bioTCIs: Middle-to-Macro Biomolecular Targeted Covalent Inhibitors Possessing Both Semi-Permanent Drug Action and Stringent Target Specificity as Potential Antibody Replacements.

Monoclonal antibody therapies targeting immuno-modulatory targets such as checkpoint proteins, chemokines, and cytokines have made significant impact in several areas, including cancer, inflammatory disease, and infection. However, antibodies are complex biologics with well-known limitations, including high cost for development and production, immunogenicity, a limited shelf-life because of aggregation, denaturation, and fragmentation of the large protein. Drug modalities such as peptides and nucleic acid aptamers showing high-affinity and highly selective interaction with the target protein have been proposed alternatives to therapeutic antibodies. The fundamental limitation of short in vivo half-life has prevented the wide acceptance of these alternatives. Covalent drugs, also known as targeted covalent inhibitors (TCIs), form permanent bonds to target proteins and, in theory, eternally exert the drug action, circumventing the pharmacokinetic limitation of other antibody alternatives. The TCI drug platform, too, has been slow in gaining acceptance because of its potential prolonged side-effect from off-target covalent binding. To avoid the potential risks of irreversible adverse drug effects from off-target conjugation, the TCI modality is broadening from the conventional small molecules to larger biomolecules possessing desirable properties (e.g., hydrolysis resistance, drug-action reversal, unique pharmacokinetics, stringent target specificity, and inhibition of protein-protein interactions). Here, we review the historical development of the TCI made of bio-oligomers/polymers (i.e., peptide-, protein-, or nucleic-acid-type) obtained by rational design and combinatorial screening. The structural optimization of the reactive warheads and incorporation into the targeted biomolecules enabling a highly selective covalent interaction between the TCI and the target protein is discussed. Through this review, we hope to highlight the middle to macro-molecular TCI platform as a realistic replacement for the antibody.

The Pharmaceutical Industry in 2022: An Analysis of FDA Drug Approvals from the Perspective of Molecules.

While 2021 ended with the world engulfed in the COVID-19 Omicron wave, 2022 has ended in almost all countries, except China, with COVID-19 being likened to the flu. In this context, the U.S. Food and Drug Administration (FDA) has authorized only 37 new drugs this year compared to an average of 52 in the last four years. Thus 2022 is the second lowest harvest after 2016 in the last six years. This ranking may be transient and will be confirmed in the coming years. In this regard, the reduction in the number of drugs accepted by the FDA this year applies only to the so-called small molecules as there has been no variation in the respective numbers of biologics or TIDES (peptides and oligonucleotides). Monoclonal antibodies (mAbs) continue to be the class with the most drugs authorized (9), while proteins/enzymes (5) and an antibody-drug conjugate complete the biologics harvest. In 2022, five TIDES and seven drugs inspired by natural products have received the green light, thus showing the same tendency as in previous years. Finally, pharmaceutical agents with nitrogen aromatic heterocycles and/or fluorine atoms continue to be predominant among small molecules this year. Furthermore, three drugs have been approved for imaging, reinforcing the trend in recent years for this class of treatments. A keyword in 2022 is bispecificity since four drugs have this property (two mAbs, one protein, and one peptide). Herein, the 37 new drugs approved by the FDA in 2022 are analyzed. On the basis of chemical structure alone, these drugs are classified as the following: biologics (antibodies, antibody-drug conjugates, proteins/enzymes), TIDES (peptide and oligonucleotides), combined drugs, natural products; nitrogen aromatic heterocycles, fluorine-containing molecules, and other small molecules.

Recent advances in transition metal-catalyzed reactions of chloroquinoxalines: Applications in bioorganic chemistry.

The importance of the quinoxaline framework is exemplified by its presence in the well-known drugs such as varenicline, brimonidine, quinacillin, etc. In the past few years, preparation of a variety of organic compounds containing the quinoxaline framework has been reported by several research groups. The chloroquinoxalines were successfully used as substrates in many of these synthetic approaches due to their easy availability along with the reactivity especially towards a diverse range of metal and transition metal-catalyzed transformations including Sonogashira, Suzuki, Heck type of cross-coupling reactions. The transition metals e.g., Pd, Cu, Fe and Nb catalysts played a key role in these transformations for the construction of various CX (e.g., CC, CN, CO, CS, CP, CSe, etc) bonds. These approaches can be classified based on the catalyst employed, type of the reaction performed and nature of CX bond formation during the reaction. Several of these resultant quinoxaline derivatives have shown diverse biological activities which include apoptosis inducing activities, SIRT1 inhibition, inhibition of luciferace enzyme, antibacterial and antifungal activities, cytotoxicity towards cancer cells, inhibition of PDE4 (phosphodiesterase 4), potential uses against COVID-19, etc. Notably, a review article covering the literature based on transition metal-catalyzed reactions of chloroquinoxalines at the same time summarizing the relevant biological activities of resultant products is rather uncommon. Therefore, an attempt is made in the current review article to summarize (i) the recent advances noted in the transition metal-catalyzed reactions of chloroquinoxalines (ii) with the relevant mechanistic discussions (iii) along with the in vitro, and in silico biological studies (wherever reported) (iv) including Structure-Activity Relationship (SAR) within the particular series of the products reported between 2010 and 2022.

