How not to develop a quantitative structure–activity or structure–property relationship (QSAR/QSPR)

Although thousands of quantitative structure–activity and structure–property relationships (QSARs/QSPRs) have been published, as well as numerous papers on the correct procedures for QSAR/QSPR analysis, many analyses are still carried out incorrectly, or in a less than satisfactory manner. We have identified 21 types of error that continue to be perpetrated in the QSAR/QSPR literature, and each of these is discussed, with examples (including some of our own). Where appropriate, we make recommendations for avoiding errors and for improving and enhancing QSAR/QSPR analyses.     

Development of an information-intensive structure–activity relationship model and its application to human respiratory chemical sensitizers

Structure–activity relationship (SAR) models are recognized as powerful tools to predict the toxicologic potential of new or untested chemicals and also provide insight into possible mechanisms of toxicity. Models have been based on physicochemical attributes and structural features of chemicals. We describe herein the development of a new SAR modeling algorithm called cat-SAR that is capable of analyzing and predicting chemical activity from divergent biological response data. The cat-SAR program develops chemical fragment-based SAR models from categorical biological response data (e.g. toxicologically active and inactive compounds). The database selected for model development was a published set of chemicals documented to cause respiratory hypersensitivity in humans. Two models were generated that differed only in that one model included explicate hydrogen containing fragments. The predictive abilities of the models were tested using leave-one-out cross-validation tests. One model had a sensitivity of 0.94 and specificity of 0.87 yielding an overall correct prediction of 91%. The second model had a sensitivity of 0.89, specificity of 0.95 and overall correct prediction of 92%. The demonstrated predictive capabilities of the cat-SAR approach, together with its modeling flexibility and design transparency, suggest the potential for its widespread applicability to toxicity prediction and for deriving mechanistic insight into toxicologic effects.     

Development of a pharmacophore for cruzain using oxadiazoles as virtual molecular probes: quantitative structure–activity relationship studies

Chagas’s is a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi. According to the World Health Organization, 7 million people are infected worldwide leading to 7000 deaths per year. Drugs available, nifurtimox and benzimidazole, are limited due to low efficacy and high toxicity. As a validated target, cruzain represents a major front in drug discovery attempts for Chagas disease. Herein, we describe the development of 2D QSAR (\(r_{{{\text{pred}}}}^{2}\)?=?0.81) and a 3D-QSAR-based pharmacophore (\(r_{{{\text{pred}}}}^{2}\)?=?0.82) from a series of non-covalent cruzain inhibitors represented mostly by oxadiazoles (lead compound, IC₅₀?=?200 nM). Both models allowed us to map key intermolecular interactions in S1′, S2 and S3 cruzain sub-sites (including halogen bond and C?H/π). To probe the predictive capacity of obtained models, inhibitors available in the literature from different classes displaying a range of scaffolds were evaluate achieving mean absolute deviation of 0.33 and 0.51 for 2D and 3D models, respectively. CoMFA revealed an unexplored region where addition of bulky substituents to produce new compounds in the series could be beneficial to improve biological activity.     

Theory of cluster self-organization of crystal-forming systems: geometrical–topological modeling of nanocluster precursors with a hierarchical structure

The current state of the art related with the self-organization of crystal-forming systems, where long-range order spontaneously appears in the arrangement of structural units of any nature (micro- and macromolecules or atomic clusters), is considered. Three partially overlapping stages of self-organization of a system accepted in physical models of ??order?Cdisorder?? kinetic transitions are matched to those used in supramolecular chemistry. An algorithmically constructed model of transition from disordered to hierarchically ordered systems is considered. The geometrical and topological modeling of density fluctuations of n-atomic species (clusters) A_n in a crystal-forming medium is carried out. Clusters A_n of a higher level of the system self-organization (the time moment t_i) were determined as assemblies of specially selected clusters at the lower level (the time moment t_(i?1)). Such clusters are built of equivalent clusters and, therefore, have a hierarchical structure; i.e., the simplest clusters are integrated into the clusters of the next higher level. Also, the mechanism of self-assembly of symmetrically and topologically different chains and microlayers (in the form of planar nets) from cyclic clusters A_n is considered in the model system. The 45 obtained nets correspond to 11 uninodal Shubnikov nets and new binodal nets. Algorithms are presented for combinatorial and topological analysis to search for precursor clusters and restore a three-dimensional net of covalent and non-covalent bonds in a crystal structure by the matrix (cluster) self-assembly mechanism. The developed model is universal. The mechanism of self-assembly has been modeled for O₃ (ozone), C₆H₆ (benzene), C₂H₂ (acetylene), NaAlSi₃O₈ (albite), K_2.25Na_0.31Ca_2.25Ba_1.44 (Al_11.5Si_30.5O₈₄H_1.4) (H₂O)₂₅ (paulingite, PAU), B(OH)₃, H₃B₃O₆, H₂SeO₃, the Friauf?CLaves structure family(which counts in 1,400 of binary and ternary compounds): MgCu₂ (cF24), MgZn₂ (hP12), and MgNi₂ (hP24), the icosahedral structures: B₁₂, C₂₀H₂₀, C₆₀, ZrZn₂₂ (cF184), and NaCd₂ (cF1192) Samson Phase.     

