Influence of oligonucleotides structures for separation of diastereomers by capillary electrophoresis method using polyvinylpyrrolidone 1,300,000.

In the field of oligonucleotides drug discovery, phosphorothioate (PS) modification has been recognized as an effective tool to overcome the nuclease digestion, and generates 2n of possible diastereomers, where n equals the number of PS linkages. However, it is also well known that differences in drug efficacy and toxicity are caused by differences in stereochemistry of oligonucleotides. Therefore, the development of a high-resolution analytical method that enables stereo discrimination of oligonucleotides is desired. Under this circumstance, capillary electrophoresis (CE) using polyvinylpyrrolidone (PVP) is considered as one of the useful tools for the separation analysis of diastereomers. In this study, we evaluated the several oligonucleotides with the structural diversities in order to understand the separation mechanism of the diastereomers by CE. Especially, five kinds of 2'-moieties were deeply examined by CE with PVP 1,300,000 polymer solution. We found that different trend of the peak shapes and the peak resolution were observed among these oligonucleotides. For example, the better peak resolution was observed in 6 mer PS3-DNA compared to the rigid structure of 6 mer PS3-LNA. As for this reason, the computational simulation revealed that difference of accessible surface area caused by the steric structure of thiophosphate in each oligonucleotide is one of the key attributes to explain the separation of the diastereomers. In addition, we achieved the separation of sixteen peak tops of the diastereomers in 6 mer PS4-DNA, and the complete separation of fifteen diastereomers in 6 mer PS4-RNA. These knowledge for the separation of the diastereomers by CE will be expected to the quality control of the oligonucleotide drugs.

Asking the right questions for mutagenicity prediction from BioMedical text.

Assessing the mutagenicity of chemicals is an essential task in the drug development process. Usually, databases and other structured sources for AMES mutagenicity exist, which have been carefully and laboriously curated from scientific publications. As knowledge accumulates over time, updating these databases is always an overhead and impractical. In this paper, we first propose the problem of predicting the mutagenicity of chemicals from textual information in scientific publications. More simply, given a chemical and evidence in the natural language form from publications where the mutagenicity of the chemical is described, the goal of the model/algorithm is to predict if it is potentially mutagenic or not. For this, we first construct a golden standard data set and then propose MutaPredBERT, a prediction model fine-tuned on BioLinkBERT based on a question-answering formulation of the problem. We leverage transfer learning and use the help of large transformer-based models to achieve a Macro F1 score of >0.88 even with relatively small data for fine-tuning. Our work establishes the utility of large language models for the construction of structured sources of knowledge bases directly from scientific publications.

In Vitro Metabolism of 2-Methoxy-N-[3-[4-[3-methyl-4-[(6-methyl- 3-pyridinyl)oxy]anilino]-6-quinazolinyl]prop-2-enyl]acetamide (CP-724,714) by Aldehyde Oxidase and Predicting Its Percent Contribution Relative to CYP-Mediated Metabolism.

2-methoxy-N-[3-[4-[3-methyl-4-[(6-methyl-3-pyridinyl)oxy]anilino]-6-quinazolinyl]prop-2-enyl]acetamide (CP-724,714) is an anticancer drug that was discontinued due to hepatotoxicity found in clinical studies. Metabolite analysis of CP-724,714 was conducted using human hepatocytes, in which twelve oxidative metabolites and one hydrolyzed metabolite were formed. Among the three mono-oxidative metabolites, the formation of two was inhibited by adding 1-aminobenzotriazole, a pan-CYP inhibitor. In contrast, the remaining one was not affected by this inhibitor but partially inhibited by hydralazine, indicating that aldehyde oxidase (AO) was involved in metabolizing CP-724,714, which contains a quinazoline substructure, a heterocyclic aromatic quinazoline ring, known to be preferably metabolized by AO. One of the oxidative metabolites of CP-724,714 observed in human hepatocytes was also generated in recombinant human AO. Although CP-724,714 is metabolized by both CYPs and AO in human hepatocytes, the contribution level of AO could not be evaluated using its specific inhibitors because of low AO activity in in vitro human materials. Here, we present a metabolic pathway for CP-724,714 in human hepatocytes and the involvement of AO in CP-724,714 metabolism. We showed here a plausible workflow for predicting AO contribution to the metabolism of CP-724,714 based on DMPK screening data. SIGNIFICANCE STATEMENT: 2-methoxy-N-[3-[4-[3-methyl-4-[(6-methyl-3-pyridinyl)oxy]anilino]-6-quinazolinyl]prop-2-enyl]acetamide (CP-724,714) was identified as a substrate of aldehyde oxidase (AO) rather than xanthine oxidase. Since CP-724,714 is also metabolized by cytochrome P450s (CYPs), the contribution levels of AO and CYPs in the metabolism of CP-724,714 were estimated simultaneously based on in vitro drug metabolism screening data.

