Strategies for translating proteomics discoveries into drug discovery for dementia

Tauopathies,diseases characterized by neuropathological aggregates of tau including Alzheimer's disease and subtypes of fro ntotemporal dementia,make up the vast majority of dementia cases.Although there have been recent developments in tauopathy biomarkers and disease-modifying treatments,ongoing progress is required to ensure these are effective,economical,and accessible for the globally ageing population.As such,continued identification of new potential drug targets and biomarkers is critical."Big data"studies,such as proteomics,can generate information on thousands of possible new targets for dementia diagnostics and therapeutics,but currently remain underutilized due to the lack of a clear process by which targets are selected for future drug development.In this review,we discuss current tauopathy biomarkers and therapeutics,and highlight areas in need of improvement,particularly when addressing the needs of frail,comorbid and cognitively impaired populations.We highlight biomarkers which have been developed from proteomic data,and outline possible future directions in this field.We propose new criteria by which potential targets in proteomics studies can be objectively ranked as favorable for drug development,and demonstrate its application to our group's recent tau interactome dataset as an example.

Artificial intelligence as a tool in drug discovery and development

The rapidly advancing field of artificial intelligence(AI)has garnered substantial attention for its potential application in drug discovery and development.This opinion review critically examined the feasibility and prospects of integrating AI as a transformative tool in the pharmaceutical industry.AI,encompassing machine learning algorithms,deep learning,and data analytics,offers unprecedented opportunities to streamline and enhance various stages of drug development.This opinion review delved into the current landscape of AI-driven approaches,discussing their utilization in target identification,lead optimization,and predictive modeling of pharmacokinetics and toxicity.We aimed to scrutinize the integration of large-scale omics data,electronic health records,and chemical informatics,highlighting the power of AI in uncovering novel therapeutic targets and accelerating drug repurposing strategies.Despite the considerable potential of AI,the review also addressed inherent challenges,including data privacy concerns,interpretability of AI models,and the need for robust validation in realworld clinical settings.Additionally,we explored ethical considerations surrounding AI-driven decision-making in drug development.This opinion review provided a nuanced perspective on the transformative role of AI in drug discovery by discussing the existing literature and emerging trends,presenting critical insights and addressing potential hurdles.In conclusion,this study aimed to stimulate discourse within the scientific community and guide future endeavors to harness the full potential of AI in drug development.

Applications and prospects of cryo-EM in drug discovery

Drug discovery is a crucial part of human healthcare and has dramatically benefited human lifespan and life quality in recent centuries, however, it is usually time-and effort-consuming. Structural biology has been demonstrated as a powerful tool to accelerate drug development. Among different techniques, cryo-electron microscopy(cryo-EM) is emerging as the mainstream of structure determination of biomacromolecules in the past decade and has received increasing attention from the pharmaceutical industry. Although cryo-EM still has limitations in resolution, speed and throughput, a growing number of innovative drugs are being developed with the help of cryo-EM. Here, we aim to provide an overview of how cryo-EM techniques are applied to facilitate drug discovery. The development and typical workflow of cryo-EM technique will be briefly introduced, followed by its specific applications in structure-based drug design, fragment-based drug discovery, proteolysis targeting chimeras, antibody drug development and drug repurposing. Besides cryo-EM, drug discovery innovation usually involves other state-of-the-art techniques such as artificial intelligence(AI), which is increasingly active in diverse areas. The combination of cryo-EM and AI provides an opportunity to minimize limitations of cryo-EM such as automation, throughput and interpretation of mediumresolution maps, and tends to be the new direction of future development of cryo-EM. The rapid development of cryo-EM will make it as an indispensable part of modern drug discovery.

Metabolomics in drug discovery: Restoring antibiotic pipeline

Metabolomics has emerged as a valuable tool in drug discovery and development,providing new insights into the mechanisms of action and toxicity of potential therapeutic agents.Metabolomics focuses on the comprehensive analysis of primary as well as secondary metabolites,within biological systems.Metabolomics provides a comprehensive understanding of the metabolic changes that occur within microbial pathogens when exposed to therapeutic agents,thus allowing for the identification of unique metabolic targets that can be exploited for therapeutic intervention.This approach can also uncover key metabolic pathways essential for survival,which can serve as potential targets for novel antibiotics.By analyzing the metabolites produced by diverse microbial communities,metabolomics can guide the discovery of previously unexplored sources of antibiotics.This review explores some examples that enable medicinal chemists to optimize drug structure,enhancing efficacy and minimizing toxicity via metabolomic approaches.

