Drug Discovery Research Articles

Unveiling the Potential of Ent-Kaurane Diterpenoids: Multifaceted Natural Products for Drug Discovery

Natural products hold immense potential for drug discovery, yet many remain unexplored in vast libraries and databases. In an attempt to fill this gap and meet the growing demand for effective drugs, this study delves into the promising world of ent-kaurane diterpenoids, a class of natural products with huge therapeutic potential. With a dataset of 570 ent-kaurane diterpenoids obtained from the literature, we conducted an in silico analysis, evaluating their physicochemical, pharmacokinetic, and toxicological properties with a focus on their therapeutic implications. Notably, these natural compounds exhibit drug-like properties, aligning closely with those of FDA-approved drugs, indicating a high potential for drug development. The ranges of the physicochemical parameters were as follows: molecular weights—288.47 to 626.82 g/mol; number of heavy atoms—21 to 44; the number of hydrogen bond donors and acceptors—0 to 8 and 1 to 11, respectively; the number of rotatable bonds—0 to 11; fraction Csp3—0.65 to 1; and TPSA—20.23 to 189.53 Ų. Additionally, the majority of these molecules display favorable safety profiles, with only 0.70%, 1.40%, 0.70%, and 46.49% exhibiting mutagenic, tumorigenic, reproduction-enhancing, and irritant properties, respectively. Importantly, ent-kaurane diterpenoids exhibit promising biopharmaceutical properties. Their average lipophilicity is optimal for drug absorption, while over 99% are water-soluble, facilitating delivery. Further, 96.5% and 28.20% of these molecules exhibited intestinal and brain bioavailability, expanding their therapeutic reach. The predicted pharmacological activities of these compounds encompass a diverse range, including anticancer, immunosuppressant, chemoprotective, anti-hepatic, hepatoprotectant, anti-inflammation, antihyperthyroidism, and anti-hepatitis activities. This multi-targeted profile highlights ent-kaurane diterpenoids as highly promising candidates for further drug discovery endeavors.

Gigantol, a promising natural drug for inflammation: a literature review and computational based study.

Gigantol, a bibenzyl compound extracted from various medicinal plants, has shown a number of biological activities, making it an attractive candidate for potential medical applications. This systematic review aims to shed light on gigantol's promising role in inflammation treatment and its underlying mechanisms. Gigantol exhibits potential anti-inflammatory properties in pre-clinical pharmacological test systems. It effectively reduced the levels of pro-inflammatory markers and arachidonic acid metabolites through various pathways, such as NF-κB, AKT, PI3K, and JNK/cPLA2/12-LOX. The in-silico investigations demonstrated that the MMP-13 enzyme served as the most promising target for gigantol with highest binding affinity (docking score = -8.8 kcal/mol). Encouragingly, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis of gigantol confirmed its compatibility with the necessary physiochemical, pharmacokinetic, and toxicity properties, bolstering its potential as a drug candidate. Gigantol, with its well-documented anti-inflammatory properties, could be a promising agent for treating inflammation in the near future.

Conformational and Electronic Variations in 1,2- and 1,6-Cyclophellitols and Their Impact on Retaining α-Glucosidase Inhibition.

Glycoside hydrolases (glycosidases) take part in myriad biological processes and are important therapeutic targets. Competitive and mechanism-based inhibitors are useful tools to dissect their biological role and comprise a good starting point for drug discovery. The natural product, cyclophellitol, a mechanism-based, covalent and irreversible retaining β-glucosidase inhibitor has inspired the design of diverse α- and β-glycosidase inhibitor and activity-based probe scaffolds. Here, we sought to deepen our understanding of the structural and functional requirements of cyclophellitol-type compounds for effective human α-glucosidase inhibition. We synthesized a comprehensive set of α-configured 1,2- and 1,6-cyclophellitol analogues bearing a variety of electrophilic traps. The inhibitory potency of these compounds was assessed towards both lysosomal and ER retaining α-glucosidases. These studies revealed the 1,6-cyclophellitols to be the most potent retaining α-glucosidase inhibitors, with the nature of the electrophile determining inhibitory mode of action (covalent or non-covalent). DFT calculations support the ability of the 1,6-cyclophellitols, but not the 1,2-congeners, to adopt conformations that mimic either the Michaelis complex or transition state of α-glucosidases.

