhibitory activity on NO production with IC50 value at the nanomolar level (0.63 ± 0.21 µM).

Atranones and dolabellanes with cardiomyocyte protective activity against cold ischemic injury from a coral-associated fungus Stachybotrys chartarum.

Five undescribed atranones, namely atranones V-Z (1-5), three undescribed dolabellane-type diterpenoids, namely stachatranones D-F (7-9), together with four known congeners (6 and 10-12), were obtained from a coral-associated strain of the toxigenic fungus Stachybotrys chartarum. Their structures were elucidated via extensive spectroscopic analyses, mainly including the HRESIMS and NMR data, single-crystal X-ray diffraction analysis, electronic circular dichroism calculation, and [Mo2(OAc)4] induced circular dichroism spectrum. The cardiomyocyte protective activity assay revealed that compound 9 significantly ameliorated cold ischemic injury at 24 h post cold ischemia (CI) in a dose-dependent manner. Moreover, compound 9 prevented CI induced dephosphorylation of phosphatidylinositol-3-kinase and RAC-α serine/threonine-protein kinase at 12 h post CI in a dose-dependent manner. In this work, the undescribed compound 9 could significantly protect cardiomyocytes against cold ischemic injury, highlighting the promising potential to be designed and developed as a novel cardioprotectant in heart transplant medicine.

Daldiconoids A-G: 3,4-Secolanostane triterpenoids from the fruiting bodies of Daldinia concentrica and their anti-inflammatory activity.

Seven undescribed 3,4-secolanostane triterpenoids, daldiconoids A-G (1-7), were isolated from the fruiting bodies of Daldinia concentrica. Daldiconoid A (1) was a highly modified 4,6,28,29-tetranorlanostane triterpenoid alkaloid featuring an unusual δ-lactam fused with a flanking cyclopentenone architecture. Their structures were determined by spectroscopic data, NMR calculations coupled with the DP4+ analysis, X-ray single-crystal diffraction, and chemical transformation. The plausible biosynthetic pathway for 1 was proposed. Compounds 1, 2, and 4-6 inhibited the expressions of IL-1ß, IL-6, and TNF-α in lipopolysaccharide stimulated RAW264.7 cells at a concentration of 10 µM. Mechanistically, Compounds 1 and 2 blocked the JAK2/STAT3 signaling pathway induced by lipopolysaccharide.

Abietane diterpenoids from Isodon amethystoides and their biological activities.

Seven undescribed abietane diterpenoids [abietamethinols A-G (1-7)] were isolated from the twigs and leaves of Isodon amethystoides. Their structures were elucidated on the basis of spectroscopic methods including 2D NMR, and they were further confirmed by X-ray crystallographic data. Lophanic acid was considered as the precursor of 1-7 in the biosynthesis pathway hypothesis. These compounds were evaluated for their cytotoxic, anti-bacterial and anti-AIV (avian influenza virus) activities. Compound 5 showed 42.9% inhibitory activity against the cancer cell line SMMC-7721 at the concentration of 40 µM, 3 and 4 could inhibit the bacterial growth of Streptococcus sobrinus by 55.3% and 63.2% at the concentrations of 148.6 and 141.9 µM, respectively, and 4 was demonstrated with antiviral activity against AIV with the inhibitory effect of 68.4% at 25 µM.

New steroids from mangrove-associated fungus Trichoderma asperellum SCNU-F0048.

Chemical investigation of the fungus Trichoderma asperellum SCNU-F0048 led to the discovery of two new steroids, ergosta-4,6,8 (14),22-tetraen-3-(3'-methyl-4'-hydroxyl-γ-butenolide) (1) and camphosterol B (2), as well as two known compounds, i.e. stigmasta-4,6,8(14),22-tetraen-3-one (3) and 4-hydroxy-17- methylincisterol (4). Their structures were elucidated by extensive nuclear mangnetic resonance, spectrum analysis and single crystal X-ray diffraction analysis. Bioassay disclosed that compound 1 showed strong cytotoxicity to a panel of tumor cell lines. Moreover, compounds 1 and 2 showed excellent antifungal activity against Penicillium italicum with IC50 values of 0.016 and 0.022 µM, respectively.