The role of SLC12A family of cation-chloride cotransporters and drug discovery methodologies

The solute carrier family 12(SLC12)of cation-chloride cotransporters(CCCs)comprises potassium chloride cotransporters(KCCs,e.g.KCC1,KCC2,KCC3,and KCC4)-mediated Cl^(-)extrusion,and sodium potassium chloride cotransporters(N[K]CCs,NKCC1,NKCC2,and NCC)-mediated Cl^(-)loading.The CCCs play vital roles in cell volume regulation and ion homeostasis.Gain-of-function or loss-of-function of these ion transporters can cause diseases in many tissues.In recent years,there have been considerable advances in our understanding of CCCs'control mechanisms in cell volume regulations,with many techniques developed in studying the functions and activities of CCCs.Classic approaches to directly measure CCC activity involve assays that measure the transport of potassium substitutes through the CCCs.These techniques include the ammonium pulse technique,radioactive or nonradioactive rubidium ion uptakeassay,and thallium ion-uptake assay.CCCs'activity can also be indirectly observed by measuring gaminobutyric acid(GABA)activity with patch-clamp electrophysiology and intracellular chloride concentration with sensitive microelectrodes,radiotracer^(36)Cl^(-),and fluorescent dyes.Other techniques include directly looking at kinase regulatory sites phosphorylation,flame photometry,22Nat uptake assay,structural biology,molecular modeling,and high-throughput drug screening.This review summarizes the role of CCCs in genetic disorders and cell volume regulation,current methods applied in studying CCCs biology,and compounds developed that directly or indirectly target the CCCs for disease treatments.

Recent insights for the emerging COVID-19:Drug discovery,therapeutic options and vaccine development

SARS-CoV-2 has been marked as a highly pathogenic coronavirus of COVID-19 disease into the human population,causing over 5.5 million confirmed cases worldwide.As COVID-19 has posed a global threat with significant human casualties and severe economic losses,there is a pressing demand to further understand the current situation and develop rational strategies to contain the drastic spread of the virus.Although there are no specific antiviral therapies that have proven effective in randomized clinical trials,currently,the rapid detection technology along with several promising therapeutics for COVID-19 have mitigated its drastic transmission.Besides,global institutions and corporations have commenced to parse out effective vaccines for the prevention of COVID-19.Herein,the present review will give exhaustive details of extensive researches concerning the drug discovery and therapeutic options for COVID-19 as well as some insightful discussions of the status of COVID-19.

Current status and challenges in drug discovery against the globally important zoonotic cryptosporidiosis

The zoonotic cryptosporidiosis is globally distributed,one of the major diarrheal diseases in humans and animals.Cryptosporidium oocysts are also one of the major environmental concerns,making it a pathogen that fits well into the One Health concept.Despite its importance,fully effective drugs are not yet available.Anti-cryptosporidial drug discovery has historically faced many unusual challenges attributed to unique parasite biology and technical burdens.While significant progresses have been made recently,anti-cryptosporidial drug discovery still faces a major obstacle:identification of systemic drugs that can be absorbed by patients experiencing watery diarrhea and effectively pass through electron-dense(ED)band at the parasite-host cell interface to act on the epicellular parasite.There may be a need to develop an in vitro assay to effectively screen hits/leads for their capability to cross ED band.In the meantime,non-systemic drugs with strong mucoadhesive properties for extended gastrointestinal exposure may represent another direction in developing anti-cryptosporidial therapeutics.For developing both systemic and non-systemic drugs,a non-ruminant animal model exhibiting diarrheal symptoms suitable for routine evaluation of drug absorption and anti-cryptosporidial efficacy may be very helpful.

Three-dimensional aspects of formulation excipients in drug discovery:a critical assessment on orphan excipients,matrix effects and drug interactions

Formulation/pharmaceutical excipients play a major role in formulating drug candidates,with the objectives of ease of administration,targeted delivery and complete availability.Many excipients used in pharmaceutical formulations are orphanized in preclinical drug discovery.These orphan excipients could enhance formulatability of highly lipophilic compounds.Additionally,they are safe in preclinical species when used below the LD50 values.However,when the excipients are used in formulating compounds with diverse physico-chemical properties,they pose challenges by modulating study results through their bioanalytical matrix effects.Excipients invariably present in study samples and not in the calibration curve standards cause over-/under-estimation of exposures.Thus,the mechanism by which excipients cause matrix effects and strategies to nullify these effects needs to be revisited.Furthermore,formulation excipients cause drug interactions by moderating the pathways of drug metabolizing enzymes and drug transport proteins.Although it is not possible to get rid of excipient driven interactions,it is always advised to be aware of these interactions and apply the knowledge to draw meaningful conclusions from study results.In this review,we will comprehensively discuss a)orphan excipients that have wider applications in preclinical formulations,b)bioanalytical matrix effects and possible approaches to mitigating these effects,and c)excipient driven drug interactions and strategies to alleviate the impacts of drug interactions.