Optimizing machine-learning models for mutagenicity prediction through better feature selection.

Assessing a compound's mutagenicity using machine learning is an important activity in the drug discovery and development process. Traditional methods of mutagenicity detection, such as Ames test, are expensive and time and labor intensive. In this context, in silico methods that predict a compound mutagenicity with high accuracy are important. Recently, machine-learning (ML) models are increasingly being proposed to improve the accuracy of mutagenicity prediction. While these models are used in practice, there is further scope to improve the accuracy of these models. We hypothesize that choosing the right features to train the model can further lead to better accuracy. We systematically consider and evaluate a combination of novel structural and molecular features which have the maximal impact on the accuracy of models. We rigorously evaluate these features against multiple classification models (from classical ML models to deep neural network models). The performance of the models was assessed using 5- and 10-fold cross-validation and we show that our approach using the molecule structure, molecular properties, and structural alerts as feature sets successfully outperform the state-of-the-art methods for mutagenicity prediction for the Hansen et al. benchmark dataset with an area under the receiver operating characteristic curve of 0.93. More importantly, our framework shows how combining features could benefit model accuracy improvements.

Osmotic pressure effects identify dehydration upon cytochrome c-cytochrome c oxidase complex formation contributing to a specific electron pathway formation.

In the electron transfer (ET) reaction from cytochrome c (Cyt c) to cytochrome c oxidase (CcO), we determined the number and sites of the hydration water released from the protein surface upon the formation of the ET complex by evaluating the osmotic pressure dependence of kinetics for the ET from Cyt c to CcO. We identified that ∼20 water molecules were dehydrated in complex formation under turnover conditions, and systematic Cyt c mutations in the interaction site for CcO revealed that nearly half of the released hydration water during the complexation were located around Ile81, one of the hydrophobic amino acid residues near the exposed heme periphery of Cyt c. Such a dehydration dominantly compensates for the entropy decrease due to the association of Cyt c with CcO, resulting in the entropy-driven ET reaction. The energetic analysis of the interprotein interactions in the ET complex predicted by the docking simulation suggested the formation of hydrophobic interaction sites surrounding the exposed heme periphery of Cyt c in the Cyt c-CcO interface (a 'molecular breakwater'). Such sites would contribute to the formation of the hydrophobic ET pathway from Cyt c to CcO by blocking water access from the bulk water phase.

Energetic Mechanism of Cytochrome c-Cytochrome c Oxidase Electron Transfer Complex Formation under Turnover Conditions Revealed by Mutational Effects and Docking Simulation.

Based on the mutational effects on the steady-state kinetics of the electron transfer reaction and our NMR analysis of the interaction site (Sakamoto, K., Kamiya, M., Imai, M., Shinzawa-Itoh, K., Uchida, T., Kawano, K., Yoshikawa, S., and Ishimori, K. (2011) Proc. Natl. Acad. Sci. U.S.A. 108, 12271-12276), we determined the structure of the electron transfer complex between cytochrome c (Cyt c) and cytochrome c oxidase (CcO) under turnover conditions and energetically characterized the interactions essential for complex formation. The complex structures predicted by the protein docking simulation were computationally selected and validated by the experimental kinetic data for mutant Cyt c in the electron transfer reaction to CcO. The interaction analysis using the selected Cyt c-CcO complex structure revealed the electrostatic and hydrophobic contributions of each amino acid residue to the free energy required for complex formation. Several charged residues showed large unfavorable (desolvation) electrostatic interactions that were almost cancelled out by large favorable (Columbic) electrostatic interactions but resulted in the destabilization of the complex. The residual destabilizing free energy is compensated by the van der Waals interactions mediated by hydrophobic amino acid residues to give the stabilized complex. Thus, hydrophobic interactions are the primary factors that promote complex formation between Cyt c and CcO under turnover conditions, whereas the change in the electrostatic destabilization free energy provides the variance of the binding free energy in the mutants. The distribution of favorable and unfavorable electrostatic interactions in the interaction site determines the orientation of the binding of Cyt c on CcO.

