Developing BioNavi for Hybrid Retrosynthesis Planning.

Illuminating synthetic pathways is essential for producing valuable chemicals, such as bioactive molecules. Chemical and biological syntheses are crucial, and their integration often leads to more efficient and sustainable pathways. Despite the rapid development of retrosynthesis models, few of them consider both chemical and biological syntheses, hindering the pathway design for high-value chemicals. Here, we propose BioNavi by innovating multitask learning and reaction templates into the deep learning-driven model to design hybrid synthesis pathways in a more interpretable manner. BioNavi outperforms existing approaches on different data sets, achieving a 75% hit rate in replicating reported biosynthetic pathways and displaying superior ability in designing hybrid synthesis pathways. Additional case studies further illustrate the potential application of BioNavi in a de novo pathway design. The enhanced web server (http://biopathnavi.qmclab.com/bionavi/) simplifies input operations and implements step-by-step exploration according to user experience. We show that BioNavi is a handy navigator for designing synthetic pathways for various chemicals.

Discovery of a SUCNR1 antagonist for potential treatment of diabetic nephropathy: In silico and in vitro studies.

Diabetic nephropathy (DN) is one of the most severe complications of diabetes mellitus. Succinate Receptor 1 (SUCNR1), a member of the G-protein-coupled receptor (GPCR) family, represents a potential target for treatment of DN. Here, utilizing multi-strategy in silico virtual screening methods containing AlphaFold2 modelling, molecular dynamics (MD) simulation, ligand-based pharmacophore screening, molecular docking and machine learning-based similarity clustering, we successfully identified a novel antagonist of SUCNR1, AK-968/12117473 (Cpd3). Through extensive in vitro experiments, including dual-luciferase reporter assay, cellular thermal shift assay, immunofluorescence, and western blotting, we substantiated that Cpd3 could specifically target SUCNR1, inhibit the activation of NF-κB pathway, and ameliorate epithelial-mesenchymal transition (EMT) and extracellular matrix (ECM) deposition in renal tubular epithelial cells (NRK-52E) under high glucose conditions. Further in silico simulations revealed the molecular basis of the SUCNR1-Cpd3 interaction, and the in vitro metabolic stability assay indicated favorable drug-like pharmacokinetic properties of Cpd3. This work not only successfully pinpointed Cpd3 as a specific antagonist of SUCNR1 to serve as a promising candidate in the realm of therapeutic interventions for DN, but also provides a paradigm of dry-wet combined discovery strategies for GPCR-based therapeutics.

Functional Characterization of Sesquiterpene Synthases and P450 Enzymes in Flammulina velutipes for Biosynthesis of Spiro [4.5] Decane Terpene.

Flammulina velutipes, a popular edible mushroom, contains sesquiterpenes with potential health benefits. We characterized 12 sesquiterpene synthases and one P450 enzyme in F. velutipes using Aspergillus oryzae as a heterologous expression system, culminating in the biosynthesis of 16 distinct sesquiterpene compounds. An enzyme encoded by the axeB gene responsible for the synthesis of the spiro [4.5] decane compound axenol was discovered, and the mechanism of spirocycle formation was elucidated through quantum mechanical calculations. Furthermore, we delineated the role of a P450 enzyme colocated with AxeB in producing the novel compound 3-oxo-axenol. Our findings highlight the diverse array of sesquiterpene skeletons and functional groups biosynthesized by these enzymes in F. velutipes and underscore the effectiveness of the A. oryzae system as a heterologous host for expressing genes in the Basidiomycota genome. These insights into the biosynthesis of bioactive compounds in F. velutipes have significant implications for functional food and drug development.

NIMO: A Natural Product-Inspired Molecular Generative Model Based on Conditional Transformer.

