A5070236246- Computational Drug Discovery Methods
- Machine Learning in Materials Science
- Cancer Genomics and Diagnostics
- Neonatal Respiratory Health Research
- Metabolomics and Mass Spectrometry Studies
- Medical Imaging and Pathology Studies
- Microbial Metabolic Engineering and Bioproduction
- Various Chemistry Research Topics
- Thermal and Kinetic Analysis
- Catalysis and Oxidation Reactions
- RNA and protein synthesis mechanisms
- Bacterial Genetics and Biotechnology
- DNA Repair Mechanisms
- Force Microscopy Techniques and Applications
- Zeolite Catalysis and Synthesis
- Synthesis and properties of polymers
- Spectroscopy and Chemometric Analyses
- Origins and Evolution of Life
- DNA and Nucleic Acid Chemistry
- Biochemical and biochemical processes
- CRISPR and Genetic Engineering
- Analytical Chemistry and Chromatography
- Chemical Synthesis and Analysis
- Conducting polymers and applications
- Electromagnetic Simulation and Numerical Methods
Purdue University West Lafayette
2020-2025
Princip (Czechia)
2024-2025
Guangxi University
2025
University of Michigan
2023-2024
Shanghai Jiao Tong University
2018-2021
Xi’an Jiaotong-Liverpool University
2021
Sichuan University
2019-2020
State Key Laboratory of Biotherapy
2019-2020
Imperial College London
2010-2018
Lu'an First People's Hospital
2013-2014
Abstract Existing reaction transition state (TS) databases are comparatively small and lack chemical diversity. Here, this data gap has been addressed using the concept of a graphically-defined model to comprehensively characterize space associated with C, H, O, N containing molecules up 10 heavy (non-hydrogen) atoms. The resulting dataset is composed 176,992 organic reactions possessing at least one validated TS, activation energy, heat reaction, reactant product geometries, frequencies,...
Transition state searches are the basis for computationally characterizing reaction mechanisms, making them a pivotal tool in myriad chemical applications. Nevertheless, common search algorithms sensitive to conformations, and conformational spaces of even medium-sized reacting systems too complex explore with brute force. Here, we show that it is possible train classifier learn features conformers conduce successful transition searches, such optimal can be down-selected before incurring...
Abstract Recently, solution‐processable n‐doped poly(benzodifurandione) (n‐PBDF) has been made through in‐situ oxidative polymerization and reductive doping, which exhibited exceptionally high electrical conductivities optical transparency. The discovery of n‐PBDF is considered a breakthrough in the field organic semiconductors. In initial report, possibility structural defect formation was proposed, based on observation isomerization from ( E )‐2H,2′H‐[3,3′‐bibenzofuranylidene]‐2,2′‐dione...
Activation energy characterization of competing reactions is a costly but crucial step for understanding the kinetic relevance distinct reaction pathways, product yields, and myriad other properties reacting systems. The standard methodology activation has historically been transition state search using highest level theory that can be afforded. However, recently, several groups have popularized idea predicting energies directly based on nothing more than reactant graphs, sufficiently...
Abstract Algorithmic reaction exploration based on transition state searches has already made inroads into many niche applications, but its potential as a general‐purpose tool is still largely unrealized. Computational cost and the absence of benchmark problems involving larger molecules remain obstacles to further progress. Here an ultra‐low algorithm implemented used explore reactivity unimolecular bimolecular reactants, comprising total 581 reactions 51 distinct reactants. The discovers...
Abstract Characterizing the reaction energies and barriers of networks is central to catalyst development. However, heterogeneous catalytic surfaces pose several unique challenges automatic network characterization, including large sizes open-ended reactant sets, that make ad hoc construction current state-of-the-art. Here, we show how automated exploration algorithms can be adapted constraints systems using ethylene oligomerization on silica-supported single-site Ga 3+ as a model system....
Achieving fast and accurate reaction prediction is central to a suite of chemical applications. Nevertheless, classic approaches based on templates or simple models are typically but with limited scope accuracy, while the emerging machine learning-based in their transferability due lack large databases. Here, we address these limitations by formalizing model concept fixed-depth condensed graphs that shown achieve cost accuracy balance applicable many problems. The can be utilized provide...
Transition state (TS) search plays a crucial role in reaction pathway analysis, offering insights into mechanisms and aiding the optimization of chemical processes. Recently, machine learning interatomic potentials (MLIPs) generative models have emerged as promising tools to accelerate TS search. In this study, we establish an end-to-end workflow benchmark seven MLIPs -- ANI-1x, CHGNet, DPA-2, LEFTNet, MACE, MatterSim, Orb alongside React-OT state-of-the-art model. Our evaluation reveals...
