A combination of 3D-QSAR, docking, local-binding energy (LBE) and GRID study of the species differences in the carcinogenicity of benzene derivatives chemicals

Innovative screening for functional improved aromatic amine derivatives: Toxicokinetics, free radical oxidation pathway and carcinogenic adverse outcome pathway

Aromatic amines, one of the most widely used low-cost antioxidants in rubbers, have been regarded as pollutants with human health concerns. To overcome this problem, this study developed a systematic molecular design, screening, and performance evaluation method to design functionally improved, environmentally friendly and synthesizable aromatic amine alternatives for the first time. Nine of 33 designed aromatic amine derivatives have improved antioxidant property (lower bond dissociation energy of N-H), and their environmental and bladder carcinogenicity impacts were evaluated through toxicokinetic model and molecular dynamics simulation. The environmental fate of the designed AAs-11-8, AAs-11-16, and AAs-12-2 after antioxidation (i.e., peroxyl radicals (ROO·), hydroxyl radicals (HO·), superoxide anion radicals (O₂·^-) and ozonation reaction) was also analyzed. Results showed that the by-products of AAs-11-8 and AAs-12-2 have less toxicity after antioxidation. In addition, human bladder carcinogenicity of the screened alternatives was also evaluated through adverse outcome pathway. The carcinogenic mechanisms were analyzed and verified through amino acid residue distribution characteristics, 3D-QSAR and 2D-QSAR models. AAs-12-2, with high antioxidation property, low environmental impacts and carcinogenicity, was screened as the optimum alternative for 3,5-Dimethylbenzenamine. This study provided theoretical support for designing environmentally friendly and functionally improved aromatic amine alternatives from toxicity evaluation and mechanism analysis.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

Going All In: A Strategic Investment in In Silico Toxicology

As vast numbers of new chemicals are introduced to market annually, we are faced with the grand challenge of protecting humans and the environment while minimizing economically and ethically costly animal testing. In silico models promise to be the solution we seek, but we find ourselves at crossroads of future development efforts that would ensure standalone applicability and reliability of these tools. A conscientious effort that prioritizes experimental testing to support the needs of in silico models (versus regulatory needs) is called for to achieve this goal. Using economic analogy in the title of this work, we argue that a prudent investment is to go all-in to support in silico model development, rather than gamble our future by keeping the status quo of a "balanced portfolio" of testing approaches. We discuss two paths to future in silico toxicology-one based on big-data statistics ("broadsword"), and the other based on direct modeling of molecular interactions ("scalpel")-and offer rationale that the latter approach is more transparent, is better aligned with our quest for fundamental knowledge, and has a greater potential to succeed if we are willing to transform our toxicity-testing paradigm.

Exploring the structural determinants of novel xanthine derivatives as A2B adenosine receptor antagonists: a computational study

Adenosine is a ubiquitous endogenous nucleoside that controls numerous physiological functions via interacting with its specific G-coupled receptors. Activation of adenosine receptors (AdoRs), particularly A_2B AdoRs promotes the release of inflammatory cytokines; reduces vascular permeabilization and induces angiogenesis, thereby making A_2B AdoR becomes a potentially pharmacological target for drug development. Presently, for investigating the structural determinants of 164 xanthine derivatives as A_2B AdoR antagonists, we performed an in silico study integrating with 3D-QSAR, docking and molecular dynamics (MD) simulation. The obtained optimal model shows strong predictability (Q² = 0.647, R²_ncv = 0.955, and R²_pred = 0.848). Additionally, to explore the binding mode of the ligand with A_2B AdoR and to understand their binding mechanism, docking analysis, MD simulations (20 ns), and the calculation of binding free energy were also carried out. Finally, the structural determinants of these xanthine derivatives were identified and a total of 20 novel A_2B AdoR antagonists with improved potency were computationally designed, and their synthetic feasibility and selectivity were also evaluated. The information derived from the present study offers a better appreciation for exploring the interaction mechanism of the ligand with A_2B AdoR, which could be helpful for designing novel potent A_2B AdoR antagonists. Communicated by Ramaswamy H. Sarma.

An in silico exploration of the interaction mechanism of pyrazolo[1,5-a]pyrimidine type CDK2 inhibitors

CDK2, which interacts with cyclin A and cyclin E, is an important member of the CDK family. Having been proved to be associated with many diseases for its vital role in cell cycle, CDK2 is a promising target of anti-cancer drugs dealing with cell cycle disorders. In the present work, a total of 111 pyrazolo[1,5-a]pyrimidines (PHTPPs) as CDK2/cyclin A inhibitors were studied to conduct three-dimensional quantitative structure-activity (3D-QSAR) analyses. The optimal comparative molecular similarity indices analysis (CoMSIA) model shows that Q(2) = 0.516, Rncv(2) = 0.912, Rpre(2) = 0.914, Rm(2) = 0.843, SEP = 0.812, SEE = 0.347 with 10 components using steric, hydrophobic and H-bond donor field descriptors, indicating its effective internal and external predictive capacity. The contour maps further indicate that (1) bulky substituents in R1 are beneficial while H-bond donor groups at this position are detrimental; (2) hydrophobic contributions in the R2 area are favorable; (3) large and hydrophilic groups are well tolerated at the R3 position (a close H-bond donor moiety is favorable while a distal H-bond donor moiety in this area is disfavored); (4) bulky and hydrophobic features in the R4 region are beneficial for the biological activities and (5) the 7-N-aryl substitution is crucial to boost the inhibitory activities of the PHTPP inhibitors. Finally, docking and MD simulations demostrate that PHTPP derivatives are stabilized in a 'flying bat' conformation mainly through the H-bond interactions and hydrophobic contacts. Comparative studies indicate that PHTPP derivatives fit well within the ATP binding cleft in CDK2, with the core heterocyclic ring overlapping significantly with the adenine group of ATP despite a small deflection. In comparison to numerous other inhibitors binding to the ATP pocket, PHTPP analogues follow the binding fashion of purine inhibitors of this kinase. It is anticipated that the binding mechanism and structural features of PHTPP inhibitors studied in the present work will benefit the discovery of more potent CDK2 inhibitors, and the valid pyrazolo[1,5-a]pyrimidine-7-N-yl inhibitors will soon emerge from the large number of screening programmes to enter in clinical studies.