Natural products (NPs) have diverse biological activity and significant medicinal value. The structural diversity of NPs is the mainstay of drug discovery. Expanding the chemical space of NPs is an urgent need. Inspired by the concept of fragment-assembled pseudo-natural products, we developed a computational tool called NIMO, which is based on the transformer neural network model. NIMO employs two tailor-made motif extraction methods to map a molecular graph into a semantic motif sequence. All these generated motif sequences are used to train our molecular generative models. Various NIMO models were trained under different task scenarios by recognizing syntactic patterns and structure-property relationships. We further explored the performance of NIMO in structure-guided, activity-oriented, and pocket-based molecule generation tasks. Our results show that NIMO had excellent performance for molecule generation from scratch and structure optimization from a scaffold.

NHC-Au-Catalyzed Isomerization of Propargylic B(MIDA)s to Allenes and Double Isomerization of Alkynes to 1,3-Dienes.

The synthesis of allenyl boronates is an important yet challenging topic in organic synthesis. Reported herein is an NHC-gold-catalyzed 1,3-H shift toward allenyl boronates synthesis from simple propargylic B(MIDA)s. Mechanistic studies suggest dual roles of the boryl moiety in the reaction: to activate the substrate for isomerization and at the same time, to prevent the allene product from further isomerization. These effects should be a result of α-anion stabilization and α-cation destabilization conferred by the B(MIDA) moiety, respectively. The NHC-Au catalyst, which is commercially available, is also found to be reactive in alkyne-to-1,3-diene isomerization reactions in an atom-economic and base-free manner.

Enzymatic-related network of catalysis, polyamine, and tumors for acetylpolyamine oxidase: from calculation to experiment.

The regulation of enzymes and development of polyamine analogs capable of controlling the dynamics of endogenous polyamines to achieve anti-tumor effects is one of the biggest challenges in polyamine research. However, the root of the problem remains unsolved. This study represents a significant milestone as it unveils, for the first time, the comprehensive catalytic map of acetylpolyamine oxidase that includes chemical transformation and product release kinetics, by utilizing multiscale simulations with over six million dynamical snapshots. The transportation of acetylspermine is strongly exothermic, and high binding affinity of enzyme and reactant is observed. The transfer of hydride from polyamine to FAD is the rate-limiting step, via an H-shift coupled electron transfer mechanism. The two products are released in a detour stepwise mechanism, which also impacts the enzymatic efficiency. Inspired by these mechanistic insights into enzymatic catalysis, we propose a novel strategy that regulates the polyamine level and catalytic progress through the action of His64. Directly suppressing APAO by mutating His64 further inhibited growth and migration of tumor cells and tumor tissue in vitro and in vivo. Therefore, the network connecting microcosmic and macroscopic scales opens up new avenues for designing polyamine compounds and conducting anti-tumor research in the future.

Biological informed graph neural network for tumor mutation burden prediction and immunotherapy-related pathway analysis in gastric cancer.

Tumor mutation burden (TMB) has emerged as an essential biomarker for assessing the efficacy of cancer immunotherapy. However, due to the inherent complexity of tumors, TMB is not always correlated with the responsiveness of immune checkpoint inhibitors (ICIs). Thus, refining the interpretation and contextualization of TMB is a requisite for enhancing clinical outcomes. In this study, we conducted a comprehensive investigation of the relationship between TMB and multi-omics data across 33 human cancer types. Our analysis revealed distinct biological changes associated with varying TMB statuses in STAD, COAD, and UCEC. While multi-omics data offer an opportunity to dissect the intricacies of tumors, extracting meaningful biological insights from such massive information remains a formidable challenge. To address this, we developed and implemented the PGLCN, a biologically informed graph neural network based on pathway interaction information. This model facilitates the stratification of patients into subgroups with distinct TMB statuses and enables the evaluation of driver biological processes through enhanced interpretability. By integrating multi-omics data for TMB prediction, our PGLCN model outperformed previous traditional machine learning methodologies, demonstrating superior TMB status prediction accuracy (STAD AUC: 0.976 ± 0.007; COAD AUC: 0.994 ± 0.007; UCEC AUC: 0.947 ± 0.023) and enhanced interpretability (BA-House: 1.0; BA-Community: 0.999; BA-Grid: 0.994; Tree-Cycles: 0.917; Tree-Grids: 0.867). Furthermore, the biological interpretability inherent to PGLCN identified the Toll-like receptor family and DNA repair pathways as potential combined biomarkers in conjunction with TMB status in gastric cancer. This finding suggests a potential synergistic targeting strategy with immunotherapy for gastric cancer, thus advancing the field of precision oncology.

