New insights into the molecular mechanism of methanol-induced inactivation of Thermomyces lanuginosus lipase: A molecular dynamics simulation study

Methanol intolerance of lipase is a major limitation in lipase-catalyzed methanolysis reactions. In this study, to understand the molecular mechanism of methanol-induced inactivation of lipases, we performed molecular dynamics (MD) simulations of Thermomyces lanuginosus lipase (TLL) in water and methanol and compared the observed structural and dynamic properties. The solvent accessibility analysis showed that in methanol, polar residues tended to be buried away from the solvent while non-polar residues tended to be more solvent-exposed in comparison to those in water. Moreover, we observed that in methanol, the van der Waals packing of the core residues in two hydrophobic regions of TLL became weak. Additionally, the catalytically relevant hydrogen bond between Asp201 OD2 and His258 ND1 in the active site was broken when the enzyme was solvated in methanol. This may affect the stability of the tetrahedral intermediates in the catalytic cycle of TLL. Furthermore, compared to those in water, some enzyme surface residues displayed enhanced movement in methanol with higher Cα root-mean-square atomic positional fluctuation values. One of such methanol-affecting surface residues (Ile241) was chosen for mutation, and MD simulation of the I241E mutant in methanol was conducted. The structural analysis of the mutant showed that replacing a non-polar surface residue with an acidic one at position 241 contributed to the stabilization of enzyme structure in methanol. Ultimately, these results, while providing molecular-level insights into the destabilizing effect of methanol on TLL, highlight the importance of surface residue redesign to improve the stability of lipases in methanol environments

Manipulations of phenylnorbornyl palladium species for multicomponent construction of a bridged polycyclic privileged scaffold

Hexahydromethanocarbazole is a privileged scaffold in the discovery of new drugs and photoactive organic materials due to its good balance between structural complexity and minimized entropy penalty upon receptor binding. To address the difficulty of synthesizing this highly desirable bridged polycyclic scaffold, we designed a convenient multicomponent reaction cascade as intercepted Heck addition/C-H activation/C-palladacycle formation/electrophilic attack of ANP/N-palladacycle formation/Buchwald amination. A distinguishing feature of this sophisticated strategy is the successive generation of two key phenylnorbornyl palladium species to control the reaction flow towards desired products. DFT calculations further reveal the crucial roles of Cs2CO3 and 5,6-diester substitutions on the norbornene reactant in preventing multiple side-reactions. This innovative method exhibits a broad scope with good yields, and therefore will enable the construction of natural-product-like compound libraries based on hexahydromethanocarbazole

Role of tryptophan residues of Erv1: Trp95 and Trp183 are important for its folding and oxidase function

Erv1 is an FAD-dependent sulphydryl oxidase of the ERV/ALR sub-family, and an essential component of the mitochondrial import and assembly pathway. Erv1 contains six tryptophan residues, which are all located in the highly conserved C-terminal FAD-binding domain. Though important structural roles were predicted for the invariable Trp95, no experimental study has been reported. In this study, we investigated the structural and functional roles of individual Trp residues of Erv1. Six single Trp-to-Phe yeast mutant strains were generated and their effects on cell viability were tested at various temperatures. Then, the mutants were purified from E. coli. Their effects on folding, FAD-binding, and Erv1 activity were characterised. Our results showed that Erv1W95F has the strongest effect on the stability and function of Erv1, and followed by Erv1W183F. Erv1W95F results in a decrease of the Tm of Erv1 by 23°C, a significant loss of the oxidase activity, and thus causing cell growth defects at both 30°C and 37°C. Erv1W183F induces changes in the oligomerisation state of Erv1, along with a pronounced effect on the stability of Erv1 and its function at 37°C, whilst the other mutants had no clear effect on the function of Erv1 including the highly conserved Trp157 mutant. Finally, computational analysis indicates that Trp95 plays a key role in stabilising the isoalloxazine ring to interact with Cys133. Taken together, this study provided important insights into the molecular mechanism of how sulfhydryl oxidases use FAD in catalyzing disulfide bond formation