Natural Products as Potential Lead Compounds for Drug Discovery Against SARS-CoV-2

For the past 2 years,the coronavirus responsible for the COVID-19 infection has become a world pandemic,ruining the lives and economies of several nations in the world.This has scaled up research on the virus and the resulting infection with the goal of developing new vaccines and therapies.Natural products are known to be a rich source of lead compounds for drug discovery,including against infectious diseases caused by microbes(viruses,bacteria and fungi).In this review article,we conducted a literature survey aimed at identifying natural products with inhibitory concentrations against the coronaviruses or their target proteins,which lie below 10μM.This led to the identification of 42 compounds belonging to the alkaloid,flavonoid,terpenoid,phenolic,xanthone and saponin classes.The cut off concentration of 10μM was to limit the study to the most potent chemical entities,which could be developed into therapies against the viral infection to make a contribution towards limiting the spread of the disease.

PPARγLBD and its ligand specificity reveal a selection of potential partial agonist:Molecular dynamics based T2D drug discovery initiative

PPARγis a peroxisome proliferator-activated receptor(PPAR)family protein and is a target for type 2 diabetes(T2D).In this paper,we have performed a molecular docking analysis between ligand molecules(CID9816265,CID11608015,CID20251380,CID20251343,CID20556263,CID624491,CID42609928,and CID86287562)and PPARγto determine the ligand specificity.It also helps to understand the ligand-binding domain(LBD)activity of PPARγduring the binding of the ligand.Further,a molecular dynamics simulation study was performed to determine the ligand biding stability in the PPARγLBD.Its ligand specificity informed us about the potentiality of selecting a partial agonist.The study also shows the binding conformation of Ceramicine B having hydrogen bonding affinity with a tricyclic polar head and stabilized theβ-sheet region.On the other hand,the tricyclic polar head of nimbolide also formed hydrogen bonding(Ser342),but it shows a lesser degree of stabilization in theβ-sheet region.It shows the binding conformation of partial agonist(PPARγ)in the Pocket-II of PPARγLBD,which has a significant role in stabilizing theβ-sheet region.It might help to regulate ERK/Cdk5 mediated phosphorylation of Ser245.The study helps us understand the valid pose of a set of ligands confirmation and target protein conformation using docking and molecular dynamics study.This in silico study will also help to initiate a drug discovery process of T2D.

Pharmacology and drug discovery

There are two general approaches to drug discovery. The oldest is the empirically-driven in vivo identification of a drug candidate, with little or no consideration given to identifying the active constituent. The alternative is mechanism-based, a process that entails the in vitro screening of purified chemical compounds to identify those that interact specifically with a selected biological target, after which they are tested for therapeutic potential. A major difference between these approaches is the extent to which the principles of pharmacology are employed to demonstrate safety and efficacy and to enable improvements in the therapeutic properties of the product. As a thorough pharmacological analysis of the pharmacokinetics and pharmacodynamics of a test agent requires that it be a stable, single, purified substance, such testing is more difficult with unpurified samples containing multiple compounds as compared to single agents. A lack of pharmacological information compromises the clinical utility of a test substance by leaving open questions about its bioavailability, metabolism, and mechanisms of therapeutic actions and toxicities. Although drug discovery success has be achieved with both the empirically-driven and mechanism-based approaches, the proper application of pharmacological techniques in the drug discovery process maximizes efficacy, safety and the chance for regulatory approval. In addition, pharmacological data provides information needed for improving the therapeutic properties of an agent, enhancing its clinical utility, and extending the product lifespan.

