Physicochemical Properties Of Drug Research Articles

Quantitative Structure-Property Relationship (QSPR) Modeling of Central Nervous System (CNS) Drug Activity using Molecular Descriptors

Background: L-type amino acid transporter-1 is a drug that stimulates the func-tions of the brain’s central nervous system. Membrane transporters have evolved, leading to a distinct approach in L-type amino acid transporter-1 drug delivery. One of the trans-porters used for transporting drugs across biological membranes is the L-type amino acid transporter-1. It is widely discussed in the medicinal field. Objectives: Numerous investigations indicate a close connection between the properties of alkanes and the diversity of central nervous system drugs in the brain, specifically log P and molecular weight. One important study that analyzes structural properties is focused on topological descriptors. Recently, topological indices have found application in the de-velopment of quantitative structure-activity relationships. These indices are correlated with the physicochemical properties of BCNS-acting drugs and their biological activity. Methods: The study employs significant methods of calculating topological indices: the edge set partition method and the Djokovi´c-Winkler relation (cut method) are utilized to calculate the values of these descriptors. Results: The results of distance and degree-based topological descriptors have been de-rived. The strong correlation between topological descriptors and the physicochemical properties of BCNS-acting drugs has been studied. Conclusions: This article identifies important topological features for various CNS medi-cations, aiming to support researchers in understanding the properties of molecules and their biological activity. Furthermore, we demonstrate how strongly these behaviors cor-respond to the physicochemical properties of central nervous system drugs.

β-Cyclodextrin Derivatives Bind Aromatic Side Chains of the Cyclic Peptide Lanreotide

Cyclodextrin complexation has a potential to modulate the physicochemical properties of peptide drugs. The ability of peptides to form an inclusion complex can be influenced by factors such as size, amino acid sequence of peptide and the size and charge of the cyclodextrin cavity. In this study, the inclusion complexes of cyclic peptide drug lanreotide acetate with two common β-cyclodextrin derivatives, Sulfobutyl ether β-CD (SBEβ-CD) and hydroxypropyl β-CD (HPβ-CD) were investigated. NMR spectroscopy was used to examine the interaction between β-cyclodextrin derivatives and specific residues of lanreotide. It was observed that the hydrophobic side chain of aromatic residues in the lanreotide sequence can be fit into the cavity of both β-cyclodextrin derivatives. Additionally, NMR revealed a lower diffusion coefficient and higher hydrodynamic radius of complex, indicative of binding to the cavities. Each aromatic residue was individually studied by substituting alanine in lanreotide to measure its association binding with both β-cyclodextrin derivatives. The alanine-substitute study indicated a stronger binding of SBEβ-CD to Lanreotide compared to HPβ-CD. Docking studies suggested that the 1:1 inclusion complex is more favorable than higher order complexes due to the steric hindrance and size considerations. The docking analysis indicated the stable conformation of all three aromatic side chains with both β-cyclodextrin derivatives, SBEβ-CDand HPβ-CD.

Dual drug molecular salt of antibacterial: Formulation, physicochemical properties study, theoretical calculations and evaluation of antibacterial activity

A molecular salt combined with the fluoroquinolone antibacterial gatifloxacin (GAT) and the sulfonamides antibacterial sulfamerazine (SMZ) is designed and synthesized successfully, which is the first report of the dual-drug cocrystallization of gatifloxacin. The precise structure of the acquired molecule salt GAT-SMZ has been characterized via single crystal X-ray diffraction and other techniques. Single crystal diffraction analysis displays that due to the transfer of protons from SMZ to GAT, the molecular salt of GAT-SMZ is formed, and the supramolecular network is dominated by charge-assisted one-dimensional hydrogen bond chain and two-dimensional accumulation layer in the crystal. Such structural feature endows molecular salt with superior physicochemical properties, including enhanced solubility and permeability. More importantly, the superior pharmaceutical performances of the dual-drug salt resulted in enhanced antibacterial activity against the tested strains. These observations are strongly supported by theoretical studies based on Hirshfeld surface and molecular docking analyses. Thus, this contribution not only highlights the validity of combining theory with experiment to drive the problem of physicochemical properties of drugs through co-crystallization methods, but also fills in the previous studies gatifloxacin dual-drug salt synergistic antibacterial research blank.

