Molecular Similarity Studies Research Articles

Computer-Assisted Drug Discovery of Potential African Anti-SARS-CoV-2 Natural Products Targeting the Helicase Protein

Objectives: In our continuous efforts to combat COVID-19, our objective was to conduct a comprehensive computer-aided drug design study utilizing 4924 African natural metabolites sourced from diverse databases across various African regions from 1962 to 2019. The primary goal was to target the SARS-CoV-2 helicase, a crucial enzyme in viral replication. Methods: We employed structural fingerprint and molecular similarity studies with VXG, the co-crystallized ligand, as a reference. Subsequently, docking and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies were conducted. Results: The structural fingerprint analysis identified 200 structurally similar compounds, then the molecular similarity studies selected 40 compounds. Among them, 15 metabolites with low free energies, favorable binding modes, and promising ADMET properties were identified. Four compounds were excluded according to the toxicity studies. Compound 1552, 1-(( S)-2,3-dihydro-2-(( R)-1-hydroxypropan-2-yl)benzofuran-5-yl)ethenone, exhibited the most favorable docking results. Molecular dynamics simulations conclusively demonstrated its stable binding to the SARS-CoV-2 helicase, characterized by low energy and optimal dynamics. Conclusion: The findings suggest promising avenues for potential COVID-19 cures, encouraging further exploration through in vitro and in vivo studies of the identified compounds, particularly compound 1552.

Self-Organizing Molecular Field Analysis on Pyridazine Analogues as Protein Tyrosine Phosphatase 1B (PTP 1B) Inhibitors

A 3D-QSAR study has been performed using Self-organizing molecular field analysis (SOMFA) on a novel class of pyridazine analogues as non-competitive and reversible inhibitors of PTP 1B. SOMFA is a novel 3D-QSAR methodology, similar to both comparative molecular field analysis (CoMFA) and molecular similarity studies. SOMFA studies have been performed to correlate chemical structures of pyridazine analogues with their observed PTP 1B inhibitory activity. The master grid obtained for the various SOMFA models indicates electrostatic and shape potential contributions. These can be mapped back onto the structural features relating to trends in activities of the molecules. On the basis of the spatial arrangement of the various shape and electrostatic potential contributions, new inhibitors of PTP 1B can be designed with improved spectrum of activity for the management of type 2 diabetes. Keywords: Insulin, NIDDM, PTP 1B, Pyridazine, 3D-QSAR, SOMFA

Statistical spectroscopy as a tool for the study of molecular similarity

This paper aims at an application of the statistical theory of spectra to the classification of chemical compounds. It has been shown that the moments of the intensity distributions may be used as molecular descriptors. The new descriptors have been tested using spectra of nitriles and amides. The dependence of the accuracy of the classification on the number of moments (up to the twelveth order) is discussed using model spectra.

Ab Initio-Quality Electrostatic Potentials for Proteins: An Application of the ADMA Approach

The electrostatic potential around a molecule is often used to describe reactions, binding, and catalysis mechanisms or to serve as a descriptor in structure−activity relationships and molecular similarity studies. Often, very accurate descriptions of this property are needed that traditionally can be obtained, at least for small molecules, by quantum chemical calculations. The aim of this paper is to extend ab initio-quality quantum chemical accuracy to larger molecules such as proteins. The additive fuzzy density fragmentation (AFDF) principle and the adjustable density matrix assembler (ADMA) method are used to divide large molecules into fuzzy fragments, for which quantum chemical calculations can be done directly using smaller, “custom-made” parent molecules including all the local interactions within a preset distance limit. In the next step, the obtained density matrices of electron density fragments are combined to approximate the global density matrix and the electron density of the whole molecules. These ADMA electron densities are then used to calculate ab inito-quality electrostatic potentials of the large molecules. The accuracy of the method is analyzed in detail by two test cases of a penta- and a hexapetide, and the efficiency of the technique is demonstrated by the calculation of the electrostatic potential of the protein crambin.

Hydrophobic similarity between molecules: a MST-based hydrophobic similarity index.

A similarity index based on the hydrophilic/hydrophobic properties of molecules is presented. Such an index is defined based on the fractional partition of the free energy of solvation developed within the framework of the self-consistent reaction field MST model, which divides the free energy of solvation or the free energy of transfer into contributions assigned to the surface elements defining the solute/solvent interface. These surface contributions can be integrated to derive atomic or group contributions. The suitability of the index to compute the molecular similarity based on hydrophobic/hydrophilic properties is examined by considering their application in a variety of test systems, including structure-activity relationships, absorption properties, and molecular recognition. The similarity index is expected to be a very powerful tool in molecular similarity studies for compounds of chemical, biochemical, and pharmaceutical interest.

The use of density functional theory-based reactivity descriptors in molecular similarity calculations

Molecular similarity is studied via density functional theory-based similarity indices using a numerical integration method. Complementary to the existing similarity indices, we introduce a reactivity-related similarity index based on the local softness. After a study of some test systems, a series of peptide isosteres is studied in view of their importance in pharmacology. The whole of the present work illustrates the importance of the study of molecular similarity based on both shape and reactivity.

