Contributions Of Molecular Fragments Research Articles

HDAC1 PREDICTOR: a simple and transparent application for virtual screening of histone deacetylase 1 inhibitors

ABSTRACT Histone deacetylases play an important role in regulating gene expression by modifying histones and changing chromatin conformation. HDAC dysregulation is involved in many diseases, such as cancer, autoimmune and neurodegenerative diseases. Histone deacetylase 1 (HDAC1) inhibitors represent an important class of drugs. Quantitative Structure-Activity Relationship (QSAR) classification models were developed using 2D RDKit molecular descriptors; ECPF4 (Extended Connectivity Fingerprint) circular fingerprints; and the Random Forest, Gradient Boosting, and Support Vector Machine methods. The developed models were integrated into the HDAC1 PREDICTOR application, which is freely available at the link https://ovttiras-hdac1-inhibitors-hdac1-predictor-app-z3mrbr.streamlitapp.com. The HDAC1 PREDICTOR web application allows one to reveal the compounds for which the predicted activity to inhibit HDAC1 is higher than that of the reference Vorinostat compound (IC50 = 11.08 nM). The algorithm implemented in HDAC1 PREDICTOR for determining the contributions of molecular fragments to the inhibitory activity can be used to find the molecule segments that increase or decrease the activity, enabling the researcher to conduct a rational molecular design of new highly active HDAC1 inhibitors. The developed QSAR models and the code for their construction in the Python programming language are freely available on the GitHub platform at https://github.com/ovttiras/HDAC1-inhibitors.

Molecular Conditional Generation and Property Analysis of Non-Fullerene Acceptors with Deep Learning.

The proposition of non-fullerene acceptors (NFAs) in organic solar cells has made great progress in the raise of power conversion efficiency, and it also broadens the ways for searching and designing new acceptor molecules. In this work, the design of novel NFAs with required properties is performed with the conditional generative model constructed from a convolutional neural network (CNN). The temporal CNN is firstly trained to be a good string-based molecular conditional generative model to directly generate the desired molecules. The reliability of generated molecular properties is then demonstrated by a graph-based prediction model and evaluated with quantum chemical calculations. Specifically, the global attention mechanism is incorporated in the prediction model to pool the extracted information of molecular structures and provide interpretability. By combining the generative and prediction models, thousands of NFAs with required frontier molecular orbital energies are generated. The generated new molecules essentially explore the chemical space and enrich the database of transformation rules for molecular design. The conditional generation model can also be trained to generate the molecules from molecular fragments, and the contribution of molecular fragments to the properties is subsequently predicted by the prediction model.

The Influence of Structural Patterns on Acute Aquatic Toxicity of Organic Compounds.

Investigation of the influence of molecular structure of different organic compounds on acute toxicity towards Fathead minnow, Daphnia magna, and Tetrahymena pyriformis has been carried out using 2D simplex representation of molecular structure and two modelling methods: Random Forest (RF) and Gradient Boosting Machine (GBM). Suitable QSAR (Quantitative Structure - Activity Relationships) models were obtained. The study was focused on QSAR models interpretation. The aim of the study was to develop a set of structural fragments that simultaneously consistently increase toxicity toward Fathead minnow, Daphnia magna, Tetrahymena pyriformis. The interpretation allowed to gain more details about known toxicophores and to propose new fragments. The results obtained made it possible to rank the contributions of molecular fragments to various types of toxicity to aquatic organisms. This information can be used for molecular optimization of chemicals. According to the results of structural interpretation, the most significant common mechanisms of the toxic effect of organic compounds on Fathead minnow, Daphnia magna and Tetrahymena pyriformis are reactions of nucleophilic substitution and inhibition of oxidative phosphorylation in mitochondria. In addition acetylcholinesterase and voltage-gated ion channel of Fathead minnow and Daphnia magna are important targets for toxicants. The on-line version of the OCHEM expert system (https://ochem.eu) were used for a comparative QSAR investigation. The proposed QSAR models comply with the OECD principles and can be used to reliably predict acute toxicity of organic compounds towards Fathead minnow, Daphnia magna and Tetrahymena pyriformis with allowance for applicability domain estimation.

