Pharmaceutical Implications Research Articles

Leveraging Artificial Intelligence in GPCR Activation Studies: Computational Prediction Methods as Key Drivers of Knowledge.

G protein-coupled receptors (GPCRs) are key molecules involved in cellular signaling and are attractive targets for pharmacological intervention. This chapter is designed to explore the range of algorithms used to predict GPCRs' activation states, while also examining the pharmaceutical implications of these predictions. Our primary objective is to show how artificial intelligence (AI) is key in GPCR research to reveal the intricate dynamics of activation and inactivation processes, shedding light on the complex regulatory mechanisms of this vital protein family. We describe several computational strategies that leverage diverse structural data from the Protein Data Bank, molecular dynamic simulations, or ligand-based methods to predict the activation states of GPCRs. We demonstrate how the integration of AI into GPCR research not only enhances our understanding of their dynamic properties but also presents immense potential for driving pharmaceutical research and development, offering promising new avenues in the search for newer, better therapeutic agents.

Exploring 5-Nitro-N-phenyl-3-(phenylamino)-1H-indazole-1-carboxamide (5-NPIC) Derivatives as Anticancer Agents: Synthesis, Docking and Molecular Dynamics Insights

The synthesis and characterization of a series of 5-nitro-[Formula: see text]-phenyl-3-(phenylamino)-1[Formula: see text]-indazole-1-carboxamide 5-NPIC derivatives (5a– 5v) have been reported as anticancer agents in this study. These derivatives were synthesized by reacting 3-chloro-5-nitro-[Formula: see text]-phenyl-1[Formula: see text]-indazole-1-carboxamide (4) with a variety of aniline derivatives in isopropanol. FT-IR, 1H-NMR, 13C-NMR and mass spectral methods were employed to confirm the structures of analogues (5a– 5v). The anticancer activity evaluation of compounds 5a– 5v revealed that 3-((3-methoxyphenyl) amino)-5-nitro-[Formula: see text]-phenyl-1[Formula: see text]-indazole-1-carboxamide (5j) exhibited good efficacy. The stability of ligand–protein complexes was systematically evaluated using molecular dynamics simulations (MDS), which demonstrated a consistent and robust binding of the most potent compound within the binding sites of target proteins. The results confirmed the anticancer activity, which was further substantiated by comprehensive molecular docking analyses that revealed complex interactions involving hydrophobic contacts, electrostatic forces and hydrogen bonds. Our results would collectively provide invaluable insights into the intricate molecular structure and dynamics of receptor target sites, thereby establishing a solid foundation for the development of novel and potent anticancer agents with optimistic pharmaceutical implications in near future.

Impact of nitrogen rates on biosynthesis pathways: A comparative study of diterpene synthases in clerodane diterpenoids and enzymes in benzylisoquinoline alkaloids

Tinospora sagittata is rich in secondary metabolites used in traditional medicine. However, environmental factors impact key enzymes in metabolite synthesis, highlighting the need for improved growth conditions. This study employs transcriptomics and metabolomics to assess nitrogen's impact on enzymes in secondary metabolites biosynthesis pathways. The gene expressions of berberine bridge enzymes (BBEs) like TsBBE2 had peak expression in low nitrogen treatments (A0 and A1) but were absent in higher nitrogen treatments (A2 and A3). Similar trends were observed for other enzymes such as (S)-scoulerine 9-O-methyltransferase (TsCMT3), Tetrahydroberberine oxidase (TsSTOX), and Columbamine O-methyltransferase (TsCoCOMT2-4) in response to nitrogen levels. In examining gene families related to diterpene synthases (diTPS), 1-deoxyxylulose 5-phosphate synthase (TsDXR1) expression increased with higher nitrogen fertilizer, while TsDXR2 peaked at maximal nitrogen levels. Geranylgeranyl diphosphate synthase (TsGGPP3 and TsGGPP5) decreased with nitrogen levels. (−)-kolavenyl diphosphate synthase (KPS) genes had higher expression in treatments, while ent-kaurene synthase (KSL) genes, especially TsKSL1 and TsKSL2, showed higher expression in control conditions with lower nitrogen fertilizer. Metabolite analysis confirmed more upregulated compounds in A3 compared to A0. These findings have practical implications for agriculture and pharmaceuticals, highlighting the link between nitrogen fertilization and specialized metabolism in medicinal plants.

