Prediction of the Iron–Sulfur Binding Sites in Proteins Using the Highly Accurate Three-Dimensional Models Calculated by AlphaFold and RoseTTAFold

AlphaFold and RoseTTAFold are deep learning-based approaches that predict the structure of proteins from their amino acid sequences. Remarkable success has recently been achieved in the prediction accuracy of not only the fold of the target protein but also the position of its amino acid side chains. In this article, I question the accuracy of these methods to predict iron–sulfur binding sites. I analyze three-dimensional models calculated by AlphaFold and RoseTTAFold of Fe–S–dependent enzymes, for which no structure of a homologous protein has been solved experimentally. In all cases, the amino acids that presumably coordinate the cluster were gathered together and facing each other, which led to a quite accurate model of the Fe–S cluster binding site. Yet, cysteine candidates were often involved in intramolecular disulfide bonds, and the number and identity of the protein amino acids that should ligate the cluster were not always clear. The experimental structure determination of the protein with its Fe–S cluster and in complex with substrate/inhibitor/product is still needed to unambiguously visualize the coordination state of the cluster and understand the conformational changes occurring during catalysis.

Effects of Polyphenols on P-Glycoprotein (ABCB1) Activity

P-glycoprotein (Pgp, ABCB1) is a member of one of the largest families of active transporter proteins called ABC transporters. Thanks to its expression in tissues with barrier functions and its broad substrate spectrum, it is an important determinant of the absorption, metabolism and excretion of many drugs. Pgp and/or some other drug transporting ABC proteins (e.g., ABCG2, MRP1) are overexpressed in nearly all cancers and cancer stem cells by which cancer cells become resistant against many drugs. Thus, Pgp inhibition might be a strategy for fighting against drug-resistant cancer cells. Previous studies have shown that certain polyphenols interact with human Pgp. We tested the effect of 15 polyphenols of sour cherry origin on the basal and verapamil-stimulated ATPase activity of Pgp, calcein-AM and daunorubicin transport as well as on the conformation of Pgp using the conformation sensitive UIC2 mAb. We found that quercetin, quercetin-3-glucoside, narcissoside and ellagic acid inhibited the ATPase activity of Pgp and increased the accumulation of calcein and daunorubicin by Pgp-positive cells. Cyanidin-3O-sophoroside, catechin, naringenin, kuromanin and caffeic acid increased the ATPase activity of Pgp, while they had only a weaker effect on the intracellular accumulation of fluorescent Pgp substrates. Several tested polyphenols including epicatechin, trans-ferulic acid, oenin, malvin and chlorogenic acid were ineffective in all assays applied. Interestingly, catechin and epicatechin behave differently, although they are stereoisomers. We also investigated the effect of quercetin, naringenin and ellagic acid added in combination with verapamil on the transport activity of Pgp. In these experiments, we found that the transport inhibitory effect of the tested polyphenols and verapamil was additive or synergistic. Generally, our data demonstrate diverse interactions of the tested polyphenols with Pgp. Our results also call attention to the potential risks of drug–drug interactions (DDIs) associated with the consumption of dietary polyphenols concurrently with chemotherapy treatment involving Pgp substrate/inhibitor drugs.

Inhibitor Resistant Mutants Give Important Insights into Candida albicans ABC Transporter Cdr1 Substrate Specificity and Help Elucidate Efflux Pump Inhibition

Overexpression of ATP-binding cassette (ABC) transporters is a major cause of drug resistance in fungal pathogens. Milbemycins, enniatin B, beauvericin and FK506 are promising leads for broad-spectrum fungal multidrug efflux pump inhibitors. The characterization of naturally generated inhibitor resistant mutants is a powerful tool to elucidate structure-activity relationships in ABC transporters. We isolated twenty Saccharomyces cerevisiae mutants overexpressing Candida albicans ABC pump Cdr1 variants resistant to fluconazole efflux inhibition by milbemycin α25 (eight mutants), enniatin B (eight) or beauvericin (four). The twenty mutations were in just nine residues at the centres of transmembrane segment 1 (TMS1) (six mutations), TMS4 (four), TMS5 (four), TMS8 (one) and TMS11 (two) and in A713P (three), a previously reported FK506-resistant ‘hotspot 1’ mutation in extracellular loop 3. Six Cdr1-G521S/C/V/R (TMS1) variants were resistant to all four inhibitors, four Cdr1-M639I (TMS4) isolates were resistant to milbemycin α25 and enniatin B, and two Cdr1-V668I/D (TMS5) variants were resistant to enniatin B and beauvericin. The eight milbemycin α25 resistant mutants were altered in four amino acids: G521R, M639I, A713P and T1355N. These four Cdr1 variants responded differently to various types of inhibitors, and each exhibited altered substrate specificity and kinetic properties. The data infer an entry gate function for Cdr1-G521 and a role for Cdr1-A713 in the constitutively high Cdr1 ATPase activity. Cdr1-M639I and -T1355N (TMS11) possibly cause inhibitor-resistance by altering TMS-contacts near the substrate/inhibitor-binding pocket. Models for the interactions of substrates and different types of inhibitors with Cdr1 at various stages of the transport cycle are presented.

