International Journal of Molecular Sciences

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Dear Colleagues,

There is currently a great, ongoing effort to better understand and treat diseases. Computational modeling is becoming increasingly important in biomedical research for understanding how biomolecules interact at the molecular level, as well as the molecular mechanisms of disease. Regarding their applications in xenobiotics, computational methods are fundamental for the discovery of drugs and the assessment of risks associated with chemicals, due to their multiple uses in the collection, processing, analysis and modeling of data. This means that animal testing is less necessary. Drug design is a multi-objective process in which various characteristics, such as efficacy, pharmacokinetics, and safety, must be optimized. With this in mind, advances in computational intelligence and machine learning are providing a basis for more effective searches of chemical spaces and the prediction of biological properties based on molecular structure. This issue aims to show different approaches and technologies that could be implemented in drug design in the near future.

Prof. Dr. Jesús Vicente de Julián-Ortiz
Dr. Francisco Torrens
Prof. Dr. Gloria Castellano
Guest Editors

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Keywords

molecular modeling
drug design
molecular mechanism
mathematical chemistry
structure–activity relationships
molecular descriptors
pharmacokinetics
toxicity

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Research

14 pages, 4051 KiB

Open AccessArticle

Dual-Target Mycobacterium tuberculosis Inhibition: Insights into the Molecular Mechanism of Antifolate Drugs

by Pritika Ramharack, Elliasu Y. Salifu and Clement Agoni

Int. J. Mol. Sci. 2023, 24(18), 14021; https://doi.org/10.3390/ijms241814021 - 13 Sep 2023

Viewed by 930

Abstract

The escalating prevalence of drug-resistant strains of Mycobacterium tuberculosis has posed a significant challenge to global efforts in combating tuberculosis. To address this issue, innovative therapeutic strategies are required that target essential biochemical pathways while minimizing the potential for resistance development. The concept of dual targeting has gained prominence in drug discovery against resistance bacteria. Dual targeting recognizes the complexity of cellular processes and disrupts more than one vital pathway, simultaneously. By inhibiting more than one essential process required for bacterial growth and survival, the chances of developing resistance are substantially reduced. A previously reported study investigated the dual-targeting potential of a series of novel compounds against the folate pathway in Mycobacterium tuberculosis. Expanding on this study, we investigated the predictive pharmacokinetic profiling and the structural mechanism of inhibition of UCP1172, UCP1175, and UCP1063 on key enzymes, dihydrofolate reductase (DHFR) and 5-amino-6-ribitylamino-2,4(1H,3H)-pyrimidinedione 5′-phosphate reductase (RV2671), involved in the folate pathway. Our findings indicate that the compounds demonstrate lipophilic physiochemical properties that promote gastrointestinal absorption, and may also inhibit the drug-metabolizing enzyme, cytochrome P450 3A4, thus enhancing their biological half-life. Furthermore, key catalytic residues (Serine, Threonine, and Aspartate), conserved in both enzymes, were found to participate in vital molecular interactions with UCP1172, which demonstrated the most favorable free binding energies to both DHFR and RV2671 (−41.63 kcal/mol, −48.04 kcal/mol, respectively). The presence of characteristic loop shifts, which are similar in both enzymes, also indicates a common inhibitory mechanism by UCP1172. This elucidation advances the understanding of UCP1172’s dual inhibition mechanism against Mycobacterium tuberculosis. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules 2.0)

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