Innovative Approaches for Drug Discovery: Quantifying Drug Distribution and Response with Raman Imaging.

Innovative Approaches for Drug Discovery: Quantifying Drug Distribution and Response with Raman Imaging.

From PDB files to protein features: a comparative analysis of PDB bind and STCRDAB datasets.

Understanding protein structures is crucial for various bioinformatics research, including drug discovery, disease diagnosis, and evolutionary studies. Protein structure classification is a critical aspect of structural biology, where supervised machine learning algorithms classify structures based on data from databases such as Protein Data Bank (PDB). However, the challenge lies in designing numerical embeddings for protein structures without losing essential information. Although some effort has been made in the literature, researchers have not effectively and rigorously combined the structural and sequence-based features for efficient protein classification to the best of our knowledge. To this end, we propose numerical embeddings that extract relevant features for protein sequences fetched from PDB structures from popular datasets such as PDB Bind and STCRDAB. The features are physicochemical properties such as aromaticity, instability index, flexibility, Grand Average of Hydropathy (GRAVY), isoelectric point, charge at pH, secondary structure fracture, molar extinction coefficient, and molecular weight. We also incorporate scaling features for the sliding windows (e.g., k-mers), which include Kyte and Doolittle (KD) hydropathy scale, Eisenberg hydrophobicity scale, Hydrophilicity scale, Flexibility of the amino acids, and Hydropathy scale. Multiple-feature selection aims to improve the accuracy of protein classification models. The results showed that the selected features significantly improved the predictive performance of existing embeddings.

Expedient Access to 18F‐Fluoroheteroarenes via Deaminative Radiofluorination of Aniline‐Derived Pyridinium Salts

Herein, we disclose that pyridinium salts derived from abundant (hetero)anilines represent a novel precursor class for nucleophilic aromatic substitution reactions with [18F]fluoride. The value of this new 18F‐fluorodeamination is demonstrated with the synthesis of over 30 structurally diverse and complex heteroaryl 18F‐fluorides, several derived from scaffolds that were yet to be labelled with fluorine‐18. The protocol tolerates heteroarenes and functionalities commonly found in drug discovery libraries, and is amenable to scale‐up and automation on a commercial radiosynthesiser.

Approach to Spirocyclohexadienes via Visible Light‐Mediated ipso‐Cyclization of Amino Acid Derivatives with N‐(2‐Phenyl)benzoyl Groups

Spirocycles are important structural motifs, found in natural and pharmaceutical compounds, which have attracted considerable interest in modern drug discovery research. Herein, we describe the development of a visible light‐mediated ipso‐cyclization of amino acid derivatives with N‐(2‐phenyl)benzoyl groups, allowing easy access to a variety of spirocyclohexadienes. The addition of water was found to be beneficial in promoting the reaction progress. Investigation of the substrate scope revealed that incorporating an electron‐donating moiety at the 3'‐position of the biphenyl group resulted in a more favorable outcome for spirocycle formation.

Expedient Access to 18F-Fluoroheteroarenes via Deaminative Radiofluorination of Aniline-Derived Pyridinium Salts.

Herein, we disclose that pyridinium salts derived from abundant (hetero)anilines represent a novel precursor class for nucleophilic aromatic substitution reactions with [18F]fluoride. The value of this new 18F-fluorodeamination is demonstrated with the synthesis of over 30 structurally diverse and complex heteroaryl 18F-fluorides, several derived from scaffolds that were yet to be labelled with fluorine-18. The protocol tolerates heteroarenes and functionalities commonly found in drug discovery libraries, and is amenable to scale-up and automation on a commercial radiosynthesiser.

