Deep learning in template-free de novo biosynthetic pathway design of natural products.

Natural products (NPs) are indispensable in drug development, particularly in combating infections, cancer, and neurodegenerative diseases. However, their limited availability poses significant challenges. Template-free de novo biosynthetic pathway design provides a strategic solution for NP production, with deep learning standing out as a powerful tool in this domain. This review delves into state-of-the-art deep learning algorithms in NP biosynthesis pathway design. It provides an in-depth discussion of databases like Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and UniProt, which are essential for model training, along with chemical databases such as Reaxys, SciFinder, and PubChem for transfer learning to expand models' understanding of the broader chemical space. It evaluates the potential and challenges of sequence-to-sequence and graph-to-graph translation models for accurate single-step prediction. Additionally, it discusses search algorithms for multistep prediction and deep learning algorithms for predicting enzyme function. The review also highlights the pivotal role of deep learning in improving catalytic efficiency through enzyme engineering, which is essential for enhancing NP production. Moreover, it examines the application of large language models in pathway design, enzyme discovery, and enzyme engineering. Finally, it addresses the challenges and prospects associated with template-free approaches, offering insights into potential advancements in NP biosynthesis pathway design.

DBPboost:A method of classification of DNA-binding proteins based on improved differential evolution algorithm and feature extraction.

DNA-binding proteins are a class of proteins that can interact with DNA molecules through physical and chemical interactions. Their main functions include regulating gene expression, maintaining chromosome structure and stability, and more. DNA-binding proteins play a crucial role in cellular and molecular biology, as they are essential for maintaining normal cellular physiological functions and adapting to environmental changes. The prediction of DNA-binding proteins has been a hot topic in the field of bioinformatics. The key to accurately classifying DNA-binding proteins is to find suitable feature sources and explore the information they contain. Although there are already many models for predicting DNA-binding proteins, there is still room for improvement in mining feature source information and calculation methods. In this study, we created a model called DBPboost to better identify DNA-binding proteins. The innovation of this study lies in the use of eight feature extraction methods, the improvement of the feature selection step, which involves selecting some features first and then performing feature selection again after feature fusion, and the optimization of the differential evolution algorithm in feature fusion, which improves the performance of feature fusion. The experimental results show that the prediction accuracy of the model on the UniSwiss dataset is 89.32%, and the sensitivity is 89.01%, which is better than most existing models.

Using TransR to enhance drug repurposing knowledge graph for COVID-19 and its complications.

MOTIVATION: The COVID-19 pandemic has been spreading globally for four years, yet specific drugs that effectively suppress the virus remain elusive. Furthermore, the emergence of complications associated with COVID-19 presents significant challenges, making the development of therapeutics for COVID-19 and its complications an urgent task. However, traditional drug development processes are time-consuming. Drug repurposing, which involves identifying new therapeutic applications for existing drugs, presents a viable alternative. RESULT: In this study, we construct a knowledge graph by retrieving information on genes, drugs, and diseases from databases such as DRUGBANK and GNBR. Next, we employ the TransR knowledge representation learning approach to embed entities and relationships into the knowledge graph. Subsequently, we train the knowledge graph using a graph neural network model based on TransR scoring. This trained knowledge graph is then utilized to predict drugs for the treatment of COVID-19 and its complications. Based on experimental results, we have identified 15 drugs out of the top 30 with the highest success rates associated with treating COVID-19 and its complications. Notably, out of these 15 drugs, 10 specifically aimed at treating COVID-19, such as Torcetrapib and Tocopherol, has not been previously identified in the knowledge graph. This finding highlights the potential of our model in aiding healthcare professionals in drug development and research related to this disease.

Digenic inheritance accounts for phenotypic variability in amelogenesis imperfecta.