Bicubic regression analysis a novel approach for estimation of physicochemical properties of skin cancer drugs through degree based entropy

Skin cancer poses a significant risk to the healthcare system worldwide and is projected to increase substantially over the next two decades, particularly if not detected in its early stages. The primary aim of this study is to construct a quantitative structure-property relationship (QSPR) by correlating calculated entropies with topological indices and specific physical-chemical properties of pharmaceuticals, in order to enhance their usefulness. The bicubic regression model is constructed through degree-based topological entropies to perform the QSPR analysis for the prediction of physiochemical properties like polar surface area, complexity, molar refractivity, boiling point, and polarity of skin cancer drugs. It is also examined that degree-based entropies provide best-fit models for skin cancer physiochemical properties. We inspected five physio-chemical properties of these anticancer drugs and found this methodology suitable for predicting best-fit approximations regarding R2 value. It is expected that this approach will be very favourable to examining problems related to mathematical chemistry.

A Machine Learning Algorithm Suggests Repurposing Opportunities for Targeting Selected GPCRs.

Repurposing utilizes existing drugs with known safety profiles and discovers new uses by combining experimental and computational approaches. The integration of computational methods has greatly advanced drug repurposing, offering a rational approach and reducing the risk of failure in these efforts. Recognizing the potential for drug repurposing, we employed our Iterative Stochastic Elimination (ISE) algorithm to screen known drugs from the DrugBank database. Repurposing in our hands is based on computer models of the actions of ligands: the ISE algorithm is a machine learning tool that creates ligand-based models by distinguishing between the physicochemical properties of known drugs and those of decoys. The models are large sets of "filters" made out, each, of molecular properties. We screen and score external sets of molecules (in our case- the DrugBank molecules) by our agonism and antagonism models based on published data (i.e., IC50, Ki, or EC50) and pick the top-scoring molecules as candidates for experiments. Such agonist and antagonist models for six G-protein coupled receptors (GPCRs) families facilitated the identification of repurposing opportunities. Our screening revealed 5982 new potential molecular actions (agonists, antagonists), which suggest repurposing candidates for the cannabinoid 2 (CB2), histamine (H1, H3, and H4), and dopamine 3 (D3) receptors, which may be useful to treat conditions such as neuroinflammation, obesity, allergic dermatitis, and drug abuse. These sets of best candidates should now be examined by experimentalists: based on previous such experiments, there is a very high chance of discovering novel highly bioactive molecules.

Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms

In order to explore the role of topological indices for predicting physio-chemical properties of anti-HIV drugs, this research uses python program-based algorithms to compute topological indices as well as machine learning algorithms. Degree-based topological indices are calculated using Python algorithm, providing important information about the structural behavior of drugs that are essential to their anti-HIV effectiveness. Furthermore, machine learning algorithms analyze the physio-chemical properties that correspond to anti-HIV activities, making use of their ability to identify complex trends in large, convoluted datasets. In addition to improving our comprehension of the links between molecular structure and effectiveness, the collaboration between machine learning and QSPR research further highlights the potential of computational approaches in drug discovery. This work reveals the mechanisms underlying anti-HIV effectiveness, which paves the way for the development of more potent anti-HIV drugs. This work reveals the mechanisms underlying anti-HIV efficiency, which paves the way for the development of more potent anti-HIV drugs which demonstrates the invaluable advantages of machine learning in assessing drug properties by clarifying the biological processes underlying anti-HIV behavior, which paves the way for the design and development of more effective anti-HIV drugs.

Intestinal Lymphatic Biology, Drug Delivery and Therapeutics: Current status and Future directions.