Study anti-viral drugs for their efficiency against multiple SARS CoV-2 drug targets within molecular docking, molecular quantum similarity, and chemical reactivity indices frameworks

The study focused on drug discovery for COVID-19, emphasizing the challenges posed by the pandemic and the importance of understanding the virus’s biology. The research utilized molecular docking and quantum similarity analyses to explore potential ligands for SARS-CoV-2 RNA-dependent RNA polymerase. Docking Results Docking outcomes for various ligands, including Oseltamivir, Prochloraz, Valacyclovir, Baricitinib, Molnupiravir, Penciclovir, Famciclovir, Lamivudine, and Nitazoxanide, were presented. Interactions between ligands and specific residues in the RNA-dependent RNA polymerase were analyzed. Reactivity Descriptors Global parameters, such as electronic chemical potential, chemical hardness, global softness, and global electrophilicity, were computed for the ligands. For the local reactivity descriptors, the Fukui Functions were used. Fukui functions, representing electrophilic and nucleophilic sites, were calculated for selected ligands (Valacyclovir and Penciclovir). Nucleophilic character assignments for specific molecular regions were discussed, providing insights into potential charge-donating interactions. Results and Discussion Challenges in COVID-19 drug discovery, such as virus mutability, rapid evolution, and resource limitations, were summarized. Progress in vaccine development and the need for ongoing research to address variants and breakthrough cases were emphasized. Overlap Operator Analysis Higher MQSM between Lamivudine and Molnupiravir (0.5742) indicates structural and electronic similarity. Lowest MQSM between Oseltamivir and Prochloraz (0.2233) implies structural dissimilarity. Coulomb Operator Analysis Higher MQSM between Lamivudine and Molnupiravir (0.9178) suggests both structural and electronic similarity. Lowest MQSM between Baricitinib and Famciclovir (0.6001) indicates greater structural diversity. Measurements above 0.5 in Table 3 suggest electronic similarity, emphasizing the electronic aspects in molecular analysis. In this sense, it study employed a multi-faceted approach combining molecular docking, quantum similarity analyses, and chemical reactivity assessments to explore potential drug candidates for COVID-19. The findings provide valuable insights into ligand interactions, reactivity patterns, and the challenges associated with drug discovery in the context of the global pandemic.

All Roads Lead to Rome: Comparing Nanoparticle- and Small Molecule-Driven Cell Autophagy.

Autophagy, vital for removing cellular waste, is triggered differently by small molecules and nanoparticles. Small molecules, like rapamycin, non-selectively activate autophagy by inhibiting the mTOR pathway, which is essential for cell regulation. This can clear damaged components but may cause cytotoxicity with prolonged use. Nanoparticles, however, induce autophagy, often causing oxidative stress, through broader cellular interactions and can lead to a targeted form known as "xenophagy." Their impact varies with their properties but can be harnessed therapeutically. In this review, the autophagy induced by nanoparticles is explored and small molecules across four dimensions: the mechanisms behind autophagy induction, the outcomes of such induction, the toxicological effects on cellular autophagy, and the therapeutic potential of employing autophagy triggered by nanoparticles or small molecules. Although small molecules and nanoparticles each induce autophagy through different pathways and lead to diverse effects, both represent invaluable tools in cell biology, nanomedicine, and drug discovery, offering unique insights and therapeutic opportunities.

Multimodal Protein Representation Learning and Target-aware Variational Auto-encoders for Protein-binding Ligand Generation

Abstract Without knowledge of specific pockets, generating ligands based on the global structure of a protein target plays a crucial role in drug discovery as it helps reduce the search space for potential drug-like candidates in the pipeline. However, contemporary methods require optimizing tailored networks for each protein, which is arduous and costly. To address this issue, we introduce TargetVAE, a target-aware variational auto-encoder that generates ligands with desirable properties including high binding affinity and high synthesizability to arbitrary target proteins, guided by a multimodal deep neural network built based on geometric and sequence models, named Protein Multimodal Network (PMN), as the prior for the generative model. PMN unifies different representations of proteins (e.g., primary structure - sequence of amino acids, 3D tertiary structure, and residue-level graph) into a single representation. Our multimodal architecture learns from the entire protein structure and is able to capture their sequential, topological, and geometrical information by utilizing language modeling, graph neural networks, and geometric deep learning. We showcase the superiority of our approach by conducting extensive experiments and evaluations, including predicting protein-ligand binding affinity in the PBDBind v2020 dataset as well as the assessment of generative model quality, ligand generation for unseen targets, and docking score computation. Empirical results demonstrate the promising and competitive performance of our proposed approach. Our software package is publicly available at https://github.com/HySonLab/Ligand_Generation

Advancements in understanding bacterial enteritis pathogenesis through organoids.