Amelogenesis imperfecta (AI) represents a group of clinically and genetically heterogeneous disorders that affect enamel formation and mineralization. Although AI is commonly considered a monogenic disorder, digenic inheritance is rarely reported. In this study, we recruited two nonconsanguineous Chinese families exhibiting diverse phenotypes of enamel defects among affected family members. Digenic variants were discovered in both probands. In family 1, the proband inherited a paternal frameshift variant in LAMA3 (NM_198129.4:c.3712dup) and a maternal deletion encompassing the entire AMELX gene. This resulted in a combined hypoplastic and hypomineralized AI phenotype, which was distinct from the parents' manifestations. In family 2, whole-exome sequencing analysis revealed the proband carried a maternal heterozygous splicing variant in COL17A1 (NC_000010.11 (NM_000494.3): c.4156 + 2dup) and compound heterozygous variants in RELT (paternal: NM_032871.4:c.260A > T; maternal: NM_032871.4:c.521 T > G). These genetic changes caused the abundant irregular enamel defects observed in the proband, whereas other affected family members carrying heterozygous variants in both COL17A1 and RELT displayed only horizontal grooves as their phenotype. The pathogenicity of the novel COL17A1 splice site variant was confirmed through RT-PCR and minigene assay. This study enhances our understanding by highlighting the potential association between the co-occurrence of variants in two genes and variable phenotypes observed in AI patients.

Total Synthesis of Ganoderma Meroterpenoids Cochlearol B and Its Congeners Driven by Structural Similarity and Biological Homology.

Secondary metabolites that have the same biological origin must share some relationship in their biosynthesis. Exploring this relationship has always been a significant task for synthetic biologists. However, from the perspective of synthetic chemists, it is equally important to propose, prove, or refute potential biosynthetic pathways in order to elucidate and understand the biosynthesis of homologous secondary metabolites. In this study, driven by the high structural similarity between the homologous Ganoderma meroterpenoids cochlearol B and ganocin B, two chemically synthetic strategies were designed and investigated sequentially for the synthesis of cochlearol B from ganocin B. These strategies include intramolecular metal-catalyzed hydrogen atom transfer (MHAT) and intramolecular photochemical [2+2] cycloaddition. The aim was to reveal their potential biosynthetic conversion relationship using chemical synthesis methods. As a result, a highly efficient total synthesis of cochlearol B, cochlearol T, cochlearol F, as well as the formal total synthesis of ganocins A-B, and ganocochlearins C-D, has been achieved. Additionally, a novel synthetic approach for the synthesis of 6,6-disubstituted 6H-dibenzo[b,d]pyran and its analogues has been developed through palladium(II)-catalyzed Wacker-type/cross-coupling cascade reactions.

A deep learning based two-layer predictor to identify enhancers and their strength.

The enhancer is a DNA sequence that can increase the activity of promoters and thus speed up the frequency of gene transcription. The enhancer plays an essential role in activating gene expression. Currently, gene sequencing technology has been developed for 30 years from the first generation to the third generation, and a variety of biological sequence data have increased significantly every year. Due to the importance of enhancer functions, it is very expensive to identify enhancers through biochemical experiments. Therefore, we need to study new methods for the identification and classification of enhancers. Based on the K-mer principle this study proposed a feature extraction method that others have not used in convolutional neural networks. Then, we combined it with one-hot encoding to build an efficient one-dimensional convolutional neural network ensemble model for predicting enhancers and their strengths. Finally, we used five commonly used classification problem evaluation indicators to compare with the models proposed by other researchers. The model proposed in this paper has a better performance by using the same independent test dataset as other models.

Mechanistic study of double boron-silicon exchange reactions between dibenzosiloles and boron tribromide.

This paper describes a mechanistic study on double boron-silicon exchange reactions between dibenzosiloles and boron tribromide. This type of reaction presents a safe and environmentally benign approach to convert electron-rich siloles into corresponding electron-deficient boroles and hence shows intriguing potential for the synthesis of boron-doped π-conjugated molecular materials. However, the detailed mechanisms for such reactions have not yet been established in the current literature. In this work, we performed density functional theory (DFT) calculations in conjunction with NMR analysis to unravel the reaction pathways and energy profiles for relevant boron-silicon exchange reactions where two dibenzolesiloles and a phenanthrosilole were employed as reactants, respectively. Our results have shown that excess boron tribromide provides beneficial microsolvation effects on key transition states and reactive intermediates to lower the activation energy barrier for the overall reaction. In the meantime, the substitution pattern at the bay region of the dibenzosilole framework exerts significant impacts on the potential energy surface of the reaction; increased steric hindrance at the bay region decelerates the second boron-silicon exchange step, while extended π-conjugation at the bay region makes the first boron-silicon exchange more challenging. Overall, our computational and experimental results provide an in-depth understanding of the reactivity and scope of this type of reaction, which in turn serves as useful guidance for ongoing research in the field of borole-based organic optoelectronic materials.