Historically, the intestinal lymphatics were considered passive conduits for fluids, immune cells, dietary lipids, lipid soluble vitamins and lipophilic drugs. Studies of intestinal lymphatic drug delivery in the late 20th century focussed primarily on the drug physicochemical properties, especially high lipophilicity, that resulted in intestinal lymphatic transport. More recent discoveries have changed our traditional view by demonstrating that the lymphatics are active, plastic and tissue-specific players in a range of biological and pathological processes, including within the intestine. These findings have, in turn, inspired exploration of lymph-specific therapies for a range of diseases, as well as the development of more sophisticated strategies to actively deliver drugs or vaccines to the intestinal lymph, including a range of nanotechnologies, lipid prodrugs and lipid-conjugated materials that 'hitchhike' on lymphatic transport pathways. With the increasing development of novel biological therapeutics there has been interest in whether these novel therapeutics are absorbed and transported through intestinal lymph after oral administration. Here we review the current state of understanding of the anatomy and physiology of the gastrointestinal lymphatic system in health and disease, with a focus on aspects relevant to drug delivery. We summarise the current state-of-the-art approaches to deliver drugs and quantify their uptake into the intestinal lymphatic system. Finally, and excitingly, we discuss recent examples of significant pharmacokinetic and therapeutic benefits achieved via intestinal lymphatic drug delivery. We also propose approaches to advance the development and clinical application of intestinal lymphatic delivery strategies into the future. Significance Statement This comprehensive review details understanding of the anatomy and physiology of the intestinal lymphatic system in health and disease, with a focus on aspects relevant to drug delivery. It highlights current state-of-the-art approaches to deliver drugs to the intestinal lymphatics and the shift toward the use of these strategies to achieve pharmacokinetic and therapeutic benefits for patients.

Improved photostability, solubility, hygroscopic stability and antimicrobial activity of fleroxacin by synthesis of fleroxacin-D-tartaric acid pharmaceutical salt

To improve the solubility of the fluoroquinolone drug fleroxacin (FL), based on the previous experience of our research group in synthesizing co-crystals/salts of quinolone drugs to improve the physicochemical properties of drugs, Fleroxacin-D-tartaric acid dihydrate salt (FL-D-TT, C17H19F3N3O3·C4H5O6·2(H2O)), was synthesized for the first time using fleroxacin and D/L-tartaric acid (D/L-TT). Structural characterization of FL-D-TT was carried out using single-crystal X-ray diffraction, infrared spectral analysis (FT-IR) and powder X-ray diffraction (PXRD). Molecular electrostatic potential analysis showed that D-tartaric acid interacted more readily with FL than L-tartaric acid. The solubility of FL-D-TT (9.71 mg/mL, 1.82 mg/mL) was significantly higher compared to FL (0.39 mg/mL, 0.71 mg/mL) in water and buffer solution at pH 7.4. This may be attributed to the formation of charge-assisted hydrogen bonds (CAHBs) between FL and D-TT that facilitates the dissociation of FL cations in the dissolution medium, leading to an increase in FL solubility. This also led to some improvement in the in vitro antimicrobial activity of FL-D-TT against E. coli, S. typhi, and S. aureus. In addition, the hygroscopic stability of FL has been improved. Surprisingly, FL-D-TT had better photostability than FL, which could be attributed to the introduction of D-TT to make the photosensitizing moiety of FL more stable, which led to the improvement of the photostability of FL.

New Horizons in Antiretroviral Drug Delivery Systems for HIV Management.

Human Immunodeficiency Virus (HIV) infection is still a major global problem, whose drug treatment consists of prophylactic prevention and antiretroviral combination therapy for better pharmacological efficacy and control of circulating virus. However, there are still pharmacological problems that need to be overcome, such as low aqueous solubility of drugs, toxicity, and low patient adherence. Drug delivery technologies can be used to overcome these barriers. This review summarized the latest drug delivery systems for HIV treatment. Initially, an overview of the current therapy was presented along with the problems it presents. Then, the latest drug delivery systems used to overcome the challenges imposed in conventional HIV therapy were discussed. Articles published in the last 10 years were reviewed to obtain information on the innovations brought to HIV treatment. Delivery systems can improve the physicochemical properties of antiretroviral drugs, causing greater aqueous solubility, stability, and cellular and membrane permeability, which was reflected in the greater bioavailability of these drugs. However, more stability studies and techniques development are still needed to allow industrial scaling for large-scale production of drugs that use these technologies.

Advancements and Challenges of Nanostructured Lipid Carriers for Wound Healing Applications.

