Magnetic Exciton Relaxation and Spin–Spin Interaction by the Time-Delayed Photoluminescence Spectra of ZnO:Mn Nanowires

ZnO:Mn nanostructures are important diluted magnetic materials, but their electronic structure and magnetic origin are still not well understood. Here we studied the time-delayed and power-dependent photoluminescence spectra of Mn­(II) doped ZnO nanowires with very low Mn concentration. From the time-delayed emission spectra, we obtained their electronic levels of single Mn ion replacement of Zn ions in ZnO nanowire. The high d-level emissions show up unusually because of the stronger p–d hybridization than that in ZnS, as well as the spin–spin coupling. After increasing Mn doping concentration, the ferromagentic cluster of the Mn–O–Mn with varied configurations can form and give individual emission peaks, which are in good agreement with the ab initio calculations. The presence of clustered Mn ions originates from their ferromagnetic coupling. The lifetimes of these d levels show strong excitation power-dependent behavior, indication of strong spin-dependent coherent emission. One-dimensional structure is critical for this coherent emission behavior. These results indicate that the d state is not within Mn ion only, but a localized exciton magnetic polaron, Mn–O–Mn coupling should be one source of ferromagnetism in ZnO:Mn lattice, the latter also can combine with free exciton for EMP and produce coherent EMP condensation and emission from a nanowire. This kind of nanowires can be expected to work for both spintronic and spin-photonic devices if we tune the transition metal ion doping concentration in it

Quaternary Alloy Semiconductor Nanobelts with Bandgap Spanning the Entire Visible Spectrum

Quaternary Alloy Semiconductor Nanobelts with Bandgap Spanning the Entire Visible Spectru

Reactivities of the Front Pocket N‑Terminal Cap Cysteines in Human Kinases

The front pocket (FP) N-terminal cap (Ncap) cysteine is the most popular site of covalent modification in kinases. A long-standing hypothesis associates the Ncap position with cysteine hyper-reactivity; however, traditional computational predictions suggest that the FP Ncap cysteines are predominantly unreactive. Here we applied the state-of-the-art continuous constant pH molecular dynamics (CpHMD) to test the Ncap hypothesis. Simulations found that the Ncap cysteines of BTK/BMX/TEC/ITK/TXK, JAK3, and MKK7 are reactive to varying degrees; however, those of BLK and EGFR/ERBB2/ERBB4 possessing a Ncap+3 aspartate are unreactive. Analysis suggested that hydrogen bonding and electrostatic interactions drive the reactivity, and their absence renders the Ncap cysteine unreactive. To further test the Ncap hypothesis, we examined the FP Ncap+2 cysteines in JNK1/JNK2/JNK3 and CASK. Our work offers a systematic understanding of the cysteine structure–reactivity relationship and illustrates the use of CpHMD to differentiate cysteines toward the design of targeted covalent inhibitors with reduced chemical reactivities

Quantum Descriptors for Predicting and Understanding the Structure–Activity Relationships of Michael Acceptor Warheads

Predictive modeling and understanding of chemical warhead reactivities have the potential to accelerate targeted covalent drug discovery. Recently, the carbanion formation free energies as well as other ground-state electronic properties from density functional theory (DFT) calculations have been proposed as predictors of glutathione reactivities of Michael acceptors; however, no clear consensus exists. By profiling the thiol-Michael reactions of a diverse set of singly- and doubly-activated olefins, including several model warheads related to afatinib, here we reexamined the question of whether low-cost electronic properties can be used as predictors of reaction barriers. The electronic properties related to the carbanion intermediate were found to be strong predictors, e.g., the change in the Cβ charge accompanying carbanion formation. The least expensive reactant-only properties, the electrophilicity index, and the Cβ charge also show strong rank correlations, suggesting their utility as quantum descriptors. A second objective of the work is to clarify the effect of the β-dimethylaminomethyl (DMAM) substitution, which is incorporated in the warheads of several FDA-approved covalent drugs. Our data suggest that the β-DMAM substitution is cationic at neutral pH in solution and promotes acrylamide’s intrinsic reactivity by enhancing the charge accumulation at Cα upon carbanion formation. In contrast, the inductive effect of the β-trimethylaminomethyl substitution is diminished due to steric hindrance. Together, these results reconcile the current views of the intrinsic reactivities of acrylamides and contribute to large-scale predictive modeling and an understanding of the structure–activity relationships of Michael acceptors for rational TCI design