Mapping Photogenerated Electron-Hole Behavior of Graphene Oxide: Insight into a New Mechanism of Photosensitive Pollutant Degradation.

The use of graphene oxide (GO) photogenerated electron-hole (e-h+) pairs to degrade pollutants is a novel green method for wastewater treatment. However, the interaction between photosensitive pollutants and a GO-light system remains unclear. In this work, the mechanism of degradation of photosensitive pollutant tetracycline (TC) promoted by GO photogenerated e-h+ pairs was studied. Our studies encompassed the determination of TC removal kinetics, analysis of active substances for TC degradation, identification of degradation products, and computational modeling. Clear evidence shows that a new reaction mechanism of enhanced adsorption and induced generation of reactive oxygen species (ROS) was involved. This mechanism was conducive to significantly enhanced TC removal. Kinetic studies showed a first-order behavior that can be well described by the Langmuir-Hinshelwood model. Radical scavenging experiments confirmed that 1O2, •O2-, and holes (h+) were the main active substances for TC degradation. Electron spin resonance analysis indicated that photoexcited TC molecules may transfer electrons to the conduction band of GO to induce the generation of additional ROS. A major transformation product (m/z 459) during TC degradation was identified with liquid chromatography-mass spectrometry. Density functional theory calculation indicated a stronger adsorption between TC and GO under photoirradiation. This mechanism of photo-enhanced adsorption and synergistic induced generation of ROS provides a new strategy for the removal of emerging pollutants in water. Overall, the new mechanism revealed in this work expands the knowledge of applying GO to wastewater treatment and is of great reference value for research in this field.

Total Synthesis of Ryanodane Diterpenoids Garajonone and 3-epi-Garajonone.

Ryanodane diterpenes are structurally complex natural products that are well-known for their high degree of oxidation and the challenges associated with synthesizing them within the terpene class. Herein, we present a two-stage synthetic strategy that draws inspiration from the broad biosynthesis of terpenes, allowing us to successfully achieve the first chemical synthesis of garajonone, a ryanodane diterpenoid that occurs naturally at low abundance, as well as its epimer, 3-epi-garajonone. The key to this success lies in the rapid construction of the carbon framework of target molecule by employing an early-stage palladium-catalyzed Heck/carbonylative esterification cascade annulation, followed by successive late-stage selective redox manipulation to establish the desired oxidation state of the molecule. This research not only showcases the synthesis of garajonone and its epimer but also provides a platform for the chemical synthesis of other members and analogs within this complex diterpenoid family.

Reduced Volume Expansion of Micron-Sized SiOx via Closed-Nanopore Structure Constructed by Mg-Induced Elemental Segregation.

The inherently huge volume expansion during Li uptake has hindered the use of Si-based anodes in high-energy lithium-ion batteries. While some pore-forming and nano-architecting strategies show promises to effectively buffer the volume change, other parameters essential for practical electrode fabrication, such as compaction density, are often compromised. Here we propose a new in situ Mg doping strategy to form closed-nanopore structure into a micron-sized SiOx particle at a high bulk density. The doped Mg atoms promote the segregation of O, so that high-density magnesium silicates form to generate closed nanopores. By altering the mass content of Mg dopant, the average radii (ranged from 5.4 to 9.7 nm) and porosities (ranged from 1.4 % to 15.9 %) of the closed pores are precisely adjustable, which accounts for volume expansion of SiOx from 77.8 % to 22.2 % at the minimum. Benefited from the small volume variation, the Mg-doped micron-SiOx anode demonstrates improved Li storage performance towards realization of a 700-(dis)charge-cycle, 11-Ah-pouch-type cell at a capacity retention of >80 %. This work offers insights into reasonable design of the internal structure of micron-sized SiOx and other materials that undergo conversion or alloying reactions with drastic volume change, to enable high-energy batteries with stable electrochemistry.

Bioinspired Total Synthesis of Cephalotaxus Diterpenoids and Their Structural Analogues.