CRISPR accelerates the cancer drug discovery

Emerging cohorts and basic studies have associated certain genetic modifications in cancer patients,such as gene mutation,amplification,or deletion,with the overall survival prognosis,underscoring patients’genetic background may directly regulate drug sensitivity/resistance during chemotherapies.Understanding the molecular mechanism underpinning drug sensitivity/resistance and further uncovering the effective drugs have been the major ambition in the cancer drug discovery.The emergence and popularity of CRISPR/Cas9 technology have reformed the entire life science research,providing a precise and simplified genome editing tool with unlimited editing possibilities.Furthermore,it presents a powerful tool in cancer drug discovery,which hopefully facilitates us with a rapid and reliable manner in developing novel therapies and understanding the molecular mechanisms of drug sensitivity/resistance.Herein,we summarized the application of CRISPR/Cas9 in drug screening,with the focus on CRISPR/Cas9 mediated gene knockout,gene knock-in,as well as transcriptional modification.Additionally,this review provides the concerns,cautions,and ethnic considerations that need to be taken when applying CRISPR in the drug discovery.

Recent progress in fragment-based drug discovery facilitated by NMR spectroscopy

Considerable developments have been observed in fragment-based lead/drug discovery(FBLD/FBDD)recently,with four drugs approved and many others under investigation.Nuclear magnetic resonance(NMR)has gained increasing popularity in FBLD due to its intrinsic capability in characterizing protein-ligand interactions in a large dynamic range of affinity,from weak hits to highly potent drugs.Here,we summarize NMR applications in fragment-based hit-to-lead evolution,including the construction of a fragment library,screening methods,spectra processing,and the delineation of the protein-ligand binding modes.These state-of-the-art NMR techniques have been exemplified in the discovery of inhibitors against multiple targets over the past five years,and they are expected to continue to provide new insights in the future.

HCS strategy targeting dysregulation of the VHL/HIF pathway for drug discovery

One-third of top-selling drugs are derived from natural products. When only a fraction of the bioactive natural products diversity has been explored, huge opportunities still remain for discovering novel leads for the development of new drugs. Clear cell renal cell carcinoma (ccRCC) is a highly vascular tumour arising from epithelial elements. Mutations in the Von Hippel-Lindau (VHL) gene are responsible for VHL disease and arise in the majority of Renal Cell Carcinoma (RCC) as well as in other types of cancer. Renal carcinoma cell lines with naturally occurring VHL mutations (RCC4 VA) and their genetically matched wild-type VHL (RCC4 VHL) counterparts were seeded onto 96-well plates and allowed to attach overnight. Fungal extracts were tested on both cell lines. Clinically useful antitumor agents were used as positive controls and as reference points to establish the efficacy and selectivity of the new compounds. Renal cell carcinoma cell lines expressing VHL or not were treated with Carboxyfluorescein succinimidyl ester (CFSE). The day after cell inoculation, extracts were added and during the following days of incubation, fluorescence intensity was measured as a surrogate marker for cell viability. The most promising extracts selectively inhibited growth of pVHL-defi- cient cells but not of wild-type VHL cells. We used High Content Bio-imaging, a complete cellular imaging workflow that integrates instruments and software to acquire and analyze images, to evaluate their effect. Cell imaging can reveal effects that would be overlooked by other cell assay approaches. This target-based whole cell screen is a new strategy, which ensures cell permeability and target selectivity especially in natural product screening where natural product purification is a labour of extensive work. This approach permitted a dynamic study where fluorescence was measured without affecting cell viability and enabling a better detection of cytotoxic effects such as autophagy, senescence or late apoptosis.

Genome-wide pan-GPCR cell libraries accelerate drug discovery

G protein-coupled receptors(GPCRs)are pivotal in mediating diverse physiological and pathological processes,rendering them promising targets for drug discovery.GPCRs account for about 40%of FDA-approved drugs,representing the most successful drug targets.However,only approximately 15%of the 800 human GPCRs are targeted by market drugs,leaving numerous opportunities for drug discovery among the remaining receptors.Cell expression systems play crucial roles in the GPCR drug discovery field,including novel target identification,structural and functional characterization,potential ligand screening,signal pathway elucidation,and drug safety evaluation.Here,we discuss the principles,applications,and limitations of widely used cell expression systems in GPCR-targeted drug discovery,GPCR function investigation,signal pathway characterization,and pharmacological property studies.We also propose three strategies for constructing genome-wide pan-GPCR cell libraries,which will provide a powerful platform for GPCR ligand screening,and facilitate the study of GPCR mechanisms and drug safety evaluation,ultimately accelerating the process of GPCR-targeted drug discovery.