Novel pH-dependent regulation of human cytosolic sialidase 2 (NEU2) activities by siastatin B and structural prediction of NEU2/siastatin B complex.

Human cytosolic sialidase (Neuraminidase 2, NEU2) catalyzes the removal of terminal sialic acid residues from glycoconjugates. The effect of siastatin B, known as a sialidase inhibitor, has not been evaluated toward human NEU2 yet. We studied the regulation of NEU2 activity by siastatin B in vitro and predicted the interaction in silico. Inhibitory and stabilizing effects of siastatin B were analyzed in comparison with DANA (2-deoxy-2,3-dehydro-N-acetylneuraminic acid) toward 4-umbelliferyl N-acetylneuraminic acid (4-MU-NANA)- and α2,3-sialyllactose-degrading activities of recombinant NEU2 produced by E. coli GST-fusion gene expression. Siastatin B exhibited to have higher competitive inhibitory activity toward NEU2 than DANA at pH 4.0. We also revealed the stabilizing effect of siastatin B toward NEU2 activity at acidic pH. Docking model was constructed on the basis of the crystal structure of NEU2/DANA complex (PDB code: 1VCU). Molecular docking predicted that electrostatic neutralization of E111 and E218 residues of the active pocket should not prevent siastatin B from binding at pH 4.0. The imino group (1NH) of siastatin B can also interact with D46, neutralized at pH 4.0. Siastatin B was suggested to have higher affinity to the active pocket of NEU2 than DANA, although it has no C7-9 fragment corresponding to that of DANA. We demonstrated here the pH-dependent affinity of siastatin B toward NEU2 to exhibit potent inhibitory and stabilizing activities. Molecular interaction between siastatin B and NEU2 will be utilized to develop specific inhibitors and stabilizers (chemical chaperones) not only for NEU2 but also the other human sialidases, including NEU1, NEU3 and NEU4, based on homology modeling.

A QSAR study on the inhibition mechanism of matrix metalloproteinase-12 by arylsulfone analogs based on molecular orbital calculations.

A binding mechanism between human matrix metalloproteinase-12 (MMP-12) and eight arylsulfone analogs having two types of carboxylic and hydroxamic acids as the most representative zinc binding group is investigated using a quantitative structure-activity relationship (QSAR) analysis based on a linear expression by representative energy terms (LERE). The LERE-QSAR analysis quantitatively reveals that the variation in the observed (experimental) inhibitory potency among the arylsulfone analogs is decisively governed by those in the intrinsic binding and dispersion interaction energies. The results show that the LERE-QSAR analysis not only can excellently reproduce the observed overall free-energy change but also can determine the contributions of representative free-energy changes. An inter-fragment interaction energy difference (IFIED) analysis based on the fragment molecular orbital (FMO) method (FMO-IFIED) leads to the identification of key residues governing the variation in the inhibitory potency as well as to the understanding of the difference between the interactions of the carboxylic and hydroxamic acid zinc binding groups. The current results that have led to the optimization of the inhibitory potency of arylsulfone analogs toward MMP-12 to be used in the treatment of chronic obstructive pulmonary disease may be useful for the development of a new potent MMP-12 inhibitor.

Combined QM/MM (ONIOM) and QSAR approach to the study of complex formation of matrix metalloproteinase­9 with a series of biphenylsulfonamides−LERE-QSAR analysis (V).