Biomacromolecular quantitative structure–activity relationship (BioQSAR): a proof-of-concept study on the modeling, prediction and interpretation of protein–protein binding affinity

Quantitative structure–activity relationship (QSAR), a regression modeling methodology that establishes statistical correlation between structure feature and apparent behavior for a series of congeneric molecules quantitatively, has been widely used to evaluate the activity, toxicity and property of various small-molecule compounds such as drugs, toxicants and surfactants. However, it is surprising to see that such useful technique has only very limited applications to biomacromolecules, albeit the solved 3D atom-resolution structures of proteins, nucleic acids and their complexes have accumulated rapidly in past decades. Here, we present a proof-of-concept paradigm for the modeling, prediction and interpretation of the binding affinity of 144 sequence-nonredundant, structure-available and affinity-known protein complexes (Kastritis et al. Protein Sci 20:482–491, 2011) using a biomacromolecular QSAR (BioQSAR) scheme. We demonstrate that the modeling performance and predictive power of BioQSAR are comparable to or even better than that of traditional knowledge-based strategies, mechanism-type methods and empirical scoring algorithms, while BioQSAR possesses certain additional features compared to the traditional methods, such as adaptability, interpretability, deep-validation and high-efficiency. The BioQSAR scheme could be readily modified to infer the biological behavior and functions of other biomacromolecules, if their X-ray crystal structures, NMR conformation assemblies or computationally modeled structures are available.     

Molecular structure and barriers to internal rotation of α-naphthalenesulfonyl chloride: a study by gas-phase electron diffraction and quantum chemical calculations

α-Naphthalenesulfonyl chloride, α-NaphSC, was studied by gas-phase electron diffraction (GED) and quantum chemical calculations (HF/6-311 + G**, HF/aug-cc-pVDZ, B3LYP/cc-pVDZ, B3LYP/cc-pVTZ, B3LYP/aug-cc-pVDZ, B3LYP/aug-cc-pVTZ, MP2/cc-pVDZ, and MP2/cc-pVTZ). The calculations predict the existence of two conformers with C ₁ (I) and C _s (II) symmetries. The most stable conformer I has an enantiomer. The experimental data of α-NaphSC obtained at 370(5) K could be best fitted by a C ₁ symmetry model indicating that only this form exists in the gas-phase. In this model the C_α–S–Cl plane deviates from the perpendicular orientation relative to the plane of the naphthalene skeleton. Under the applied experimental conditions, the mole fraction of a second less stable conformer II of α-NaphSC predicted by calculations is no more than 1 %. The following geometrical parameters of conformer I were obtained from the experiment (Å and °; uncertainties are in parentheses): r _h1(C–H) = 1.082(6), r _h1(C–C)_cp = 1.407(3), r _h1(C–S) = 1.764(5), r _h1(S–O)_av = 1.425(3), r _h1(S–Cl) = 2.051(5), ∠C–C_α–C = 122.5(1), ∠C_α–S–Cl = 101.5(10); C9–C1–S–Cl = 71.4(21). The calculated barriers to internal rotation of the sulfonyl chloride group exceed considerably the thermal energy values corresponding to the temperatures of the GED experiments. Natural bond orbitals analysis of the electron density distribution was carried out to explain the peculiarities of the molecular structure of the studied compound and the deviation from the structures of β-NaphSHal molecules and their benzene analogs.     

Antioxidant properties of phenolic Schiff bases: structure–activity relationship and mechanism of action

Phenolic Schiff bases are known for their diverse biological activities and ability to scavenge free radicals. To elucidate (1) the structure–antioxidant activity relationship of a series of thirty synthetic derivatives of 2-methoxybezohydrazide phenolic Schiff bases and (2) to determine the major mechanism involved in free radical scavenging, we used density functional theory calculations (B3P86/6-31+(d,p)) within polarizable continuum model. The results showed the importance of the bond dissociation enthalpies (BDEs) related to the first and second (BDE_d) hydrogen atom transfer (intrinsic parameters) for rationalizing the antioxidant activity. In addition to the number of OH groups, the presence of a bromine substituent plays an interesting role in modulating the antioxidant activity. Theoretical thermodynamic and kinetic studies demonstrated that the free radical scavenging by these Schiff bases mainly proceeds through proton-coupled electron transfer rather than sequential proton loss electron transfer, the latter mechanism being only feasible at relatively high pH.     