Herein, we present a unified chemical synthesis of three subgroups of cephalotaxus diterpenoids. Key to the success lies in adopting a synthetic strategy that is inspired by biosynthesis but is opposite in nature. By employing selective one-carbon introduction and ring expansion operations, we have successfully converted cephalotane-type C18 dinorditerpenoids (using cephanolide B as a starting material) into troponoid-type C19 norditerpenoids and intact cephalotane-type C20 diterpenoids. This synthetic approach has enabled us to synthesize cephinoid H, 13-oxo-cephinoid H, 7-oxo-cephinoid H, fortalpinoid C, 7-epi-fortalpinoid C, cephanolide E, and 13-epi-cephanolide E. Furthermore, through the development of an intermolecular asymmetric Michael reaction between ß-oxo esters and ß-substituted enones, we have achieved the enantioselective synthesis of advanced intermediates within our synthetic sequence, thus formally realizing the asymmetric total synthesis of the cephalotaxus diterpenoids family.

Long-range Through-space Charge Transfer in a pH-responsive Mixed Cyclophane of Pyridine and Teropyrene.

A large, strained (SE=44.2 kcal/mol) and conformationally flexible mixed cyclophane of pyridine and teropyrene was synthesized using two intramolecular Wurtz coupling reactions and an unprecedented Scholl reaction between the unreactive 2 positions of the pyrene systems in a triply bridged pyrenophane. Protonation of the pyridine unit results in a greatly enhanced preference for nesting in the cavity of the highly bent teropyrene system (θcalc =162.6°) and emergence of a charge transfer absorption band (λmax =592 nm) due to a long range (5.0-5.5 Å), through-space intramolecular transition between the teropyrene and pyridinium units, which does not exist in the neutral cyclophane.

Donor-Acceptor Fluorophores and Macrocycles Built Upon Wedge-Shaped π-Extended Phenanthroimidazoles.

A class of wedge-shaped organic π-fluorophores featuring a 6,9-diphenyl-substituted phenanthroimidazole (PI) core was designed, synthesized, and characterized. Among them, a π-extended PI derivative containing two electron-withdrawing aldehyde groups was found to exhibit versatile solid-state packing properties as well as strong solvatofluorochromism in different organic solvents. Another PI derivative that was functionalized with two electron-donating 1,4-dithiafulvenyl (DTF) end groups showed versatile redox reactivities and quenched fluorescence. Treatment of this wedge-shaped bis(DTF)-PI compound with iodine resulted in oxidative coupling reactions, leading to the formation of intriguing macrocyclic products that carry redox-active tetrathiafulvalene vinylogue (TTFV) moieties in their structures. Mixing the bis(DTF)-PI derivative with fullerene (C60 or C70) in an organic solvent resulted in substantial fluorescence enhancement (turn-on). In this process, fullerene acted as a photosensitizer to generate singlet oxygen, which in turn induced oxidative C = C bond cleavages and converted nonfluorescent bis(DTF)-PI into highly fluorescent dialdehyde-substituted PI. Treatment of TTFV-PI macrocycles with a small amount of fullerene also led to a moderate degree of fluorescence enhancement, but this is not because of photosensitized oxidative cleavage reactions. Instead, competitive photoinduced electron transfer from TTFV to fullerene can be attributed to their fluorescence turn-on behavior.

dPromoter-XGBoost: Detecting promoters and strength by combining multiple descriptors and feature selection using XGBoost.

Promoters play an irreplaceable role in biological processes and genetics, which are responsible for stimulating the transcription and expression of specific genes. Promoter abnormalities have been found in some diseases, and the level of promoter-binding transcription factors can be used as a marker before a disease occurs. Hence, detecting promoters from DNA sequences has important biological significance, particular, distinguishing strong promoters can help to elucidate differences in gene expression and the mechanisms of specific diseases. With the introduction of third-generation sequencing, it is difficult to match the speed of sequencing to the speed of labeling promoters experimentally. Many computing models have been designed to fill this gap and identify unlabeled DNA. However, their feature representation methods are very singular, which cannot reflect the information contained in the original samples. With the aim of avoiding information loss, we propose a computational model based on multiple descriptors and feature selection to jointly express samples. It is worth mentioning that a new feature descriptor called K-mer word vector is defined. The promoter model of multiple feature descriptors dominated by K-mer word vector achieves similar performance to existing methods, the sensitivity of 85.72% can distinguish the promoter more effectively than other methods. Furthermore, the performance of the promoter strength has surpassed published methods, and accuracy of 77.00% greatly improves the ability to distinguish between strong and weak promoters.