We previously proposed a novel QSAR (quantitative structure-activity relationship) procedure called LERE (linear expression by representative energy terms)-QSAR involving molecular calculations such as an ab initio fragment molecular orbital ones. In the present work, we applied LERE-QSAR to complex formation of matrix metalloproteinase-9 (MMP-9) with a series of substituted biphenylsulfonamides. The results shows that the overall free-energy change accompanying complex formation is due to predominantly the contribution from the electrostatic interaction with the zinc atom in the active site of MMP-9. Carbonic anhydrase (CA) belongs to the zinc-containing protease family. In contrast to the current case of MMP-9, the overall free-energy change during complex formation of CA with a series of benzenesulfonamides is due to the contributions from the solvation and dissociation free-energy changes, as previously reported. Comparison of the two sets of results indicates quantitative differences in the relative contributions of free-energy components to the overall free-energy change between the two data sets, corresponding with those in the respective classical QSAR equations. The LERE-QSAR procedure was demonstrated to quantitatively reveal differences in the binding mechanisms between the two cases involving similar but different zinc-containing proteins at the electronic and atomic levels.

Reassessment of Hammett σ as an effective parameter representing intermolecular interaction energy-links between traditional and modern QSAR approaches.

The Hammett σ constant has for a long time been known to be one of most important linear free-energy related parameters that correlate with biological activity. It is a conventionally used electronic parameter in studies of enzymatic quantitative structure-activity relationships (QSAR). However, it is not necessarily obvious why σ represents variations in the free-energy change associated with the complex formation between a congeneric series of ligands with their target protein. So far, several powerful molecular calculations, such as the ab initio fragment molecular orbital (FMO) one, that are directly applicable to ligand-protein complexes have emerged. In this study, we comprehensively reevaluate experimentally derived parameter σ confirming it represents intermolecular interaction energy terms, by applying molecular orbital (MO) calculations to a simple ligand-protein complex model. The current results provide a rational and quantitative basis for bridging the gap between the traditional QSAR approach and 'the modern QSAR one', which involves the molecular calculations to evaluate the overall free-energy change for complex formation.

Correlation analyses on binding affinity of sialic acid analogues and anti-influenza drugs with human neuraminidase using ab initio MO calculations on their complex structures--LERE-QSAR analysis (IV).

We carried out full ab initio fragment molecular orbital (FMO) calculations for complexes comprising human neuraminidase-2 (hNEU2) and sialic acid analogues including anti-influenza drugs zanamivir (Relenza) and oseltamivir (Tamiflu) in order to examine the variation in the observed inhibitory activity toward hNEU2 at the atomic and electronic levels. We recently proposed the LERE (linear expression by representative energy terms)-QSAR (quantitative structure-activity relationship) procedure. LERE-QSAR analysis quantitatively revealed that the complex formation is driven by hydrogen-bonding and electrostatic interaction of hNEU2 with sialic acid analogues. The most potent inhibitory activity, that of zanamivir, is attributable to the strong electrostatic interaction of a positively charged guanidino group in zanamivir with negatively charged amino acid residues in hNEU2. After we confirmed that the variation in the observed inhibitory activity among sialic acid analogues is excellently reproducible with the LERE-QSAR equation, we examined the reason for the remarkable difference between the inhibitory potencies of oseltamivir as to hNEU2 and influenza A virus neuraminidase-1 (N1-NA). Several amino acid residues in close contact with a positively charged amino group in oseltamivir are different between hNEU2 and N1-NA. FMO-IFIE (interfragment interaction energy) analysis showed that the difference in amino acid residues causes a remarkably large difference between the overall interaction energies of oseltamivir with hNEU2 and N1-NA. The current results will be useful for the development of new anti-influenza drugs with high selectivity and without the risk of adverse side effects.

Density functional theory study of hydrogen atom abstraction from a series of para-substituted phenols: why is the Hammett σ(p)+ constant able to represent radical reaction rates?

The rate of hydrogen atom abstraction from phenolic compounds by a radical is known to be often linear with the Hammett substitution constant σ(+), defined using the S(N)1 solvolysis rates of substituted cumyl chlorides. Nevertheless, a physicochemical reason for the above "empirical fact" has not been fully revealed. The transition states of complexes between the 2,2-diphenyl-1-picrylhydrazyl radical (dpph·) and a series of para-substituted phenols were determined by DFT (Density Functional Theory) calculations, and then the activation energy as well as the homolytic bond dissociation energy of the O-H bond and charge distribution in the transition state were calculated. The heterolytic bond dissociation energy of the C-Cl bond and charge distribution in the corresponding para-substituted cumyl chlorides were calculated in parallel. Excellent correlations among σ(+), charge distribution, and activation and bond dissociation energies revealed quantitatively that there is a strong similarity between the two reactions, showing that the electron-deficiency of the π-electron system conjugated with a substituent plays a crucial role in determining rates of the two reactions. The results provide a new insight into and physicochemical understanding of σ(+) in the hydrogen abstraction from substituted phenols by a radical.