A comparative study of molecular similarity, statistical, and neural methods for predicting toxic modes of action

AbstractQuantitative structure–activity relationship (QSAR) models are routinely used in predicting toxicologic and ecotoxicologic effects of untested chemicals. One critical factor in QSAR‐based risk assessment is the proper assignment of a chemical to a mode of action and associated QSAR. In this paper, we used molecular similarity, neural networks, and discriminant analysis methods to predict acute toxic modes of action for a set of 283 chemicals. The majority of these molecules had been previously determined through toxicodynamic studies in fish to be narcotics (two classes), electrophiles/proelectrophiles, uncouplers of oxidative phosphorylation, acetylcholinesterase inhibitors, and neurotoxicants. Nonempirical parameters, such as topological indices and atom pairs, were used as structural descriptors for the development of similarity‐based, statistical, and neural network models. Rates of correct classification ranged from 65 to 95% for these 283 chemicals.

Synthesis and olfactoric activity of keto-β-santalol and methoxy-β-santalol

In extension of structure-activity relationship investigations on β-santalol, where the shape of the molecular surface was found to be of high importance, the influence of the electrostatic properties of the molecules was investigated. Two derivatives of β-santalol with similar molecular shape but with an oxygen atom instead of carbon atoms were synthesized: keto-β-santalol and methoxy-β-santalol. These two oxygen-containing santalol analogues were synthesized by total syntheses starting from apocamphenilone. A common intermediate for both target molecules, an appropriate tricyclic ketoaldehyde, proved to be inapplicable. Therefore methoxy-β-santalol was prepared by insertion of an ethyldioxolane sidechain into apocamphenilone and completing the synthesis by five additional steps. Keto-β-santalol was prepared on a convergent route by insertion of the already prefabricated sidechain into the starting ketone, followed by one additional step. The presence of the second oxygen atom leads to the complete loss of the odour, which is the evidence that apart from the molecular shape, the electrostatic potential has to be taken into account in molecular similarity studies of this class of compounds.

Characterization of Molecular Structures Using Topological Indices

The characterization of molecular structure using structural invariants has increased greatly over the last ten years. Specifically, topological indices have become more widely used in the quantification of molecular structure for use in quantitative structure-activity relationship studies, chemical documentation, and molecular similarity studies. The basis, calculation, and utility of topological indices has been examined, with an eye to the specific advantages and problems in their use. In addition, variable clustering and principal component analysis are examinee as two potential solutions to the problem of index intercorrelation.

Molecular similarity studies on sandalwood odour molecules: Investigations of the conformational space

Odour differences of some campholene and fencholene derivatives are explained by the analysis of the conformational space and the molecular shape of these molecules. The high flexibility caused by free rotation of some carbon-carbon bonds leads in one case to a large number of energetically possible conformations which have to be taken into account for a study of molecular similarity. In another case, steric restrictions reduce the number of relevant conformations such that no active conformation exists in a thermodynamic equilibrium.

Three-dimensional hydrogen-bond geometry and probability information from a crystal survey.

An extensive crystal survey of the Cambridge Structural Database has been carried out to provide hydrogen-bond data for use in drug-design strategies. Previous crystal surveys have generated 1D frequency distributions of hydrogen-bond distances and angles, which are not sufficient to model the hydrogen bond as a ligand-receptor interaction. For each hydrogen-bonding group of interest to the drug designer, geometric hydrogen-bond criteria have been derived. The 3D distribution of complementary atoms about each hydrogen-bonding group has been ascertained by dividing the space about each group into bins of equal volume and counting the number of observed hydrogen-bonding contacts in each bin. Finally, the propensity of each group to form a hydrogen bond has been calculated. Together, these data can be used to predict the potential site points with which a ligand could interact and therefore could be used in molecular-similarity studies, pharmacophore query searching of databases, or de novo design algorithms.

Discrete characterization of cross-sections of molecular surfaces

The three-dimensional shape of molecules can be described by appropriately chosen, formal molecular surfaces, such as electronic isodensity contours, molecular electrostatic isopotential contours, and similar functions. The characterization of the shape of such molecular surfaces, in particular, their changes along reaction paths, is of importance in several areas of theoretical and applied chemistry, biochemistry, and pharmacology. Molecular shapes are often represented in terms of cross-sections of such molecular surfaces, by appropriately chosen planes. Thus, the characterization of 3D shape is transformed into the 2D problem of characterizing a number of plane curves, the cross-sections. The problem is further simplified if these continuous curves are characterized using the methods of discrete mathematics, which are often more suitable for computer applications. In this work we formalize a number of possible approaches to provide a discrete characterization of molecular surface cross-sections. The method is graph-theoretical in nature and it allows one to provide a concise description of the curves, and their changes with the rearrangements in the nuclear configuration. The vertices of the graph are the inflexion points of the cross-section and the edges are their mutual visibility relations. The procedure is easily programmable as an algorithm, permitting an automatic evaluation of the shape descriptors for a large number of cross-sections and molecules. This possibility is of importance with respect to molecular similarity studies of computer-assisted drug design. Several simple examples are chosen to illustrate the shape descriptors. The basic ideas are illustrated by detailed cross-sections of the electronic density for the molecule of water, as functions of changes in bond angle and bond lengths. Molecular electrostatic maps for molecules of biochemical interest (nucleotide bases) are analyzed with respect to shape similarities. Finally, some of the notions are generalized to deal with cross-sections of surfaces of hard-sphere molecular models (the so-called van der Waals surfaces).