Cell-penetrating peptides (CPPs) are naturally able to cross the lipid bilayer membrane that protects cells. These peptides share common structural and physicochemical properties and show different pharmaceutical applications, among which drug delivery is the most important. Due to their ability to cross the membranes by pulling high-molecular-weight polar molecules, they are termed Trojan horses. In this study, we proposed a machine learning (ML)-based framework named BChemRF-CPPred (beyondchemicalrules-basedframework forCPP prediction) that uses an artificial neural network, a support vector machine, and a Gaussian process classifier to differentiate CPPs from non-CPPs, using structure- and sequence-based descriptors extracted from PDB and FASTA formats. The performance of our algorithm was evaluated by tenfold cross-validation and compared with those of previously reported prediction tools using an independent dataset. The BChemRF-CPPred satisfactorily identified CPP-like structures using natural and synthetic modified peptide libraries and also obtained better performance than those of previously reported ML-based algorithms, reaching the independent test accuracy of 90.66% (AUC = 0.9365) for PDB, and an accuracy of 86.5% (AUC = 0.9216) for FASTA input. Moreover, our analyses of the CPP chemical space demonstrated that these peptides break some molecular rules related to the prediction of permeability of therapeutic molecules in cell membranes. This is the first comprehensive analysis to predict synthetic and natural CPP structures and to evaluate their chemical space using an ML-based framework. Our algorithm is freely available for academic use at http://comptools.linc.ufpa.br/BChemRF-CPPred.
Odorant-binding proteins (OBPs) are the main olfactory
proteins
of mosquitoes, and their structures have been widely explored to develop
new repellents. In the present study, we combined ligand- and structure-based
virtual screening approaches using as a starting point 1633 compounds
from 71 botanical families obtained from the Essential Oil Database
(EssOilDB). Using as reference the crystallographic structure of N,N-diethyl-meta-toluamide
interacting with the OBP1 homodimer of Anopheles gambiae (AgamOBP1), we performed a structural and pharmacophoric
similarity search to select potential natural products from the library. Thymol acetate, 4-(4-methyl phenyl)-pentanal, thymyl isovalerate,
and p-cymen-8-yl demonstrated a favorable chemical
correlation with DEET and also had high-affinity interactions with
the OBP binding pocket that molecular dynamics simulations showed
to be stable. To the best of our knowledge, this is the first study
to evaluate on a large scale the potentiality of NPs from essential
oils as inhibitors of the mosquito OBP1 using in silico approaches.
Our results could facilitate the design of novel repellents with improved
selectivity and affinity to the protein binding pocket and can shed
light on the mechanism of action of these compounds against insect
olfactory recognition.
Tobacco smoke contains various cancer-causing toxic substances, including nicotine and nitrosamines 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N′-nitrosonornicotine (NNN). The cytochrome 2A13 is involved in nicotine metabolism and in the activation of the pro-carcinogenic agents NNK and NNN, by means of α-hydroxylation reactions. Despite the significance of cytochrome 2A13 in the biotransformation of these molecules, its conformational mechanism and the molecular basis involved in the process are not fully understood. In this study, we used molecular dynamics and principal component analysis simulations for an in-depth analysis of the essential protein motions involved in the interaction of cytochrome 2A13 with its substrates. We also evaluated the interaction of these substrates with the amino acid residues in the binding pocket of cytochrome 2A13. Furthermore, we quantified the nature of these chemical interactions from free energy calculations using the Molecular Mechanics/Generalized Born Surface Area method. The ligands remained favorably oriented toward compound I (cytochrome P450 OFe IV state), to undergo α-hydroxylation. The hydrogen bond with asparagine 297 was essential to maintaining the substrates in a favorable catalytic orientation. The plot of first principal motion vs second principal motion revealed that the enzyme's interaction with nicotine and NNK involved different conformational subgroups, whereas the conformational subgroups in the interaction with NNN are more similar. These results provide new mechanistic insights into the mode of interaction of the substrates with the active site of cytochrome 2A13, in the presence of compound I, which is essential for α-hydroxylation.
Enolpyruvyl transfer from phosphoenolpyruvate (PEP) to the hydroxyl group of shikimate-5-OH-3-phosphate (S3P) is catalyzed by 5-enolpyruvylshikimate 3-phosphate (EPSP) synthase in a reaction that involves breaking the C-O bond of PEP. Catalysis involves an addition-elimination mechanism with the formation of a tetrahedral intermediate (THI). Experiments have elucidated the mechanism of THI formation and breakdown. However, the catalytic action of EPSP synthase and the individual roles of catalytic residues Asp313 and Glu341 remains unclear. We have used a hybrid quantum mechanical/molecular mechanical (QM/MM) approach to explore the free energy surface in a reaction catalyzed by EPSP synthase. The Glu341 was the most favorable acid/base catalyst. Our results indicate that the protonation of PEP C3 precedes the nucleophilic attack on PEP C2 in the addition mechanism. Also, the breaking of the C-O bond of THI to form an EPSP cation intermediate must occur before proton transfer from PEP C3 to Glu341 in the elimination mechanism. Analysis of the FES supports cationic intermediate formation during the reaction catalyzed by EPSP synthase. Finally, the computational model indicates a proton transfer shift (Hammond shift) from Glu341 to C3 for an enzyme-based reaction with the shifted transition state, earlier than in the reference reaction in water.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.