Structural and Catalytic Insight into the Unique Pentacyclic Triterpene Synthase TwOSC.

The oxidosqualene cyclase (OSC) catalyzed cyclization of the linear substrate (3S)-2,3-oxidosqualene to form diverse pentacyclic triterpenoid (PT) skeletons is one of the most complex reactions in nature. Friedelin has a unique PT skeleton involving a fascinating nine-step cation shuttle run (CSR) cascade rearrangement reaction, in which the carbocation formed at C2 moves to the other side of the skeleton, runs back to C3 to yield a friedelin cation, which is finally deprotonated. However, as crystal structure data of plant OSCs are lacking, it remains unknown why the CSR cascade reactions occur in friedelin biosynthesis, as does the exact catalytic mechanism of the CSR. In this study, we determined the first cryogenic electron microscopy structure of a plant OSC, friedelin synthase, from Tripterygium wilfordii Hook. f (TwOSC). We also performed quantum mechanics/molecular mechanics simulations to reveal the energy profile for the CSR cascade reaction and identify key residues crucial for PT skeleton formation. Furthermore, we semirationally designed two TwOSC mutants, which significantly improved the yields of friedelin and ß-amyrin, respectively.

Infection Characteristics and Drug Susceptibility of Multidrug-Resistant Bacteria in Patients with Diabetic Foot Ulcers.

BACKGROUND: We aimed to analyze the infection characteristics of multidrug-resistant organisms (MDROs) and their resistance to antibiotics in patients with diabetic foot and provide guidance for the use of antibiotics in clinical practice. METHODS: The clinical data of 737 patients with diabetic foot who were hospitalized at our institution from February 2020 to January 2023 were retrospectively analyzed. Purulent secretions were collected from the patient's ulcers and bacterial culture, identification, and drug susceptibility tests were performed. The multidrug resistance (MDR) rate of different bacteria, composition ratio of MDROs, drug resistance characteristics of the main MDROs, distribution characteristics of multidrug-resistant gram-positive cocci and gram-negative bacilli in patients with different Wagner Grades, MDR in patients with different Wagner Grades, bacterial infection rate, and other indicators were analyzed. RESULTS: Pathogenic bacteria from wound secretions of 505 patients were cultured, and 509 pathogenic bacteria were obtained. Among the pathogenic bacteria, 225 strains were gram-positive cocci, of which 172 (76.44%) were MDROs, and 284 were gram-negative bacilli, of which 232 (81.69%) were MDROs. Among the 404 multidrug-resistant strains, gram-positive cocci and gram-negative bacilli accounted for 42.57% and 57.43%, respectively. The top five dominant MDROs were Staphylococcus aureus (18.56%), coagulase-negative Staphylococcus (10.89%), Escherichia coli (10.15%), Proteus mirabilis (8.17%), Proteus vulgaris (6.19%), and Pseudomonas aeruginosa (6.19%). Staphylococcus aureus and coagulase-negative Staphylococcus were more resistant to penicillin, oxacillin, erythromycin, azithromycin, and clarithromycin, with resistance rates of 50.0 - 95.0%. The resistance rates of E. coli to ampicillin, cefazolin, cefuroxime, ceftriaxone, and cefepime were > 75%. With an increase in Wagner Grade, the proportion of gram-negative bacilli among the pathogenic bacteria of MDROs increased significantly (p < 0.05), as did the infection rate of MDROs in patients with diabetic foot (χ2 = 14.045, p < 0.05). CONCLUSIONS: MDROs in patients with diabetic foot are mainly gram-negative bacilli, followed by gram-positive cocci. The drug resistance of various MDROs varies greatly. With the increase in Wagner Grade and MDR of diabetic foot patients, the infection rate of drug-resistant bacteria has increased significantly. Therefore, clinicians should use drugs rationally according to drug sensitivity results.

QM/MM Modeling Aided Enzyme Engineering in Natural Products Biosynthesis.