Quantum Descriptors for Predicting and Understanding the Structure–Activity Relationships of Michael Acceptor Warheads

Predictive modeling and understanding of chemical warhead reactivities have the potential to accelerate targeted covalent drug discovery. Recently, the carbanion formation free energies as well as other ground-state electronic properties from density functional theory (DFT) calculations have been proposed as predictors of glutathione reactivities of Michael acceptors; however, no clear consensus exists. By profiling the thiol-Michael reactions of a diverse set of singly- and doubly-activated olefins, including several model warheads related to afatinib, here we reexamined the question of whether low-cost electronic properties can be used as predictors of reaction barriers. The electronic properties related to the carbanion intermediate were found to be strong predictors, e.g., the change in the Cβ charge accompanying carbanion formation. The least expensive reactant-only properties, the electrophilicity index, and the Cβ charge also show strong rank correlations, suggesting their utility as quantum descriptors. A second objective of the work is to clarify the effect of the β-dimethylaminomethyl (DMAM) substitution, which is incorporated in the warheads of several FDA-approved covalent drugs. Our data suggest that the β-DMAM substitution is cationic at neutral pH in solution and promotes acrylamide’s intrinsic reactivity by enhancing the charge accumulation at Cα upon carbanion formation. In contrast, the inductive effect of the β-trimethylaminomethyl substitution is diminished due to steric hindrance. Together, these results reconcile the current views of the intrinsic reactivities of acrylamides and contribute to large-scale predictive modeling and an understanding of the structure–activity relationships of Michael acceptors for rational TCI design

Quantum Descriptors for Predicting and Understanding the Structure–Activity Relationships of Michael Acceptor Warheads

Predictive modeling and understanding of chemical warhead reactivities have the potential to accelerate targeted covalent drug discovery. Recently, the carbanion formation free energies as well as other ground-state electronic properties from density functional theory (DFT) calculations have been proposed as predictors of glutathione reactivities of Michael acceptors; however, no clear consensus exists. By profiling the thiol-Michael reactions of a diverse set of singly- and doubly-activated olefins, including several model warheads related to afatinib, here we reexamined the question of whether low-cost electronic properties can be used as predictors of reaction barriers. The electronic properties related to the carbanion intermediate were found to be strong predictors, e.g., the change in the Cβ charge accompanying carbanion formation. The least expensive reactant-only properties, the electrophilicity index, and the Cβ charge also show strong rank correlations, suggesting their utility as quantum descriptors. A second objective of the work is to clarify the effect of the β-dimethylaminomethyl (DMAM) substitution, which is incorporated in the warheads of several FDA-approved covalent drugs. Our data suggest that the β-DMAM substitution is cationic at neutral pH in solution and promotes acrylamide’s intrinsic reactivity by enhancing the charge accumulation at Cα upon carbanion formation. In contrast, the inductive effect of the β-trimethylaminomethyl substitution is diminished due to steric hindrance. Together, these results reconcile the current views of the intrinsic reactivities of acrylamides and contribute to large-scale predictive modeling and an understanding of the structure–activity relationships of Michael acceptors for rational TCI design

Analysis of the ERK Pathway Cysteinome for Targeted Covalent Inhibition of RAF and MEK Kinases