Bacterial enteritis has a substantial role in contributing to a large portion of the global disease burden and serves as a major cause of newborn mortality. Despite advancements gained from current animal and cell models in improving our understanding of pathogens, their widespread application is hindered by apparent drawbacks. Therefore, more precise models are imperatively required to develop more accurate studies on host-pathogen interactions and drug discovery. Since the emergence of intestinal organoids, massive studies utilizing organoids have been conducted to study the pathogenesis of bacterial enteritis, revealing new mechanisms and validating established ones. In this review, we focus on the advancements of several bacterial pathogenesis mechanisms observed in intestinal organoid/enteroid models, exploring the host response and bacterial effectors during the infection process. Finally, we address the features that warrant additional investigation or could be enhanced in existing organoid models in order to guide future research endeavors.

Exploring the potential of Aspergillus wentii: secondary metabolites and biological properties.

Fungi are of considerable importance due to their capacity to biosynthesize various secondary metabolites with bioactive properties that draw high attention in new drug discovery with beneficial uses for improving human well-being and life quality. Aspergillus genus members are widespread and cosmopolitan species with varying economic significance in the fields of industry, medicine, and agriculture. Its species are renowned for their biosynthesis of secondary metabolites, characterized by both potent biological activity and structural novelty, making them a substantial reservoir for the development of new pharmaceuticals. The current work aimed at focusing on one species of this genus, Aspergillus wentii Wehmer, including its reported secondary metabolites in the period from 1951 to November 2023. A total of 97 compounds, including nitro-compounds, terpenoids, anthraquinones, xanthones, benzamides, and glucans. A summary of their bioactivities, as well as their biosynthesis was highlighted. Additionally, the reported applications of this fungus and its enzymes have been discussed. This review offers a useful reference that can direct future research into this fungus and its active metabolites, as well as their possible pharmacological and biotechnological applications.

Generation of conformational ensembles of small molecules via surrogate model-assisted molecular dynamics

The accurate prediction of thermodynamic properties is crucial in various fields such as drug discovery and materials design. This task relies on sampling from the underlying Boltzmann distribution, which is challenging using conventional approaches such as simulations. In this work, we introduce surrogate model-assisted molecular dynamics (SMA-MD), a new procedure to sample the equilibrium ensemble of molecules. First, SMA-MD leverages deep generative models to enhance the sampling of slow degrees of freedom. Subsequently, the generated ensemble undergoes statistical reweighting, followed by short simulations. Our empirical results show that SMA-MD generates more diverse and lower energy ensembles than conventional MD simulations. Furthermore, we showcase the application of SMA-MD for the computation of thermodynamical properties by estimating implicit solvation free energies.

Detergent Chemistry Modulates the Transgression of Planetary Boundaries including Antimicrobial Resistance and Drug Discovery.

Detergent chemistry enables applications in the world today while harming safe operating spaces that humanity needs for survival. Aim of this review is to support a holistic thought process in the design of detergent chemistry. We harness the planetary boundary concept as a framework for literature survey to identify progresses and knowledge gaps in context with detergent chemistry and five planetary boundaries that are currently transgressed, i.e., climate, freshwater, land system, novel entities, biosphere integrity. Our survey unveils the status of three critical challenges to be addressed in the years to come, including (i) the implementation of a holistically, climate-friendly detergent industry; (ii) the alignment of materialistic and social aspects in creating technical solutions by means of sustainable chemistry; (iii) the development of detergents that serve the purpose of applications but do not harm the biosphere in their role as novel entities. Specifically, medically relevant case reports revealed that even the most sophisticated detergent design cannot sufficiently accelerate drug discovery to outperform the antibiotic resistance development that detergents simultaneously promote as novel entities. Safe operating spaces that humanity needs for its survival may be secured by directing future efforts beyond sustainable chemistry, resource efficiency, and net zero emission targets.