New pharmaceuticals approved by FDA in 2020: Small-molecule drugs derived from amino acids and related compounds.

Amino acids (AAs) play an important role in the modern health industry as key synthetic precursors for pharmaceuticals, biomaterials, biosensors, and drug delivery systems. Currently, over 30% of small-molecule drugs contain residues of tailor-made AAs or derived from them amino-alcohols and di-amines. In this review article, we profile 12 AA-derived new pharmaceuticals approved by the FDA in 2020. These newly introduced drugs include Tazverik (epithelioid sarcoma), Gemtesa (overactive bladder), Zeposia (multiple sclerosis), Byfavo (induction and maintenance of procedural sedation), Cu 64 dotatate, and Gallium 68 PSMA-11 (both PET imaging), Rimegepant (acute migraine), Zepzelca (lung cancer), Remdesivir (COVID-19), Amisulpride (nausea and vomiting), Setmelanotide (obesity), and Lonafarnib (progeria syndrome). For each compound, we describe the spectrum of biological activity, medicinal chemistry discovery, and synthetic preparation.

NICEdrug.ch, a workflow for rational drug design and systems-level analysis of drug metabolism.

The discovery of a drug requires over a decade of intensive research and financial investments - and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch resource, which incorporates 250,000 bioactive molecules, and studied their enzymatic metabolic targets, fate, and toxicity. NICEdrug.ch includes a unique fingerprint that identifies reactive similarities between drug-drug and drug-metabolite pairs. We validated the application, scope, and performance of NICEdrug.ch over similar methods in the field on golden standard datasets describing drugs and metabolites sharing reactivity, drug toxicities, and drug targets. We use NICEdrug.ch to evaluate inhibition and toxicity by the anticancer drug 5-fluorouracil, and suggest avenues to alleviate its side effects. We propose shikimate 3-phosphate for targeting liver-stage malaria with minimal impact on the human host cell. Finally, NICEdrug.ch suggests over 1300 candidate drugs and food molecules to target COVID-19 and explains their inhibitory mechanism for further experimental screening. The NICEdrug.ch database is accessible online to systematically identify the reactivity of small molecules and druggable enzymes with practical applications in lead discovery and drug repurposing.

Development of Polypyrrole Modified Screen-Printed Carbon Electrode Based Sensors for Determination of L-Tyrosine in Pharmaceutical Products.

Good health, of vital importance in order to carry out our daily routine, consists of both physical and mental health. Tyrosine (Tyr) deficiency as well as its excess are issues that can affect mental health and can generate disorders such as depression, anxiety, or stress. Tyr is the amino acid (AA) responsible for maintaining good mental health, and for this reason, the present research presents the development of new electrochemical sensors modified with polypyrrole (PPy) doped with different doping agents such as potassium hexacyanoferrate (II) (FeCN), sodium nitroprusside (NP), and sodium dodecyl sulfate (SDS) for a selective and sensitive detection of Tyr. The development of the sensors was carried out by chronoamperometry (CA) and the electrochemical characterization was carried out by cyclic voltammetry (CV). The detection limits (LOD) obtained with each modified sensor were 8.2 × 10-8 M in the case of PPy /FeCN-SPCE, 4.3 × 10-7 M in the case of PPy/NP-SPCE, and of 3.51 × 10-7 M in the case of PPy/SDS-SPCE, thus demonstrating a good sensitivity of these sensors detecting L-Tyr. The validation of sensors was carried out through quantification of L-Tyr from three pharmaceutical products by the standard addition method with recoveries in the range 99.92-103.97%. Thus, the sensors present adequate selectivity and can be used in the pharmaceutical and medical fields.

AMIDE v2: High-Throughput Screening Based on AutoDock-GPU and Improved Workflow Leading to Better Performance and Reliability.