DFT investigations of phenyldithiafulvene dimers at different oxidation states.

Oxidative dimerization of aryl-substituted dithiafulvenes (Ar-DTFs) presents an efficient C-C bond forming method for the preparation of diverse redox-active π-conjugated molecules and conductive polymers. Previous experimental data indicated a reaction pathway in which direct combination of two Ar-DTF radical cations is a key step. However, mechanistic details about how Ar-DTF dimers are formed under different oxidation states have not yet been clearly established prior to this work. The assembly of two Ar-DTF molecules generates a vast conformational and configurational landscape, which is quite complex but fundamentally important for understanding the dimerization mechanism. To cast a deep insight into this aspect, we have performed density functional theory (DFT) calculations at the M06-2X/Def2-SVP level of theory to thoroughly investigate the potential energy surfaces (PESs) of various dimers of a phenyl-substituted dithiafulvene (Ph-DTF) in the mixed-valence radical cation and dication states. Key stationary points in these PESs, including minimum-energy conformers (π-dimers and σ-dimers) as well as the transition states connected to them, were examined and compared. We have also calculated the binding energies of these dimers to evaluate the energetic driving forces for their formation. Based on our computational results, the roles that various Ph-DTF dimers play in different pathways of oxidative dimerization have been clarified.

DFT mechanistic studies of boron-silicon exchange reactions between silyl-substituted arenes and boron bromides.

C-B bond forming reactions are important methodologies in modern synthetic chemistry, since many borylated organic substrates, ranging from alkanes and alkenes to arenes and heteroarenes, are useful intermediates for the synthesis of natural products, pharmaceuticals, and organic π-conjugated materials. Among numerous borylation methods, C-Si/B-Br exchange reactions have attracted increasing attention in recent years. While experimental exploration has been continually carried out for more than two decades, mechanistic insights into this type of reaction have not yet been clearly established. To address this deficiency of knowledge, we performed density functional theory (DFT) calculations to map out the reaction pathways for a range of boron-silicon exchange reactions between boron tribromide (BBr3) and trimethylsilyl-substituted arenes (TMSAr). Our computational analyses have disclosed the energetic, structural, and electronic properties for key stationary points on the potential energy surfaces (PES) in both the gas and solution (CH2Cl2) phases.

Targeting Glutamine Metabolism as an Attractive Therapeutic Strategy for Acute Myeloid Leukemia.

OPINION STATEMENT: Relapse after chemotherapy and hematopoietic stem cell transplantation leads to adverse prognosis for acute myeloid leukemia (AML) patients. As a "conditionally essential amino acid," glutamine contributes to the growth and proliferation of AML cells. Glutamine-target strategies as new treatment approaches have been widely explored in AML treatment to improve outcome. Glutamine-target strategies including depletion of systemic glutamine and application of glutamine uptake inhibitors, glutamine antagonists/analogues, and glutaminase inhibitors. Because glutamine metabolism involved in multiple pathways in cells and each pathway of glutamine metabolism has many regulatory factors, therefore, AML therapy targeting glutamine metabolism should focus on how to inhibit multiple metabolic pathways without affecting normal cells and host immune to achieve effective treatment for AML.

Histological analysis for pulp mineralisation after severe intrusive luxation of immature molars in rats.

BACKGROUND/AIM: Pulp mineralisation is a survival process that may occur in the pulp of immature teeth following trauma. However, the mechanism of this process remains unclear. The aim of this study was to evaluate the histological manifestations of pulp mineralisation after intrusion in immature molars of rats. MATERIALS AND METHODS: Three-week-old male Sprague-Dawley rats were subjected to intrusive luxation of the right maxillary second molar by an impact force from a striking instrument through a metal force transfer rod. The left maxillary second molar of each rat was used as a control. The control and injured maxillae were collected at 3, 7, 10, 14, and 30 days after trauma (n = 15 per time group) and evaluated using haematoxylin and eosin staining and immunohistochemistry. Independent two-tailed Student's t-test was used for statistical comparison of the immunoreactive area. RESULTS: Pulp atrophy and mineralisation were observed in 30%-40% of the animals, and no pulp necrosis occurred. Ten days after trauma, pulp mineralisation, with osteoid tissue rather than reparative dentin, formed around the newly vascularised areas in the coronal pulp. CD90-immunoreactive cells were observed in the sub-odontoblastic multicellular layer in control molars, whereas the number of these cells was decreased in the traumatised teeth. CD105 localised in cells around the pulp osteoid tissue of the traumatised teeth, whereas in control teeth, it was only expressed in the vascular endothelial cells of capillaries in the odontoblastic or sub-odontoblastic layers. In specimens with pulp atrophy at 3-10 days after trauma, hypoxia inducible factor expression and CD11b-immunoreactive inflammatory cells increased. CONCLUSIONS: Following intrusive luxation of immature teeth without crown fractures in rats, no pulp necrosis occurred. Instead, pulp atrophy and osteogenesis around neovascularisation with activated CD105-immunoreactive cells were observed in the coronal pulp microenvironment characterised by hypoxia and inflammation.