Fentanyl-Type Antagonist of the µ-Opioid Receptor: Important Role of Axial Chirality in the Active Conformation.

In recent years, synthetic opioids have emerged as a predominant cause of drug-overdose-related fatalities, causing the "opioid crisis." To design safer therapeutic agents, we accidentally discovered µ-opioid receptor (MOR) antagonists based on fentanyl with a relatively uncomplicated chemical composition that potentiates structural modifications. Here, we showed the development of novel atropisomeric fentanyl analogues that exhibit more potent antagonistic activity against MOR than naloxone, a morphinan MOR antagonist. Derivatives displaying stable axial chirality were synthesized based on the amide structure of fentanyl. The aS- and aR-enantiomers exerted antagonistic and agonistic effects on the MOR, respectively, and each atropisomer interacted with the MOR by assuming a distinct binding mode through molecular docking. These findings suggest that introducing atropisomerism into fentanyl may serve as a key feature in the molecular design of future MOR antagonists to help mitigate the opioid crisis.

Empirical Chiroptical Analyses of Vicinal Bromochloro Natural Products by van't Hoff's Principle of Optical Superposition: Assignment of the C-16 Configurations of Callophycols A and B.

A simple empirical method is described that allows the assignment of absolute configurations of natural products containing chiral vicinal bromochloro (VBC) units, including the bromochloro substituted isoprenyl units present in the structures of antiproliferative halomon (1a) and its halogen-swapped isomer iso-halomon (1b) from the red alga, Portieria hornemannii, and callophycols A (3) and B (4) from Callophycus serratus. The relative configurations of 3 and 4, published in 2007, were incomplete: C-16 was left unassigned. It is now shown that the additivity of molar rotations, [M]D (herein, abbreviated [M])─a consequence of van't Hoff's principle of optical superposition─could be used to deconvolute rotatory contributions, designated as [MX] and [MY] of the two remotely spaced chiral substructures within 3 and 4 using simple arithmetic. Input of proxy values, [M Y1] and [MY2], for the two different VBC units in two equations for [MX] and application of a "conditional test" returns the same value for [MX] only when a proxy with the correct configuration is included. It is revealed that 3 and 4 have opposite configurations at the C-16 stereocenter: 16S and 16R, respectively. Two important implications lie in these findings: 3 and 4 appear to qualify as paired-regioisomers, coupled through a putative dyotropic rearrangement (DR), and the biosyntheses of other Callophycus secondary metabolites, now numbering over 50, are tightly controlled by stereoelectronic considerations including neighboring group interactions of the DR. It now appears, counter to earlier suggestions, that the chirality of Callophycus secondary metabolites, despite their high chemodiversity, are surprisingly highly conserved. Enantiofacial halogenation additions to the C═C double bonds of precursor alkenes appear to direct the formation of the remaining stereocenters at both the halogenated benzoate-decalin core and the distal VBC of 3 and 4. A consistent hypothesis is proposed to account for macrolactonizations in other Callophycus natural products including bromophycolides A and B. The conditional test of molar rotations was applied in a different context to understand the chiroptical properties and trends observed in the highly iodinated meroditerpenes, iodocallophycols A-E, also from Callophycus sp., resulting in the revision of the configuration of callophycol E from (10R,14R) to (10S,14S).

Simultaneous Protein Colorful Imaging via Raman Signal Classification.

Protein imaging aids diagnosis and drug development by revealing protein-drug interactions or protein levels. However, the challenges of imaging multiple proteins, reduced sensitivity, and high reliance on specific protein properties such as Raman peaks or refractive index hinder the understanding. Here, we introduce multiprotein colorful imaging through Raman signal classification. Our method utilized machine learning-assisted classification of Raman signals, which are the distinctive features of label-free proteins. As a result, three types of proteins could be imaged simultaneously. In addition, we could quantify individual proteins from a mixture of multiple proteins over a wide detection range (10 fg/mL-1 µg/mL). These results showed a 1000-fold improvement in sensitivity and a 30-fold increase in the upper limit of detection compared to existing methods. These advances will enhance our understanding of biology and facilitate the development of disease diagnoses and treatments.