Natural products and their derivatives are widely used across various industries, particularly pharmaceuticals. Modern engineered biosynthesis provides an alternative way of producing and meeting the growing need for diverse natural products. Natural enzymes, on the other hand, often exhibit unsatisfactory catalytic characteristics and necessitate further enzyme engineering modifications. QM/MM, as a powerful and extensively used computational tool in the field of enzyme catalysis, has been increasingly applied in rational enzyme engineering over the past decade. In this review, we summarize recent advances in QM/MM computational investigation on enzyme catalysis and enzyme engineering for natural product biosynthesis. The challenges and perspectives for future QM/MM applications aided enzyme engineering in natural product biosynthesis will also be discussed.

Molecular insights into the catalytic promiscuity of a bacterial diterpene synthase.

Diterpene synthase VenA is responsible for assembling venezuelaene A with a unique 5-5-6-7 tetracyclic skeleton from geranylgeranyl pyrophosphate. VenA also demonstrates substrate promiscuity by accepting geranyl pyrophosphate and farnesyl pyrophosphate as alternative substrates. Herein, we report the crystal structures of VenA in both apo form and holo form in complex with a trinuclear magnesium cluster and pyrophosphate group. Functional and structural investigations on the atypical 115DSFVSD120 motif of VenA, versus the canonical Asp-rich motif of DDXX(X)D/E, reveal that the absent second Asp of canonical motif is functionally replaced by Ser116 and Gln83, together with bioinformatics analysis identifying a hidden subclass of type I microbial terpene synthases. Further structural analysis, multiscale computational simulations, and structure-directed mutagenesis provide significant mechanistic insights into the substrate selectivity and catalytic promiscuity of VenA. Finally, VenA is semi-rationally engineered into a sesterterpene synthase to recognize the larger substrate geranylfarnesyl pyrophosphate.

Discovering a uniform functional trade-off of the CBC-type 2,3-oxidosqualene cyclases and deciphering its chemical logic.

Many functionally promiscuous plant 2,3-oxidosqualene cyclases (OSCs) have been found, but complete functional reshaping is rarely reported. In this study, we have identified two new plant OSCs: a unique protostadienol synthase (AoPDS) and a common cycloartenol synthase (AoCAS) from Alisma orientale (Sam.) Juzep. Multiscale simulations and mutagenesis experiments revealed that threonine-727 is an essential residue responsible for protosta-13 (17),24-dienol biosynthesis in AoPDS and that the F726T mutant completely reshapes the native function of AoCAS into a PDS function to yield almost exclusively protosta-13 (17),24-dienol. Unexpectedly, various native functions were uniformly reshaped into a PDS function by introducing the phenylalanine → threonine substitution at this conserved position in other plant and non-plant chair-boat-chair-type OSCs. Further computational modeling elaborated the trade-off mechanisms of the phenylalanine → threonine substitution that leads to the PDS activity. This study demonstrates a general strategy for functional reshaping by using a plastic residue based on the decipherment of the catalytic mechanism.

Developing TeroENZ and TeroMAP modules for the terpenome research platform TeroKit.

Terpenoids and their derivatives are collectively known as the terpenome and are the largest class of natural products, whose biosynthesis refers to various kinds of enzymes. To date, there is no terpenome-related enzyme database, which is a desire for enzyme mining, metabolic engineering and discovery of new natural products related to terpenoids. In this work, we have constructed a comprehensive database called TeroENZ (http://terokit.qmclab.com/browse_enz.html) containing 13 462 enzymes involved in the terpenoid biosynthetic pathway, covering 2541 species and 4293 reactions reported in the literature and public databases. At the same time, we classify enzymes according to their catalytic reactions into cyclase, oxidoreductase, transferase, and so on, and also make a classification according to species. This meticulous classification is beneficial for users as it can be retrieved and downloaded conveniently. We also provide a computational module for isozyme prediction. Moreover, a module named TeroMAP (http://terokit.qmclab.com/browse_rxn.html) is also constructed to organize all available terpenoid enzymatic reactions into an interactive network by interfacing with the previously established database of terpenoid compounds, TeroMOL. Finally, all these databases and modules are integrated into the web server TeroKit (http://terokit.qmclab.com/) to shed light on the field of terpenoid research. Database URL http://terokit.qmclab.com/.