In silico modelling of thiazolidine derivatives with antioxidant potency: Models quantify the degree of contribution of molecular fragments towards the free radical scavenging ability

Design and development of antioxidant supplements constitute an essential aspect of research in order to derive molecules that would help to combat the free radical invasion to the human body and curb oxidative stress related diseases. The present work deals with the development of in silico models for a series of thiazolidine derivatives having antioxidant potential. The objective of the work is to obtain models that would help to design new thazolidine derivatives based on substituent modification and thereby predict their activity profile. The QSAR model thus developed helps in quantification of the extent of contribution of the various molecular fragments towards the activity of the molecules, while the 3D pharmacophore model provides a brief idea of the essential molecular features that help the molecules to interact with the neighbouring free radicals. Both the models have been extensively validated which ensures their predictive ability as well the potential to search molecular databases for selection of thiazolidine derivatives with potent antioxidant activity. The models can thus be utilised effectively for database searching with the aim to isolate active antioxidants belonging to the thiazolidine group.

Transfer of non-ionic surfactants across the water-oil interface: A molecular dynamics study

Compounds able to adsorb at the interface of two immiscible liquids are of high importance for numerous chemical, physical and biological processes. Deeper understanding of the interfacial phenomena in such systems can contribute significantly to the rational practical application of small amphiphiles in electrochemistry, extraction, stabilization of emulsions, and drug design. Particularly interesting are the oil-water formulations, where the aqueous and the hydrophobic phases tend to express different molecular structure and characteristics under identical conditions. Surfactant behaviour in such environments is known to differ distinctly from the one observed in bulk water or oil or at the gas-liquid interface. It has been demonstrated that the free energy of adsorption and transfer of amphiphiles across water-oil interfaces can be decomposed into specific contributions of molecular fragments. The models developed so far do not provide information about the specifics of the functional groups contributions. To elaborate further on this topic, classical molecular dynamics simulations, combined with umbrella sampling calculations and weighted histograms method analysis are applied to reconstruct the free energy profile for several water-oil-amphiphile models along a relocation coordinate normal to the interface. Normal pentane, hexane, and heptane are chosen as models of the hydrophobic liquids and three short-chained normal alcohols⿿as low-molecular-weight amphiphiles. Gibbs energies of transfer and adsorption, as well as the average contributions per unit of elongation of the alkyl chain, are estimated and compared to experimental data and empirical results. The experimental trends of all quantities are reproduced correctly. Some quantitative differences are discussed. A detailed analysis of the free energy change vs. position of alcohol molecules shows that the transfer process can be decomposed into several stages. Such more precise stratification of the interfacial region is employed to determine and rationalize the free energy contributions of the separate alkanol functional groups.

Quantification of contributions of molecular fragments for eye irritation of organic chemicals using QSAR study

The eye irritation potential of chemicals has largely been evaluated using the Draize rabbit-eye test for a very long time. The Draize eye-irritation data on 38 compounds established by the European Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) has been used in the present quantitative structure–activity relationship (QSAR) analysis in order to predict molar-adjusted eye scores (MES) and determine possible structural requisites and attributes that are primarily responsible for the eye irritation caused by the studied solutes. The developed model was rigorously validated internally as well as externally by applying principles of the Organization for Economic Cooperation and Development (OECD). The test for applicability domain was also carried out in order to check the reliability of the predictions. Important fragments contributing to higher MES values of the solutes were identified through critical analysis and interpretation of the developed model. Considering all the identified structural attributes, one can choose or design safe solutes with low eye irritant properties. The presented approach suggests a model for use in the context of virtual screening of relevant solute libraries. The developed QSAR model can be used to predict existing as well as future chemicals falling within the applicability domain of the model in order to reduce the use of animals.

Universal Approach for Structural Interpretation of QSAR/QSPR Models.

In this paper we offer a novel approach for the structural interpretation of QSAR models. The major advantage of our developed methodology is its universality, i.e., it can be applied to any QSAR/QSPR model irrespective of chemical descriptors and machine learning methods applied. This universality was achieved by using only the information obtained from substructures of the compounds of interest to interpret model outcomes. Reliability of the offered approach was confirmed by the results of three case studies, including end-points of different types (continuous and binary classification) and nature (solubility, mutagenicity, and inhibition of Transglutaminase 2), various fragment and whole-molecule descriptors (Simplex and Dragon), and multiple modeling techniques (partial least squares, random forest, and support vector machines). We compared the global contributions of molecular fragments obtained using our methodology with known SAR rules derived experimentally. In all cases high concordance between our interpretation and results published by others was observed. Although the proposed interpretation approach could be easily extended to any type of descriptors, we would recommend using Simplex descriptors to achieve a larger variety of investigated molecular fragments. The developed approach is a good tool for interpretation of such "black box" models like random forest, neural networks, etc. Analysis of fragment global contributions and their deviation across a dataset could be useful for the identification of key fragments and structural alerts. This information could be helpful to maximize the positive influence of structural surroundings on the given fragment and to decrease the negative effects.

