HSQCid: A Powerful Tool for Paving the Way to High-Throughput Structural Dereplication of Natural Products Based on Fast NMR Experiments

Structural dereplication is an essential step in the study of natural products (NPs). The number of discovered NPs is so large that efficient dereplication is highly desirable. NMR spectroscopy is still the gold standard for structural identification. 13C NMR spectrum is an effective molecular fingerprint, but their acquisition is time-consuming, especially for mass-limited NPs. Several alternative methods or tools have been proposed but have never reached general use for some reasons. Here, a new artificial intelligence tool, HSQCid, using contrastive learning between 1H-13C HSQC spectra and structures, is proposed for effective structural identification. Two structure encoders are compared, and the graph neural network is preferred over the Transformer. In this way, 80% and 20% of about 400,000 predicted data could be used for training and testing, respectively. Besides, with 17,971 experimental data as external test data, the top-1 and top-10 accuracies reach 74.5% and 94.8%, respectively. Top-1 accuracy increases by at least 12% when combined with other easily obtainable structure features, such as the total number of hydrogens connected to carbons from 1H NMR spectra. Further data analysis shows that the filters by structure features nearly eliminate the influence (>10%) of the difference between predicted and experimental data. Surprisingly, the influence of the number or the ratio of nonprotonated carbons on the identification accuracy is only significant in specific and rare cases (2.65%). Furthermore, the benchmark method, which matches 13C peaks, is compared and is markedly inferior to the proposed method, with or without structural features. The HSQCid code is available online. It is believed that HSQCid contributes to paving the way for high-throughput or highly effective structural dereplication of NPs.

The adsorption routes of 4IR technologies for effective desulphurization using cellulose nanocrystals: Current trends, challenges, and future perspectives

The combustion of liquid fuels as energy sources for transportation and power generation has necessitated governments worldwide to direct petroleum refineries to produce sulphur-free fuels for environmental sustainability. This review highlights the novel application of artificial intelligence for optimizing and predicting adsorptive desulphurization operating parameters and green isolation conditions of nanocellulose crystals from lignocellulosic biomass waste. The shortcomings of the traditional modelling and optimization techniques are stated, and artificial intelligence's role in overcoming them is broadly discussed. Also, the relationship between nanotechnology and artificial intelligence and the future perspectives of fourth industrial revolution (4IR) technologies for optimization and modelling of the adsorptive desulphurization process are elaborately discussed. The current study surveys different adsorbents used in adsorptive desulphurization and how biomass-based nanocellulose crystals (green adsorbents) are suitable alternatives for achieving cleaner fuels and environmental sustainability. Likewise, the present study reports the challenges and potential solutions to fully implementing 4IR technologies for effective desulphurization of liquid fuels in petroleum refineries. Hence, this study provides insightful information to benefit a broad audience in waste valorization for sustainability, environmental protection, and clean energy generation.

Alkaloids in Contemporary Drug Discovery to Meet Global Disease Needs

An overview is presented of the well-established role of alkaloids in drug discovery, the application of more sustainable chemicals, and biological approaches, and the implementation of information systems to address the current challenges faced in meeting global disease needs. The necessity for a new international paradigm for natural product discovery and development for the treatment of multidrug resistant organisms, and rare and neglected tropical diseases in the era of the Fourth Industrial Revolution and the Quintuple Helix is discussed.