Why insulin aspart and insulin degludec exhibit distinct release mechanisms

AbstractExploring the molecular mechanisms underlying insulin analogs is important for protein engineering to design innovative drug proteins. Insulin aspart (IAsp) and insulin degludec (IDeg) are representative examples of insulin analogs with distinct release profiles synthesized by targeted mutagenesis in protein engineering. Despite their importance in diabetes treatment, there remains a gap in our understanding of the molecular basis for their differential release mechanisms. In this study, ordinary molecular dynamics simulation and steered molecular dynamics are utilized to investigate the structural stability, solubility analysis, and monomer interactions of these insulins, with the aim to explain the mesoscale differences between the two insulin release mechanisms. Simulation findings have further been validated through experimental verification, shedding light on the intricate mechanisms underlying insulin release and providing valuable insights into pharmaceutical implications and potential advancements in the design of insulin therapy.

Studies on N-(6-Indazolyl) benzenesulfonamide Derivatives as Potential Anticancer Agents: Integrating Synthesis, In silico Docking, and Molecular Dynamics Simulations

A new series of benzenesulfonamide derivatives, namely N-(1-(2-chloropyrimidin-4-yl)-1[Formula: see text]-indazol-5-yl) compounds (4a-i) and N-(1-(2-chloropyrimidin-4-yl)-6-ethoxy-1[Formula: see text]-indazol-5-yl) derivatives (5a-i), were synthesized. This was achieved by reducing 1-(2-halopyrimidin-4-yl)-5-nitro-1[Formula: see text]-indazole (3) with SnCl2, followed by reacting with various aryl sulphonyl chlorides in pyridine. Structural confirmation was carried out through IR, 1H-NMR, [Formula: see text]C-NMR and mass spectral methods. Anticancer activity evaluation of compounds 4a-i and 5a-i revealed that N-(1-(2-chloropyrimidin-4-yl)-6-ethoxy-1H-indazol-5-yl)-2-nitrobenzenesulfonamide (5b) displayed exceptional efficacy. Molecular dynamics simulations were employed to rigorously assess the stability of ligand–protein complexes, highlighting a consistent and robust binding of the most potent compound within the binding sites of target proteins. The results unequivocally affirmed the remarkable anticancer activity, supported by comprehensive molecular docking analyses uncovering intricate interactions involving hydrogen bonds, electrostatic forces and hydrophobic contacts. These findings collectively offer invaluable insights into the complex molecular structure and dynamics of receptor target sites, establishing a robust foundation for the development of novel and potent anticancer agents with promising pharmaceutical implications.

PHARMACEUTICAL AUDIT PROCESS, OUTCOMES, AND IMPLICATIONS–OVERVIEW

PHARMACEUTICAL AUDIT PROCESS, OUTCOMES, AND IMPLICATIONS–OVERVIEW

The Controlled Release of Abscisic Acid (ABA) Utilizing Alginate-Chitosan Gel Blends: A Synergistic Approach for an Enhanced Small-Molecule Delivery Controller.

The integration of abscisic acid (ABA) into a chitosan-alginate gel blend unveils crucial insights into the formation and stability of these two substances. ABA, a key phytohormone in plant growth and stress responses, is strategically targeted for controlled release within these complexes. This study investigates the design and characterization of this novel controlled-release system, showcasing the potential of alginate-chitosan gel blends in ABA delivery. Computational methods, including molecular dynamics simulations, are employed to analyze the structural effects of microencapsulation, offering valuable insights into complex behavior under varying conditions. This paper focuses on the controlled release of ABA from these complexes, highlighting its strategic importance in drug delivery systems and beyond. This controlled release enables targeted and regulated ABA delivery, with far-reaching implications for pharmaceuticals, agriculture, and plant stress response studies. While acknowledging context dependency, the paper suggests that the liberation or controlled release of ABA holds promise in applications, urging further research and experimentation to validate its utility across diverse fields. Overall, this work significantly contributes to understanding the characteristics and potential applications of chitosan-alginate complexes, marking a noteworthy advancement in the field of controlled-release systems.