COVID-19 drug discovery and treatment options.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused substantial morbidity and mortality, and serious social and economic disruptions worldwide. Unvaccinated or incompletely vaccinated older individuals with underlying diseases are especially prone to severe disease. In patients with non-fatal disease, long COVID affecting multiple body systems may persist for months. Unlike SARS-CoV and Middle East respiratory syndrome coronavirus, which have either been mitigated or remained geographically restricted, SARS-CoV-2 has disseminated globally and is likely to continue circulating in humans with possible emergence of new variants that may render vaccines less effective. Thus, safe, effective and readily available COVID-19 therapeutics are urgently needed. In this Review, we summarize the major drug discovery approaches, preclinical antiviral evaluation models, representative virus-targeting and host-targeting therapeutic options, and key therapeutics currently in clinical use for COVID-19. Preparedness against future coronavirus pandemics relies not only on effective vaccines but also on broad-spectrum antivirals targeting conserved viral components or universal host targets, and new therapeutics that can precisely modulate the immune response during infection.

Detergent Chemistry Modulates the Transgression of Planetary Boundaries including Antimicrobial Resistance and Drug Discovery

Detergent chemistry enables applications in the world today while harming safe operating spaces that humanity needs for survival. Aim of this review is to support a holistic thought process in the design of detergent chemistry. We harness the planetary boundary concept as a framework for literature survey to identify progresses and knowledge gaps in context with detergent chemistry and five planetary boundaries that are currently transgressed, i.e., climate, freshwater, land system, novel entities, biosphere integrity. Our survey unveils the status of three critical challenges to be addressed in the years to come, including (i) the implementation of a holistically, climate‐friendly detergent industry; (ii) the alignment of materialistic and social aspects in creating technical solutions by means of sustainable chemistry; (iii) the development of detergents that serve the purpose of applications but do not harm the biosphere in their role as novel entities. Specifically, medically relevant case reports revealed that even the most sophisticated detergent design cannot sufficiently accelerate drug discovery to outperform the antibiotic resistance development that detergents simultaneously promote as novel entities. Safe operating spaces that humanity needs for its survival may be secured by directing future efforts beyond sustainable chemistry, resource efficiency, and net zero emission targets.

Genome mining of Mycobacterium tuberculosis: targeting SufD as a novel drug candidate through in silico characterization and inhibitor screening

Tuberculosis (TB) stands as the second most fatal infectious disease globally, causing 1.3 million deaths in 2022. The resurgence of TB and the alarming rise of antibiotic resistance demand urgent call to develop novel antituberculosis drugs. Despite concerted efforts to control TB, the disease persists and spreads rapidly on a global scale. Targeting stress response pathways in Mycobacterium tuberculosis (Mtb) has become imperative to achieve complete eradication. This study employs subtractive genomics to identify and prioritize potential drug targets among the hypothetical proteins of Mtb, focusing on indispensable pathways. Amongst 177 essential hypothetical proteins, 152 were nonhomologous to human. These proteins participated in 34 pathways, and a 20-fold enrichment of SUF pathway genes led to its selection as a target pathway. Fe–S clusters are fundamental, widely distributed protein cofactors involved in vital cellular processes. The survival of Mtb in a hypoxic environment relies on the iron–sulfur (Fe–S) cluster biogenesis pathway for the repair of damaged Fe–S clusters. It also protects pathogen against drugs, ensuring controlled iron utilization and contributing to drug resistance. In Mtb, six proteins of Fe–S cluster assembly pathway are encoded by the suf operon. The present study was focused on SufD because of its role in iron acquisition and prevention of Fenton reaction. The research further delves into the in silico characterization of SufD, utilizing bioinformatics tools for sequence and structure based analysis. The protein’s structural features, including the identification of conserved regions, motifs, and 3D structure prediction enhanced functional annotation. Target based virtual screening of compounds from the ChEMBL database resulted in 12 inhibitors with best binding affinities. Drug likeness and ADMET profiling of potential inhibitors identified promising compounds with favorable drug-like properties. The study also involved cloning in SUMO-pRSF-Duet1 expression vector, overexpression, and purification of recombinant SufD from E. coli BL21 (DE3) cells. Optimization of expression conditions resulted in soluble production, and subsequent purification highlighting the efficacy of the SUMO fusion system for challenging Mtb proteins in E. coli. These findings provide valuable insights into pharmacological targets for future experimental studies, holding promise for the development of targeted therapy against Mtb.