Heterocyclic compounds as antiviral drugs: Synthesis,structure–activity relationship and traditional applications

A virus outbreak challenges the economic, medical, and public health infrastructure worldwide. More than one virus capable of triggering diseases have been identified per year since 1972, which requires the development of new ways of treatment and prevention, however, such processes are not rapid and easy. With the pandemic scenario experienced since early 2020, several drugs with well-known purposes have gained prominence, due to speculation of their use in the treatment against the new coronavirus. Among the main drugs studied, the vast majority contain a heterocyclic structure. In this review, we presented the traditional and efficient synthesis of 15 drugs that have been studied for the COVID-19 treatment, containing in their structure heterocycles like indole, quinoline, pyrimidone, tetrahydrofuran, pyrrolidine, triazole, pyridazine, pyrazole, pyrrolopyrimidine, azetidine, pyrrolotriazine, pyrazine, tetrahydropyran, benzofuran, spiroketal, and thiazole. Furthermore, we have shown the original applications, as well as their structure–activity relationship and what is their situation as a drug candidate against COVID-19. Thus, the objective was to consolidate the main synthetic and pharmacological aspects involving clinically developed heterocycles that at some point were presented as promising against SARS-CoV-2.     

Predicting hexadecane–air equilibrium partition coefficients (L) using a group contribution approach constructed from high quality data

A group contribution-based quantitative structure–property relationship (QSPR) for the hexadecane–air equilibrium partition coefficients (L) of organic chemicals is developed using the iterative fragment selection (IFS) approach. This new QSPR includes in its training and external validation data sets L values for a large number of structurally complex chemicals measured by the same group using consistent methods. The resulting QSPR has better predictive power than other prediction methods trained primarily using data for chemicals of simpler structures, and measurements of L values from diverse sources. For a subset of chemicals in which the L values have non-additive effects caused by intramolecular hydrogen bonds, the new QSPR gives much better performance in comparison to the most commonly used prediction method.     

Predicting toxicity of benzene derivatives by molecular hologram derived quantitative structure–activity relationships (QSARS)

Holographic quantitative structure–activity relationship (HQSAR) is an emerging QSAR technique with the combined application of molecular hologram, which encodes the frequency of occurrence of various molecular fragment types, and the subsequent partial least squares (PLS) regression analysis. Based on molecular hologram, alignment-free QSAR models could be rapidly and easily developed with highly statistical significance and predictive ability. In this paper, the toxicity data for a series of 83 benzene derivatives to the autotrophic Chlorella vulgaris (IGC⁵⁰, negative logarithmic form of 6-h 50% population growth inhibition concentration in mmol/l) were subjected to HQSAR analysis and this resulted in a model with a high predictive ability. The robustness and predictive ability of the model were validated by “leave-one-out” (LOO) cross-validation procedure and an external testing set. The influence of fragment distinction parameters and fragment size on the quality of the HQSAR model have been also discussed.     

The lithium–thiophene interaction: a critical study using highly correlated electronic structure approaches of quantum chemistry

The fundamental multicentric interaction of a lithium atom with a single thiophene ring is addressed. A systematic study of the interaction energy (IE) and geometry for the Li–T charge-transfer complex is done at the MP2 and CCSD(T) levels using increasingly large basis sets up to aug-cc-pVQZ (AVQZ). Basis set superposition errors (BSSE) are evaluated and shown to have a major impact on the value of the IE. The Fixed-Node Diffusion Monte Carlo (FN-DMC) method is used as an alternative basis-set-free approach to obtain what is likely to be the most accurate estimate of the IE obtained so far. While counterpoise-corrected MP2/AVQZ and CCSD(T)/AVTZ interaction energies are found to be ?3.8 and ?7.5 kcal/mol, the FN-DMC method yields +1.3 ± 1.7 kcal/mol. The slow convergence of the ab initio IE (and some key structural parameters) with respect to basis set quality and the discrepancy with the FN-DMC result is discussed. A visualization of the electron pairing using the electron pair localization function (EPLF) for the Li-doped versus undoped thiophene is also presented.