The future of prodrugs – design by quantum mechanics methods

How can machine learning and multiscale modeling benefit ocular drug development?

The eyes possess sophisticated physiological structures, diverse disease targets, limited drug delivery space, distinctive barriers, and complicated biomechanical processes, requiring a more in-depth understanding of the interactions between drug delivery systems and biological systems for ocular formulation development. However, the tiny size of the eyes makes sampling difficult and invasive studies costly and ethically constrained. Developing ocular formulations following conventional trial-and-error formulation and manufacturing process screening procedures is inefficient. Along with the popularity of computational pharmaceutics, non-invasive in silico modeling & simulation offer new opportunities for the paradigm shift of ocular formulation development. The current work first systematically reviews the theoretical underpinnings, advanced applications, and unique advantages of data-driven machine learning and multiscale simulation approaches represented by molecular simulation, mathematical modeling, and pharmacokinetic (PK)/pharmacodynamic (PD) modeling for ocular drug development. Following this, a new computer-driven framework for rational pharmaceutical formulation design is proposed, inspired by the potential of in silico explorations in understanding drug delivery details and facilitating drug formulation design. Lastly, to promote the paradigm shift, integrated in silico methodologies were highlighted, and discussions on data challenges, model practicality, personalized modeling, regulatory science, interdisciplinary collaboration, and talent training were conducted in detail with a view to achieving more efficient objective-oriented pharmaceutical formulation design.

Inclusion of Levodopa into β-Cyclodextrin: A Comprehensive Computational Study

This study focused on the inclusion of levodopa (LVDP) into β-cyclodextrin (BCD) using various computational methods such as quantum mechanics (QM), molecular dynamics/steered molecular dynamics (MD/SMD), and QM/molecular mechanics/Poison-Boltzmann surface area (QM/MM/PBSA). The QM results assigned the most significant charge-transfer atoms and the higher stability of LVDP in the aqueous phase. The MD results indicate the formation of a 1:1 complex with a reasonable estimation of the effective radius of the complex, the significant contribution of hydrogen bonding in the binding energy, and the enhancement of the water solubility of LVDP. By accounting for the water hydrogen bonds and their dipolar effects, QM/MM calculations lead to the more accurate IR spectrum and binding energy of the BCD-LVDP complex. By considering carboxylic and amine functional groups' more precise arrangement, QM/MM assigns stronger hydrogen bonds between LVDP and BCD. While all the methods provide a reasonable estimation of the binding energy, the most accurate value (-4.14 kcal/mol) is obtained from QM/MM/PBSA.

Enzyme Models-From Catalysis to Prodrugs

Enzymes are highly specific biological catalysts that accelerate the rate of chemical reactions within the cell. Our knowledge of how enzymes work remains incomplete. Computational methodologies such as molecular mechanics (MM) and quantum mechanical (QM) methods play an important role in elucidating the detailed mechanisms of enzymatic reactions where experimental research measurements are not possible. Theories invoked by a variety of scientists indicate that enzymes work as structural scaffolds that serve to bring together and orient the reactants so that the reaction can proceed with minimum energy. Enzyme models can be utilized for mimicking enzyme catalysis and the development of novel prodrugs. Prodrugs are used to enhance the pharmacokinetics of drugs; classical prodrug approaches focus on alternating the physicochemical properties, while chemical modern approaches are based on the knowledge gained from the chemistry of enzyme models and correlations between experimental and calculated rate values of intramolecular processes (enzyme models). A large number of prodrugs have been designed and developed to improve the effectiveness and pharmacokinetics of commonly used drugs, such as anti-Parkinson (dopamine), antiviral (acyclovir), antimalarial (atovaquone), anticancer (azanucleosides), antifibrinolytic (tranexamic acid), antihyperlipidemia (statins), vasoconstrictors (phenylephrine), antihypertension (atenolol), antibacterial agents (amoxicillin, cephalexin, and cefuroxime axetil), paracetamol, and guaifenesin. This article describes the works done on enzyme models and the computational methods used to understand enzyme catalysis and to help in the development of efficient prodrugs.

Recent advances in prodrug-based nanoparticle therapeutics

Extensive research into prodrug modification of active pharmaceutical ingredients and nanoparticle drug delivery systems has led to unprecedented levels of control over the pharmacological properties of drugs and resulted in the approval of many prodrug or nanoparticle-based therapies. In recent years, the combination of these two strategies into prodrug-based nanoparticle drug delivery systems (PNDDS) has been explored as a way to further advance nanomedicine and identify novel therapies for difficult-to-treat indications. Many of the PNDDS currently in the clinical development pipeline are expected to enter the market in the coming years, making the rapidly evolving field of PNDDS highly relevant to pharmaceutical scientists. This review paper is intended to introduce PNDDS to the novice reader while also updating those working in the field with a comprehensive summary of recent efforts. To that end, first, an overview of FDA-approved prodrugs is provided to familiarize the reader with their advantages over traditional small molecule drugs and to describe the chemistries that can be used to create them. Because this article is part of a themed issue on nanoparticles, only a brief introduction to nanoparticle-based drug delivery systems is provided summarizing their successful application and unfulfilled opportunities. Finally, the review's centerpiece is a detailed discussion of rationally designed PNDDS formulations in development that successfully leverage the strengths of prodrug and nanoparticle approaches to yield highly effective therapeutic options for the treatment of many diseases.