FDA-Approved Tedizolid Phosphate Prevents Cisplatin-Induced Hearing Loss Without Decreasing Its Anti-tumor Effect.

Cisplatin is a low-cost clinical anti-tumor drug widely used to treat solid tumors. However, its use could damage cochlear hair cells, leading to irreversible hearing loss. Currently, there appears one drug approved in clinic only used for reducing ototoxicity associated with cisplatin in pediatric patients, which needs to further explore other candidate drugs. Here, by screening 1967 FDA-approved drugs to protect cochlear hair cell line (HEI-OC1) from cisplatin damage, we found that Tedizolid Phosphate (Ted), a drug indicated for the treatment of acute infections, had the best protective effect. Further, we evaluated the protective effect of Ted against ototoxicity in mouse cochlear explants, zebrafish, and adult mice. The mechanism of action of Ted was further explored using RNA sequencing analysis and verified. Meanwhile, we also observed the effect of Ted on the anti-tumor effect of cisplatin. Ted had a strong protective effect on hair cell (HC) loss induced by cisplatin in zebrafish and mouse cochlear explants. In addition, when administered systemically, it protected mice from cisplatin-induced hearing loss. Moreover, antitumor studies showed that Ted had no effect on the antitumor activity of cisplatin both in vitro and in vivo. RNA sequencing analysis showed that the otoprotective effect of Ted was mainly achieved by inhibiting phosphorylation of ERK. Consistently, ERK activator aggravated the damage of cisplatin to HCs. Collectively, these results showed that FDA-approved Ted protected HCs from cisplatin-induced HC loss by inhibiting ERK phosphorylation, indicating its potential as a candidate for preventing cisplatin ototoxicity in clinical settings.

A Multistep In Silico Approach Identifies Potential Glioblastoma Drug Candidates via Inclusive Molecular Targeting of Glioblastoma Stem Cells.

Glioblastoma (GBM) is the highest grade of glioma for which no effective therapy is currently available. Despite extensive research in diagnosis and therapy, there has been no significant improvement in GBM outcomes, with a median overall survival continuing at a dismal 15-18months. In recent times, glioblastoma stem cells (GSCs) have been identified as crucial drivers of treatment resistance and tumor recurrence, and GBM therapies targeting GSCs are expected to improve patient outcomes. We used a multistep in silico screening strategy to identify repurposed candidate drugs against selected therapeutic molecular targets in GBM with potential to concomitantly target GSCs. Common differentially expressed genes (DEGs) were identified through analysis of multiple GBM and GSC datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). For identification of target genes, we selected the genes with most significant effect on overall patient survival. The relative mRNA and protein expression of the selected genes in TCGA control versus GBM samples was also validated and their cancer dependency scores were assessed. Drugs targeting these genes and their corresponding proteins were identified from LINCS database using Connectivity Map (CMap) portal and by in silico molecular docking against each individual target using FDA-approved drug library from the DrugBank database, respectively. The molecules thus obtained were further evaluated for their ability to cross blood brain barrier (BBB) and their likelihood of resulting in drug resistance by acting as p-glycoprotein (p-Gp) substrates. The growth inhibitory effect of these final shortlisted compounds was examined on a panel of GBM cell lines and compared with temozolomide through the drug sensitivity EC50 values and AUC from the PRISM Repurposing Secondary Screen, and the IC50 values were obtained from GDSC portal. We identified RPA3, PSMA2, PSMC2, BLVRA, and HUS1 as molecular targets in GBM including GSCs with significant impact on patient survival. Our results show GSK-2126458/omipalisib, linifanib, drospirenone, eltrombopag, nilotinib, and PD198306 as candidate drugs which can be further evaluated for their anti-tumor potential against GBM. Through this work, we identified repurposed candidate therapeutics against GBM utilizing a GSC inclusive targeting approach, which demonstrated high in vitro efficacy and can prospectively evade drug resistance. These drugs have the potential to be developed as individual or combination therapy to improve GBM outcomes.