A comprehensive review of molecular optimization in artificial intelligence-based drug discovery

Drug discovery is aimed to design novel molecules with specific chemical properties for the treatment of targeting diseases. Generally, molecular optimization is one important step in drug discovery, which optimizes the physical and chemical properties of a molecule. Currently, artificial intelligence techniques have shown excellent success in drug discovery, which has emerged as a new strategy to address the challenges of drug design including molecular optimization, and drastically reduce the costs and time for drug discovery. We review the latest advances of molecular optimization in artificial intelligence-based drug discovery, including data resources, molecular properties, optimization methodologies, and assessment criteria for molecular optimization. Specifically, we classify the optimization methodologies into molecular mapping-based, molecular distribution matching-based, and guided search-based methods, respectively, and discuss the principles of these methods as well as their pros and cons. Moreover, we highlight the current challenges in molecular optimization and offer a variety of perspectives, including interpretability, multidimensional optimization, and model generalization, on potential new lines of research to pursue in future. This study provides a comprehensive review of molecular optimization in artificial intelligence-based drug discovery, which points out the challenges as well as the new prospects. This review will guide researchers who are interested in artificial intelligence molecular optimization.

Perspectives of autophagy-tethering compounds(ATTECs)in drug discovery

Degrader technologies provide unprecedented strategies to tackle diseases caused by pathogenic proteins that are difficult to target by the traditional inhibitor approach.One pioneering technology,proteolysis-targeting chimera(PROTAC),has re-volutionized small-molecule drug discovery.However,PROTACs hijack the ubiqui-tination-proteasome pathway,which is incapable of degrading certain categories of targets.To address this limitation,scientists introduced autophagy-tethering com-pounds(ATTECs),capitalizing on the autophagosome protein LC3 to selectively break down both pathogenic proteins and organelles.This review explores multiple dimensions of ATTECs,focusing on their mechanisms of action and potential appli-cations in drug discovery.

AI-driven drug discovery from natural products

The latest review published in Nature Reviews Drug Discovery by Michael W.Mullowney and co-authors focuses on the use of artificial intelligence techniques,specifically machine learning,in natural product drug discovery.The authors discussed various applications of AI in this field,such as genome and metabolome mining,structural characterization of natural products,and predicting targets and biological activities of these compounds.They also highlighted the challenges associated with creating and managing large datasets for training algorithms,as well as strategies to address these obstacles.Additionally,the authors examine common pitfalls in algorithm training and offer suggestions for avoiding them.

Drug discovery by targeting the protein–protein interactions involved in autophagy

Autophagy is a cellular process in which proteins and organelles are engulfed in autophagosomal vesicles and transported to the lysosome/vacuole for degradation.Protein–protein interactions(PPIs)play a crucial role at many stages of autophagy,which present formidable but attainable targets for autophagy regulation.Moreover,selective regulation of PPIs tends to have a lower risk in causing undesired off-target effects in the context of a complicated biological network.Thus,small-molecule regulators,including peptides and peptidomimetics,targeting the critical PPIs involved in autophagy provide a new opportunity for innovative drug discovery.This article provides general background knowledge of the critical PPIs involved in autophagy and reviews a range of successful attempts on discovering regulators targeting those PPIs.Successful strategies and existing limitations in this field are also discussed.

Function,mechanism and drug discovery of ubiquitin and ubiquitin-like modification with multiomics profiling for cancer therapy

Ubiquitin(Ub)and ubiquitin-like(Ubl)pathways are critical post-translational modifications that determine whether functional proteins are degraded or activated/inactivated.To date,>600 associated enzymes have been reported that comprise a hierarchical task network(e.g.,E1–E2–E3 cascade enzymatic reaction and deubiquitination)to modulate substrates,including enormous oncoproteins and tumor-suppressive proteins.Several strategies,such as classical biochemical approaches,multiomics,and clinical sample analysis,were combined to elucidate the functional relations between these enzymes and tumors.In this regard,the fundamental advances and follow-on drug discoveries have been crucial in providing vital information concerning contemporary translational efforts to tailor individualized treatment by targeting Ub and Ubl pathways.Correspondingly,emphasizing the current progress of Ub-related pathways as therapeutic targets in cancer is deemed essential.In the present review,we summarize and discuss the functions,clinical significance,and regulatory mechanisms of Ub and Ubl pathways in tumorigenesis as well as the current progress of small-molecular drug discovery.In particular,multiomics analyses were integrated to delineate the complexity of Ub and Ubl modifications for cancer therapy.The present review will provide a focused and up-to-date overview for the researchers to pursue further studies regarding the Ub and Ubl pathways targeted anticancer strategies.