Molecular docking is widely used in computed drug discovery and biological target identification, but getting fast results can be tedious and often requires supercomputing solutions. AMIDE stands for AutoMated Inverse Docking Engine. It was initially developed in 2014 to perform inverse docking on High Performance Computing. AMIDE version 2 brings substantial speed-up improvement by using AutoDock-GPU and by pulling a total revision of programming workflow, leading to better performances, easier use, bug corrections, parallelization improvements and PC/HPC compatibility. In addition to inverse docking, AMIDE is now an optimized tool capable of high throughput inverse screening. For instance, AMIDE version 2 allows acceleration of the docking up to 12.4 times for 100 runs of AutoDock compared to version 1, without significant changes in docking poses. The reverse docking of a ligand on 87 proteins takes only 23 min on 1 GPU (Graphics Processing Unit), while version 1 required 300 cores to reach the same execution time. Moreover, we have shown an exponential acceleration of the computation time as a function of the number of GPUs used, allowing a significant reduction of the duration of the inverse docking process on large datasets.

Liposome composition in drug delivery design, synthesis, characterization, and clinical application.

Liposomal drug delivery represents a highly adaptable therapeutic platform for treating a wide range of diseases. Natural and synthetic lipids, as well as surfactants, are commonly utilized in the synthesis of liposomal drug delivery vehicles. The molecular diversity in the composition of liposomes enables drug delivery with unique physiological functions, such as pH response, prolonged blood circulation, and reduced systemic toxicity. Herein, we discuss the impact of composition on liposome synthesis, function, and clinical utility.

Existing Drugs Considered as Promising in COVID-19 Therapy.

COVID-19 is a respiratory disease caused by newly discovered severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease at first was identified in the city of Wuhan, China in December 2019. Being a human infectious disease, it causes high fever, cough, breathing problems. In some cases it can be fatal, especially in people with comorbidities like heart or kidney problems and diabetes. The current COVID-19 treatment is based on symptomatic therapy, so finding an appropriate drug against COVID-19 remains an immediate and crucial target for the global scientific community. Two main processes are thought to be responsible for the COVID-19 pathogenesis. In the early stages of infection, disease is determined mainly by virus replication. In the later stages of infection, by an excessive immune/inflammatory response, leading to tissue damage. Therefore, the main treatment options are antiviral and immunomodulatory/anti-inflammatory agents. Many clinical trials have been conducted concerning the use of various drugs in COVID-19 therapy, and many are still ongoing. The majority of trials examine drug reposition (repurposing), which seems to be a good and effective option. Many drugs have been repurposed in COVID-19 therapy including remdesivir, favipiravir, tocilizumab and baricitinib. The aim of this review is to highlight (based on existing and accessible clinical evidence on ongoing trials) the current and available promising drugs for COVID-19 and outline their characteristics.

Improved multidetector asymmetrical-flow field-flow fractionation method for particle sizing and concentration measurements of lipid-based nanocarriers for RNA delivery.

Lipid-based nanoparticles for RNA delivery (LNP-RNA) are revolutionizing the nanomedicine field, with one approved gene therapy formulation and two approved vaccines against COVID-19, as well as multiple ongoing clinical trials. As for other innovative nanopharmaceuticals (NPhs), the advancement of robust methods to assess their quality and safety profiles-in line with regulatory needs-is critical for facilitating their development and clinical translation. Asymmetric-flow field-flow fractionation coupled to multiple online optical detectors (MD-AF4) is considered a very versatile and robust approach for the physical characterisation of nanocarriers, and has been used successfully for measuring particle size, polydispersity and physical stability of lipid-based systems, including liposomes and solid lipid nanoparticles. However, the unique core structure of LNP-RNA, composed of ionizable lipids electrostatically complexed with RNA, and the relatively labile lipid-monolayer coating, is more prone to destabilization during focusing in MD-AF4 than previously characterised nanoparticles, resulting in particle aggregation and sample loss. Hence characterisation of LNP-RNA by MD-AF4 needs significant adaptation of the methods developed for liposomes. To improve the performance of MD-AF4 applied to LNP-RNA in a systematic and comprehensive manner, we have explored the use of the frit-inlet channel where, differently from the standard AF4 channel, the particles are relaxed hydrodynamically as they are injected. The absence of a focusing step minimizes contact between the particle and the membrane, reducing artefacts (e.g. sample loss, particle aggregation). Separation in a frit-inlet channel enables satisfactory reproducibility and acceptable sample recovery in the commercially available MD-AF4 instruments. In addition to slice-by-slice measurements of particle size, MD-AF4 also allows to determine particle concentration and the particle size distribution, demonstrating enhanced versatility beyond standard sizing measurements.

PreDTIs: prediction of drug-target interactions based on multiple feature information using gradient boosting framework with data balancing and feature selection techniques.