The current treatments for wound healing still exhibit drawbacks due to limited availability at the action sites, susceptibility to degradation, and immediate drug release, all of which are detrimental in chronic conditions. Nano-modification strategies, offering various advantages that can enhance the physicochemical properties of drugs, have been employed in efforts to maximize the efficacy of wound healing medications. Nowadays, nanostructured lipid carriers (NLCs) provide drug delivery capabilities that can safeguard active compounds from environmental influences and enable controlled release profiles. Consequently, NLCs are considered an alternative therapy to address the challenges encountered in wound treatment. This review delves into the application of NLCs in drug delivery for wound healing, encompassing discussions on their composition, preparation methods, and their impact on treatment effectiveness. The modification of drugs into the NLC model can be facilitated using relatively straightforward technologies such as pressure-based processes, emulsification techniques, solvent utilization methods, or phase inversion. Moreover, NLC production with minimal material compositions can accommodate both single and combination drug delivery. Through in vitro, in vivo, and clinical studies, it has been substantiated that NLCs can enhance the therapeutic potential of various drug types in wound healing treatments. NLCs enhance efficacy by reducing the active substance particle size, increasing solubility and bioavailability, and prolonging drug release, ensuring sustained dosage at the wound site for chronic wounds. In summary, NLCs represent an effective nanocarrier system for optimizing the bioavailability of active pharmacological ingredients in the context of wound healing.

Potential of Pullulan-Based Polymeric Nanoparticles for Improving Drug Physicochemical Properties and Effectiveness.

This scientific review aims to comprehensively discuss and summarize recent advancements in pullulan-based polymeric nanoparticles, focusing on their formulation, characterization, evaluation, and efficacy. A search on Scopus, PubMed, and Google Scholar, using "Pullulan and Nanoparticle" as keywords, identified relevant articles in recent years. The literature search highlighted a diverse range of studies on the pullulan-based polymeric nanoparticles, including the success of high-selectivity hybrid pullulan-based nanoparticles for efficient boron delivery in colon cancer as the active targeting nanoparticle, the specific and high-efficiency release profile of the development of hyalgan-coated pullulan-based nanoparticles, and the design of multifunctional microneedle patches that incorporated pullulan-collagen-based nanoparticle-loaded antimicrobials to accelerate wound healing. These studies collectively underscore the versatility and transformative potential of pullulan-based polymeric nanoparticles in addressing biomedical challenges. Pullulan-based polymeric nanoparticles are promising candidates for innovative drug delivery systems, with the potential to overcome the limitations associated with traditional delivery methods.

Advances in Modeling Approaches for Oral Drug Delivery: Artificial Intelligence, Physiologically-Based Pharmacokinetics, and First-Principles Models.

Oral drug absorption is the primary route for drug administration. However, this process hinges on multiple factors, including the drug's physicochemical properties, formulation characteristics, and gastrointestinal physiology. Given its intricacy and the exorbitant costs associated with experimentation, the trial-and-error method proves prohibitively expensive. Theoretical models have emerged as a cost-effective alternative by assimilating data from diverse experiments and theoretical considerations. These models fall into three categories: (i) data-driven models, encompassing classical pharmacokinetics, quantitative-structure models (QSAR), and machine/deep learning; (ii) mechanism-based models, which include quasi-equilibrium, steady-state, and physiologically-based pharmacokinetics models; and (iii) first principles models, including molecular dynamics and continuum models. This review provides an overview of recent modeling endeavors across these categories while evaluating their respective advantages and limitations. Additionally, a primer on partial differential equations and their numerical solutions is included in the appendix, recognizing their utility in modeling physiological systems despite their mathematical complexity limiting widespread application in this field.

Magnetic/Acoustic Dual-Controlled Microrobot Overcoming Oto-Biological Barrier for On-Demand Multidrug Delivery against Hearing Loss.

Multidrug combination therapy in the inner ear faces diverse challenges due to the distinct physicochemical properties of drugs and the difficulties of overcoming the oto-biologic barrier. Although nanomedicine platforms offer potential solutions to multidrug delivery, the access of drugs to the inner ear remains limited. Micro/nanomachines, capable of delivering cargo actively, are promising tools for overcoming bio-barriers. Herein, a novel microrobot-based strategy to penetrate the round window membrane (RWM) is presented and multidrug in on-demand manner is delivered. The tube-type microrobot (TTMR) is constructed using the template-assisted layer-by-layer (LbL) assembly of chitosan/ferroferric oxide/silicon dioxide (CS/Fe3O4/SiO2) and loaded with anti-ototoxic drugs (curcumin, CUR and tanshinone IIA, TSA) and perfluorohexane (PFH). Fe3O4 provides magnetic actuation, while PFH ensures acoustic propulsion. Upon ultrasound stimulation, the vaporization of PFH enables a microshotgun-like behavior, propelling the drugs through barriers and driving them into the inner ear. Notably, the proportion of drugs entering the inner ear can be precisely controlled by varying the feeding ratios. Furthermore, in vivo studies demonstrate that the drug-loaded microrobot exhibits superior protective effects and excellent biosafety toward cisplatin (CDDP)-induced hearing loss. Overall, the microrobot-based strategy provides a promising direction for on-demand multidrug delivery for ear diseases.