Structural Insights into Three Sesquiterpene Synthases for the Biosynthesis of Tricyclic Sesquiterpenes and Chemical Space Expansion by Structure-Based Mutagenesis.

The cyclization of farnesyl diphosphate (FPP) into highly strained polycyclic sesquiterpenes is challenging. We here determined the crystal structures of three sesquiterpene synthases (STSs, namely, BcBOT2, DbPROS, and CLM1) catalyzing the biosynthesis of the tricyclic sesquiterpenes presilphiperfolan-8ß-ol (1), Δ6-protoilludene (2), and longiborneol (3). All three STS structures contain a substrate mimic, the benzyltriethylammonium cation (BTAC), in their active sites, providing ideal templates for quantum mechanics/molecular mechanics (QM/MM) analyses toward their catalytic mechanisms. The QM/MM-based molecular dynamics (MD) simulations revealed the cascade reactions toward the enzyme products, and different key active site residues that play important roles in stabilizing reactive carbocation intermediates along the three pathways. Site-directed mutagenesis experiments confirmed the roles of these key residues and concomitantly resulted in 17 shunt products (4-20). Isotopic labeling experiments addressed the key hydride and methyl migrations toward the main and several shunt products. These combined methods provided deep insights into the catalytic mechanisms of the three STSs and demonstrated how the chemical space of STSs can rationally be expanded, which may facilitate applications in synthetic biology approaches toward pharmaceutical and perfumery agents.

Unnatural activities and mechanistic insights of cytochrome P450 PikC gained from site-specific mutagenesis by non-canonical amino acids.

Cytochrome P450 enzymes play important roles in the biosynthesis of macrolide antibiotics by mediating a vast variety of regio- and stereoselective oxidative modifications, thus improving their chemical diversity, biological activities, and pharmaceutical properties. Tremendous efforts have been made on engineering the reactivity and selectivity of these useful biocatalysts. However, the 20 proteinogenic amino acids cannot always satisfy the requirement of site-directed/random mutagenesis and rational protein design of P450 enzymes. To address this issue, herein, we practice the semi-rational non-canonical amino acid mutagenesis for the pikromycin biosynthetic P450 enzyme PikC, which recognizes its native macrolide substrates with a 12- or 14-membered ring macrolactone linked to a deoxyamino sugar through a unique sugar-anchoring mechanism. Based on a semi-rationally designed substrate binding strategy, non-canonical amino acid mutagenesis at the His238 position enables the unnatural activities of several PikC mutants towards the macrolactone precursors without any sugar appendix. With the aglycone hydroxylating activities, the pikromycin biosynthetic pathway is rewired by the representative mutant PikCH238pAcF carrying a p-acetylphenylalanine residue at the His238 position and a promiscuous glycosyltransferase. Moreover, structural analysis of substrate-free and three different enzyme-substrate complexes of PikCH238pAcF provides significant mechanistic insights into the substrate binding and catalytic selectivity of this paradigm biosynthetic P450 enzyme.

A DFT study of the endo-selectivity mechanism of the Diels-Alder reaction in lindenane dimeric sesquiterpene synthesis promoted by pyridines.

The lindenane dimeric sesquiterpenoids with versatile biological activities are accessible via biometric synthesis, in which the endo-selective Diels-Alder reaction plays an important role. To explore the endo-selectivity of the Diels-Alder reaction between lindenane sesquiterpenes promoted by pyridines, density functional theory (DFT) calculations were performed to explore the reaction mechanism between pyridines and D-A monomers. The calculations performed on the reaction pathways explain why pyridines can promote endo-selectivity via hydrogen bonding, and the hydrogen bond strength is a key factor driving the Diels-Alder reaction in major biochemical systems. These DFT-level insights will pave the way for designing better promoters for Diels-Alder reactions in biometric synthesis applications.

Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP.