Fluorescence and single-particle cryo-EM analysis of ribosome/nascent-globin complexes: Protein-protein interactions and pharmaceutical implications

Fluorescence and single-particle cryo-EM analysis of ribosome/nascent-globin complexes: Protein-protein interactions and pharmaceutical implications

Supramolecular assemblies of citalopram and escitalopram in β-cyclodextrin dimeric cavity: Crystallographic and theoretical insights

Cyclodextrin (CD) encapsulation improves physicochemical and pharmacological properties of selective serotonin reuptake inhibitors (SSRIs), which are efficacious in treating depression, a global mental health problem. Here, we scrutinize β-CD inclusion complexes with racemate citalopram (rac-CTP; 1) and escitalopram ((S)-CTP; 2) by combined single-crystal X-ray diffraction and DFT full-geometry optimization. X-ray analysis unveiled that the 2:2 inclusion complexes of 1 and 2 with similar inclusion modes and topologies are stabilized by various intermolecular interactions of host–guest CH···π, host–host OH···O H-bonds, and guest–guest F···F in the tail-to-tail dimeric asymmetric unit. In the crystals, these dimers are stacked on top of each other, yielding similar channel structures of distinct crystal symmetries, triclinic, P1 (1) and monoclinic, P21 (2), which are further maintained by guest–guest π···π and CN···π interactions. The thermodynamic stabilities evaluated by DFT calculation indicate the vital role of weak intermolecular interactions in the formation and stabilization of the β-CD monomeric and dimeric inclusion complexes. This study provides crystallographic and theoretical evidence for the improved stability and the masked bitterness of CTP through β-CD encapsulation as patented previously and suggests the pharmaceutical implications in the drug delivery and enantioseparation.

Exploration of N‐(6‐Indazolyl) benzenesulfonamide Derivatives as Potential Antioxidants and Antimicrobial Agents: Integrating Synthesis, In Silico Docking, and Bioactivity Profiling

AbstractA new series of N‐(1‐(2‐chloropyrimidin‐4‐yl)‐1H‐indazol‐5‐yl) benzenesulfonamide derivatives (4 a–i) and N‐(1‐(2‐chloropyrimidin‐4‐yl)‐6‐ethoxy‐1H‐indazol‐5‐yl) benzenesulfonamide derivatives (5 a–i) was synthesized via reduction of 1‐(2‐halopyrimidin‐4‐yl)‐5‐nitro‐1H‐indazole (3) with SnCl2 followed by reaction with various aryl sulphonyl chlorides in pyridine. The structures were confirmed using IR, 1H‐NMR, 13C‐NMR, and mass spectral methods. Compounds 4 a–i and 5 a–i were evaluated for antifungal and antibacterial activities against Gram‐negative and Gram‐positive bacteria. They also exhibited antioxidant potential in DPPH (IC50=0.094‐0.467 μmol/ml) and ABTS assays (IC50=0.101–0.496 μmol/ml). Remarkably, N‐(1‐(2‐chloropyrimidin‐4‐yl)‐1H‐indazol‐5‐yl)‐2‐nitrobenzenesulfonamide displayed the highest antibacterial activity, while N‐(1‐(2‐chloropyrimidin‐4‐yl)‐1H‐indazol‐5‐yl)‐4‐methoxybenzenesulfonamide showed excellent antifungal potential. Compound N‐(1‐(2‐chloropyrimidin‐4‐yl)‐1H‐indazol‐5‐yl)‐2‐nitrobenzenesulfonamide exhibited the most significant antioxidant activity. In this study, molecular dynamics simulations were utilized to rigorously examine the stability of ligand‐protein complexes, demonstrating a consistent and robust binding of the most potent compound within the target proteins′ binding sites. Computational assessments were further employed to predict the drug‐likeness and ADMET properties of the synthesized compounds. The results unequivocally confirmed the remarkable antioxidant and antimicrobial potential of all derivatives, a finding substantiated by comprehensive molecular docking analyses that revealed intricate interactions involving hydrogen bonds, electrostatic forces, and hydrophobic contacts. These findings collectively provide invaluable insights into the complex molecular structure and receptor target site dynamics, laying a strong foundation for the development of novel active antioxidant and antimicrobial agents with promising pharmaceutical implications.