The ERK pathway is one of the most important signaling cascades involved in tumorigenesis. So far, eight noncovalent inhibitors of RAF and MEK kinases in the ERK pathway have been approved by the FDA for the treatment of cancers; however, their efficacies are limited due to various resistance mechanisms. There is an urgent need to develop novel targeted covalent inhibitors. Here we report a systematic study of the covalent ligandabilities of the ERK pathway kinases (ARAF, BRAF, CRAF, KSR1, KSR2, MEK1, MEK2, ERK1, and ERK2) using constant pH molecular dynamics titration and pocket analysis. Our data revealed that the hinge GK (gate keeper)+3 cysteine in RAF family kinases (ARAF, BRAF, CRAF, KSR1, and KSR2) and the back loop cysteine in MEK1 and MEK2 are reactive and ligandable. Structure analysis suggests that the type II inhibitors belvarafenib and GW5074 may be used as scaffolds for designing pan-RAF or CRAF-selective covalent inhibitors directed at the GK+3 cysteine, while the type III inhibitor cobimetinib may be modified to label the back loop cysteine in MEK1/2. The reactivities and ligandabilities of the remote cysteine in MEK1/2 and the DFG-1 cysteine in MEK1/2 and ERK1/2 are also discussed. Our work provides a starting point for medicinal chemists to design novel covalent inhibitors of the ERK pathway kinases. The computational protocol is general and can be applied to the systematic evaluation of covalent ligandabilities of the human cysteinome

Table_1_The Application and Limitation of Universal Chloroplast Markers in Discriminating East Asian Evergreen Oaks.xls

<p>The East Asian subtropics mostly occupied by evergreen broad-leaved forests (EBLFs), is one of the global diversity centers for evergreen oaks. Evergreen oaks are keystone canopy trees in EBLFs with important ecosystem function and crucial significance for regional biodiversity conservation. However, the species composition and diversity of Asian evergreen oaks are poorly understood. Here, we test whether the four chloroplast markers atpI-atpH, matK, psbA-trnH, and ycf1, can discriminate the two evergreen oak sections in Asia – Cyclobalanopsis and Ilex. Two hundred and seventy-two individuals representing 57 species were scanned and 17 species from other oaks sections were included for phylogenetic reconstruction. The genetic diversity of the Quercus sections was also compared. Overall, we found that universal chloroplast DNA (cpDNA) barcoding markers could resolve two clades in Quercus, i.e., subgenus Cerris (Old World Clade) and subgenus Quercus (New World Clade). The chloroplast markers distinguished the main sections, with few exceptions. Each cpDNA region showed no barcoding gap and none of them provided good resolution at the species level. The best species resolution (27.78%) was obtained when three or four markers were combined and analyzed using BLAST. The high conservation of the cpDNA and complicated evolutionary patterns, due to incomplete lineage sorting, interspecific hybridization and introgressions may hinder the ability of cpDNA markers to discriminate different species. When comparing diversification pattern across Quercus sections (Cyclobalanopsis, Ilex, Cerris, Quercus, and Protobalanus), we found that section Ilex was the most genetically diverse, and section Cyclobalanopsis was lower genetically diverse. This diversification pattern may have resulted from the interplay of the Eurasia Cenozoic tectonic movements, climate changes and different niches of their ancestral lineages.</p

Machine Learning Models to Interrogate Proteome-Wide Covalent Ligandabilities Directed at Cysteines

Machine learning (ML) identification of covalently ligandable sites may accelerate targeted covalent inhibitor design and help expand the druggable proteome space. Here, we report the rigorous development and validation of the tree-based models and convolutional neural networks (CNNs) trained on a newly curated database (LigCys3D) of over 1000 liganded cysteines in nearly 800 proteins represented by over 10,000 three-dimensional structures in the protein data bank. The unseen tests yielded 94 and 93% area under the receiver operating characteristic curves for the tree models and CNNs, respectively. Based on the AlphaFold2 predicted structures, the ML models recapitulated the newly liganded cysteines in the PDB with over 90% recall values. To assist the community of covalent drug discoveries, we report the predicted ligandable cysteines in 392 human kinases and their locations in the sequence-aligned kinase structure, including the PH and SH2 domains. Furthermore, we disseminate a searchable online database LigCys3D (https://ligcys.computchem.org/) and a web prediction server DeepCys (https://deepcys.computchem.org/), both of which will be continuously updated and improved by including newly published experimental data. The present work represents an important step toward the ML-led integration of big genome data and structure models to annotate the human proteome space for the next-generation covalent drug discoveries