The complete biosynthetic pathways are unknown for most natural products (NPs), it is thus valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user-friendly toolkit, BioNavi-NP, is developed to predict the biosynthetic pathways for both NPs and NP-like compounds. First, a single-step bio-retrosynthesis prediction model is trained using both general organic and biosynthetic reactions through end-to-end transformer neural networks. Based on this model, plausible biosynthetic pathways can be efficiently sampled through an AND-OR tree-based planning algorithm from iterative multi-step bio-retrosynthetic routes. Extensive evaluations reveal that BioNavi-NP can identify biosynthetic pathways for 90.2% of 368 test compounds and recover the reported building blocks as in the test set for 72.8%, 1.7 times more accurate than existing conventional rule-based approaches. The model is further shown to identify biologically plausible pathways for complex NPs collected from the recent literature. The toolkit as well as the curated datasets and learned models are freely available to facilitate the elucidation and reconstruction of the biosynthetic pathways for NPs.

Rationally engineering santalene synthase to readjust the component ratio of sandalwood oil.

Plant essential oils (PEOs) are widely used in cosmetic and nutraceutical industries. The component ratios of PEOs determine their qualities. Controlling the component ratios is challenging in construction of PEO biotechnological platforms. Here, we explore the catalytic reaction pathways of both product-promiscuous and product-specific santalene synthases (i.e., SaSSy and SanSyn) by multiscale simulations. F441 of SanSyn is found as a key residue restricting the conformational dynamics of the intermediates, and thereby the direct deprotonation by the general base T298 dominantly produce α-santalene. The subsequent mutagenesis of this plastic residue leads to generation of a mutant enzyme SanSynF441V which can produce both α- and ß-santalenes. Through metabolic engineering efforts, the santalene/santalol titer reaches 704.2 mg/L and the component ratio well matches the ISO 3518:2002 standard. This study represents a paradigm of constructing biotechnological platforms of PEOs with desirable component ratios by the combination of metabolic and enzymatic engineering.

Bio-inspired chemical space exploration of terpenoids.

Many computational methods are devoted to rapidly generating pseudo-natural products to expand the open-ended border of chemical spaces for natural products. However, the accessibility and chemical interpretation were often ignored or underestimated in conventional library/fragment-based or rule-based strategies, thus hampering experimental synthesis. Herein, a bio-inspired strategy (named TeroGen) is developed to mimic the two key biosynthetic stages (cyclization and decoration) of terpenoid natural products, by utilizing physically based simulations and deep learning models, respectively. The precision and efficiency are validated for different categories of terpenoids, and in practice, more than 30 000 sesterterpenoids (10 times as many as the known sesterterpenoids) are predicted to be linked in a reaction network, and their synthetic accessibility and chemical interpretation are estimated by thermodynamics and kinetics. Since it could not only greatly expand the chemical space of terpenoids but also numerate plausible biosynthetic routes, TeroGen is promising for accelerating heterologous biosynthesis, bio-mimic and chemical synthesis of complicated terpenoids and derivatives.

Chemotaxonomic investigation of plant terpenoids with an established database (TeroMOL).

Terpenoids constitute the biggest class of plant-derived natural products with diverse chemical structures and extensive biological activities. Interpreting enzyme functions and mining new structures of terpenoids could be inspired by the cheminformatic and chemotaxonomic analysis, whereas it is hampered by the incompleteness of available data for terpenoids. Here a dedicated terpenoids database, TeroMOL, is developed to collect more than 170 000 terpenoids and their derivatives annotated with reported biological sources, along with a user-friendly and freely accessible webserver to visualise and analyse the terpenoids skeletons and organism sources. The quantitative distributions as well as the qualitative trends between terpenoid skeletons and organism sources in plant kingdom are revealed from a chemotaxonomic view, while no comparisons are attempted due to the inherent data biases. Nevertheless, the terpenoid chemomarkers in several organisms are discussed based on the available data with highly enriched and exclusive carbon skeletons. We believe that the TeroMOL database and its accessory computational tools will be very promising for exploring the chemical space and biological sources of terpenoids, and assisting the terpenoid research community in the future.