Metabolic Profiling, Antiviral Activity and the Microbiome of Some Mauritian Soft Corals.

Soft corals, recognized as sessile marine invertebrates, rely mainly on chemical, rather than physical defense, by secreting intricate secondary metabolites with plausible pharmaceutical implication. Their ecological niche encompasses a diverse community of symbiotic microorganisms which potentially contribute to the biosynthesis of these bioactive metabolites. The emergence of new viruses and heightened viral resistance underscores the urgency to explore novel pharmacological reservoirs. Thus, marine organisms, notably soft corals and their symbionts, have drawn substantial attention. In this study, the chemical composition of four Mauritian soft corals: Sinularia polydactya, Cespitularia simplex, Lobophytum patulum, and Lobophytum crassum was investigated using LC-MS techniques. Concurrently, Illumina 16S metagenomic sequencing was used to identify the associated bacterial communities in the named soft corals. The presence of unique biologically important compounds and vast microbial communities found therein was further followed up to assess their antiviral effects against SARS-CoV-2 and HPV pseudovirus infection. Strikingly, among the studied soft corals, L. patulum displayed an expansive repertoire of unique metabolites alongside a heightened bacterial consort. Moreover, L. patulum extracts exerted some promising antiviral activity against SARS-CoV-2 and HPV pseudovirus infection, and our findings suggest that L. patulum may have the potential to serve as a therapeutic agent in the prevention of infectious diseases, thereby warranting further investigation.

Herbs for lochia discharge used among postpartum women in Taiwan

Ethnopharmacological relevanceIn the traditional Taiwanese culture of “postpartum confinement”, the term “lochia discharge” is a synonym for assisting postpartum uterine involution. Postpartum women in Taiwan consult traditional Chinese medicine (TCM) pharmacies to obtain various TCM formulations that facilitate lochia discharge. Aim of the studyAs an ethnopharmacy study, we aimed to conduct field investigations to explore the herbal composition of TCM formulations for lochia discharge provided by TCM pharmacies in Taiwan and to identify the pharmaceutical implications of these TCM formulations. Materials and methodsThrough stratified sampling, we collected 98 formulations for postpartum lochia discharge from TCM pharmacies, which used a total of 60 medicinal materials. ResultsThe most common plant families of the medicinal materials found in Taiwanese lochia discharge formulations were Fabaceae and Lauraceae. Abiding by the TCM theory of nature and flavor, most drugs were warm in nature and sweet in flavor, and predominantly focused on the traditional functions of qi tonifying and blood activating. Correlation and network analyses of the medicinal components of lochia discharge formulations identified 11 core herbs, which, in the order of most to least frequently used, include Angelica sinensis, Ligusticum striatum, Glycyrrhiza uralensis, Zingiber officinale, Prunus persica, Eucommia ulmoides, Leonurus japonicus, Lycium chinense, Hedysarum polybotrys, Rehmannia glutinosa, and Paeonia lactiflora. These 11 herbs formed a total of 136 drug combinations in the 98 formulations, with 2–7 herbs in each combination. In addition, in the center of the network were A. sinensis and L. striatum, which jointly appeared in 92.8% of the formulations analyzed. ConclusionsTo our knowledge, this is the first study to systematically review lochia discharge formulations in Taiwan. The results of this study could provide an important basis for subsequent research in the clinical efficacy of Taiwanese lochia discharge formulations and the pharmacological mechanisms of their herbal components.