Computational studies of dihydrofolate reductase from Thermotoga maritima

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Molecular dynamics simulation of thermal unfolding of Thermatoga maritima DHFR

Molecular dynamics simulations of the temperature-induced unfolding reaction of native dimeric dihydrofolate reductase from the hyperthermophile Thermatoga maritima (TmDHFR) and the experimentally inaccessible TmDHFR monomer were carried out at 400 K, 450 K and 500 K. The results revealed that the unfolding of TmDHFR subunits followed a similar path to that of the monomeric DHFR from the mesophile E. coli (EcDHFR). An initial collapse of the adenosine-binding domain (ABD) was followed by the loss of the N-terminal and loop domains (NDLD). Interestingly, the elements of the secondary structure of the isolated TmDHFR monomer were maintained for significantly longer periods of time for the hyperthermophilic enzyme, suggesting that subunit stability contributes to the enhanced resistance of TmDHFR to temperature-induced unfolding. The interactions between the subunits of the TmDHFR dimer led to a stabilisation of the NDLD. The hydrogen bonds between residues 140-143 in betaG of one subunit and residues 125-127 in betaF of the other subunit were retained for significant parts of the simulations at all temperatures. These intermolecular hydrogen bonds were lost after the unfolding of the individual subunits. The high stability of the dimer mediated by strong intersubunit contacts together with an intrinsically enhanced stability of the subunits compared to EcDHFR provides a molecular rational for the higher stability of the thermophilic enzyme. The computed unfolding pathways suggest that the partly folded dimer may be a genuine folding intermediate

Using Natural Language Processing (NLP)-inspired molecular embedding approach to predict Hansen solubility parameters

Hansen solubility parameters (HSPs) have three components, δd, δp and δh, accounting for dispersion forces, polar forces, and hydrogen bonding of a molecule, which were designed to better understand how molecular structure affects miscibility/solubility. HSP is widely used throughout the pipeline of pharmaceutical research and yet has not been as well studied computationally as the aqueous solubility. In the current study, we predicted HSPs using only the SMILES of molecules and utilise the molecular embedding approach inspired by Natural Language Processing (NLP). Two pre-trained deep learning models – Mol2Vec and ChemBERTa have been used to derive the embeddings. A dataset of ∼1200 organic molecules with experimentally determined HSPs was used as the labelled dataset. Upon finetuning, the ChemBERTa model “learned” relevant molecular features and shifted attention to functional groups that give rise to the relevant HSPs. The finetuned ChemBERTa model outperforms both the Mol2Vec model and the baseline Morgan fingerprint method albeit not to a significant extent. Interestingly, the embedding models can predict δd significantly better than δh and δp and overall, the accuracy of predicted HSPs is lower than the well-benchmarked ESOL aqueous solubility. Our study indicates that the extent of transfer learning leveraged from the pre-trained models is related to the labelled molecular properties. It also highlights how δp and δh may have large intrinsic errors in the way they are defined and therefore introduces inherent limitations to their accurate prediction using machine learning models. Our work reveals several interesting findings that will help explore the potential of BERT-based models for molecular property prediction. It may also guide the possible refinement of the Hansen solubility framework, which will generate a wide impact across the pharmaceutical industry and research

Weather Factors Associated with Reduced Risk of Dengue Transmission in an Urbanized Tropical City