Computational Simulations to Guide Enzyme-Mediated Prodrug Activation

Prodrugs are designed to improve pharmaceutical/biopharmaceutical characteristics, pharmacokinetic/pharmacodynamic properties, site-specificity, and more. A crucial step in successful prodrug is its activation, which releases the active parent drug, exerting a therapeutic effect. Prodrug activation can be based on oxidation/reduction processes, or through enzyme-mediated hydrolysis, from oxidoreductases (i.e., Cytochrome P450) to hydrolytic enzymes (i.e., carboxylesterase). This study provides an overview of the novel in silico methods for the optimization of enzyme-mediated prodrug activation. Computational methods simulating enzyme-substrate binding can be simpler like molecular docking, or more complex, such as quantum mechanics (QM), molecular mechanics (MM), and free energy perturbation (FEP) methods such as molecular dynamics (MD). Examples for MD simulations used for elucidating the mechanism of prodrug (losartan, paclitaxel derivatives) metabolism via CYP450 enzyme are presented, as well as an MD simulation for optimizing linker length in phospholipid-based prodrugs. Molecular docking investigating quinazolinone prodrugs as substrates for alkaline phosphatase is also presented, as well as QM and MD simulations used for optimal fit of different prodrugs within the human carboxylesterase 1 catalytical site. Overall, high quality computational simulations may show good agreement with experimental results, and should be used early in the prodrug development process.

User-Friendly Quantum Mechanics: Applications for Drug Discovery

Quantum mechanics (QM) methods provide a fine description of receptor-ligand interactions and of chemical reactions. Their use in drug design and drug discovery is increasing, especially for complex systems including metal ions in the binding sites, for the design of highly selective inhibitors, for the optimization of bi-specific compounds, to understand enzymatic reactions, and for the study of covalent ligands and prodrugs. They are also used for generating molecular descriptors for predictive QSAR/QSPR models and for the parameterization of force fields. Thanks to the continuous increase of computational power offered by GPUs and to the development of sophisticated algorithms, QM methods are becoming part of the standard tools used in computer-aided drug design (CADD). We present the most used QM methods and software packages, and we discuss recent representative applications in drug design and drug discovery.

Carbon Monoxide and Its Controlled Release: Therapeutic Application, Detection, and Development of Carbon Monoxide Releasing Molecules (CORMs)

Carbon monoxide (CO) is attracting increasing attention because of its role as a gasotransmitter with cytoprotective and homeostatic properties. Carbon monoxide releasing molecules (CORMs) are spatially and temporally controlled CO releasers that exhibit superior and more effective pharmaceutical traits than gaseous CO because of their chemistry and structure. Experimental and preclinical research in animal models has shown the therapeutic potential of inhaled CO and CORMs, and the biological effects of CO and CORMs have also been observed in preclinical trials via the genetic modulation of heme oxygenase-1 (HO-1). In this review, we describe the pharmaceutical use of CO and CORMs, methods of detecting CO release, and developments in CORM design and synthesis. Many valuable clinical CORMs formulated using macromolecules and nanomaterials are also described.

Designing metal-contained enzyme mimics for prodrug activation

Enzyme-activated prodrug therapy (EAPT) is a widely-used and effective treatment method for cancer by converting prodrugs into drugs at the demanded time and space, whose key step is prodrug activation. Traditional prodrug activations are mostly dependent on natural enzymes, which are unstable, expensive and hard to be functionalized. The emerging enzyme mimics, especially the metal-contained enzyme mimics (MEMs), provide a potential chance for improving the traditional EAPT because of their high stability, low cost and easiness of preparation and functionalization. The existing MEMs can be classified into three categories: catalytic core-scaffold MEM (csMEM), nanoparticle MEM (npMEMs) and metal-organic framework (MOF) MEM (mofMEM). These MEMs can mimic diverse functions corresponding to natural enzymes, and some of which are potentially used in prodrug activation, such as DNase, RNase, carbonate esterase, etc. In this review, we briefly summarize the MEMs according to their structure and composition, and highlight the successful and potential applications for prodrug activation mediated by hydrolase-like and oxidoreductase-like MEMs.

Recent updates in utilizing prodrugs in drug delivery (2013-2015)

INTRODUCTION

Utilizing the prodrug approach as a method to overcome various pharmaceutical and pharmacokinetic barriers to drug delivery is significantly accelerating and achieving successes. In contrast to the older traditional prodrugs which suffer from decreased bioavailability and a high profile of side effects, due to activation at undesired sites, the targeted prodrug approach utilizes delivery systems to improve delivery for a wide range of therapeutics including anti-cancer, anti-bacterial and anti-inflammatory drugs.

AREAS COVERED

Recent updates in utilization of prodrugs in drug delivery between 2013 and 2015 are discussed. Targeted prodrugs against cancer, solid tumors, microbial infections, inflammation and other diseases using advanced delivery systems such as theranostic approaches, siRNA, DOX immunoconjugate, C 60-ser carrier vector, biotinylated prodrug, human serum albumin (HSA) carrier and others are presented.

EXPERT OPINION

Recent research efforts have been directed at developing targeted prodrugs to replace the classical prodrugs. The use of this approach has accelerated following the emergence of encouraging results from several studies on targeted prodrugs that have highlighted their higher efficiency and improved safety profiles. Targeted prodrug delivery is now considered more than a chemical modification method. It is an applicable and promising approach and, in the future, better knowledge and wide application of this approach may be attained which may pave the way for more forward-thinking and creative techniques.