The zeolite-catalyzed methanol-to-aromatics (MTA) process is a promising avenue for industrial decarbonization. This process predominantly utilizes 3-dimensional 10-member ring (10-MR) zeolites like ZSM-5 and ZSM-11, chosen for their confinement effect essential for aromatization. Current research mainly focuses on enhancing selectivity and mitigating catalyst deactivation by modulating zeolites' physicochemical properties. Despite the potential, the MTA technology is at a low Technology Readiness Level, hindered by mechanistic complexities in achieving the desired selectivity towards liquid aromatics. To bridge this knowledge gap, this study proposes a roadmap for MTA catalysis by strategically combining controlled catalytic experiments with advanced characterization methods (including operando conditions and "mobility-dependent" solid-state NMR spectroscopy). It identifies the descriptor-role of Koch-carbonylated intermediates, longer-chain hydrocarbons, and the zeolites' intersectional cavities in yielding preferential liquid aromatics selectivity. Understanding these selectivity descriptors and architectural impacts is vital, potentially advancing other zeolite-catalyzed emerging technologies.
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http://dx.doi.org/10.1002/anie.202411197 | DOI Listing |
J Chem Inf Model
January 2025
Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Road, 518172 Shenzhen, China.
Drug-induced liver injury (DILI) is a major challenge in drug development, often leading to clinical trial failures and market withdrawals due to liver toxicity. This study presents StackDILI, a computational framework designed to accelerate toxicity assessment by predicting DILI risk. StackDILI integrates multiple molecular descriptors to extract structural and physicochemical features, including the constitution, pharmacophore, MACCS, and E-state descriptors.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, People's Republic of China.
Proteolysis-targeting chimeras (PROTACs) are heterobifunctional molecules that target undruggable proteins, enhance selectivity and prevent target accumulation through catalytic activity. The unique structure of PROTACs presents challenges in structural identification and drug design. Liquid chromatography (LC), combined with mass spectrometry (MS), enhances compound annotation by providing essential retention time (RT) data, especially when MS alone is insufficient.
View Article and Find Full Text PDFMAbs
December 2025
Department of Purification, Microbiology and Virology, Genentech Inc, South San Francisco, CA, USA.
In early-stage development of therapeutic monoclonal antibodies, assessment of the viability and ease of their purification typically requires extensive experimentation. However, the work required for upstream protein expression and downstream purification development often conflicts with timeline pressures and material constraints, limiting the number of molecules and process conditions that can reasonably be assessed. Recently, high-throughput batch-binding screen data along with improved molecular descriptors have enabled development of robust quantitative structure-property relationship (QSPR) models that predict monoclonal antibody chromatographic binding behavior from the amino acid sequence.
View Article and Find Full Text PDFNAR Genom Bioinform
March 2025
National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.
Small proteins (≤100 amino acids) play important roles across all life forms, ranging from unicellular bacteria to higher organisms. In this study, we have developed SProtFP which is a machine learning-based method for functional annotation of prokaryotic small proteins into selected functional categories. SProtFP uses independent artificial neural networks (ANNs) trained using a combination of physicochemical descriptors for classifying small proteins into antitoxin type 2, bacteriocin, DNA-binding, metal-binding, ribosomal protein, RNA-binding, type 1 toxin and type 2 toxin proteins.
View Article and Find Full Text PDFChem Sci
December 2024
Shenzhen Grubbs Institute, Department of Chemistry, Guangdong Provincial Key Laboratory of Catalysis, Southern University of Science and Technology Shenzhen 518055 China
Distortion can play crucial roles in influencing structures and properties, as well as enhancing reactivity or selectivity in many chemical and biological systems. The distortion/interaction or activation-strain model is a popular and powerful method for deciphering the origins of activation energies, in which distortion and interaction energies dictate an activation energy. However, decomposition of local distortion energy at the atomic scale remains less clear and straightforward.
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