This study assessed the impact of weather factors, including novel predictors—pollutant standards index (PSI) and wind speed—on dengue incidence in Singapore between 2012 and 2019. Autoregressive integrated moving average (ARIMA) model was fitted to explore the autocorrelation in time series and quasi-Poisson model with a distributed lag non-linear term (DLNM) was set up to assess any non-linear association between climatic factors and dengue incidence. In DLNM, a PSI level of up to 111 was positively associated with dengue incidence; incidence reduced as PSI level increased to 160. A slight rainfall increase of up to 7 mm per week gave rise to higher dengue risk. On the contrary, heavier rainfall was protective against dengue. An increase in mean temperature under around 28.0 °C corresponded with increased dengue cases whereas the association became negative beyond 28.0 °C; the minimum temperature was significantly positively associated with dengue incidence at around 23–25 °C, and the relationship reversed when temperature exceed 27 °C. An overall positive association, albeit insignificant, was observed between maximum temperature and dengue incidence. Wind speed was associated with decreasing relative risk (RR). Beyond prevailing conclusions on temperature, this study observed that extremely poor air quality, high wind speed, minimum temperature ≥27 °C, and rainfall volume beyond 12 mm per week reduced the risk of dengue transmission in an urbanized tropical environment

Assignment of the vibrational spectra of enzyme-bound tryptophan tryptophyl quinones using a combined QM/MM approach

Fourier transform infrared (FTIR) spectroscopy can be used to provide a detailed time-resolved probe of reaction intermediates in enzyme-catalyzed systems. Accurate assignment of the respective chemical species being studied is key to the success of this approach. The plethora of signals from the protein environment, leading to complexity in the spectra, presents a particular challenge. Here we present a combined QM/MM-based approach that can be used to assign key resonances in the FTIR spectrum of tryptophan tryptophyl quinone (TTQ) in the TTQ-dependent quinoprotein aromatic amine dehydrogenase (AADH). We show that consideration of the cofactor alone is not sufficient to identify correctly the experimentally observed resonances—inclusion of the protein is required for this. However, to enable accurate peak assignment, a stepwise approach is needed that builds up increasing levels of complexity from a simple system. This study serves as a benchmark for future QM/MM-based studies to predict the spectroscopic changes during the interconversion of intermediates in the reductive half-reaction catalyzed by AADH, and more generally for using a combined QM/MM approach to calculate spectroscopic data of protein cofactors and cofactor-based adducts. Copyright © 2009 American Chemical Society

New insights into the multi-step reaction pathway of the reductive half-reaction catalysed by aromatic amine dehydrogenase: a QM/MM study

Computational insight into the multi-step reaction cycle of aromatic amine dehydrogenase is presented, identifying the energy landscape and pathway for multiple proton transfers. This atomistic picture of the reaction sequence—including short-lived reaction intermediates and a stepwise reaction mechanism—bridges the gap between a small number of crystallographic snapshots

Hydride transfer reaction catalyzed by hyperthermophilic dihydrofolate reductase is dominated by quantum mechanical tunneling and is promoted by both inter- and intramonomeric correlated motions

Simulations of hydride and deuteride transfer catalyzed by dihydrofolate reductase from the hyperthermophile Thermotoga maritima (TmDHFR) are presented. TmDHFR was modeled with its active homodimeric quaternary structure, where each monomer has three subdomains. The potential energy function was a combined quantum mechanical and molecular mechanical potential (69 atoms were treated quantum mechanically, and 35 287, by molecular mechanics). The calculations of the rate constants by ensemble-averaged variational transition state theory with multidimensional tunneling predicted that hydride and deuteride transfer at 278 K proceeded with 81 and 80% by tunneling. These percentages decreased to 50 and 49% at 338 K. The kinetic isotope effect was dominated by contributions of bound vibrations and decreased from 3.0 to 2.2 over the temperature range. The calculated rates for hydride and deuteride transfer catalyzed by the hypothetical monomer were smaller by approximately 2 orders of magnitude. At 298 K tunneling contributed 73 and 66% to hydride and deuteride transfer in the monomer. The decreased catalytic efficiency of the monomer was therefore not the result of a decrease of the tunneling contribution but an increase in the quasi-classical activation free energy. The catalytic effect was associated in the dimer with correlated motions between domains as well as within and between subunits. The intrasubunit correlated motions were decreased in the monomer when compared to both native dimeric TmDHFR and monomeric E. coli enzyme. TmDHFR and its E. coli homologue involve similar patterns of correlated interactions that affect the free energy barrier of hydride transfer despite only 27% sequence identity and different quaternary structures