Correlation analyses on binding affinity of sialic acid analogues with influenza virus neuraminidase-1 using ab initio MO calculations on their complex structures.

We carried out full ab initio molecular orbital calculations on complexes between neuraminidase-1 (N1-NA) in the influenza A virus and a series of eight sialic acid analogues including oseltamivir (Tamiflu) in order to quantitatively examine the binding mechanism and variation in the inhibitory potency at the atomic and electronic levels. FMO-MP2-IFIE (interfragment interaction energy at the MP2 level of ab initio fragment molecular orbital calculations) analyses quantitatively revealed (1) that the complex formation is driven by strong electrostatic interactions of charged functional groups in the analogues with ionized amino acid residues and water molecules in the active site of N1-NA, and (2) that the variation in the inhibitory potency among the eight analogues is determined by the dispersion and/or hydrophobic interaction energies of the 3-pentyl ether and charged amino moieties in oseltamivir with certain residues and water molecules in the active site of N1-NA. The current results will be useful for the development of new antiinfluenza drugs with high potency against various subtypes of wild-type and drug-resistant NAs.

Correlation analyses on binding affinity of substituted benzenesulfonamides with carbonic anhydrase using ab initio MO calculations on their complex structures.

Quantitative structure-activity relationship analyses on the free energy change during complex formation between substituted benzenesulfonamides (BSAs) and bovine carbonic anhydrase II (bCA II) were performed using generilized Born/surface area (GB/SA) and ab initio fragment molecular orbital (FMO) calculations for the whole complex structures. The result shows that the overall free energy change is governed by the contribution from solvation and dissociation free energy changes accompanying by complex formation. The FMO-IFIE (interfragment interaction energy) analysis quantitatively revealed that the intrinsic interaction energy of bCA II with BSAs is mostly from interactions with amino acid residues in the active site of bCA II. The "Zn block" (Zn(2+) and three histidine residues coordinated to Zn(2+)) in the active site shows the lowest interaction energy and the greatest variance of interaction energy with BSAs through their coordination interaction. The proposed procedure was demonstrated to provide a quantitative basis for understanding a ligand-protein interaction at electronic and atomic levels.

Expression and molecular dynamics studies on effect of amino acid substitutions at Arg344 in human cathepsin A on the protein local conformation.

Human lysosomal protective protein/cathepsin A (CathA) is a multifunctional protein that exhibits not only protective functions as to lysosomal glycosidases, i.e., neuraminidase 1 (NEU1) and beta-galactosidase (GLB), but also its own serine carboxypeptidase activity, and exhibits conserved structural similarity to yeast and wheat homologs (CPY and CPW). Our previous study revealed that the R344 (Arg344) residue in CathA could contribute to the binding and recognition of the serine peptidase inhibitor chymostatin. We examined here the effects of substitution of R344 with other amino acids, including A, D, E, G, I, K, M, N, P, Q, S, and V, denoted as R344X, including the wild-type CathA, on expression of CathA activity and intracellular processing. Among the mutant gene products, the 54-kDa precursor/zymogen with the R344D substitution was not processed to the 32/20-kDa mature form with CathA activity in a fibroblastic cell line derived from a galactosialidosis patient. Molecular dynamics (MD) simulations on the total twelve R344X mutants and the wild-type revealed that only R344D takes on a significantly different conformation of S293-D295 in the excision peptide (M285-R298) compared to the other R344X mutants; the side chains of S293 and D295 in R344D are exposed on the molecular surface, although those in the other twelve R344X mutants are buried inside the protein. The results of the current work strongly suggest that the distinct conformational change of the S293-D295 region in the R344D protein causes the processing defect of the 54-kDa precursor of the R344D mutant gene product in cultured cells.