Perspectives on cutting-edge nanoparticulate drug delivery technologies based on lipids and their applications.

Numerous nanotech arenas in therapeutic biology have recently provided a scientific platform to manufacture a considerable swath of unique chemical entities focusing on drugs. Recently, nanoparticulate drug delivery systems have emerged to deliver a specific drug to a specified site. Among all other carriers, lipids possess features exclusive to nanostructured dosage forms. The bioavailability of orally administered drugs is typically negatively affected by their poor water solubility, resulting from the unique chemical moieties introduced. Because of their unique advantages, lipid nanoparticles must become increasingly predictable as a robust delivery mechanism. The enhanced biopharmaceutical properties and significance of lipid-based targeting technologies such as liposomes, niosomes, solid lipid nanoparticles and micelles are highlighted in this review. Pharmaceutical implications of lipid nanocarriers for the transport and distribution of various therapeutic agents, such as biotechnological products and small pharmaceutical molecules, is a booming topic. Lipid nanoparticles as drug delivery systems have many appealing properties, including high biocompatibility, ease of preparation, tissue specificity, avoidance of reticuloendothelial systems, delayed drug release, scale-up feasibility, nontoxicity and targeted delivery. The use of lipid nanoparticles to enhance the transport of biopharmaceuticals is currently considered state-of-the-art. Similarly, we critically examine the upcoming guidelines that therapeutic scientists should handle.

Protein function annotation based on heterogeneous biological networks

BackgroundAccurate annotation of protein function is the key to understanding life at the molecular level and has great implications for biomedicine and pharmaceuticals. The rapid developments of high-throughput technologies have generated huge amounts of protein–protein interaction (PPI) data, which prompts the emergence of computational methods to determine protein function. Plagued by errors and noises hidden in PPI data, these computational methods have undertaken to focus on the prediction of functions by integrating the topology of protein interaction networks and multi-source biological data. Despite effective improvement of these computational methods, it is still challenging to build a suitable network model for integrating multiplex biological data.ResultsIn this paper, we constructed a heterogeneous biological network by initially integrating original protein interaction networks, protein-domain association data and protein complexes. To prove the effectiveness of the heterogeneous biological network, we applied the propagation algorithm on this network, and proposed a novel iterative model, named Propagate on Heterogeneous Biological Networks (PHN) to score and rank functions in descending order from all functional partners, Finally, we picked out top L of these predicted functions as candidates to annotate the target protein. Our comprehensive experimental results demonstrated that PHN outperformed seven other competing approaches using cross-validation. Experimental results indicated that PHN performs significantly better than competing methods and improves the Area Under the Receiver-Operating Curve (AUROC) in Biological Process (BP), Molecular Function (MF) and Cellular Components (CC) by no less than 33%, 15% and 28%, respectively.ConclusionsWe demonstrated that integrating multi-source data into a heterogeneous biological network can preserve the complex relationship among multiplex biological data and improve the prediction accuracy of protein function by getting rid of the constraints of errors in PPI networks effectively. PHN, our proposed method, is effective for protein function prediction.

New Drug Development strategies with special reference to the endocarp of multifaceted agriculture crop – Cocos nucifera Linn

Coconut shell botanically represents the hard endocarp from the fruit of Cocos nucifera Linn. It is the usually discarded part of the plant with folklore claim in metabolic disorders.Being an inexpensive and easily availablenatural product with ethno medicinal significance, it seems highly relevant to scientifically validate the pharmaceutical implications of the drug. Till date, the new drug development strategies based on quality and efficacy parameters for the crude drug sample of Coconut shell has not been developed. The present study was intended to develop and scientifically validate the quality, purity, safety, potency and efficacy parameters of Coconut shell and thereby exploring the new drug development strategies for the drug. Materials andmethods: The study focused on the screening ofCoconut shell based on macroscopic, microscopic, organoleptic, histo-chemicaland HPTLC studies. Results:Characteristic presence of thin walled fibres, fibrosclereids,lignins and tannins were observed in themicroscopic analysis of Coconut shell. HPTLC studies also exemplifiedthe detailed bioactive chemical profile of Coconut shell.Conclusion: The study outcome suggestsCoconut shell as a novel reliable source of bioactive phytoconstituents with broad prospective in new drug development process.