A literature review of drug transport mechanisms during lactation.

Despite the benefits of breastfeeding, lactating mothers who take prescribed medications may discontinue breastfeeding due to concerns associated with infant drug exposure in breastmilk. Consolidating the current knowledge of drug transport to breastmilk may inform understanding of the safety of medication use during lactation. This literature review summarizes the mechanisms of drug transport to breastmilk, details the physicochemical drug properties that may alter the extent of passive transport, and describes the expressional changes in mammary drug transporters that may affect active transport. During the period of 20 July 2023 to 11 August 2023, PubMed® was searched to identify journal articles pertinent to the mechanisms of drug transport from maternal plasma to breastmilk and the expression of mammary drug transporters during lactation. From the 28 studies included in this review, four mechanisms were identified for transporting drugs from maternal plasma to breastmilk: passive transport, active transport, lipid co-transport, and transcytosis. The lactational expression of 20 drug transporters was further summarized, with 9 transporters demonstrating downregulated expression during lactation and 11 transporters demonstrating upregulated expression during lactation. Understanding the mechanisms of drug transport to breastmilk may aid in estimating infant drug exposure, developing physiologically based pharmacokinetic (PBPK) models that describe drug transfer, and initiating clinical drug development programs in the lactating population.

Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians.

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.

Mechanism of Ocular Penetration of Lipophilic Drugs from Lipophilic Vehicles

Since eyedrops have conventionally been formulated in aqueous vehicles, ocular pharmacokinetic studies are generally performed using aqueous buffers to identify physicochemical properties of the drug and the vehicles that influence drug absorption. In recent years, biocompatible lipophilic vehicles are increasingly finding application in ocular drug delivery; however, the mechanism of drug penetration from these non-aqueous vehicles is poorly understood. This study aims to compare ocular penetration of the model lipophilic drug curcumin when incorporated into lipophilic vehicles. To elucidate whether intrinsic solubility in the lipophilic vehicle influences ocular penetration, a curcumin solution and suspension were prepared in medium chain triglycerides (MCT) and squalane, respectively. Ocular penetration and distribution of curcumin from both vehicles was compared and evaluated qualitatively and quantitatively ex vivo. Significantly greater and faster penetration was observed from the squalane suspension than from the MCT solution in all ocular tissues. Our results suggest that the ability of lipophilic drugs to partition out of lipophilic vehicles and into cell membranes, rather than their intrinsic solubility in the lipophilic vehicle, determines the rate and extent of their ocular penetration.

Hot Melt Extrusion Technique for Developing Pharmaceutical Co-crystals: A Review

Background: In the era of pharmaceutical research and development, the most challenging aspect is to enhance the physicochemical properties of drugs. Hot Melt Extrusion (HME) is a solvent-free, one-step, continuous, scalable, and industrially feasible method for developing pharmaceutical co-crystals. Co-crystallization, as a technique, has gained significant attention for its potential to modify various physicochemical properties of drugs like solubility, stability, compressibility, permeability, taste masking, and therapeutic efficacy Methods: We determine the characteristic features of HME and explore published literature using the keywords, HME, co-crystals, and PAT, in databases, such as PubMed, Google Scholar, ScienceDirect, and Research Gate. Result: The present review embarks on a detailed journey through the multifaceted domain of HME and its pivotal role in co-crystal development. The process parameters, such as temperature, extruder type, screw configuration, screw speed, and feed rate, are involved in determining the characteristics of the co-crystals produced. Additionally, the review explores the role of materials, including Active Pharmaceutical Ingredients (APIs), plasticizers, polymers, and other pharmaceutical aids, underlining their impact on co-crystal development. The existing literature on HME and its application for pharmaceutical co-crystal production is comprehensively surveyed. Conclusion: The review highlights the utility of Process Analytical Technology (PAT) in real-time process control. The role of HME in the future of pharmaceutical co-crystal development is discussed, making this review essential for researchers and industry professionals alike.