Point mutations in Candida glabrata 3-hydroxy-3-methylglutaryl-coenzyme A reductase (CgHMGR) decrease enzymatic activity and substrate/inhibitor affinity

Abstract3-Hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR) is a crucial enzyme in the ergosterol biosynthesis pathway. The aim of this study was to obtain, purify, characterize, and overexpress five point mutations in highly conserved regions of the catalytic domain of Candida glabrata HMGR (CgHMGR) to explore the function of key amino acid residues in enzymatic activity. Glutamic acid (Glu) was substituted by glutamine in the E680Q mutant (at the dimerization site), Glu by glutamine in E711Q (at the substrate binding site), aspartic acid by alanine in D805A, and methionine by arginine in M807R (the latter two at the cofactor binding site). A double mutation, E680Q-M807R, was included. Regarding recombinant and wild-type CgHMGR, in vitro enzymatic activity was significantly lower for the former, as was the in silico binding energy of simvastatin, alpha-asarone and the HMG-CoA substrate. E711Q displayed the lowest enzymatic activity and binding energy, suggesting the importance of Glu711 (in the substrate binding site). The double mutant CgHMGR E680Q-M807R exhibited the second lowest enzymatic activity. Based on the values of the kinetic parameters KM and Vmax, the mutated amino acids appear to participate in binding. The current findings provide insights into the role of residues in the catalytic site of CgHMGR.

Inhibition of Kallikrein-related peptidases 7 restrains pancreatic tumor growth through induction of ferroptosis

Pancreatic cancer is one of the most aggressive and lethal malignancies with extremely poor prognosis, and KLK7 was considered as a potential therapeutic target. In this study, we analyzed the expression of KLK7 in TCGA and GTEx databases and found that KLK7 had a negative correlation to long-term survival rate (>1.5 years) of pancreatic cancer patients. Compound 42 is a coumarinic derivative, a suicide substrate inhibitor of KLK7, which has been proved to inhibit the proliferation of PANC-1 cells in vitro effectively in our previous study. In this study, we further investigated the inhibition ability of Compound 42 in tumor formation and development in CDX and PDX tumor models of pancreatic cancer subsequently. Besides, we studied the inhibitory mechanism of Compound 42 and the result showed that Compound 42 arrested the pancreatic cancer cell cycle in G0/G1 phase and induced ferroptosis through down-regulation of GPX4 protein level and accumulation of iron ion. Thus, these experiments demonstrate that Compound 42, suppressing pancreatic cancer in vivo, is expected to become a novel drug for pancreatic cancer treatment.

Structural Changes in the Cap of Rv0183/mtbMGL Modulate the Shape of the Binding Pocket

Tuberculosis continues to be a major threat to the human population. Global efforts to eradicate the disease are ongoing but are hampered by the increasing occurrence of multidrug-resistant strains of Mycobacterium tuberculosis. Therefore, the development of new treatment, and the exploration of new druggable targets and treatment strategies, are of high importance. Rv0183/mtbMGL, is a monoacylglycerol lipase of M. tuberculosis and it is involved in providing fatty acids and glycerol as building blocks and as an energy source. Since the lipase is expressed during the dormant and active phase of an infection, Rv0183/mtbMGL is an interesting target for inhibition. In this work, we determined the crystal structures of a surface-entropy reduced variant K74A Rv0183/mtbMGL in its free form and in complex with a substrate mimicking inhibitor. The two structures reveal conformational changes in the cap region that forms a major part of the substrate/inhibitor binding region. We present a completely closed conformation in the free form and semi-closed conformation in the ligand-bound form. These conformations differ from the previously published, completely open conformation of Rv0183/mtbMGL. Thus, this work demonstrates the high conformational plasticity of the cap from open to closed conformations and provides useful insights into changes in the substrate-binding pocket, the target of potential small-molecule inhibitors.