Discovering drug-target (protein) interactions (DTIs) is of great significance for researching and developing novel drugs, having a tremendous advantage to pharmaceutical industries and patients. However, the prediction of DTIs using wet-lab experimental methods is generally expensive and time-consuming. Therefore, different machine learning-based methods have been developed for this purpose, but there are still substantial unknown interactions needed to discover. Furthermore, data imbalance and feature dimensionality problems are a critical challenge in drug-target datasets, which can decrease the classifier performances that have not been significantly addressed yet. This paper proposed a novel drug-target interaction prediction method called PreDTIs. First, the feature vectors of the protein sequence are extracted by the pseudo-position-specific scoring matrix (PsePSSM), dipeptide composition (DC) and pseudo amino acid composition (PseAAC); and the drug is encoded with MACCS substructure fingerings. Besides, we propose a FastUS algorithm to handle the class imbalance problem and also develop a MoIFS algorithm to remove the irrelevant and redundant features for getting the best optimal features. Finally, balanced and optimal features are provided to the LightGBM Classifier to identify DTIs, and the 5-fold CV validation test method was applied to evaluate the prediction ability of the proposed method. Prediction results indicate that the proposed model PreDTIs is significantly superior to other existing methods in predicting DTIs, and our model could be used to discover new drugs for unknown disorders or infections, such as for the coronavirus disease 2019 using existing drugs compounds and severe acute respiratory syndrome coronavirus 2 protein sequences.

Challenges in Biomaterial-Based Drug Delivery Approach for the Treatment of Neurodegenerative Diseases: Opportunities for Extracellular Vesicles.

Biomaterials have been the subject of numerous studies to pursue potential therapeutic interventions for a wide variety of disorders and diseases. The physical and chemical properties of various materials have been explored to develop natural, synthetic, or semi-synthetic materials with distinct advantages for use as drug delivery systems for the central nervous system (CNS) and non-CNS diseases. In this review, an overview of popular biomaterials as drug delivery systems for neurogenerative diseases is provided, balancing the potential and challenges associated with the CNS drug delivery. As an effective drug delivery system, desired properties of biomaterials are discussed, addressing the persistent challenges such as targeted drug delivery, stimuli responsiveness, and controlled drug release in vivo. Finally, we discuss the prospects and limitations of incorporating extracellular vesicles (EVs) as a drug delivery system and their use for biocompatible, stable, and targeted delivery with limited immunogenicity, as well as their ability to be delivered via a non-invasive approach for the treatment of neurodegenerative diseases.

Cryo-EM as a powerful tool for drug discovery.

The recent revolution in cryo-EM has produced an explosion of structures at near-atomic or better resolution. This has allowed cryo-EM structures to provide visualization of bound small-molecule ligands in the macromolecules, and these new structures have provided unprecedented insights into the molecular mechanisms of complex biochemical processes. They have also had a profound impact on drug discovery, defining the binding modes and mechanisms of action of well-known drugs as well as driving the design and development of new compounds. This review will summarize and highlight some of these structures. Most excitingly, the latest cryo-EM technology has produced structures at 1.2 Å resolution, further solidifying cryo-EM as a powerful tool for drug discovery. Therefore, cryo-EM will play an ever-increasing role in drug discovery in the coming years.

Potential anti-SARS-CoV-2 drug candidates identified through virtual screening of the ChEMBL database for compounds that target the main coronavirus protease.

A novel coronavirus [severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or 2019 novel coronavirus] has been identified as the pathogen of coronavirus disease 2019. The main protease (Mpro , also called 3-chymotrypsin-like protease) of SARS-CoV-2 is a potential target for treatment of COVID-19. A Mpro homodimer structure suitable for docking simulations was prepared using a crystal structure (PDB ID: 6Y2G; resolution 2.20 Å). Structural refinement was performed in the presence of peptidomimetic α-ketoamide inhibitors, which were previously disconnected from each Cys145 of the Mpro homodimer, and energy calculations were performed. Structure-based virtual screenings were performed using the ChEMBL database. Through a total of 1 485 144 screenings, 64 potential drugs (11 approved, 14 clinical, and 39 preclinical drugs) were predicted to show high binding affinity with Mpro . Additional docking simulations for predicted compounds with high binding affinity with Mpro suggested that 28 bioactive compounds may have potential as effective anti-SARS-CoV-2 drug candidates. The procedure used in this study is a possible strategy for discovering anti-SARS-CoV-2 drugs from drug libraries that may significantly shorten the clinical development period with regard to drug repositioning.

Sulfobutylether-ß-cyclodextrin.

This review presents the early history, the motivation, the research and some of the backstories behind the discovery and development of sulfobutylether-ß-cyclodextrin as a novel parenterally safe solubilizer and stabilizer. A specific sulfobutylether-ß-cyclodextrin with an average degree of 6.5 sulfobutyl-groups variably substituted on the 2-, 3- and 6-hydroxyls of the seven glucopyranose (dextrose) units of ß-cyclodextrin, is known by its commercial name, Captisol®. Today it is in 13 FDA approved injectables and numerous clinical candidates. It is also an example of a novel product discovered and initially preclinically developed at an academic institution.