Reassessing the two-year rodent carcinogenicity bioassay: a review of the applicability to human risk and current perspectives

The 2-year rodent carcinogenicity test has been the regulatory standard for the prediction of human outcomes for exposure to industrial and agro-chemicals, food additives, pharmaceuticals and environmental pollutants for over 50 years. The extensive experience and data accumulated over that time has spurred a vigorous debate and assessment, particularly over the last 10 years, of the usefulness of this test in terms of cost and time for the information obtained. With renewed interest in the United States and globally, plus new regulations in the European Union, to reduce, refine and replace sentinel animals, this review offers the recommendation that reliance on information obtained from detailed shorter-term, 6 months rodent studies, combined with genotoxicity and chemical mode of action can realize effective prediction of human carcinogenicity instead of the classical two year rodent bioassay. The aim of carcinogenicity studies should not be on the length of time, and by obligation, number of animals expended but on the combined systemic pathophysiologic influence of a suspected chemical in determining disease. This perspective is in coordination with progressive regulatory standards and goals globally to utilize effectively resources of animal usage, time and cost for the goal of human disease predictability.

Sweet taste receptor gene variation and aspartame taste in primates and other species

Aspartame is a sweetener added to foods and beverages as a low-calorie sugar replacement. Unlike sugars, which are apparently perceived as sweet and desirable by a range of mammals, the ability to taste aspartame varies, with humans, apes, and Old World monkeys perceiving aspartame as sweet but not other primate species. To investigate whether the ability to perceive the sweetness of aspartame correlates with variations in the DNA sequence of the genes encoding sweet taste receptor proteins, T1R2 and T1R3, we sequenced these genes in 9 aspartame taster and nontaster primate species. We then compared these sequences with sequences of their orthologs in 4 other nontasters species. We identified 9 variant sites in the gene encoding T1R2 and 32 variant sites in the gene encoding T1R3 that distinguish aspartame tasters and nontasters. Molecular docking of aspartame to computer-generated models of the T1R2 + T1R3 receptor dimer suggests that species variation at a secondary, allosteric binding site in the T1R2 protein is the most likely origin of differences in perception of the sweetness of aspartame. These results identified a previously unknown site of aspartame interaction with the sweet receptor and suggest that the ability to taste aspartame might have developed during evolution to exploit a specialized food niche.

Structural alerts for estimating the carcinogenicity of pesticides and biocides

More than 20 years ago, Ashby and Tennant showed the interest of structural alerts for the prediction of the carcinogenicity of chemicals. These structural alerts are functional groups or structural features of various sizes that are linked to the level of carcinogenicity of chemicals. Since this pioneering work it has been possible to refine the alerts over time, as more experimental results have become available and additional mechanistic insights have been gained. To date, one of the most advanced lists of structural alerts for evaluating the carcinogenic potential of chemicals is the list proposed by Benigni and Bossa and that is implemented as a rule-based system in Toxtree and in the OECD QSAR Application Toolbox. In order to gain insight into the applicability of this system to the detection of potential carcinogens we screened about 200 pesticides and biocides showing a high structural diversity. Prediction results were compared with experimental data retrieved from an extensive bibliographical review. The prediction correctness was only equal to 60.14%. Attempts were made to analyse the sources of mispredictions.

Studies of new fused benzazepine as selective dopamine D3 receptor antagonists using 3D-QSAR, molecular docking and molecular dynamics

In recent years, great interest has been paid to the development of compounds with high selectivity for central dopamine (DA) D3 receptors, an interesting therapeutic target in the treatment of different neurological disorders. In the present work, based on a dataset of 110 collected benzazepine (BAZ) DA D3 antagonists with diverse kinds of structures, a variety of in silico modeling approaches, including comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), homology modeling, molecular docking and molecular dynamics (MD) were carried out to reveal the requisite 3D structural features for activity. Our results show that both the receptor-based (Q(2) = 0.603, R(2) (ncv) = 0.829, R(2) (pre) = 0.690, SEE = 0.316, SEP = 0.406) and ligand-based 3D-QSAR models (Q(2) = 0.506, R(2) (ncv) =0.838, R(2) (pre) = 0.794, SEE = 0.316, SEP = 0.296) are reliable with proper predictive capacity. In addition, a combined analysis between the CoMFA, CoMSIA contour maps and MD results with a homology DA receptor model shows that: (1) ring-A, position-2 and R(3) substituent in ring-D are crucial in the design of antagonists with higher activity; (2) more bulky R(1) substituents (at position-2 of ring-A) of antagonists may well fit in the binding pocket; (3) hydrophobicity represented by MlogP is important for building satisfactory QSAR models; (4) key amino acids of the binding pocket are CYS101, ILE105, LEU106, VAL151, PHE175, PHE184, PRO254 and ALA251. To our best knowledge, this work is the first report on 3D-QSAR modeling of the new fused BAZs as DA D3 antagonists. These results might provide information for a better understanding of the mechanism of antagonism and thus be helpful in designing new potent DA D3 antagonists.