Development and validation of regression-based QSAR models for quantification of contributions of molecular fragments to skin sensitization potency of diverse organic chemicals

In our present work, we have developed regression-based QSAR models for skin sensitization potential of 51 diverse organic chemicals. The objective behind the present work is to determine the influence of different molecular features on the skin sensitizing potential of chemicals. Among several models developed, the two best ones are discussed to unveil specific information regarding the contribution of different structural and physicochemical features towards the property of skin sensitization. The QSAR models suggested that aromatic compounds are more skin sensitizing than aliphatic ones, but in the case of carbonyl compounds, aliphatic ones are more skin sensitizing than aromatic ones. Other descriptors such as LUMO and <2-Atype_H-47> signify the importance of the electrophilic and hydrophilic character respectively of the molecules for showing skin sensitizing property. Another two descriptors, <Dipole-mag-2.72> and 3χC also exert significant contributions towards the skin sensitization potential of the chemicals. Further, it is observed that the nitrogen atoms (nN), triple bonds (nTB) and also the fragment Al-C(=X)-Al (Atype_C38) are responsible for skin sensitizing property. All the above information provides additional support for further research involving identification of the skin sensitization potential of new chemicals.

Insight into crucial inhibitor–enzyme interaction of arylamides as novel direct inhibitors of the enoyl ACP reductase (InhA) from Mycobacterium tuberculosis: computer-aided molecular design

The enoyl ACP reductase enzyme (InhA) involved in the type II fatty acid biosynthesis pathway of Mycobacterium tuberculosis is an attractive target enzyme for antitubercular drug development. Arylamide derivatives are a novel class of InhA inhibitors used to overcome the drug-resistance problem of isoniazid, the frontline drug for tuberculosis treatment. Their remarkable property of inhibiting the InhA enzyme directly without requiring any coenzyme, makes them especially appropriate for the design of new antibacterials. In order to find a sound binding conformation for the different arylamide analogs, molecular docking experiments were performed with subsequent QSAR investigations. The X-ray conformation of one arylamide within its cocrystallized complex with InhA was used as a starting conformation for the docking experiments. The results thus obtained are perfectly consistent (rmsd = 0.73 A) with the results from X-ray analysis. A thorough investigation of the arylamide binding modes with InhA provided ample information about structural requirements for appropriate inhibitor–enzyme interactions. Three different QSAR models were established using two three-dimensional (CoMFA and CoMSIA) and one two-dimensional (HQSAR) techniques. With statistically ensured models, the QSAR results obtained had high correlation coefficients between molecular structure properties of 28 arylamide derivatives and their biological activity. Molecular fragment contributions to the biological activity of arylamides could be obtained from the HQSAR model. Finally, a graphic interpretation designed in different contour maps provided coincident information about the ligand–receptor interaction thus offering guidelines for syntheses of novel analogs with enhanced biological activity.

UV Resonance Raman Elucidation of the Terminal and Internal Peptide Bond Conformations of Crystalline and Solution Oligoglycines

Spectroscopic investigations of macromolecules generally attempt to interpret the measured spectra in terms of the summed contributions of the different molecular fragments. This is the basis of the local mode approximation in vibrational spectroscopy. In the case of resonance Raman spectroscopy independent contributions of molecular fragments require both a local mode-like behavior and the uncoupled electronic transitions. Here we show that the deep UV resonance Raman spectra of aqueous solution phase oligoglycines show independent peptide bond molecular fragment contributions indicating that peptide bonds electronic transitions and vibrational modes are uncoupled. We utilize this result to separately determine the conformational distributions of the internal and penultimate peptide bonds of oligoglycines. Our data indicate that in aqueous solution the oligoglycine terminal residues populate conformations similar to those found in crystals (3(1)-helices and β-strands), but with a broader distribution, while the internal peptide bond conformations are centered around the 3(1)-helix Ramachandran angles.