Casirivimab and Imdevimab for the Treatment of Hospitalized Patients With COVID-19.

BACKGROUND: The open-label RECOVERY study reported improved survival in hospitalized, SARS-CoV-2 seronegative patients treated with casirivimab and imdevimab (CAS + IMD). METHODS: In this phase 1/2/3, double-blind, placebo-controlled trial conducted prior to widespread circulation of Delta and Omicron, hospitalized COVID-19 patients were randomized (1:1:1) to 2.4 g or 8.0 g CAS + IMD or placebo, and characterized at baseline for viral load and SARS-CoV-2 serostatus. RESULTS: In total, 1336 patients on low-flow or no supplemental (low-flow/no) oxygen were treated. The primary endpoint was met in seronegative patients, the least-squares mean difference (CAS + IMD versus placebo) for time-weighted average change from baseline in viral load through day 7 was -0.28 log10 copies/mL (95% confidence interval [CI], -.51 to -.05; P = .0172). The primary clinical analysis of death or mechanical ventilation from day 6 to 29 in patients with high viral load had a strong positive trend but did not reach significance. CAS + IMD numerically reduced all-cause mortality in seronegative patients through day 29 (relative risk reduction, 55.6%; 95% CI, 24.2%-74.0%). No safety concerns were noted. CONCLUSIONS: In hospitalized COVID-19 patients on low-flow/no oxygen, CAS + IMD reduced viral load and likely improves clinical outcomes in the overall population, with the benefit driven by seronegative patients, and no harm observed in seropositive patients. CLINICAL TRIALS REGISTRATION: NCT04426695.

Lay Summary . Monoclonal antibody therapies that block the virus that causes COVID-19 (SARS-CoV-2) can prevent patients from being hospitalized. We hypothesized that these antibodies may also benefit patients who are already hospitalized with COVID-19. Therefore, we performed a study to determine if the monoclonal antibody combination of casirivimab and imdevimab (CAS + IMD) can decrease the amount of virus in the nose of hospitalized patients and prevent the disease from becoming more severe. The study, conducted from June 2020 to April 2021, found that CAS + IMD treatment reduced the amount of virus in these patients, and may reduce their chance of dying or needing a ventilator (a machine that helps patients breathe). Patients were examined in 2 groups: those whose immune systems, at the start of the study, had not produced their own antibodies to fight SARS-CoV-2 (seronegative patients); or those that had already produced their own antibodies (seropositive patients) at the start of the study. Seronegative patients benefited the most from CAS + IMD. No safety concerns related to CAS + IMD were observed. These results demonstrate that monoclonal antibody therapy can help hospitalized patients with COVID-19 and may decrease their chances of needing assistance to breathe or dying.

Total Synthesis of Metaphanine and Oxoepistephamiersine.

Herein, we report a concise and divergent synthesis of the complex hasubanan alkaloids metaphanine and oxoepistephamiersine from commercially available and inexpensive cyclohexanedione monoethylene acetal. Our synthesis features a palladium-catalyzed cascade cyclization reaction to set the tricyclic carbon framework of the desired molecules, a regioselective Baeyer-Villiger oxidation followed by a MeNH2 triggered skeletal reorganization cascade to construct the benzannulated aza[4.4.3]propellane, and a strategically late-stage regio-/diastereoselective oxidative annulation of sp3 C-H bond to form the challenging THF ring system and hemiketal moiety in a single step. In addition, a highly enantioselective alkylation of cyclohexanedione monoethylene acetal paved the way for the asymmetric synthesis of target molecular.