Point Mutations In Candida Glabrata 3-Hydroxy-3-Methyl Glutaryl Coenzyme A Reductase (HMGRCg) An Antifungal Target, Decrease Enzymatic Activity And Substrate/Inhibitor Affinity

An alternative target for antifungal drugs is 3-hydroxy-3-methyl glutaryl coenzyme A reductase (HMGR), a key enzyme in the ergosterol biosynthesis pathway. The aim of this study was to obtain, purify, characterize, and overexpress five point mutations in highly conserved regions of the catalytic domain of Candida glabrata HMGR (HMGRCg) to explore the function of key amino acid residues. Glutamic acid (Glu) was substituted by glutamine in the E680Q mutant (at the dimerization site), Glu by glutamine in E711Q (at the substrate binding site), aspartic acid by alanine in D805A and methionine by arginine in M807R (the latter two at the cofactor binding site). A double mutation, E680Q-M807R, was also made. The in vitro enzymatic activity decreased significantly in all recombinant (versus wild-type) HMGRCg, and the in silico binding energy for simvastatin, alpha-asarone and the substrate HMG-CoA was also lower for the mutants. The lowest enzymatic activity and binding energy was displayed by E711Q, suggesting that Glu711 (in the substrate binding site) is an important residue for enzymatic activity. The double mutant HMGRCg E680Q-M807R exhibited the second lowest enzymatic activity. The current findings provide insights into the role of residues in the catalytic site of HMGRCg.

Machine learning models for classification tasks related to drug safety

In this review, we outline the current trends in the field of machine learning-driven classification studies related to ADME (absorption, distribution, metabolism and excretion) and toxicity endpoints from the past six years (2015–2021). The study focuses only on classification models with large datasets (i.e. more than a thousand compounds). A comprehensive literature search and meta-analysis was carried out for nine different targets: hERG-mediated cardiotoxicity, blood–brain barrier penetration, permeability glycoprotein (P-gp) substrate/inhibitor, cytochrome P450 enzyme family, acute oral toxicity, mutagenicity, carcinogenicity, respiratory toxicity and irritation/corrosion. The comparison of the best classification models was targeted to reveal the differences between machine learning algorithms and modeling types, endpoint-specific performances, dataset sizes and the different validation protocols. Based on the evaluation of the data, we can say that tree-based algorithms are (still) dominating the field, with consensus modeling being an increasing trend in drug safety predictions. Although one can already find classification models with great performances to hERG-mediated cardiotoxicity and the isoenzymes of the cytochrome P450 enzyme family, these targets are still central to ADMET-related research efforts. Graphical abstract

Decoupling salinity and carbonate chemistry: low calcium ion concentration rather than salinity limits calcification in Baltic Sea mussels

The Baltic Sea has a salinity gradient decreasing from fully marine (> 25) in the west to below 7 in the central Baltic Proper. Habitat-forming and ecologically dominant mytilid mussels exhibit decreasing growth when salinity < 11; however, the mechanisms underlying reduced calcification rates in dilute seawater are not fully understood. Both [HCO3-] and [Ca2+] also decrease with salinity, challenging calcifying organisms through CaCO3 undersaturation (Ω≤1) and unfavourable ratios of calcification substrates ([Ca2+] and [HCO3-]) to the inhibitor (H+), expressed as the extended substrate–inhibitor ratio (ESIR). This study combined in situ monitoring of three southwest Baltic mussel reefs with two laboratory experiments to assess how various environmental conditions and isolated abiotic factors (salinity, [Ca2+], [HCO3-] and pH) impact calcification in mytilid mussels along the Baltic salinity gradient. Laboratory experiments rearing juvenile Baltic Mytilus at a range of salinities (6, 11 and 16), HCO3- concentrations (300–2100 µmol kg−1) and Ca2+ concentrations (0.5–4 mmol kg−1) reveal that as individual factors, low [HCO3-], pH and salinity cannot explain low calcification rates in the Baltic Sea. Calcification rates are impeded when Ωaragonite ≤ 1 or ESIR ≤ 0.7 primarily due to [Ca2+] limitation which becomes relevant at a salinity of ca. 11 in the Baltic Sea. Field monitoring of carbonate chemistry and calcification rates suggest increased food availability may be able to mask the negative impacts of periodic sub-optimal carbonate chemistry, but not when seawater conditions are permanently adverse, as observed in two Baltic reefs at salinities < 11. Regional climate models predict a rapid desalination of the southwest and central Baltic over the next century and potentially a reduction in [Ca2+] which may shift the distribution of marine calcifiers westward. It is therefore vital to understand the mechanisms by which the ionic composition of seawater impacts bivalve calcification for better predicting the future of benthic Baltic ecosystems.