Aromatic L-amino acid decarboxylases: mechanistic features and microbial applications.

Aromatic L-amino acid decarboxylases (AADCs) catalyze the conversion of aromatic L-amino acids into aromatic monoamines that play diverse physiological and biosynthetic roles in living organisms. For example, dopamine and serotonin serve as major neurotransmitters in animals, whereas tryptamine and tyramine are essential building blocks for synthesizing a myriad of secondary metabolites in plants. In contrast to the vital biological roles of AADCs in higher organisms, microbial AADCs are found in rather a limited range of microorganisms. For example, lactic acid bacteria are known to employ AADCs to achieve intracellular pH homeostasis and engender accumulation of tyramine, causing a toxic effect in fermented foods. Owing to the crucial pharmaceutical implications of aromatic monoamines and their derivatives, synthetic applications of AADCs have attracted growing attention. Besides, recent studies have uncovered that AADCs of human gut microbes influence host physiology and are involved in drug availability of Parkinson's disease medication. These findings bring the bacterial AADCs into a new arena of extensive research for biomedical applications. Here, we review catalytic features of AADCs and present microbial applications and challenges for biotechnological exploitation of AADCs. KEY POINTS: • Aromatic monoamines and their derivatives are increasingly important in the drug industry. • Aromatic L-amino acid decarboxylases are the only enzyme for synthesizing aromatic monoamines. • Microbial applications of aromatic L-amino acid decarboxylases have drawn growing attention.

Hepatic Models in Precision Medicine: An African Perspective on Pharmacovigilance.

Pharmaceuticals are indispensable to healthcare as the burgeoning global population is challenged by diseases. The African continent harbors unparalleled genetic diversity, yet remains largely underrepresented in pharmaceutical research and development, which has serious implications for pharmaceuticals approved for use within the African population. Adverse drug reactions (ADRs) are often underpinned by unique variations in genes encoding the enzymes responsible for their uptake, metabolism, and clearance. As an example, individuals of African descent (14–34%) harbor an exclusive genetic variant in the gene encoding a liver metabolizing enzyme (CYP2D6) which reduces the efficacy of the breast cancer chemotherapeutic Tamoxifen. However, CYP2D6 genotyping is not required prior to dispensing Tamoxifen in sub-Saharan Africa. Pharmacogenomics is fundamental to precision medicine and the absence of its implementation suggests that Africa has, to date, been largely excluded from the global narrative around stratified healthcare. Models which could address this need, include primary human hepatocytes, immortalized hepatic cell lines, and induced pluripotent stem cell (iPSC) derived hepatocyte-like cells. Of these, iPSCs, are promising as a functional in vitro model for the empirical evaluation of drug metabolism. The scale with which pharmaceutically relevant African genetic variants can be stratified, the expediency with which these platforms can be established, and their subsequent sustainability suggest that they will have an important role to play in the democratization of stratified healthcare in Africa. Here we discuss the requirement for African hepatic models, and their implications for the future of pharmacovigilance on the African continent.

Crocin Inhibits the Fibrillation of Human α-synuclein and Disassembles Mature Fibrils: Experimental Findings and Mechanistic Insights from Molecular Dynamics Simulation.