Nose-to-Brain Drug Delivery and Physico-Chemical Properties of Nanosystems: Analysis and Correlation Studies of Data from Scientific Literature.

In the last few decades, nose-to-brain delivery has been investigated as an alternative route to deliver molecules to the Central Nervous System (CNS), bypassing the Blood-Brain Barrier. The use of nanotechnological carriers to promote drug transfer via this route has been widely explored. The exact mechanisms of transport remain unclear because different pathways (systemic or axonal) may be involved. Despite the large number of studies in this field, various aspects still need to be addressed. For example, what physicochemical properties should a suitable carrier possess in order to achieve this goal? To determine the correlation between carrier features (eg, particle size and surface charge) and drug targeting efficiency percentage (DTE%) and direct transport percentage (DTP%), correlation studies were performed using machine learning. Detailed analysis of the literature from 2010 to 2021 was performed on Pubmed in order to build "NANOSE" database. Regression analyses have been applied to exploit machine-learning technology. A total of 64 research articles were considered for building the NANOSE database (102 formulations). Particle-based formulations were characterized by an average size between 150-200 nm and presented a negative zeta potential (ZP) from -10 to -25 mV. The most general-purpose model for the regression of DTP/DTE values is represented by Decision Tree regression, followed by K-Nearest Neighbors Regressor (KNeighbor regression). A literature review revealed that nose-to-brain delivery has been widely investigated in neurodegenerative diseases. Correlation studies between the physicochemical properties of nanosystems (mean size and ZP) and DTE/DTP parameters suggest that ZP may be more significant than particle size for DTP/DTE predictability.

The use of green protic ionic liquids in the crystallization of isoniazid: Evaluation of physicochemical and biological properties of drug

This study evaluated the synthesis of protic ionic liquids (PILs), 2-hydroxy ethylammonium formate (2-HEAF) and 2-hydroxy ethylammonium acetate (2-HEAA), and their applicability in the crystallization process of the active pharmaceutical ingredient isoniazid (INH) as anti-solvent. Isoniazid is an antibiotic used in the treatment of tuberculosis infections, being used as a first-line chemotherapeutic agent against Mycobacterium tuberculosis. Futhermore, this investigation was conducted in order to evaluate how these PILs can influence the habit, solubility, stability, and therapeutic efficiency of the obtained isoniazid crystals. The 2-HEAF and 2-HEAA PILs were easily formed in reactions between ethanolamine and carboxylic acids (formic or acetic acid), and they have no toxicity against Artemia salina. The PILs were able to crystallize isoniazid, influencing the crystal habit and size. The greatest variations in the hydrogen signals of the NH2 and NH groups of the amine and low variations in the chemical shifts of the hydrogens of the cation of the ethanolamine group from 2-HEAA and 2-HEAF indicate that PILs establish possibly weak interactions with INH. The obtained crystals were amorphous and showed higher solubility in water than standard INH. Moreover, these crystals showed therapeutic efficiency inantimycobacterial activity to inhibit the growth of Mycobacterium tuberculosis. The INH:2-HEAF only degraded 5.1 % (w/w), however, INH:2-HEAA degraded 32.8 % (w/w) after 60 days in an accelerated atmosphere. Then, the 2-HEAA and 2-HEAF were able to crystallize isoniazid, being a new application for these PILs. The used PILs also influenced the characteristics of isoniazid crystals.

On topological indices and QSPR analysis of some drugs used for treating Coronavirus patients

A topological index is a real number obtained from the molecular graph structure. It can predict the physicochemical and biological properties of many anticoronavirus drugs. In this article, the topological index of some drugs for the treatment of coronavirus was computed using the Wiener-Hosoya eigenvalues of the molecular structure of hydroxychloroquine, chloroquine, camostat, nafamostat, remdesivir, and lopinavir compounds, and the Quantitative Structure Property Relationship (QSPR) study of some properties: Boiling point, Molar weight, Flash point and Enthalpy were investigated. It was observed that the regression model value r is more than 0.6 and p value shows less than 0.05.