Infectious bronchitis virus (IBV) is a major pathogen that causes significant economic losses in the global poultry industry. Current vaccination strategies provide only partial protection, highlighting need for more effective prevention and treatment methods. This study aimed to develop novel compound throat anti-viral (CTA) from natural plants using data Traditional Chinese Medicine Inheritance System identification through liquid chromatography-mass spectrometry. CTA demonstrated...
Resolving the reaction networks associated with biomass pyrolysis is central to understanding product selectivity and aiding catalyst design produce more valuable products. However, even network of relatively simple [Formula: see text]-D-glucose remains unresolved due its significant complexity in terms depth number major Here, a transition-state-guided exploration has been performed that provides complete pathways most experimental products text]-D-glucose. The resulting involves over...
The search for prebiotic chemical pathways to biologically relevant molecules is a long-standing puzzle that has generated menagerie of competing hypotheses with limited experimental prospects falsification. However, the advent computational network exploration methodologies created opportunity compare kinetic plausibility various channels and even propose new pathways. Here, space organic can be formed within four polar or pericyclic reactions from water hydrogen cyanide (HCN), two...
Newly developed Δ 2 -learning models enable state-of-the-art accuracy in predicting the properties of chemical reactions.
The gas-phase enthalpy of formation (ΔHf) plays a fundamental role in predicting reaction thermodynamics and constructing kinetic models. With advances computational power method development, chemically accurate quantum chemistry methods that can predict ΔHf values for small molecules are available; however, large still out reach. Increment theories provide means extending the prediction capability high-level by decomposing molecular into additive contributions from individual atoms, bonds,...
Force-field development has undergone a revolution in the past decade with proliferation of quantum chemistry based parametrizations and introduction machine learning approximations atomistic potential energy surface. Nevertheless, transferable force fields broad coverage organic chemical space remain necessary for applications materials discovery where throughput, consistency, computational cost are paramount. Here, we introduce force-field framework called Topology Automated Force-Field...
As the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas12a (previously known as Cpf1) system cleaves double-stranded DNA and produces a sticky end, it could serve useful tool for assembly/editing. To broaden its application, variety of engineered FnCas12a proteins are generated with expanded protospacer adjacent motif (PAM) requirements. Two variants (FnCas12a-EP15 EP16) increased targeting range by approximately fourfold. They can efficiently recognize broad PAM...
Deductive solution strategies are required in prediction scenarios that under determined, when contradictory information is available, or more generally wherever one-to-many non-functional mappings occur. In contrast, most contemporary machine learning (ML) the chemical sciences inductive from example, with a fixed set of features. Chemical workflows replete situations requiring deduction, including many aspects lab automation and spectral interpretation. Here, general strategy described for...
Mismatch uracil DNA glycosylase (Mug) from Escherichia coli is an initiating enzyme in the base-excision repair pathway. As with other glycosylases, abasic product potentially more harmful than initial lesion. Since Mug known to bind its tightly, inhibiting turnover, understanding how binds of significance when considering interacts downstream enzymes We have demonstrated differential binding modes between substrate and using both band shift fluorescence anisotropy assays. cooperatively, a...
Abstract Algorithmic reaction exploration based on transition state searches has already made inroads into many niche applications, but its potential as a general‐purpose tool is still largely unrealized. Computational cost and the absence of benchmark problems involving larger molecules remain obstacles to further progress. Here an ultra‐low algorithm implemented used explore reactivity unimolecular bimolecular reactants, comprising total 581 reactions 51 distinct reactants. The discovers...
Extant reaction transition state (TS) databases are comparatively small and lack chemical diversity. Here, this data gap has been addressed using the concept of a graphically-defined model to comprehensively characterize space associated with C, H, O N containing molecules up 10 heavy (non-hydrogen) atoms. The resulting dataset is composed 176,992 organic reactions possessing at least one validated TS, activation energy, heat reaction, reactant product geometries, frequencies, atom-mapping....
We have previously demonstrated that the two Exonuclease III (Xth) family members present within obligate human pathogen Neisseria meningitidis, NApe and NExo, are important for survival under conditions of oxidative stress. Of these, only possesses AP endonuclease activity, while primary function NExo remained unclear. now reveal further functional specialization at level 3′-PO4 processing NExo. demonstrate bi-functional meningococcal glycosylases Nth MutM can perform strand incisions...
Computational predictions of the thermodynamic properties molecules and materials play a central role in contemporary reaction prediction kinetic modeling. Due to lack experimental data computational cost high-level quantum chemistry methods, approximate methods based on additivity schemes more recently machine learning are currently only approaches capable supplying chemical coverage throughput necessary for such applications. For both approaches, ring-containing pose challenge...