The aggregation of human alpha-synuclein (hαS) is pivotally implicated in the development of most types of synucleinopathies. Molecules that can inhibit or reverse the aggregation process of amyloidogenic proteins have potential therapeutic value. The anti-aggregating activity of multiple carotenoid compounds has been reported over the past decades against a growing list of amyloidogenic polypeptides. Here, we aimed to determine whether crocin, the main carotenoid glycoside component of saffron, would inhibit hαS aggregation or could disassemble its preformed fibrils. By employing a series of biochemical and biophysical techniques, crocin was exhibited to inhibit hαS fibrillation in a dose-dependent fashion by stabilizing very early aggregation intermediates in off-pathway non-toxic conformations with little β-sheet content. We also observed that crocin at high concentrations could efficiently destabilize mature fibrils and disassemble them into seeding-incompetent intermediates by altering their β-sheet conformation and reshaping their structure. Our atomistic molecular dynamics (MD) simulations demonstrated that crocin molecules bind to both the non amyloid-β component (NAC) region and C-terminal domain of hαS. These interactions could thereby stabilize the autoinhibitory conformation of the protein and prevent it from adopting aggregation-prone structures. MD simulations further suggested that ligand molecules prefer to reside longitudinally along the fibril axis onto the edges of the inter-protofilament interface where they establish hydrogen and hydrophobic bonds with steric zipper stabilizing residues. These interactions turned out to destabilize hαS fibrils by altering the interstrand twist angles, increasing the rigidity of the fibril core, and elevating its radius of gyration. Our findings suggest the potential pharmaceutical implication of crocin in synucleinopathies.

New Medical Device and Therapeutic Approvals in Otolaryngology: State of the Art Review 2020.

ObjectivesTo evaluate new drugs and devices relevant to otolaryngology–head and neck surgery that were approved by the US Food and Drug Administration (FDA) in 2020.Data SourcesPublicly available device and therapeutic approvals from ENT (ear, nose, and throat), anesthesia, neurology (neurosurgery), and plastic and general surgery FDA committees.Review MethodsMembers of the American Academy of Otolaryngology–Head and Neck Surgery’s Medical Devices and Drugs Committee reviewed new therapeutics and medical devices from a query of the FDA’s device and therapeutic approvals. Two independent reviewers assessed the drug’s or device’s relevance to otolaryngology, classified to subspecialty field, with a critical review of available scientific literature.ConclusionsThe Medical Devices and Drugs Committee reviewed 53 new therapeutics and 1094 devices (89 ENT, 140 anesthesia, 511 plastic and general surgery, and 354 neurology) approved in 2020. Ten drugs and 17 devices were considered relevant to the otolaryngology community. Rhinology saw significant improvements around image guidance systems; indications for cochlear implantation expanded; several new monoclonal therapeutics were added to head and neck oncology’s armamentarium; and several new approvals appeared for facial plastics surgery, pediatric otolaryngology, and comprehensive otolaryngology.Implications for PracticeNew technologies and pharmaceuticals offer the promise of improving how we care for otolaryngology patients. However, judicious introduction of innovations into practice requires a nuanced understanding of safety, advantages, and limitations. Working knowledge of new drugs and medical devices approved for the market helps clinicians tailor patient care accordingly.

Recent Advances in the Prediction of Protein Structural Classes: Feature Descriptors and Machine Learning Algorithms

In the postgenomic age, rapid growth in the number of sequence-known proteins has been accompanied by much slower growth in the number of structure-known proteins (as a result of experimental limitations), and a widening gap between the two is evident. Because protein function is linked to protein structure, successful prediction of protein structure is of significant importance in protein function identification. Foreknowledge of protein structural class can help improve protein structure prediction with significant medical and pharmaceutical implications. Thus, a fast, suitable, reliable, and reasonable computational method for protein structural class prediction has become pivotal in bioinformatics. Here, we review recent efforts in protein structural class prediction from protein sequence, with particular attention paid to new feature descriptors, which extract information from protein sequence, and the use of machine learning algorithms in both feature selection and the construction of new classification models. These new feature descriptors include amino acid composition, sequence order, physicochemical properties, multiprofile Bayes, and secondary structure-based features. Machine learning methods, such as artificial neural networks (ANNs), support vector machine (SVM), K-nearest neighbor (KNN), random forest, deep learning, and examples of their application are discussed in detail. We also present our view on possible future directions, challenges, and opportunities for the applications of machine learning algorithms for prediction of protein structural classes.