DESIGN OF HYBRID INHIBITORS TO HIV-1 PROTEASE

A series of HIV-1 protease (PR) inhibitors are designed to increase the binding affinity with PR subsites based on the quantum analysis of the contributions of molecular fragments in six FDA-approved PR drugs to the total binding interaction. The binding free energies were estimated by modified linear interaction energy approach [Zoete H, Michielin O, Karplus M, J Comput Aided Mol Des17:861, 2003], in which the binding free energy is written as a linear combination of the electrostatic interaction energy between PR and the ligand, Eelec, the van der Waals interaction energy between PR and the ligand, E vdW , and the difference of the solvation free energies of the complex, the receptor and the isolated ligand, ΔG solv . The parameters of these energy terms were fitted for a training set of 14 HIV-1 protease–inhibitor complexes of known 3D structure with a correlation coefficient of 0.91 and an unsigned mean error of 0.83 kcal/mol.

Calculation of densities of organic compounds from contributions of molecular fragments

A method for calculating the densities of organic compounds from the contributions of molecular fragments was suggested. A correlation between the densities of solid and liquid substances at 20°C was examined.

Estimation of fundamental frequencies of perhalogenated ethylenes in terms of molecular fragment contributions

A model, in which a molecule is subdivided into a number of subunits, is used to calculate approximately fundamental frequencies of perhalogenated ethylenes in terms of contributions of subunits and clusters of subunits. Different levels of approximation are defined by a subunit additivity scheme, a linear subunit pair and subunit triple scheme as well as by a nonlinear coupled subunit pair scheme. Algebraic dependencies of the approximate formulas for distinct ethylene derivatives are used as criteria for testing the different schemes. The method is applied to the fundamental frequencies of normal vibrations which, with respect to symmetry, correlate uniquely in the series of substituted ethylenes considered, otherwise the method is applied to corresponding sums of frequencies. For the fundamental frequencies of the 27 ethylene derivatives C2FnClmBr4−n−m, n+m≤4, completely known from a normal coordinate analysis, the main results are: (a) The out-of-plane frequencies correlate uniquely in these molecules, three of the in-plane frequencies and two sums formed from the remaining ones correlate as well. (b) The simple additivity scheme with three parameters for each set of correlating frequencies yields a sufficiently exact fit of the out-of-plane frequencies; their mean absolute deviation is about 5 cm−1. (c) The linear subunit pair approximation with twelve parameters for each set is sufficiently exact for all the correlating frequencies and sums of frequencies, respectively; their mean absolute deviation is about 1 cm−1.

Modeling lipophilicity from the distribution of electrostatic potential on a molecular surface.

Molecular lipophilicity L is represented as a function of four surface electrostatic potential descriptors: L = f(B+F, B-F, B+R, B-R). Each B descriptor is computed from the products of elements of molecular surface area, delta(si), and the molecular electrostatic potential (MEP), V(ri), at the center of an area element: B = sigma(i) delta(si) V(r(i)). Octanol-water partition coefficients (P(ow)) are correlated with these four surface-MEP descriptors: log P(ow) = c0 + c1B+F + c2B-F + c3B+R + c4B-R. Good correlations are obtained for homologous series of aliphatic alcohols, amines and acids, as well as for a set of aromatic compounds with various functional groups. Within this approach, we find that the molecular fragment contributions of surface-MEP descriptions to log P are approximately additive. We have computed the values for the following fragments: -CH2-, -CH3, _COOH, -OH and -NH2. These contributions can be used to estimate the molecular lipophilicity and partition coefficients of new compounds, without additional quantum-mechanical calculations. The proposed approach provides a reasonably accurate tool that can be useful in quantitative structure-activity relations for computer-aided rational drug design. More importantly, the correlation model is conceptually simpler than previous work in the literature and can be improved systematically.

On the Usefulness and Reliability of Existing QSBRs for Risk Assessment and Priority Setting

Abstract The results of a survey of quantitative structure-biodegradability relationships (QSBRs) are presented. The survey was made to evaluate the use of QSBRs for risk assessment and priority setting. It appears that few models can actually be used for legislative purposes. The major reason for this is that many models are either based on biodegradation end-points that are inconvenient for legislative purposes, or are not reproducible, or are based on too few data. It is concluded that single descriptor models cannot accurately predict the biodegradability of a broad range of chemicals. Most of these models therefore apply to narrow subclasses of chemicals only. The development of multiple descriptor models is still rather modest. More generally applicable models are based on molecular fragment contributions to biodegradability. However, for most of these models the chemical domain is uncertain. Despite the fact that none of the models in the survey meet the criteria set for judging a model to be useful for legislative purposes, three models are given the benefit of the doubt and are qualified as “best available”. Finally, some new validation results on the models selected are presented and recommendations for model development are given.