Average Electron Density: A Quantitative Tool for Evaluating Non-Classical Bioisosteres of Amides

Bioisosterism is strategically used in drug design to enhance the pharmacokinetic and pharmacodynamic properties of therapeutic molecules. The average electron density (AED) tool has been used in several studies to quantify similarities among nonclassical bioisosteres of carboxylic acid. In this study, the AED tool is used to quantify the similarities among nonclassical bioisosteres of an amide group. In particular, amide-to-1,2,3-triazole bioisosterism is considered. To evaluate the AED differences exhibited by isomers of nonclassical bioisosteres, both isomers of amide (cis and trans) and 1,2,3-triazole (1,4 and 1,5 disubstituted moieity) were considered. The amide and 1,2,3-triazole bioisosteric moieties were capped with various R groups (R= methyl, hydrogen, and chloro) to account for changes in their environment. Amide-to-triazole bioisosteric substitutions were then explored in a more realistic environment, that is, within the FDA-approved anticancer imatinib drug. The AED tool effectively identified similarities between substantially different moieties, 1,2,3-triazole and amide, showing AED differences of no more than 4%. The AED tool was also proven to be useful in evaluating the contribution of various factors affecting triazole-amide bioisosterism including isomerism and changes in their environment. The AED values of each bioisostere were transferable within a maximum difference of 2.6%, irrespective of the change in environment. The 1,4- and 1,5-disubstituted isomers of 1,2,3-triazole have AED values that differ by less than unity, 0.52%. Similarly, the AED values of the cis- and trans-amide isomers differ by only 1.31%. Overall, the AED quantitative tool not only replicated experimental observations regarding similarities in bioisosteres, but also explained and quantified each contributing factor. This demonstrates the extended utility of the AED tool from nonclassical carboxylic acid bioisosteres to amide equivalents.On the contrary, electrostatic potential maps, usually used in the literature to qualitatively evaluate bioisosterism, were not similar for the 1,2,3-triazole and amide bioisosteres, under different environments. Overall, the AED tool proves to be powerful in quantitatively evaluating and predicting bioisosterism across diverse moieties considering structural and environmental variations, making it valuable in drug design.

Quantum and Classical Evaluations of Carboxylic Acid Bioisosteres: From Capped Moieties to a Drug Molecule

Using the Quantum Theory of Atoms in Molecules, the average electron density (AED) tool was developed and employed to quantitatively evaluate the similarities between bioisosteric moieties in drug design. Bioisosteric replacements are valuable in drug molecules to fine-tune their pharmacokinetic and pharmacodynamic properties while maintaining their biological activity. This study was performed on non-classical bioisosteres of carboxylic acid. It was found that the AED of a given bioisostere is generally transferable, within less than 5% difference, irrespective of its environment. It was shown that the AED tool succeeds at depicting not only the similarities of bioisosteric groups but also at highlighting, as counter examples, the differences in non-bioisosteric groups. For the first time, the AED was used to evaluate bioisosterism in an FDA-approved drug molecule, furosemide, and in five analogues of this medicine. In one of the analogues, non-bioisosteric moieties were exchanged, and in four of the analogues, carboxylic acid was replaced with either furan or sulfonamide, and vice versa. It was also found that irrespective of the pH, the AED tool consistently reproduced experimental predictions. The distinct power of the AED tool in quantitatively and precisely measuring the similarity among bioisosteric groups is contrasted with the relatively ambiguous bioisosteric evaluations through the classical qualitative electrostatic potential (ESP) maps. The ESP maps were demonstrated to fail, even qualitatively, in depicting the similarities, in some cases.

Artificial intelligence in drug design: algorithms, applications, challenges and ethics

The discovery paradigm of drugs is rapidly growing due to advances in machine learning (ML) and artificial intelligence (AI). This review covers myriad faces of AI and ML in drug design. There is a plethora of AI algorithms, the most common of which are summarized in this review. In addition, AI is fraught with challenges that are highlighted along with plausible solutions to them. Examples are provided to illustrate the use of AI and ML in drug discovery and in predicting drug properties such as binding affinities and interactions, solubility, toxicology, blood–brain barrier permeability and chemical properties. The review also includes examples depicting the implementation of AI and ML in tackling intractable diseases such as COVID-19, cancer and Alzheimer’s disease. Ethical considerations and future perspectives of AI are also covered in this review.

Electron density analysis of CDK complexes using the AlteQ method

Background: A principle of complementarity is a well-established concept in chemistry and biology. This concept is based on the overlap of electron clouds of the molecules in question. Materials & methods: In this article, one such approach (an in-house developed quantum free-orbital AlteQ method) was used to evaluate the complementarity of 51 CDK-ligand complexes. Results: A significant universally applicable correlation (adjusted R² = 0.9749; p < 2.2 × 10^-16) relating the product of ligand and enzyme electron densities to the product of distances between the contacting atomic centers and the type of atoms involved in the interaction was found. Conclusion: The terms calculated in this article can provide a good basis for prognosis of bioactivity and scientifically based molecular docking.

Atomic and molecular properties of nonclassical bioisosteric replacements of the carboxylic acid group

Aim: Drug design is fraught with challenges as small differences in the structure of a drug molecule can significantly affect its biological activity. Bioisosteres are interchangeably used to adjust pharmacokinetic and pharmacodynamic properties without affecting the biological activity of the drug. While electrostatic potential maps (EPMs) are typically used to show the similarity in the 'key and lock' interactions between a drug and its receptor, they are limited to qualitative comparisons. Methodology & results: Using the quantum theory of atoms in molecules, quantitative similarities among nonclassical bioisosteres of carboxylic acid were evaluated. Conclusion: The similarity in the bioisosteric groups was captured with the average electron density tool which generated remarkably close average electron densities regardless of the capping group, the isodensity values or the protonation state of the molecule. The similarities among bioisosteres was less obvious using the EPM tool.

Routes to drug design via bioisosterism of carboxyl and sulfonamide groups

AIM

The similarity in the biological function of the bioisosteric pair, carboxyl and sulfonamide functional groups, is studied using the quantitative tool, average electron density of the bioisosteric moiety in drug molecules and the qualitative tool, electrostatic potential. Results/methodology: Five different capping groups (methyl, phenyl, chlorine, hydrogen and amine) were considered to investigate the effect of the environment on the properties of the bioisosteres. The molecules were considered in their neutral and anionic forms to account for the change in pH depending on the medium of the drug-receptor interactions.

CONCLUSION

The new developed approach, average electron density, is not only advantageous as a qualitative descriptor, it is also more consistent compared with the conventionally accepted method, electrostatic potential, especially for the anions.